Preprints
Available on bioRxiv.
Publications
2025
FROM THE LAB
Justas Dauparas, Gyu Rie Lee, Robert Pecoraro, Linna An, Ivan Anishchenko, Cameron Glasscock,, David Baker
Atomic context-conditioned protein sequence design using LigandMPNN Journal Article
In: Nature Methods, 2025.
@article{Dauparas2025,
title = {Atomic context-conditioned protein sequence design using LigandMPNN},
author = {Justas Dauparas, Gyu Rie Lee, Robert Pecoraro, Linna An, Ivan Anishchenko, Cameron Glasscock, and David Baker },
url = {https://www.nature.com/articles/s41592-025-02626-1, Nature Methods
https://www.bakerlab.org/wp-content/uploads/2025/03/s41592-025-02626-1.pdf, PDF},
year = {2025},
date = {2025-03-28},
urldate = {2025-03-28},
journal = {Nature Methods},
abstract = {Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprotein atoms and molecules. Here we describe a deep-learning-based protein sequence design method called LigandMPNN that explicitly models all nonprotein components of biomolecular systems. LigandMPNN significantly outperforms Rosetta and ProteinMPNN on native backbone sequence recovery for residues interacting with small molecules (63.3% versus 50.4% and 50.5%), nucleotides (50.5% versus 35.2% and 34.0%) and metals (77.5% versus 36.0% and 40.6%). LigandMPNN generates not only sequences but also sidechain conformations to allow detailed evaluation of binding interactions. LigandMPNN has been used to design over 100 experimentally validated small-molecule and DNA-binding proteins with high affinity and high structural accuracy (as indicated by four X-ray crystal structures), and redesign of Rosetta small-molecule binder designs has increased binding affinity by as much as 100-fold. We anticipate that LigandMPNN will be widely useful for designing new binding proteins, sensors and enzymes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprotein atoms and molecules. Here we describe a deep-learning-based protein sequence design method called LigandMPNN that explicitly models all nonprotein components of biomolecular systems. LigandMPNN significantly outperforms Rosetta and ProteinMPNN on native backbone sequence recovery for residues interacting with small molecules (63.3% versus 50.4% and 50.5%), nucleotides (50.5% versus 35.2% and 34.0%) and metals (77.5% versus 36.0% and 40.6%). LigandMPNN generates not only sequences but also sidechain conformations to allow detailed evaluation of binding interactions. LigandMPNN has been used to design over 100 experimentally validated small-molecule and DNA-binding proteins with high affinity and high structural accuracy (as indicated by four X-ray crystal structures), and redesign of Rosetta small-molecule binder designs has increased binding affinity by as much as 100-fold. We anticipate that LigandMPNN will be widely useful for designing new binding proteins, sensors and enzymes.
Jason Z Zhang, Nathan Greenwood, Jason Hernandez, Josh T Cuperus, Buwei Huang, Bryan D Ryder, Christine Queitsch, Jason E Gestwicki, David Baker
De novo designed Hsp70 activator dissolves intracellular condensates Journal Article
In: Cell Chemical Biology, 2025.
@article{pmid39922190,
title = {De novo designed Hsp70 activator dissolves intracellular condensates},
author = {Jason Z Zhang and Nathan Greenwood and Jason Hernandez and Josh T Cuperus and Buwei Huang and Bryan D Ryder and Christine Queitsch and Jason E Gestwicki and David Baker},
url = {https://www.cell.com/cell-chemical-biology/fulltext/S2451-9456(25)00029-7, Cell Chemical Biology
https://www.bakerlab.org/wp-content/uploads/2025/03/PIIS2451945625000297.pdf, PDF},
doi = {10.1016/j.chembiol.2025.01.006},
year = {2025},
date = {2025-03-20},
urldate = {2025-03-01},
journal = {Cell Chemical Biology},
abstract = {Protein quality control (PQC) is carried out in part by the chaperone Hsp70 in concert with adapters of the J-domain protein (JDP) family. The JDPs, also called Hsp40s, are thought to recruit Hsp70 into complexes with specific client proteins. However, the molecular principles regulating this process are not well understood. We describe the de novo design of Hsp70 binding proteins that either inhibit or stimulate Hsp70 ATPase activity. An ATPase stimulating design promoted the refolding of denatured luciferase in vitro, similar to native JDPs. Targeting of this design to intracellular condensates resulted in their nearly complete dissolution and revealed roles as cell growth promoting signaling hubs. The designs inform our understanding of chaperone structure-function relationships and provide a general and modular way to target PQC systems to regulate condensates and other cellular targets.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein quality control (PQC) is carried out in part by the chaperone Hsp70 in concert with adapters of the J-domain protein (JDP) family. The JDPs, also called Hsp40s, are thought to recruit Hsp70 into complexes with specific client proteins. However, the molecular principles regulating this process are not well understood. We describe the de novo design of Hsp70 binding proteins that either inhibit or stimulate Hsp70 ATPase activity. An ATPase stimulating design promoted the refolding of denatured luciferase in vitro, similar to native JDPs. Targeting of this design to intracellular condensates resulted in their nearly complete dissolution and revealed roles as cell growth promoting signaling hubs. The designs inform our understanding of chaperone structure-function relationships and provide a general and modular way to target PQC systems to regulate condensates and other cellular targets.
Wei Yang, Derrick R Hicks, Agnidipta Ghosh, Tristin A Schwartze, Brian Conventry, Inna Goreshnik, Aza Allen, Samer F Halabiya, Chan Johng Kim, Cynthia S Hinck, David S Lee, Asim K Bera, Zhe Li, Yujia Wang, Thomas Schlichthaerle, Longxing Cao, Buwei Huang, Sarah Garrett, Stacey R Gerben, Stephen Rettie, Piper Heine, Analisa Murray, Natasha Edman, Lauren Carter, Lance Stewart, Steven C Almo, Andrew P Hinck, David Baker
Design of high-affinity binders to immune modulating receptors for cancer immunotherapy Journal Article
In: Nature Communications, 2025.
@article{pmid40011465,
title = {Design of high-affinity binders to immune modulating receptors for cancer immunotherapy},
author = {Wei Yang and Derrick R Hicks and Agnidipta Ghosh and Tristin A Schwartze and Brian Conventry and Inna Goreshnik and Aza Allen and Samer F Halabiya and Chan Johng Kim and Cynthia S Hinck and David S Lee and Asim K Bera and Zhe Li and Yujia Wang and Thomas Schlichthaerle and Longxing Cao and Buwei Huang and Sarah Garrett and Stacey R Gerben and Stephen Rettie and Piper Heine and Analisa Murray and Natasha Edman and Lauren Carter and Lance Stewart and Steven C Almo and Andrew P Hinck and David Baker},
url = {https://www.nature.com/articles/s41467-025-57192-z, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2025/03/s41467-025-57192-z.pdf, PDF},
doi = {10.1038/s41467-025-57192-z},
year = {2025},
date = {2025-02-26},
urldate = {2025-02-01},
journal = {Nature Communications},
abstract = {Immune receptors have emerged as critical therapeutic targets for cancer immunotherapy. Designed protein binders can have high affinity, modularity, and stability and hence could be attractive components of protein therapeutics directed against these receptors, but traditional Rosetta based protein binder methods using small globular scaffolds have difficulty achieving high affinity on convex targets. Here we describe the development of helical concave scaffolds tailored to the convex target sites typically involved in immune receptor interactions. We employed these scaffolds to design proteins that bind to TGFβRII, CTLA-4, and PD-L1, achieving low nanomolar to picomolar affinities and potent biological activity following experimental optimization. Co-crystal structures of the TGFβRII and CTLA-4 binders in complex with their respective receptors closely match the design models. These designs should have considerable utility for downstream therapeutic applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Immune receptors have emerged as critical therapeutic targets for cancer immunotherapy. Designed protein binders can have high affinity, modularity, and stability and hence could be attractive components of protein therapeutics directed against these receptors, but traditional Rosetta based protein binder methods using small globular scaffolds have difficulty achieving high affinity on convex targets. Here we describe the development of helical concave scaffolds tailored to the convex target sites typically involved in immune receptor interactions. We employed these scaffolds to design proteins that bind to TGFβRII, CTLA-4, and PD-L1, achieving low nanomolar to picomolar affinities and potent biological activity following experimental optimization. Co-crystal structures of the TGFβRII and CTLA-4 binders in complex with their respective receptors closely match the design models. These designs should have considerable utility for downstream therapeutic applications.
Anna Lauko, Samuel J. Pellock, Kiera H. Sumida, Ivan Anishchenko, David Juergens, Woody Ahern, Jihun Jeung, Alex Shida, Andrew Hunt, Indrek Kalvet, Christoffer Norn, Ian R. Humphreys, Cooper Jamieson, Rohith Krishna, Yakov Kipnis, Alex Kang, Evans Brackenbrough, Asim K. Bera, Banumathi Sankaran, K. N. Houk, David Baker
Computational design of serine hydrolases Journal Article
In: Science, 2025.
@article{Lauko2025,
title = {Computational design of serine hydrolases},
author = {Anna Lauko and Samuel J. Pellock and Kiera H. Sumida and Ivan Anishchenko and David Juergens and Woody Ahern and Jihun Jeung and Alex Shida and Andrew Hunt and Indrek Kalvet and Christoffer Norn and Ian R. Humphreys and Cooper Jamieson and Rohith Krishna and Yakov Kipnis and Alex Kang and Evans Brackenbrough and Asim K. Bera and Banumathi Sankaran and K. N. Houk and David Baker},
url = {https://www.science.org/stoken/author-tokens/ST-2422/full, Science},
doi = {10.1126/science.adu2454},
year = {2025},
date = {2025-02-13},
urldate = {2025-02-13},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion with an ensemble generation method for assessing active site preorganization to design enzymes starting from minimal active site descriptions. Experimental characterization revealed catalytic efficiencies (kcat/Km) up to 2.2x105 M−1 s−1 and crystal structures that closely match the design models (Cα RMSDs < 1 Å). Selection for structural compatibility across the reaction coordinate enabled identification of new catalysts in low-throughput screens with five different folds distinct from those of natural serine hydrolases. Our de novo approach provides insight into the geometric basis of catalysis and a roadmap for designing enzymes that catalyze multistep transformations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion with an ensemble generation method for assessing active site preorganization to design enzymes starting from minimal active site descriptions. Experimental characterization revealed catalytic efficiencies (kcat/Km) up to 2.2×105 M−1 s−1 and crystal structures that closely match the design models (Cα RMSDs < 1 Å). Selection for structural compatibility across the reaction coordinate enabled identification of new catalysts in low-throughput screens with five different folds distinct from those of natural serine hydrolases. Our de novo approach provides insight into the geometric basis of catalysis and a roadmap for designing enzymes that catalyze multistep transformations.
Jason Z. Zhang, Nathan Greenwood, Jason Hernandez, Josh T. Cuperus, Buwei Huang, Bryan D. Ryder, Christine Queitsch, Jason E. Gestwicki, David Baker
De novo designed Hsp70 activator dissolves intracellular condensates Journal Article
In: Cell Chemical Biology, 2025.
@article{Zhang2025b,
title = {De novo designed Hsp70 activator dissolves intracellular condensates},
author = {Jason Z. Zhang and Nathan Greenwood and Jason Hernandez and Josh T. Cuperus and Buwei Huang and Bryan D. Ryder and Christine Queitsch and Jason E. Gestwicki and David Baker},
url = {https://www.cell.com/cell-chemical-biology/fulltext/S2451-9456(25)00029-7, Cell Chemical Biology},
doi = {10.1016/j.chembiol.2025.01.006},
year = {2025},
date = {2025-02-07},
urldate = {2025-02-00},
journal = {Cell Chemical Biology},
publisher = {Elsevier BV},
abstract = {Protein quality control (PQC) is carried out in part by the chaperone Hsp70 in concert with adapters of the J-domain protein (JDP) family. The JDPs, also called Hsp40s, are thought to recruit Hsp70 into complexes with specific client proteins. However, the molecular principles regulating this process are not well understood. We describe the de novo design of Hsp70 binding proteins that either inhibit or stimulate Hsp70 ATPase activity. An ATPase stimulating design promoted the refolding of denatured luciferase in vitro, similar to native JDPs. Targeting of this design to intracellular condensates resulted in their nearly complete dissolution and revealed roles as cell growth promoting signaling hubs. The designs inform our understanding of chaperone structure-function relationships and provide a general and modular way to target PQC systems to regulate condensates and other cellular targets.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein quality control (PQC) is carried out in part by the chaperone Hsp70 in concert with adapters of the J-domain protein (JDP) family. The JDPs, also called Hsp40s, are thought to recruit Hsp70 into complexes with specific client proteins. However, the molecular principles regulating this process are not well understood. We describe the de novo design of Hsp70 binding proteins that either inhibit or stimulate Hsp70 ATPase activity. An ATPase stimulating design promoted the refolding of denatured luciferase in vitro, similar to native JDPs. Targeting of this design to intracellular condensates resulted in their nearly complete dissolution and revealed roles as cell growth promoting signaling hubs. The designs inform our understanding of chaperone structure-function relationships and provide a general and modular way to target PQC systems to regulate condensates and other cellular targets.
Susana Vázquez Torres, Melisa Benard Valle, Stephen P. Mackessy, Stefanie K. Menzies, Nicholas R. Casewell, Shirin Ahmadi, Nick J. Burlet, Edin Muratspahić, Isaac Sappington, Max D. Overath, Esperanza Rivera-de-Torre, Jann Ledergerber, Andreas H. Laustsen, Kim Boddum, Asim K. Bera, Alex Kang, Evans Brackenbrough, Iara A. Cardoso, Edouard P. Crittenden, Rebecca J. Edge, Justin Decarreau, Robert J. Ragotte, Arvind S. Pillai, Mohamad Abedi, Hannah L. Han, Stacey R. Gerben, Analisa Murray, Rebecca Skotheim, Lynda Stuart, Lance Stewart, Thomas J. A. Fryer, Timothy P. Jenkins, David Baker
De novo designed proteins neutralize lethal snake venom toxins Journal Article
In: Nature, 2025.
@article{VázquezTorres2025,
title = {De novo designed proteins neutralize lethal snake venom toxins},
author = {Susana Vázquez Torres and Melisa Benard Valle and Stephen P. Mackessy and Stefanie K. Menzies and Nicholas R. Casewell and Shirin Ahmadi and Nick J. Burlet and Edin Muratspahić and Isaac Sappington and Max D. Overath and Esperanza Rivera-de-Torre and Jann Ledergerber and Andreas H. Laustsen and Kim Boddum and Asim K. Bera and Alex Kang and Evans Brackenbrough and Iara A. Cardoso and Edouard P. Crittenden and Rebecca J. Edge and Justin Decarreau and Robert J. Ragotte and Arvind S. Pillai and Mohamad Abedi and Hannah L. Han and Stacey R. Gerben and Analisa Murray and Rebecca Skotheim and Lynda Stuart and Lance Stewart and Thomas J. A. Fryer and Timothy P. Jenkins and David Baker},
url = {https://www.nature.com/articles/s41586-024-08393-x, Nature
https://www.bakerlab.org/wp-content/uploads/2025/03/s41586-024-08393-x-1.pdf, PDF},
doi = {10.1038/s41586-024-08393-x},
year = {2025},
date = {2025-01-15},
urldate = {2025-01-15},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {Snakebite envenoming remains a devastating and neglected tropical disease, claiming over 100,000 lives annually and causing severe complications and long-lasting disabilities for many more1,2. Three-finger toxins (3FTx) are highly toxic components of elapid snake venoms that can cause diverse pathologies, including severe tissue damage3 and inhibition of nicotinic acetylcholine receptors, resulting in life-threatening neurotoxicity4. At present, the only available treatments for snakebites consist of polyclonal antibodies derived from the plasma of immunized animals, which have high cost and limited efficacy against 3FTxs5,6,7. Here we used deep learning methods to de novo design proteins to bind short-chain and long-chain α-neurotoxins and cytotoxins from the 3FTx family. With limited experimental screening, we obtained protein designs with remarkable thermal stability, high binding affinity and near-atomic-level agreement with the computational models. The designed proteins effectively neutralized all three 3FTx subfamilies in vitro and protected mice from a lethal neurotoxin challenge. Such potent, stable and readily manufacturable toxin-neutralizing proteins could provide the basis for safer, cost-effective and widely accessible next-generation antivenom therapeutics. Beyond snakebite, our results highlight how computational design could help democratize therapeutic discovery, particularly in resource-limited settings, by substantially reducing costs and resource requirements for the development of therapies for neglected tropical diseases.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Snakebite envenoming remains a devastating and neglected tropical disease, claiming over 100,000 lives annually and causing severe complications and long-lasting disabilities for many more1,2. Three-finger toxins (3FTx) are highly toxic components of elapid snake venoms that can cause diverse pathologies, including severe tissue damage3 and inhibition of nicotinic acetylcholine receptors, resulting in life-threatening neurotoxicity4. At present, the only available treatments for snakebites consist of polyclonal antibodies derived from the plasma of immunized animals, which have high cost and limited efficacy against 3FTxs5,6,7. Here we used deep learning methods to de novo design proteins to bind short-chain and long-chain α-neurotoxins and cytotoxins from the 3FTx family. With limited experimental screening, we obtained protein designs with remarkable thermal stability, high binding affinity and near-atomic-level agreement with the computational models. The designed proteins effectively neutralized all three 3FTx subfamilies in vitro and protected mice from a lethal neurotoxin challenge. Such potent, stable and readily manufacturable toxin-neutralizing proteins could provide the basis for safer, cost-effective and widely accessible next-generation antivenom therapeutics. Beyond snakebite, our results highlight how computational design could help democratize therapeutic discovery, particularly in resource-limited settings, by substantially reducing costs and resource requirements for the development of therapies for neglected tropical diseases.
COLLABORATOR LED
Ban-Seok Jeong, Hwanhee C. Kim, Catherine M. Sniezek, Stephanie Berger, Justin M. Kollman, David Baker, Joshua C. Vaughan, Xiaohu Gao
Intracellular delivery of proteins for live cell imaging Journal Article
In: Journal of Controlled Release, 2025.
@article{Jeong2025,
title = {Intracellular delivery of proteins for live cell imaging},
author = {Ban-Seok Jeong and Hwanhee C. Kim and Catherine M. Sniezek and Stephanie Berger and Justin M. Kollman and David Baker and Joshua C. Vaughan and Xiaohu Gao},
url = {https://www.sciencedirect.com/science/article/pii/S0168365925002718, Journal of Controlled Release
https://www.bakerlab.org/wp-content/uploads/2025/03/1-s2.0-S0168365925002718-main.pdf, PDF},
doi = {10.1016/j.jconrel.2025.113651},
year = {2025},
date = {2025-03-28},
urldate = {2025-05-00},
journal = {Journal of Controlled Release},
publisher = {Elsevier BV},
abstract = {The majority of cellular functions are regulated by intracellular proteins, and regulating their interactions can unlock fundamental insights in biology and open new avenues for drug discovery. Because the vast majority of intracellular targets remain undruggable, there is significant current interest in developing protein-based agents especially monoclonal antibodies due to their specificity, availability, and established screening/engineering methods. However, efficient delivery of proteins into the cytoplasm has been a major challenge in biological engineering and drug discovery. We previously reported a platform technology based on a Coomassie blue-cholesterol conjugate (CB-tag) capable of delivering small proteins directly into the cytoplasm. Here, we report a new generation of CB-tag that can bring proteins with a wide size range into the cytoplasm, bypassing endosomal sequestration. Remarkably, intracellular targets with distinct structures were visualized. Overall, the new CB-tag demonstrated a robust ability in protein delivery with broad applications ranging from live-cell immunofluorescence to protein-based therapeutic development.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The majority of cellular functions are regulated by intracellular proteins, and regulating their interactions can unlock fundamental insights in biology and open new avenues for drug discovery. Because the vast majority of intracellular targets remain undruggable, there is significant current interest in developing protein-based agents especially monoclonal antibodies due to their specificity, availability, and established screening/engineering methods. However, efficient delivery of proteins into the cytoplasm has been a major challenge in biological engineering and drug discovery. We previously reported a platform technology based on a Coomassie blue-cholesterol conjugate (CB-tag) capable of delivering small proteins directly into the cytoplasm. Here, we report a new generation of CB-tag that can bring proteins with a wide size range into the cytoplasm, bypassing endosomal sequestration. Remarkably, intracellular targets with distinct structures were visualized. Overall, the new CB-tag demonstrated a robust ability in protein delivery with broad applications ranging from live-cell immunofluorescence to protein-based therapeutic development.
Ryan M. Francis, Irina Kopyeva, Nicholas Lai, Shiyu Yang, Jeremy R. Filteau, Xinru Wang, David Baker, Cole A. DeForest
Rapid and Inexpensive Image‐Guided Grayscale Biomaterial Customization via LCD Printing Journal Article
In: J Biomedical Materials Res, 2025.
@article{Francis2025,
title = {Rapid and Inexpensive Image‐Guided Grayscale Biomaterial Customization via LCD Printing},
author = {Ryan M. Francis and Irina Kopyeva and Nicholas Lai and Shiyu Yang and Jeremy R. Filteau and Xinru Wang and David Baker and Cole A. DeForest},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jbm.a.37897, J Biomedical Materials Res},
doi = {10.1002/jbm.a.37897},
year = {2025},
date = {2025-03-27},
urldate = {2025-04-00},
journal = {J Biomedical Materials Res},
publisher = {Wiley},
abstract = {Hydrogels are an important class of biomaterials that permit cells to be cultured and studied within engineered microenvironments of user-defined physical and chemical properties. Though conventional 3D extrusion and stereolithographic (SLA) printing readily enable homogeneous and multimaterial hydrogels to be formed with specific macroscopic geometries, strategies that further afford spatiotemporal customization of the underlying gel physicochemistry in a non-discrete manner would be profoundly useful toward recapitulating the complexity of native tissue in vitro. Here, we demonstrate that grayscale control over local biomaterial biochemistry and mechanics can be rapidly achieved across large constructs using an inexpensive (~$300) and commercially available liquid crystal display (LCD)-based printer. Template grayscale images are first processed into a “height-extruded” 3D object, which is then printed on a standard LCD printer with an immobile build head. As the local height of the 3D object corresponds to the final light dosage delivered at the corresponding xy-coordinate, this method provides a route toward spatially specifying the extent of various dosage-dependent and biomaterial, forming/modifying photochemistries. Demonstrating the utility of this approach, we photopattern the grayscale polymerization of poly(ethylene glycol) (PEG) diacrylate gels, biochemical functionalization of agarose- and PEG-based gels via oxime ligation, and the controlled 2D adhesion and 3D growth of cells in response to a de novo-designed α5β1-modulating protein via thiol-norbornene click chemistry. Owing to the method's low cost, simple implementation, and high compatibility with many biomaterial photochemistries, we expect this strategy will prove useful toward fundamental biological studies and functional tissue engineering alike.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hydrogels are an important class of biomaterials that permit cells to be cultured and studied within engineered microenvironments of user-defined physical and chemical properties. Though conventional 3D extrusion and stereolithographic (SLA) printing readily enable homogeneous and multimaterial hydrogels to be formed with specific macroscopic geometries, strategies that further afford spatiotemporal customization of the underlying gel physicochemistry in a non-discrete manner would be profoundly useful toward recapitulating the complexity of native tissue in vitro. Here, we demonstrate that grayscale control over local biomaterial biochemistry and mechanics can be rapidly achieved across large constructs using an inexpensive (~$300) and commercially available liquid crystal display (LCD)-based printer. Template grayscale images are first processed into a “height-extruded” 3D object, which is then printed on a standard LCD printer with an immobile build head. As the local height of the 3D object corresponds to the final light dosage delivered at the corresponding xy-coordinate, this method provides a route toward spatially specifying the extent of various dosage-dependent and biomaterial, forming/modifying photochemistries. Demonstrating the utility of this approach, we photopattern the grayscale polymerization of poly(ethylene glycol) (PEG) diacrylate gels, biochemical functionalization of agarose- and PEG-based gels via oxime ligation, and the controlled 2D adhesion and 3D growth of cells in response to a de novo-designed α5β1-modulating protein via thiol-norbornene click chemistry. Owing to the method's low cost, simple implementation, and high compatibility with many biomaterial photochemistries, we expect this strategy will prove useful toward fundamental biological studies and functional tissue engineering alike.
Meghana Kshirsagar, Artur Meller, Ian R Humphreys, Samuel Sledzieski, Yixi Xu, Rahul Dodhia, Eric Horvitz, Bonnie Berger, Gregory R Bowman, Juan Lavista Ferres, David Baker, Minkyung Baek
Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm Journal Article
In: Nature Communications, 2025.
@article{pmid40016259,
title = {Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm},
author = {Meghana Kshirsagar and Artur Meller and Ian R Humphreys and Samuel Sledzieski and Yixi Xu and Rahul Dodhia and Eric Horvitz and Bonnie Berger and Gregory R Bowman and Juan Lavista Ferres and David Baker and Minkyung Baek},
url = {https://www.nature.com/articles/s41467-025-57148-3, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2025/03/s41467-025-57148-3.pdf, PDF},
doi = {10.1038/s41467-025-57148-3},
year = {2025},
date = {2025-02-27},
urldate = {2025-02-27},
journal = {Nature Communications},
abstract = {The majority of proteins must form higher-order assemblies to perform their biological functions, yet few machine learning models can accurately and rapidly predict the symmetry of assemblies involving multiple copies of the same protein chain. Here, we address this gap by finetuning several classes of protein foundation models, to predict homo-oligomer symmetry. Our best model named Seq2Symm, which utilizes ESM2, outperforms existing template-based and deep learning methods achieving an average AUC-PR of 0.47, 0.44 and 0.49 across homo-oligomer symmetries on three held-out test sets compared to 0.24, 0.24 and 0.25 with template-based search. Seq2Symm uses a single sequence as input and can predict at the rate of ~80,000 proteins/hour. We apply this method to 5 proteomes and ~3.5 million unlabeled protein sequences, showing its promise to be used in conjunction with downstream computationally intensive all-atom structure generation methods such as RoseTTAFold2 and AlphaFold2-multimer. Code, datasets, model are available at: https://github.com/microsoft/seq2symm .},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The majority of proteins must form higher-order assemblies to perform their biological functions, yet few machine learning models can accurately and rapidly predict the symmetry of assemblies involving multiple copies of the same protein chain. Here, we address this gap by finetuning several classes of protein foundation models, to predict homo-oligomer symmetry. Our best model named Seq2Symm, which utilizes ESM2, outperforms existing template-based and deep learning methods achieving an average AUC-PR of 0.47, 0.44 and 0.49 across homo-oligomer symmetries on three held-out test sets compared to 0.24, 0.24 and 0.25 with template-based search. Seq2Symm uses a single sequence as input and can predict at the rate of ~80,000 proteins/hour. We apply this method to 5 proteomes and ~3.5 million unlabeled protein sequences, showing its promise to be used in conjunction with downstream computationally intensive all-atom structure generation methods such as RoseTTAFold2 and AlphaFold2-multimer. Code, datasets, model are available at: https://github.com/microsoft/seq2symm .
Alena Khmelinskaia, Neville P Bethel, Farzad Fatehi, Bhoomika Basu Mallik, Aleksandar Antanasijevic, Andrew J Borst, Szu-Hsueh Lai, Ho Yeung Chim, Jing Yang 'John' Wang, Marcos C Miranda, Andrew M Watkins, Cassandra Ogohara, Shane Caldwell, Mengyu Wu, Albert J R Heck, David Veesler, Andrew B Ward, David Baker, Reidun Twarock, Neil P King
Local structural flexibility drives oligomorphism in computationally designed protein assemblies Journal Article
In: Nature Structural and Molecular Biology, 2025.
@article{pmid40011747,
title = {Local structural flexibility drives oligomorphism in computationally designed protein assemblies},
author = {Alena Khmelinskaia and Neville P Bethel and Farzad Fatehi and Bhoomika Basu Mallik and Aleksandar Antanasijevic and Andrew J Borst and Szu-Hsueh Lai and Ho Yeung Chim and Jing Yang 'John' Wang and Marcos C Miranda and Andrew M Watkins and Cassandra Ogohara and Shane Caldwell and Mengyu Wu and Albert J R Heck and David Veesler and Andrew B Ward and David Baker and Reidun Twarock and Neil P King},
url = {https://www.nature.com/articles/s41594-025-01490-z, Nature Structural and Molecular Biology
https://www.bakerlab.org/wp-content/uploads/2025/03/s41594-025-01490-z.pdf, PDF},
doi = {10.1038/s41594-025-01490-z},
year = {2025},
date = {2025-02-26},
urldate = {2025-02-26},
journal = {Nature Structural and Molecular Biology},
abstract = {Many naturally occurring protein assemblies have dynamic structures that allow them to perform specialized functions. Although computational methods for designing novel self-assembling proteins have advanced substantially over the past decade, they primarily focus on designing static structures. Here we characterize three distinct computationally designed protein assemblies that exhibit unanticipated structural diversity arising from flexibility in their subunits. Cryo-EM single-particle reconstructions and native mass spectrometry reveal two distinct architectures for two assemblies, while six cryo-EM reconstructions for the third likely represent a subset of its solution-phase structures. Structural modeling and molecular dynamics simulations indicate that constrained flexibility within the subunits of each assembly promotes a defined range of architectures rather than nonspecific aggregation. Redesigning the flexible region in one building block rescues the intended monomorphic assembly. These findings highlight structural flexibility as a powerful design principle, enabling exploration of new structural and functional spaces in protein assembly design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many naturally occurring protein assemblies have dynamic structures that allow them to perform specialized functions. Although computational methods for designing novel self-assembling proteins have advanced substantially over the past decade, they primarily focus on designing static structures. Here we characterize three distinct computationally designed protein assemblies that exhibit unanticipated structural diversity arising from flexibility in their subunits. Cryo-EM single-particle reconstructions and native mass spectrometry reveal two distinct architectures for two assemblies, while six cryo-EM reconstructions for the third likely represent a subset of its solution-phase structures. Structural modeling and molecular dynamics simulations indicate that constrained flexibility within the subunits of each assembly promotes a defined range of architectures rather than nonspecific aggregation. Redesigning the flexible region in one building block rescues the intended monomorphic assembly. These findings highlight structural flexibility as a powerful design principle, enabling exploration of new structural and functional spaces in protein assembly design.
Yuhao Li, Bradley S. Harris, Zhongwu Li, Chenyang Shi, Jobaer Abdullah, Sagardip Majumder, Samuel Berhanu, Anastassia A. Vorobieva, Sydney K. Myers, Jeevapani Hettige, Marcel D. Baer, James J. De Yoreo, David Baker, Aleksandr Noy
Water, Solute, and Ion Transport in De Novo-Designed Membrane Protein Channels Journal Article
In: ACS Nano, 2025.
@article{Li2024,
title = {Water, Solute, and Ion Transport in De Novo-Designed Membrane Protein Channels},
author = {Yuhao Li and Bradley S. Harris and Zhongwu Li and Chenyang Shi and Jobaer Abdullah and Sagardip Majumder and Samuel Berhanu and Anastassia A. Vorobieva and Sydney K. Myers and Jeevapani Hettige and Marcel D. Baer and James J. De Yoreo and David Baker and Aleksandr Noy},
url = {https://pubs.acs.org/doi/10.1021/acsnano.4c11317, ACS Nano
https://www.bakerlab.org/wp-content/uploads/2025/02/li-et-al-2024-water-solute-and-ion-transport-in-de-novo-designed-membrane-protein-channels.pdf, PDF},
doi = {10.1021/acsnano.4c11317},
year = {2025},
date = {2025-01-21},
urldate = {2025-01-21},
journal = {ACS Nano},
publisher = {American Chemical Society (ACS)},
abstract = {Biological organisms engineer peptide sequences to fold into membrane pore proteins capable of performing a wide variety of transport functions. Synthetic de novo-designed membrane pores can mimic this approach to achieve a potentially even larger set of functions. Here we explore water, solute, and ion transport in three de novo designed β-barrel membrane channels in the 5–10 Å pore size range. We show that these proteins form passive membrane pores with high water transport efficiencies and size rejection characteristics consistent with the pore size encoded in the protein structure. Ion conductance and ion selectivity measurements also show trends consistent with the pore size, with the two larger pores showing weak cation selectivity. MD simulations of water and ion transport and solute size exclusion are consistent with the experimental trends and provide further insights into structure–function correlations in these membrane pores.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Biological organisms engineer peptide sequences to fold into membrane pore proteins capable of performing a wide variety of transport functions. Synthetic de novo-designed membrane pores can mimic this approach to achieve a potentially even larger set of functions. Here we explore water, solute, and ion transport in three de novo designed β-barrel membrane channels in the 5–10 Å pore size range. We show that these proteins form passive membrane pores with high water transport efficiencies and size rejection characteristics consistent with the pore size encoded in the protein structure. Ion conductance and ion selectivity measurements also show trends consistent with the pore size, with the two larger pores showing weak cation selectivity. MD simulations of water and ion transport and solute size exclusion are consistent with the experimental trends and provide further insights into structure–function correlations in these membrane pores.
2024
FROM THE LAB
Quinton M. Dowling, Young-Jun Park, Chelsea N. Fries, Neil C. Gerstenmaier, Sebastian Ols, Erin C. Yang, Adam J. Wargacki, Annie Dosey, Yang Hsia, Rashmi Ravichandran, Carl D. Walkey, Anika L. Burrell, David Veesler, David Baker, Neil P. King
Hierarchical design of pseudosymmetric protein nanocages Journal Article
In: Nature, 2024.
@article{Dowling2024,
title = {Hierarchical design of pseudosymmetric protein nanocages},
author = {Quinton M. Dowling and Young-Jun Park and Chelsea N. Fries and Neil C. Gerstenmaier and Sebastian Ols and Erin C. Yang and Adam J. Wargacki and Annie Dosey and Yang Hsia and Rashmi Ravichandran and Carl D. Walkey and Anika L. Burrell and David Veesler and David Baker and Neil P. King},
url = {https://www.nature.com/articles/s41586-024-08360-6, Nature [Open Access]},
doi = {10.1038/s41586-024-08360-6},
year = {2024},
date = {2024-12-18},
urldate = {2024-12-18},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {Discrete protein assemblies ranging from hundreds of kilodaltons to hundreds of megadaltons in size are a ubiquitous feature of biological systems and perform highly specialized functions. Despite remarkable recent progress in accurately designing new self-assembling proteins, the size and complexity of these assemblies has been limited by a reliance on strict symmetry. Here, inspired by the pseudosymmetry observed in bacterial microcompartments and viral capsids, we developed a hierarchical computational method for designing large pseudosymmetric self-assembling protein nanomaterials. We computationally designed pseudosymmetric heterooligomeric components and used them to create discrete, cage-like protein assemblies with icosahedral symmetry containing 240, 540 and 960 subunits. At 49, 71 and 96 nm diameter, these nanocages are the largest bounded computationally designed protein assemblies generated to date. More broadly, by moving beyond strict symmetry, our work substantially broadens the variety of self-assembling protein architectures that are accessible through design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Discrete protein assemblies ranging from hundreds of kilodaltons to hundreds of megadaltons in size are a ubiquitous feature of biological systems and perform highly specialized functions. Despite remarkable recent progress in accurately designing new self-assembling proteins, the size and complexity of these assemblies has been limited by a reliance on strict symmetry. Here, inspired by the pseudosymmetry observed in bacterial microcompartments and viral capsids, we developed a hierarchical computational method for designing large pseudosymmetric self-assembling protein nanomaterials. We computationally designed pseudosymmetric heterooligomeric components and used them to create discrete, cage-like protein assemblies with icosahedral symmetry containing 240, 540 and 960 subunits. At 49, 71 and 96 nm diameter, these nanocages are the largest bounded computationally designed protein assemblies generated to date. More broadly, by moving beyond strict symmetry, our work substantially broadens the variety of self-assembling protein architectures that are accessible through design.
Sangmin Lee, Ryan D. Kibler, Green Ahn, Yang Hsia, Andrew J. Borst, Annika Philomin, Madison A. Kennedy, Buwei Huang, Barry Stoddard, David Baker
Four-component protein nanocages designed by programmed symmetry breaking Journal Article
In: Nature, 2024.
@article{Lee2024b,
title = {Four-component protein nanocages designed by programmed symmetry breaking},
author = {Sangmin Lee and Ryan D. Kibler and Green Ahn and Yang Hsia and Andrew J. Borst and Annika Philomin and Madison A. Kennedy and Buwei Huang and Barry Stoddard and David Baker},
url = {https://www.nature.com/articles/s41586-024-07814-1, Nature [Open Access]},
doi = {10.1038/s41586-024-07814-1},
year = {2024},
date = {2024-12-18},
urldate = {2024-12-18},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {Four, eight or twenty C3 symmetric protein trimers can be arranged with tetrahedral, octahedral or icosahedral point group symmetry to generate closed cage-like structures1,2. Viruses access more complex higher triangulation number icosahedral architectures by breaking perfect point group symmetry3,4,5,6,7,8,9, but nature appears not to have explored similar symmetry breaking for tetrahedral or octahedral symmetries. Here we describe a general design strategy for building higher triangulation number architectures starting from regular polyhedra through pseudosymmetrization of trimeric building blocks. Electron microscopy confirms the structures of T = 4 cages with 48 (tetrahedral), 96 (octahedral) and 240 (icosahedral) subunits, each with 4 distinct chains and 6 different protein–protein interfaces, and diameters of 33 nm, 43 nm and 75 nm, respectively. Higher triangulation number viruses possess very sophisticated functionalities; our general route to higher triangulation number nanocages should similarly enable a next generation of multiple antigen-displaying vaccine candidates10,11 and targeted delivery vehicles12,13.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Four, eight or twenty C3 symmetric protein trimers can be arranged with tetrahedral, octahedral or icosahedral point group symmetry to generate closed cage-like structures1,2. Viruses access more complex higher triangulation number icosahedral architectures by breaking perfect point group symmetry3,4,5,6,7,8,9, but nature appears not to have explored similar symmetry breaking for tetrahedral or octahedral symmetries. Here we describe a general design strategy for building higher triangulation number architectures starting from regular polyhedra through pseudosymmetrization of trimeric building blocks. Electron microscopy confirms the structures of T = 4 cages with 48 (tetrahedral), 96 (octahedral) and 240 (icosahedral) subunits, each with 4 distinct chains and 6 different protein–protein interfaces, and diameters of 33 nm, 43 nm and 75 nm, respectively. Higher triangulation number viruses possess very sophisticated functionalities; our general route to higher triangulation number nanocages should similarly enable a next generation of multiple antigen-displaying vaccine candidates10,11 and targeted delivery vehicles12,13.
Ryan D. Kibler, Sangmin Lee, Madison A. Kennedy, Basile I. M. Wicky, Stella M. Lai, Marius M. Kostelic, Ann Carr, Xinting Li, Cameron M. Chow, Tina K. Nguyen, Lauren Carter, Vicki H. Wysocki, Barry L. Stoddard, David Baker
Design of pseudosymmetric protein hetero-oligomers Journal Article
In: Nature Communications, 2024.
@article{Kibler2024,
title = {Design of pseudosymmetric protein hetero-oligomers},
author = {Ryan D. Kibler and Sangmin Lee and Madison A. Kennedy and Basile I. M. Wicky and Stella M. Lai and Marius M. Kostelic and Ann Carr and Xinting Li and Cameron M. Chow and Tina K. Nguyen and Lauren Carter and Vicki H. Wysocki and Barry L. Stoddard and David Baker},
url = {https://www.nature.com/articles/s41467-024-54913-8, Nature Communications [Open Access]},
doi = {10.1038/s41467-024-54913-8},
year = {2024},
date = {2024-12-18},
urldate = {2024-12-00},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
abstract = {Pseudosymmetric hetero-oligomers with three or more unique subunits with overall structural (but not sequence) symmetry play key roles in biology, and systematic approaches for generating such proteins de novo would provide new routes to controlling cell signaling and designing complex protein materials. However, the de novo design of protein hetero-oligomers with three or more distinct chains with nearly identical structures is a challenging unsolved problem because it requires the accurate design of multiple protein-protein interfaces simultaneously. Here, we describe a divide-and-conquer approach that breaks the multiple-interface design challenge into a set of more tractable symmetric single-interface redesign tasks, followed by structural recombination of the validated homo-oligomers into pseudosymmetric hetero-oligomers. Starting from de novo designed circular homo-oligomers composed of 9 or 24 tandemly repeated units, we redesigned the inter-subunit interfaces to generate 19 new homo-oligomers and structurally recombined them to make 24 new hetero-oligomers, including ABC heterotrimers, A2B2 heterotetramers, and A3B3 and A2B2C2 heterohexamers which assemble with high structural specificity. The symmetric homo-oligomers and pseudosymmetric hetero-oligomers generated for each system have identical or nearly identical backbones, and hence are ideal building blocks for generating and functionalizing larger symmetric and pseudosymmetric assemblies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Pseudosymmetric hetero-oligomers with three or more unique subunits with overall structural (but not sequence) symmetry play key roles in biology, and systematic approaches for generating such proteins de novo would provide new routes to controlling cell signaling and designing complex protein materials. However, the de novo design of protein hetero-oligomers with three or more distinct chains with nearly identical structures is a challenging unsolved problem because it requires the accurate design of multiple protein-protein interfaces simultaneously. Here, we describe a divide-and-conquer approach that breaks the multiple-interface design challenge into a set of more tractable symmetric single-interface redesign tasks, followed by structural recombination of the validated homo-oligomers into pseudosymmetric hetero-oligomers. Starting from de novo designed circular homo-oligomers composed of 9 or 24 tandemly repeated units, we redesigned the inter-subunit interfaces to generate 19 new homo-oligomers and structurally recombined them to make 24 new hetero-oligomers, including ABC heterotrimers, A2B2 heterotetramers, and A3B3 and A2B2C2 heterohexamers which assemble with high structural specificity. The symmetric homo-oligomers and pseudosymmetric hetero-oligomers generated for each system have identical or nearly identical backbones, and hence are ideal building blocks for generating and functionalizing larger symmetric and pseudosymmetric assemblies.
Matthias Glögl, Aditya Krishnakumar, Robert J. Ragotte, Inna Goreshnik, Brian Coventry, Asim K. Bera, Alex Kang, Emily Joyce, Green Ahn, Buwei Huang, Wei Yang, Wei Chen, Mariana Garcia Sanchez, Brian Koepnick, David Baker
Target-conditioned diffusion generates potent TNFR superfamily antagonists and agonists Journal Article
In: Science, 2024.
@article{Glögl2024,
title = {Target-conditioned diffusion generates potent TNFR superfamily antagonists and agonists},
author = {Matthias Glögl and Aditya Krishnakumar and Robert J. Ragotte and Inna Goreshnik and Brian Coventry and Asim K. Bera and Alex Kang and Emily Joyce and Green Ahn and Buwei Huang and Wei Yang and Wei Chen and Mariana Garcia Sanchez and Brian Koepnick and David Baker},
url = {https://www.science.org/doi/abs/10.1126/science.adp1779, Science
https://www.bakerlab.org/wp-content/uploads/2024/12/Glogl-et-al-Science-Diffusion-of-TNF-binders.pdf, PDF},
doi = {10.1126/science.adp1779},
year = {2024},
date = {2024-12-06},
urldate = {2024-12-06},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {Despite progress in designing protein-binding proteins, the shape matching of designs to targets is lower than in many native protein complexes, and design efforts have failed for the tumor necrosis factor receptor 1 (TNFR1) and other protein targets with relatively flat and polar surfaces. We hypothesized that free diffusion from random noise could generate shape-matched binders for challenging targets and tested this approach on TNFR1. We obtain designs with low picomolar affinity whose specificity can be completely switched to other family members using partial diffusion. Designs function as antagonists or as superagonists when presented at higher valency for OX40 and 4-1BB. The ability to design high-affinity and high-specificity antagonists and agonists for pharmacologically important targets in silico presages a coming era in protein design in which binders are made by computation rather than immunization or random screening approaches.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Despite progress in designing protein-binding proteins, the shape matching of designs to targets is lower than in many native protein complexes, and design efforts have failed for the tumor necrosis factor receptor 1 (TNFR1) and other protein targets with relatively flat and polar surfaces. We hypothesized that free diffusion from random noise could generate shape-matched binders for challenging targets and tested this approach on TNFR1. We obtain designs with low picomolar affinity whose specificity can be completely switched to other family members using partial diffusion. Designs function as antagonists or as superagonists when presented at higher valency for OX40 and 4-1BB. The ability to design high-affinity and high-specificity antagonists and agonists for pharmacologically important targets in silico presages a coming era in protein design in which binders are made by computation rather than immunization or random screening approaches.
Dan I. Piraner, Mohamad H. Abedi, Maria J. Duran Gonzalez, Adam Chazin-Gray, Annie Lin, Iowis Zhu, Pavithran T. Ravindran, Thomas Schlichthaerle, Buwei Huang, Tyler H. Bearchild, David Lee, Sarah Wyman, Young-wook Jun, David Baker, Kole T. Roybal
Engineered receptors for soluble cellular communication and disease sensing Journal Article
In: Nature, 2024.
@article{Piraner2024,
title = {Engineered receptors for soluble cellular communication and disease sensing},
author = {Dan I. Piraner and Mohamad H. Abedi and Maria J. Duran Gonzalez and Adam Chazin-Gray and Annie Lin and Iowis Zhu and Pavithran T. Ravindran and Thomas Schlichthaerle and Buwei Huang and Tyler H. Bearchild and David Lee and Sarah Wyman and Young-wook Jun and David Baker and Kole T. Roybal},
url = {https://www.nature.com/articles/s41586-024-08366-0, Nature},
doi = {10.1038/s41586-024-08366-0},
year = {2024},
date = {2024-11-14},
urldate = {2024-11-14},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {Despite recent advances in mammalian synthetic biology, there remains a lack of modular synthetic receptors that can robustly respond to soluble ligands and in turn activate bespoke cellular functions. Such receptors would have extensive clinical potential to regulate the activity of engineered therapeutic cells, but to date only receptors against cell surface targets have approached clinical translation1. To address this gap, we developed a receptor architecture called synthetic intramembrane proteolysis receptor (SNIPR), that has the added ability to be activated by soluble ligands, both natural and synthetic, with remarkably low baseline activity and high fold activation, through an endocytic, pH-dependent cleavage mechanism. We demonstrate the therapeutic capabilities of the receptor platform by localizing the activity of CAR T cells to solid tumors where soluble disease-associated factors are expressed, bypassing the major hurdle of on-target off-tumor toxicity in bystander organs. We further applied the SNIPR platform to engineer fully synthetic signaling networks between cells orthogonal to natural signaling pathways, expanding the scope of synthetic biology. Our design framework enables cellular communication and environmental interactions, extending the capabilities of synthetic cellular networking in clinical and research contexts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Despite recent advances in mammalian synthetic biology, there remains a lack of modular synthetic receptors that can robustly respond to soluble ligands and in turn activate bespoke cellular functions. Such receptors would have extensive clinical potential to regulate the activity of engineered therapeutic cells, but to date only receptors against cell surface targets have approached clinical translation1. To address this gap, we developed a receptor architecture called synthetic intramembrane proteolysis receptor (SNIPR), that has the added ability to be activated by soluble ligands, both natural and synthetic, with remarkably low baseline activity and high fold activation, through an endocytic, pH-dependent cleavage mechanism. We demonstrate the therapeutic capabilities of the receptor platform by localizing the activity of CAR T cells to solid tumors where soluble disease-associated factors are expressed, bypassing the major hurdle of on-target off-tumor toxicity in bystander organs. We further applied the SNIPR platform to engineer fully synthetic signaling networks between cells orthogonal to natural signaling pathways, expanding the scope of synthetic biology. Our design framework enables cellular communication and environmental interactions, extending the capabilities of synthetic cellular networking in clinical and research contexts.
Sidney Lyayuga Lisanza, Jacob Merle Gershon, Samuel W. K. Tipps, Jeremiah Nelson Sims, Lucas Arnoldt, Samuel J. Hendel, Miriam K. Simma, Ge Liu, Muna Yase, Hongwei Wu, Claire D. Tharp, Xinting Li, Alex Kang, Evans Brackenbrough, Asim K. Bera, Stacey Gerben, Bruce J. Wittmann, Andrew C. McShan, David Baker
Multistate and functional protein design using RoseTTAFold sequence space diffusion Journal Article
In: Nature Biotechnology, 2024.
@article{Lisanza2024,
title = {Multistate and functional protein design using RoseTTAFold sequence space diffusion},
author = {Sidney Lyayuga Lisanza and Jacob Merle Gershon and Samuel W. K. Tipps and Jeremiah Nelson Sims and Lucas Arnoldt and Samuel J. Hendel and Miriam K. Simma and Ge Liu and Muna Yase and Hongwei Wu and Claire D. Tharp and Xinting Li and Alex Kang and Evans Brackenbrough and Asim K. Bera and Stacey Gerben and Bruce J. Wittmann and Andrew C. McShan and David Baker},
url = {https://www.nature.com/articles/s41587-024-02395-w, Nature Biotechnology [Open Access]},
doi = {10.1038/s41587-024-02395-w},
year = {2024},
date = {2024-09-25},
urldate = {2024-09-25},
journal = {Nature Biotechnology},
publisher = {Springer Science and Business Media LLC},
abstract = {Protein denoising diffusion probabilistic models are used for the de novo generation of protein backbones but are limited in their ability to guide generation of proteins with sequence-specific attributes and functional properties. To overcome this limitation, we developed ProteinGenerator (PG), a sequence space diffusion model based on RoseTTAFold that simultaneously generates protein sequences and structures. Beginning from a noised sequence representation, PG generates sequence and structure pairs by iterative denoising, guided by desired sequence and structural protein attributes. We designed thermostable proteins with varying amino acid compositions and internal sequence repeats and cage bioactive peptides, such as melittin. By averaging sequence logits between diffusion trajectories with distinct structural constraints, we designed multistate parent–child protein triples in which the same sequence folds to different supersecondary structures when intact in the parent versus split into two child domains. PG design trajectories can be guided by experimental sequence–activity data, providing a general approach for integrated computational and experimental optimization of protein function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein denoising diffusion probabilistic models are used for the de novo generation of protein backbones but are limited in their ability to guide generation of proteins with sequence-specific attributes and functional properties. To overcome this limitation, we developed ProteinGenerator (PG), a sequence space diffusion model based on RoseTTAFold that simultaneously generates protein sequences and structures. Beginning from a noised sequence representation, PG generates sequence and structure pairs by iterative denoising, guided by desired sequence and structural protein attributes. We designed thermostable proteins with varying amino acid compositions and internal sequence repeats and cage bioactive peptides, such as melittin. By averaging sequence logits between diffusion trajectories with distinct structural constraints, we designed multistate parent–child protein triples in which the same sequence folds to different supersecondary structures when intact in the parent versus split into two child domains. PG design trajectories can be guided by experimental sequence–activity data, providing a general approach for integrated computational and experimental optimization of protein function.
Buwei Huang, Mohamad Abedi, Green Ahn, Brian Coventry, Isaac Sappington, Cong Tang, Rong Wang, Thomas Schlichthaerle, Jason Z. Zhang, Yujia Wang, Inna Goreshnik, Ching Wen Chiu, Adam Chazin-Gray, Sidney Chan, Stacey Gerben, Analisa Murray, Shunzhi Wang, Jason O’Neill, Li Yi, Ronald Yeh, Ayesha Misquith, Anitra Wolf, Luke M. Tomasovic, Dan I. Piraner, Maria J. Duran Gonzalez, Nathaniel R. Bennett, Preetham Venkatesh, Maggie Ahlrichs, Craig Dobbins, Wei Yang, Xinru Wang, Danny D. Sahtoe, Dionne Vafeados, Rubul Mout, Shirin Shivaei, Longxing Cao, Lauren Carter, Lance Stewart, Jamie B. Spangler, Kole T. Roybal, Per Jr Greisen, Xiaochun Li, Gonçalo J. L. Bernardes, Carolyn R. Bertozzi, David Baker
Designed endocytosis-inducing proteins degrade targets and amplify signals Journal Article
In: Nature, 2024.
@article{Huang2024b,
title = {Designed endocytosis-inducing proteins degrade targets and amplify signals},
author = {Buwei Huang and Mohamad Abedi and Green Ahn and Brian Coventry and Isaac Sappington and Cong Tang and Rong Wang and Thomas Schlichthaerle and Jason Z. Zhang and Yujia Wang and Inna Goreshnik and Ching Wen Chiu and Adam Chazin-Gray and Sidney Chan and Stacey Gerben and Analisa Murray and Shunzhi Wang and Jason O’Neill and Li Yi and Ronald Yeh and Ayesha Misquith and Anitra Wolf and Luke M. Tomasovic and Dan I. Piraner and Maria J. Duran Gonzalez and Nathaniel R. Bennett and Preetham Venkatesh and Maggie Ahlrichs and Craig Dobbins and Wei Yang and Xinru Wang and Danny D. Sahtoe and Dionne Vafeados and Rubul Mout and Shirin Shivaei and Longxing Cao and Lauren Carter and Lance Stewart and Jamie B. Spangler and Kole T. Roybal and Per Jr Greisen and Xiaochun Li and Gonçalo J. L. Bernardes and Carolyn R. Bertozzi and David Baker},
url = {https://www.nature.com/articles/s41586-024-07948-2, Nature [Open Access]
https://www.bakerlab.org/wp-content/uploads/2025/03/Huang-et-al-EndoTags-Nature-25Sep2024.pdf, PDF},
doi = {10.1038/s41586-024-07948-2},
year = {2024},
date = {2024-09-25},
urldate = {2024-09-25},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {Endocytosis and lysosomal trafficking of cell surface receptors can be triggered by endogenous ligands. Therapeutic approaches such as lysosome-targeting chimaeras1,2 (LYTACs) and cytokine receptor-targeting chimeras3 (KineTACs) have used this to target specific proteins for degradation by fusing modified native ligands to target binding proteins. Although powerful, these approaches can be limited by competition with native ligands and requirements for chemical modification that limit genetic encodability and can complicate manufacturing, and, more generally, there may be no native ligands that stimulate endocytosis through a given receptor. Here we describe computational design approaches for endocytosis-triggering binding proteins (EndoTags) that overcome these challenges. We present EndoTags for insulin-like growth factor 2 receptor (IGF2R) and asialoglycoprotein receptor (ASGPR), sortilin and transferrin receptors, and show that fusing these tags to soluble or transmembrane target protein binders leads to lysosomal trafficking and target degradation. As these receptors have different tissue distributions, the different EndoTags could enable targeting of degradation to different tissues. EndoTag fusion to a PD-L1 antibody considerably increases efficacy in a mouse tumour model compared to antibody alone. The modularity and genetic encodability of EndoTags enables AND gate control for higher-specificity targeted degradation, and the localized secretion of degraders from engineered cells. By promoting endocytosis, EndoTag fusion increases signalling through an engineered ligand–receptor system by nearly 100-fold. EndoTags have considerable therapeutic potential as targeted degradation inducers, signalling activators for endocytosis-dependent pathways, and cellular uptake inducers for targeted antibody–drug and antibody–RNA conjugates.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Endocytosis and lysosomal trafficking of cell surface receptors can be triggered by endogenous ligands. Therapeutic approaches such as lysosome-targeting chimaeras1,2 (LYTACs) and cytokine receptor-targeting chimeras3 (KineTACs) have used this to target specific proteins for degradation by fusing modified native ligands to target binding proteins. Although powerful, these approaches can be limited by competition with native ligands and requirements for chemical modification that limit genetic encodability and can complicate manufacturing, and, more generally, there may be no native ligands that stimulate endocytosis through a given receptor. Here we describe computational design approaches for endocytosis-triggering binding proteins (EndoTags) that overcome these challenges. We present EndoTags for insulin-like growth factor 2 receptor (IGF2R) and asialoglycoprotein receptor (ASGPR), sortilin and transferrin receptors, and show that fusing these tags to soluble or transmembrane target protein binders leads to lysosomal trafficking and target degradation. As these receptors have different tissue distributions, the different EndoTags could enable targeting of degradation to different tissues. EndoTag fusion to a PD-L1 antibody considerably increases efficacy in a mouse tumour model compared to antibody alone. The modularity and genetic encodability of EndoTags enables AND gate control for higher-specificity targeted degradation, and the localized secretion of degraders from engineered cells. By promoting endocytosis, EndoTag fusion increases signalling through an engineered ligand–receptor system by nearly 100-fold. EndoTags have considerable therapeutic potential as targeted degradation inducers, signalling activators for endocytosis-dependent pathways, and cellular uptake inducers for targeted antibody–drug and antibody–RNA conjugates.
Ian R. Humphreys, Jing Zhang, Minkyung Baek, Yaxi Wang, Aditya Krishnakumar, Jimin Pei, Ivan Anishchenko, Catherine A. Tower, Blake A. Jackson, Thulasi Warrier, Deborah T. Hung, S. Brook Peterson, Joseph D. Mougous, Qian Cong, David Baker
Protein interactions in human pathogens revealed through deep learning Journal Article
In: Nature Microbiology, 2024, ISSN: 2058-5276.
@article{Humphreys2024,
title = {Protein interactions in human pathogens revealed through deep learning},
author = {Ian R. Humphreys and Jing Zhang and Minkyung Baek and Yaxi Wang and Aditya Krishnakumar and Jimin Pei and Ivan Anishchenko and Catherine A. Tower and Blake A. Jackson and Thulasi Warrier and Deborah T. Hung and S. Brook Peterson and Joseph D. Mougous and Qian Cong and David Baker},
url = {https://www.nature.com/articles/s41564-024-01791-x, Nature Microbiology [Open Access]},
doi = {10.1038/s41564-024-01791-x},
issn = {2058-5276},
year = {2024},
date = {2024-09-18},
urldate = {2024-09-18},
journal = {Nature Microbiology},
publisher = {Springer Science and Business Media LLC},
abstract = {Identification of bacterial protein–protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lite, a rapid deep learning model that leverages residue–residue coevolution and protein structure prediction to systematically identify and structurally characterize protein–protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1,923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer-membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Identification of bacterial protein–protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lite, a rapid deep learning model that leverages residue–residue coevolution and protein structure prediction to systematically identify and structurally characterize protein–protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1,923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer-membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.
Adam P. Moyer, Theresa A. Ramelot, Mariano Curti, Margaret A. Eastman, Alex Kang, Asim K. Bera, Roberto Tejero, Patrick J. Salveson, Carles Curutchet, Elisabet Romero, Gaetano T. Montelione, David Baker
Enumerative Discovery of Noncanonical Polypeptide Secondary Structures Journal Article
In: Journal of the American Chemical Society, 2024.
@article{Moyer2024,
title = {Enumerative Discovery of Noncanonical Polypeptide Secondary Structures},
author = {Adam P. Moyer and Theresa A. Ramelot and Mariano Curti and Margaret A. Eastman and Alex Kang and Asim K. Bera and Roberto Tejero and Patrick J. Salveson and Carles Curutchet and Elisabet Romero and Gaetano T. Montelione and David Baker},
url = {https://pubs.acs.org/doi/full/10.1021/jacs.4c04991, LACS [Open Access]},
doi = {10.1021/jacs.4c04991},
year = {2024},
date = {2024-09-18},
urldate = {2024-09-18},
journal = {Journal of the American Chemical Society},
publisher = {American Chemical Society (ACS)},
abstract = {Energetically favorable local interactions can overcome the entropic cost of chain ordering and cause otherwise flexible polymers to adopt regularly repeating backbone conformations. A prominent example is the α helix present in many protein structures, which is stabilized by i, i + 4 hydrogen bonds between backbone peptide units. With the increased chemical diversity offered by unnatural amino acids and backbones, it has been possible to identify regularly repeating structures not present in proteins, but to date, there has been no systematic approach for identifying new polymers likely to have such structures despite their considerable potential for molecular engineering. Here we describe a systematic approach to search through dipeptide combinations of 130 chemically diverse amino acids to identify those predicted to populate unique low-energy states. We characterize ten newly identified dipeptide repeating structures using circular dichroism spectroscopy and comparison with calculated spectra. NMR and X-ray crystallographic structures of two of these dipeptide-repeat polymers are similar to the computational models. Our approach is readily generalizable to identify low-energy repeating structures for a wide variety of polymers, and our ordered dipeptide repeats provide new building blocks for molecular engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Energetically favorable local interactions can overcome the entropic cost of chain ordering and cause otherwise flexible polymers to adopt regularly repeating backbone conformations. A prominent example is the α helix present in many protein structures, which is stabilized by i, i + 4 hydrogen bonds between backbone peptide units. With the increased chemical diversity offered by unnatural amino acids and backbones, it has been possible to identify regularly repeating structures not present in proteins, but to date, there has been no systematic approach for identifying new polymers likely to have such structures despite their considerable potential for molecular engineering. Here we describe a systematic approach to search through dipeptide combinations of 130 chemically diverse amino acids to identify those predicted to populate unique low-energy states. We characterize ten newly identified dipeptide repeating structures using circular dichroism spectroscopy and comparison with calculated spectra. NMR and X-ray crystallographic structures of two of these dipeptide-repeat polymers are similar to the computational models. Our approach is readily generalizable to identify low-energy repeating structures for a wide variety of polymers, and our ordered dipeptide repeats provide new building blocks for molecular engineering.
Buwei Huang, Brian Coventry, Marta T. Borowska, Dimitrios C. Arhontoulis, Marc Exposit, Mohamad Abedi, Kevin M. Jude, Samer F. Halabiya, Aza Allen, Cami Cordray, Inna Goreshnik, Maggie Ahlrichs, Sidney Chan, Hillary Tunggal, Michelle DeWitt, Nathaniel Hyams, Lauren Carter, Lance Stewart, Deborah H. Fuller, Ying Mei, K. Christopher Garcia, David Baker
De novo design of miniprotein antagonists of cytokine storm inducers Journal Article
In: Nature Communications, 2024.
@article{Huang2024,
title = {De novo design of miniprotein antagonists of cytokine storm inducers},
author = {Buwei Huang and Brian Coventry and Marta T. Borowska and Dimitrios C. Arhontoulis and Marc Exposit and Mohamad Abedi and Kevin M. Jude and Samer F. Halabiya and Aza Allen and Cami Cordray and Inna Goreshnik and Maggie Ahlrichs and Sidney Chan and Hillary Tunggal and Michelle DeWitt and Nathaniel Hyams and Lauren Carter and Lance Stewart and Deborah H. Fuller and Ying Mei and K. Christopher Garcia and David Baker},
url = {https://www.nature.com/articles/s41467-024-50919-4, Nature Communications [Open Access]},
doi = {10.1038/s41467-024-50919-4},
year = {2024},
date = {2024-08-16},
urldate = {2024-08-16},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
abstract = {Cytokine release syndrome (CRS), commonly known as cytokine storm, is an acute systemic inflammatory response that is a significant global health threat. Interleukin-6 (IL-6) and interleukin-1 (IL-1) are key pro-inflammatory cytokines involved in CRS and are hence critical therapeutic targets. Current antagonists, such as tocilizumab and anakinra, target IL-6R/IL-1R but have limitations due to their long half-life and systemic anti-inflammatory effects, making them less suitable for acute or localized treatments. Here we present the de novo design of small protein antagonists that prevent IL-1 and IL-6 from interacting with their receptors to activate signaling. The designed proteins bind to the IL-6R, GP130 (an IL-6 co-receptor), and IL-1R1 receptor subunits with binding affinities in the picomolar to low-nanomolar range. X-ray crystallography studies reveal that the structures of these antagonists closely match their computational design models. In a human cardiac organoid disease model, the IL-1R antagonists demonstrated protective effects against inflammation and cardiac damage induced by IL-1β. These minibinders show promise for administration via subcutaneous injection or intranasal/inhaled routes to mitigate acute cytokine storm effects.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cytokine release syndrome (CRS), commonly known as cytokine storm, is an acute systemic inflammatory response that is a significant global health threat. Interleukin-6 (IL-6) and interleukin-1 (IL-1) are key pro-inflammatory cytokines involved in CRS and are hence critical therapeutic targets. Current antagonists, such as tocilizumab and anakinra, target IL-6R/IL-1R but have limitations due to their long half-life and systemic anti-inflammatory effects, making them less suitable for acute or localized treatments. Here we present the de novo design of small protein antagonists that prevent IL-1 and IL-6 from interacting with their receptors to activate signaling. The designed proteins bind to the IL-6R, GP130 (an IL-6 co-receptor), and IL-1R1 receptor subunits with binding affinities in the picomolar to low-nanomolar range. X-ray crystallography studies reveal that the structures of these antagonists closely match their computational design models. In a human cardiac organoid disease model, the IL-1R antagonists demonstrated protective effects against inflammation and cardiac damage induced by IL-1β. These minibinders show promise for administration via subcutaneous injection or intranasal/inhaled routes to mitigate acute cytokine storm effects.
Arvind Pillai, Abbas Idris, Annika Philomin, Connor Weidle, Rebecca Skotheim, Philip J. Y. Leung, Adam Broerman, Cullen Demakis, Andrew J. Borst, Florian Praetorius, David Baker
De novo design of allosterically switchable protein assemblies Journal Article
In: Nature, 2024.
@article{Pillai2024,
title = {De novo design of allosterically switchable protein assemblies},
author = {Arvind Pillai and Abbas Idris and Annika Philomin and Connor Weidle and Rebecca Skotheim and Philip J. Y. Leung and Adam Broerman and Cullen Demakis and Andrew J. Borst and Florian Praetorius and David Baker},
url = {https://www.nature.com/articles/s41586-024-07813-2, Nature [Open Access]},
doi = {10.1038/s41586-024-07813-2},
year = {2024},
date = {2024-08-14},
urldate = {2024-08-14},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {Allosteric modulation of protein function, wherein the binding of an effector to a protein triggers conformational changes at distant functional sites, plays a central part in the control of metabolism and cell signalling. There has been considerable interest in designing allosteric systems, both to gain insight into the mechanisms underlying such ‘action at a distance’ modulation and to create synthetic proteins whose functions can be regulated by effectors. However, emulating the subtle conformational changes distributed across many residues, characteristic of natural allosteric proteins, is a significant challenge. Here, inspired by the classic Monod–Wyman–Changeux model of cooperativity, we investigate the de novo design of allostery through rigid-body coupling of peptide-switchable hinge modules to protein interfaces that direct the formation of alternative oligomeric states. We find that this approach can be used to generate a wide variety of allosterically switchable systems, including cyclic rings that incorporate or eject subunits in response to peptide binding and dihedral cages that undergo effector-induced disassembly. Size-exclusion chromatography, mass photometry and electron microscopy reveal that these designed allosteric protein assemblies closely resemble the design models in both the presence and absence of peptide effectors and can have ligand-binding cooperativity comparable to classic natural systems such as haemoglobin. Our results indicate that allostery can arise from global coupling of the energetics of protein substructures without optimized side-chain–side-chain allosteric communication pathways and provide a roadmap for generating allosterically triggerable delivery systems, protein nanomachines and cellular feedback control circuitry.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Allosteric modulation of protein function, wherein the binding of an effector to a protein triggers conformational changes at distant functional sites, plays a central part in the control of metabolism and cell signalling. There has been considerable interest in designing allosteric systems, both to gain insight into the mechanisms underlying such ‘action at a distance’ modulation and to create synthetic proteins whose functions can be regulated by effectors. However, emulating the subtle conformational changes distributed across many residues, characteristic of natural allosteric proteins, is a significant challenge. Here, inspired by the classic Monod–Wyman–Changeux model of cooperativity, we investigate the de novo design of allostery through rigid-body coupling of peptide-switchable hinge modules to protein interfaces that direct the formation of alternative oligomeric states. We find that this approach can be used to generate a wide variety of allosterically switchable systems, including cyclic rings that incorporate or eject subunits in response to peptide binding and dihedral cages that undergo effector-induced disassembly. Size-exclusion chromatography, mass photometry and electron microscopy reveal that these designed allosteric protein assemblies closely resemble the design models in both the presence and absence of peptide effectors and can have ligand-binding cooperativity comparable to classic natural systems such as haemoglobin. Our results indicate that allostery can arise from global coupling of the energetics of protein substructures without optimized side-chain–side-chain allosteric communication pathways and provide a roadmap for generating allosterically triggerable delivery systems, protein nanomachines and cellular feedback control circuitry.
Linna An, Meerit Said, Long Tran, Sagardip Majumder, Inna Goreshnik, Gyu Rie Lee, David Juergens, Justas Dauparas, Ivan Anishchenko, Brian Coventry, Asim K. Bera, Alex Kang, Paul M. Levine, Valentina Alvarez, Arvind Pillai, Christoffer Norn, David Feldman, Dmitri Zorine, Derrick R. Hicks, Xinting Li, Mariana Garcia Sanchez, Dionne K. Vafeados, Patrick J. Salveson, Anastassia A. Vorobieva, David Baker
Binding and sensing diverse small molecules using shape-complementary pseudocycles Journal Article
In: Science, 2024.
@article{An2024,
title = {Binding and sensing diverse small molecules using shape-complementary pseudocycles},
author = {Linna An and Meerit Said and Long Tran and Sagardip Majumder and Inna Goreshnik and Gyu Rie Lee and David Juergens and Justas Dauparas and Ivan Anishchenko and Brian Coventry and Asim K. Bera and Alex Kang and Paul M. Levine and Valentina Alvarez and Arvind Pillai and Christoffer Norn and David Feldman and Dmitri Zorine and Derrick R. Hicks and Xinting Li and Mariana Garcia Sanchez and Dionne K. Vafeados and Patrick J. Salveson and Anastassia A. Vorobieva and David Baker},
url = {https://www.science.org/doi/10.1126/science.adn3780, Science},
doi = {10.1126/science.adn3780},
year = {2024},
date = {2024-07-19},
urldate = {2024-07-19},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {We describe an approach for designing high-affinity small molecule–binding proteins poised for downstream sensing. We use deep learning–generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe an approach for designing high-affinity small molecule–binding proteins poised for downstream sensing. We use deep learning–generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.
Samuel Berhanu, Sagardip Majumder, Thomas Müntener, James Whitehouse, Carolin Berner, Asim K. Bera, Alex Kang, Binyong Liang, Nasir Khan, Banumathi Sankaran, Lukas K. Tamm, David J. Brockwell, Sebastian Hiller, Sheena E. Radford, David Baker, Anastassia A. Vorobieva
Sculpting conducting nanopore size and shape through de novo protein design Journal Article
In: Science, 2024.
@article{Berhanu2024,
title = {Sculpting conducting nanopore size and shape through de novo protein design},
author = {Samuel Berhanu and Sagardip Majumder and Thomas Müntener and James Whitehouse and Carolin Berner and Asim K. Bera and Alex Kang and Binyong Liang and Nasir Khan and Banumathi Sankaran and Lukas K. Tamm and David J. Brockwell and Sebastian Hiller and Sheena E. Radford and David Baker and Anastassia A. Vorobieva},
url = {https://www.science.org/doi/10.1126/science.adn3796, Science},
doi = {10.1126/science.adn3796},
year = {2024},
date = {2024-07-19},
urldate = {2024-07-19},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {Transmembrane β-barrels have considerable potential for a broad range of sensing applications. Current engineering approaches for nanopore sensors are limited to naturally occurring channels, which provide suboptimal starting points. By contrast, de novo protein design can in principle create an unlimited number of new nanopores with any desired properties. Here we describe a general approach to designing transmembrane β-barrel pores with different diameters and pore geometries. Nuclear magnetic resonance and crystallographic characterization show that the designs are stably folded with structures resembling those of the design models. The designs have distinct conductances that correlate with their pore diameter, ranging from 110 picosiemens (~0.5 nanometer pore diameter) to 430 picosiemens (~1.1 nanometer pore diameter). Our approach opens the door to the custom design of transmembrane nanopores for sensing and sequencing applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Transmembrane β-barrels have considerable potential for a broad range of sensing applications. Current engineering approaches for nanopore sensors are limited to naturally occurring channels, which provide suboptimal starting points. By contrast, de novo protein design can in principle create an unlimited number of new nanopores with any desired properties. Here we describe a general approach to designing transmembrane β-barrel pores with different diameters and pore geometries. Nuclear magnetic resonance and crystallographic characterization show that the designs are stably folded with structures resembling those of the design models. The designs have distinct conductances that correlate with their pore diameter, ranging from 110 picosiemens (~0.5 nanometer pore diameter) to 430 picosiemens (~1.1 nanometer pore diameter). Our approach opens the door to the custom design of transmembrane nanopores for sensing and sequencing applications.
Stephanie Berger, Franziska Seeger, Ta-Yi Yu, Merve Aydin, Huilin Yang, Daniel Rosenblum, Laure Guenin-Macé, Caleb Glassman, Lauren Arguinchona, Catherine Sniezek, Alyssa Blackstone, Lauren Carter, Rashmi Ravichandran, Maggie Ahlrichs, Michael Murphy, Ingrid Swanson Pultz, Alex Kang, Asim K. Bera, Lance Stewart, K. Christopher Garcia, Shruti Naik, Jamie B. Spangler, Florian Beigel, Matthias Siebeck, Roswitha Gropp, David Baker
Preclinical proof of principle for orally delivered Th17 antagonist miniproteins Journal Article
In: Cell, 2024.
@article{Berger2024,
title = {Preclinical proof of principle for orally delivered Th17 antagonist miniproteins},
author = {Stephanie Berger and Franziska Seeger and Ta-Yi Yu and Merve Aydin and Huilin Yang and Daniel Rosenblum and Laure Guenin-Macé and Caleb Glassman and Lauren Arguinchona and Catherine Sniezek and Alyssa Blackstone and Lauren Carter and Rashmi Ravichandran and Maggie Ahlrichs and Michael Murphy and Ingrid Swanson Pultz and Alex Kang and Asim K. Bera and Lance Stewart and K. Christopher Garcia and Shruti Naik and Jamie B. Spangler and Florian Beigel and Matthias Siebeck and Roswitha Gropp and David Baker},
url = {https://www.cell.com/cell/fulltext/S0092-8674(24)00631-7, Cell [Open Access]},
doi = {10.1016/j.cell.2024.05.052},
year = {2024},
date = {2024-06-26},
urldate = {2024-06-00},
journal = {Cell},
publisher = {Elsevier BV},
abstract = {Interleukin (IL)-23 and IL-17 are well-validated therapeutic targets in autoinflammatory diseases. Antibodies targeting IL-23 and IL-17 have shown clinical efficacy but are limited by high costs, safety risks, lack of sustained efficacy, and poor patient convenience as they require parenteral administration. Here, we present designed miniproteins inhibiting IL-23R and IL-17 with antibody-like, low picomolar affinities at a fraction of the molecular size. The minibinders potently block cell signaling in vitro and are extremely stable, enabling oral administration and low-cost manufacturing. The orally administered IL-23R minibinder shows efficacy better than a clinical anti-IL-23 antibody in mouse colitis and has a favorable pharmacokinetics (PK) and biodistribution profile in rats. This work demonstrates that orally administered de novo-designed minibinders can reach a therapeutic target past the gut epithelial barrier. With high potency, gut stability, and straightforward manufacturability, de novo-designed minibinders are a promising modality for oral biologics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Interleukin (IL)-23 and IL-17 are well-validated therapeutic targets in autoinflammatory diseases. Antibodies targeting IL-23 and IL-17 have shown clinical efficacy but are limited by high costs, safety risks, lack of sustained efficacy, and poor patient convenience as they require parenteral administration. Here, we present designed miniproteins inhibiting IL-23R and IL-17 with antibody-like, low picomolar affinities at a fraction of the molecular size. The minibinders potently block cell signaling in vitro and are extremely stable, enabling oral administration and low-cost manufacturing. The orally administered IL-23R minibinder shows efficacy better than a clinical anti-IL-23 antibody in mouse colitis and has a favorable pharmacokinetics (PK) and biodistribution profile in rats. This work demonstrates that orally administered de novo-designed minibinders can reach a therapeutic target past the gut epithelial barrier. With high potency, gut stability, and straightforward manufacturability, de novo-designed minibinders are a promising modality for oral biologics.
Natasha I. Edman, Ashish Phal, Rachel L. Redler, Thomas Schlichthaerle, Sanjay R. Srivatsan, Devon Duron Ehnes, Ali Etemadi, Seong J. An, Andrew Favor, Zhe Li, Florian Praetorius, Max Gordon, Thomas Vincent, Silvia Marchiano, Leslie Blakely, Chuwei Lin, Wei Yang, Brian Coventry, Derrick R. Hicks, Longxing Cao, Neville Bethel, Piper Heine, Analisa Murray, Stacey Gerben, Lauren Carter, Marcos Miranda, Babak Negahdari, Sangwon Lee, Cole Trapnell, Ying Zheng, Charles E. Murry, Devin K. Schweppe, Benjamin S. Freedman, Lance Stewart, Damian C. Ekiert, Joseph Schlessinger, Jay Shendure, Gira Bhabha, Hannele Ruohola-Baker, David Baker,
Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies Journal Article
In: Cell, 2024.
@article{Edman2024,
title = {Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies},
author = {Natasha I. Edman,
Ashish Phal,
Rachel L. Redler,
Thomas Schlichthaerle,
Sanjay R. Srivatsan,
Devon Duron Ehnes,
Ali Etemadi,
Seong J. An,
Andrew Favor,
Zhe Li,
Florian Praetorius,
Max Gordon,
Thomas Vincent,
Silvia Marchiano,
Leslie Blakely,
Chuwei Lin,
Wei Yang,
Brian Coventry,
Derrick R. Hicks,
Longxing Cao,
Neville Bethel,
Piper Heine,
Analisa Murray,
Stacey Gerben,
Lauren Carter,
Marcos Miranda,
Babak Negahdari,
Sangwon Lee,
Cole Trapnell,
Ying Zheng,
Charles E. Murry,
Devin K. Schweppe,
Benjamin S. Freedman,
Lance Stewart,
Damian C. Ekiert,
Joseph Schlessinger,
Jay Shendure,
Gira Bhabha,
Hannele Ruohola-Baker,
David Baker, },
url = {https://authors.elsevier.com/sd/article/S0092-8674(24)00534-8, Cell (Open Access)
https://www.bakerlab.org/wp-content/uploads/2024/06/Cell_13439_Modulation_of_FGF_pathway_signalling_2024.pdf, PDF},
doi = {10.1016/j.cell.2024.05.025},
year = {2024},
date = {2024-06-10},
journal = {Cell},
abstract = {Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications.
Jiang, Hanlun and Jude, Kevin M. and Wu, Kejia and Fallas, Jorge and Ueda, George and Brunette, T. J. and Hicks, Derrick R. and Pyles, Harley and Yang, Aerin and Carter, Lauren and Lamb, Mila and Li, Xinting and Levine, Paul M. and Stewart, Lance and Garcia, K. Christopher and Baker, David
De novo design of buttressed loops for sculpting protein functions Journal Article
In: Nature Chemical Biology, 2024.
@article{Jiang2024,
title = {De novo design of buttressed loops for sculpting protein functions},
author = {Jiang, Hanlun
and Jude, Kevin M.
and Wu, Kejia
and Fallas, Jorge
and Ueda, George
and Brunette, T. J.
and Hicks, Derrick R.
and Pyles, Harley
and Yang, Aerin
and Carter, Lauren
and Lamb, Mila
and Li, Xinting
and Levine, Paul M.
and Stewart, Lance
and Garcia, K. Christopher
and Baker, David},
url = {https://www.nature.com/articles/s41589-024-01632-2, Nature Chemical Biology [Open Access]
https://www.bakerlab.org/wp-content/uploads/2024/05/s41589-024-01632-2.pdf, PDF},
doi = {10.1038/s41589-024-01632-2},
year = {2024},
date = {2024-05-30},
urldate = {2024-05-30},
journal = {Nature Chemical Biology},
abstract = {In natural proteins, structured loops have central roles in molecular recognition, signal transduction and enzyme catalysis. However, because of the intrinsic flexibility and irregularity of loop regions, organizing multiple structured loops at protein functional sites has been very difficult to achieve by de novo protein design. Here we describe a solution to this problem that designs tandem repeat proteins with structured loops (9–14 residues) buttressed by extensive hydrogen bonding interactions. Experimental characterization shows that the designs are monodisperse, highly soluble, folded and thermally stable. Crystal structures are in close agreement with the design models, with the loops structured and buttressed as designed. We demonstrate the functionality afforded by loop buttressing by designing and characterizing binders for extended peptides in which the loops form one side of an extended binding pocket. The ability to design multiple structured loops should contribute generally to efforts to design new protein functions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In natural proteins, structured loops have central roles in molecular recognition, signal transduction and enzyme catalysis. However, because of the intrinsic flexibility and irregularity of loop regions, organizing multiple structured loops at protein functional sites has been very difficult to achieve by de novo protein design. Here we describe a solution to this problem that designs tandem repeat proteins with structured loops (9–14 residues) buttressed by extensive hydrogen bonding interactions. Experimental characterization shows that the designs are monodisperse, highly soluble, folded and thermally stable. Crystal structures are in close agreement with the design models, with the loops structured and buttressed as designed. We demonstrate the functionality afforded by loop buttressing by designing and characterizing binders for extended peptides in which the loops form one side of an extended binding pocket. The ability to design multiple structured loops should contribute generally to efforts to design new protein functions.
Erin C. Yang, Robby Divine, Marcos C. Miranda, Andrew J. Borst, Will Sheffler, Jason Z. Zhang, Justin Decarreau, Amijai Saragovi, Mohamad Abedi, Nicolas Goldbach, Maggie Ahlrichs, Craig Dobbins, Alexis Hand, Suna Cheng, Mila Lamb, Paul M. Levine, Sidney Chan, Rebecca Skotheim, Jorge Fallas, George Ueda, Joshua Lubner, Masaharu Somiya, Alena Khmelinskaia, Neil P. King, David Baker
Computational design of non-porous pH-responsive antibody nanoparticles Journal Article
In: Nature Structural & Molecular Biololgy, 2024.
@article{Yang2024,
title = {Computational design of non-porous pH-responsive antibody nanoparticles},
author = {Erin C. Yang and Robby Divine and Marcos C. Miranda and Andrew J. Borst and Will Sheffler and Jason Z. Zhang and Justin Decarreau and Amijai Saragovi and Mohamad Abedi and Nicolas Goldbach and Maggie Ahlrichs and Craig Dobbins and Alexis Hand and Suna Cheng and Mila Lamb and Paul M. Levine and Sidney Chan and Rebecca Skotheim and Jorge Fallas and George Ueda and Joshua Lubner and Masaharu Somiya and Alena Khmelinskaia and Neil P. King and David Baker},
url = {https://www.nature.com/articles/s41594-024-01288-5, NSMB [Open Access]
https://www.bakerlab.org/wp-content/uploads/2024/05/Yang-etal-NSMB2024-s41594-024-01288-5.pdf, PDF},
doi = {10.1038/s41594-024-01288-5},
year = {2024},
date = {2024-05-09},
urldate = {2024-05-09},
journal = {Nature Structural & Molecular Biololgy},
publisher = {Springer Science and Business Media LLC},
abstract = {Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and is important for targeted delivery of biologics. Here we describe the design of octahedral non-porous nanoparticles with a targeting antibody on the two-fold symmetry axis, a designed trimer programmed to disassemble below a tunable pH transition point on the three-fold axis, and a designed tetramer on the four-fold symmetry axis. Designed non-covalent interfaces guide cooperative nanoparticle assembly from independently purified components, and a cryo-EM density map closely matches the computational design model. The designed nanoparticles can package protein and nucleic acid payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between 5.9 and 6.7. The ability to incorporate almost any antibody into a non-porous pH-dependent nanoparticle opens up new routes to antibody-directed targeted delivery.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and is important for targeted delivery of biologics. Here we describe the design of octahedral non-porous nanoparticles with a targeting antibody on the two-fold symmetry axis, a designed trimer programmed to disassemble below a tunable pH transition point on the three-fold axis, and a designed tetramer on the four-fold symmetry axis. Designed non-covalent interfaces guide cooperative nanoparticle assembly from independently purified components, and a cryo-EM density map closely matches the computational design model. The designed nanoparticles can package protein and nucleic acid payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between 5.9 and 6.7. The ability to incorporate almost any antibody into a non-porous pH-dependent nanoparticle opens up new routes to antibody-directed targeted delivery.
Timothy W. Craven, Mark D. Nolan, Jonathan Bailey, Samir Olatunji, Samantha J. Bann, Katherine Bowen, Nikita Ostrovitsa, Thaina M. Da Costa, Ross D. Ballantine, Dietmar Weichert, Paul M. Levine, Lance J. Stewart, Gaurav Bhardwaj, Joan A. Geoghegan, Stephen A. Cochrane, Eoin M. Scanlan, Martin Caffrey, David Baker
Computational Design of Cyclic Peptide Inhibitors of a Bacterial Membrane Lipoprotein Peptidase Journal Article
In: ACS Chemical Biology, 2024.
@article{Craven2024,
title = {Computational Design of Cyclic Peptide Inhibitors of a Bacterial Membrane Lipoprotein Peptidase},
author = {Timothy W. Craven and Mark D. Nolan and Jonathan Bailey and Samir Olatunji and Samantha J. Bann and Katherine Bowen and Nikita Ostrovitsa and Thaina M. Da Costa and Ross D. Ballantine and Dietmar Weichert and Paul M. Levine and Lance J. Stewart and Gaurav Bhardwaj and Joan A. Geoghegan and Stephen A. Cochrane and Eoin M. Scanlan and Martin Caffrey and David Baker},
url = {https://pubs.acs.org/doi/10.1021/acschembio.4c00076, ACS Chem. Bio. [Open Access]
https://www.bakerlab.org/wp-content/uploads/2024/05/craven-et-al-2024-computational-design-of-cyclic-peptide-inhibitors-of-a-bacterial-membrane-lipoprotein-peptidase.pdf, PDF},
doi = {10.1021/acschembio.4c00076},
year = {2024},
date = {2024-05-07},
urldate = {2024-05-07},
journal = {ACS Chemical Biology},
publisher = {American Chemical Society (ACS)},
abstract = {There remains a critical need for new antibiotics against multi-drug-resistant Gram-negative bacteria, a major global threat that continues to impact mortality rates. Lipoprotein signal peptidase II is an essential enzyme in the lipoprotein biosynthetic pathway of Gram-negative bacteria, making it an attractive target for antibacterial drug discovery. Although natural inhibitors of LspA have been identified, such as the cyclic depsipeptide globomycin, poor stability and production difficulties limit their use in a clinical setting. We harness computational design to generate stable de novo cyclic peptide analogues of globomycin. Only 12 peptides needed to be synthesized and tested to yield potent inhibitors, avoiding costly preparation of large libraries and screening campaigns. The most potent analogues showed comparable or better antimicrobial activity than globomycin in microdilution assays against ESKAPE-E pathogens. This work highlights computational design as a general strategy to combat antibiotic resistance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
There remains a critical need for new antibiotics against multi-drug-resistant Gram-negative bacteria, a major global threat that continues to impact mortality rates. Lipoprotein signal peptidase II is an essential enzyme in the lipoprotein biosynthetic pathway of Gram-negative bacteria, making it an attractive target for antibacterial drug discovery. Although natural inhibitors of LspA have been identified, such as the cyclic depsipeptide globomycin, poor stability and production difficulties limit their use in a clinical setting. We harness computational design to generate stable de novo cyclic peptide analogues of globomycin. Only 12 peptides needed to be synthesized and tested to yield potent inhibitors, avoiding costly preparation of large libraries and screening campaigns. The most potent analogues showed comparable or better antimicrobial activity than globomycin in microdilution assays against ESKAPE-E pathogens. This work highlights computational design as a general strategy to combat antibiotic resistance.
Patrick J. Salveson, Adam P. Moyer, Meerit Y. Said, Gizem Gӧkçe, Xinting Li, Alex Kang, Hannah Nguyen, Asim K. Bera, Paul M. Levine, Gaurav Bhardwaj, David Baker
Expansive discovery of chemically diverse structured macrocyclic oligoamides Journal Article
In: Science, 2024.
@article{Salveson2024,
title = {Expansive discovery of chemically diverse structured macrocyclic oligoamides},
author = {Patrick J. Salveson and Adam P. Moyer and Meerit Y. Said and Gizem Gӧkçe and Xinting Li and Alex Kang and Hannah Nguyen and Asim K. Bera and Paul M. Levine and Gaurav Bhardwaj and David Baker},
url = {https://www.science.org/doi/abs/10.1126/science.adk1687, Science
https://www.bakerlab.org/wp-content/uploads/2024/04/Salveson-et-al-Science-2024.pdf, PDF},
doi = {10.1126/science.adk1687},
year = {2024},
date = {2024-04-25},
urldate = {2024-01-01},
journal = {Science},
abstract = {Small macrocycles with four or fewer amino acids are among the most potent natural products known, but there is currently no way to systematically generate such compounds. We describe a computational method for identifying ordered macrocycles composed of alpha, beta, gamma, and 17 other amino acid backbone chemistries, which we used to predict 14.9 million closed cycles composed of >42,000 monomer combinations. We chemically synthesized 18 macrocycles predicted to adopt single low-energy states and determined their x-ray or nuclear magnetic resonance structures; 15 of these were very close to the design models. We illustrate the therapeutic potential of these macrocycle designs by developing selective inhibitors of three protein targets of current interest. By opening up a vast space of readily synthesizable drug-like macrocycles, our results should considerably enhance structure-based drug design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Small macrocycles with four or fewer amino acids are among the most potent natural products known, but there is currently no way to systematically generate such compounds. We describe a computational method for identifying ordered macrocycles composed of alpha, beta, gamma, and 17 other amino acid backbone chemistries, which we used to predict 14.9 million closed cycles composed of >42,000 monomer combinations. We chemically synthesized 18 macrocycles predicted to adopt single low-energy states and determined their x-ray or nuclear magnetic resonance structures; 15 of these were very close to the design models. We illustrate the therapeutic potential of these macrocycle designs by developing selective inhibitors of three protein targets of current interest. By opening up a vast space of readily synthesizable drug-like macrocycles, our results should considerably enhance structure-based drug design.
Hao Shen, Eric M. Lynch, Susrut Akkineni, Joseph L. Watson, Justin Decarreau, Neville P. Bethel, Issa Benna, William Sheffler, Daniel Farrell, Frank DiMaio, Emmanuel Derivery, James J. De Yoreo, Justin Kollman, David Baker
De novo design of pH-responsive self-assembling helical protein filaments Journal Article
In: Nature Nanotechnology, 2024.
@article{Shen2024,
title = {De novo design of pH-responsive self-assembling helical protein filaments},
author = {Hao Shen and Eric M. Lynch and Susrut Akkineni and Joseph L. Watson and Justin Decarreau and Neville P. Bethel and Issa Benna and William Sheffler and Daniel Farrell and Frank DiMaio and Emmanuel Derivery and James J. De Yoreo and Justin Kollman and David Baker},
url = {https://link.springer.com/article/10.1038/s41565-024-01641-1, Nature Nanotechnology [Open Access]
https://www.bakerlab.org/wp-content/uploads/2024/04/s41565-024-01641-1.pdf, PDF},
doi = {10.1038/s41565-024-01641-1},
year = {2024},
date = {2024-04-03},
urldate = {2024-04-03},
journal = {Nature Nanotechnology},
publisher = {Springer Science and Business Media LLC},
abstract = {Biological evolution has led to precise and dynamic nanostructures that reconfigure in response to pH and other environmental conditions. However, designing micrometre-scale protein nanostructures that are environmentally responsive remains a challenge. Here we describe the de novo design of pH-responsive protein filaments built from subunits containing six or nine buried histidine residues that assemble into micrometre-scale, well-ordered fibres at neutral pH. The cryogenic electron microscopy structure of an optimized design is nearly identical to the computational design model for both the subunit internal geometry and the subunit packing into the fibre. Electron, fluorescent and atomic force microscopy characterization reveal a sharp and reversible transition from assembled to disassembled fibres over 0.3 pH units, and rapid fibre disassembly in less than 1 s following a drop in pH. The midpoint of the transition can be tuned by modulating buried histidine-containing hydrogen bond networks. Computational protein design thus provides a route to creating unbound nanomaterials that rapidly respond to small pH changes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Biological evolution has led to precise and dynamic nanostructures that reconfigure in response to pH and other environmental conditions. However, designing micrometre-scale protein nanostructures that are environmentally responsive remains a challenge. Here we describe the de novo design of pH-responsive protein filaments built from subunits containing six or nine buried histidine residues that assemble into micrometre-scale, well-ordered fibres at neutral pH. The cryogenic electron microscopy structure of an optimized design is nearly identical to the computational design model for both the subunit internal geometry and the subunit packing into the fibre. Electron, fluorescent and atomic force microscopy characterization reveal a sharp and reversible transition from assembled to disassembled fibres over 0.3 pH units, and rapid fibre disassembly in less than 1 s following a drop in pH. The midpoint of the transition can be tuned by modulating buried histidine-containing hydrogen bond networks. Computational protein design thus provides a route to creating unbound nanomaterials that rapidly respond to small pH changes.
Sangmin Lee, Ryan D. Kibler, Quinton Dowling, Yang Hsia, Neil P. King, David Baker
Expanding protein nanocages through designed symmetry-breaking Online
2024.
@online{Lee2024,
title = {Expanding protein nanocages through designed symmetry-breaking},
author = {Sangmin Lee and Ryan D. Kibler and Quinton Dowling and Yang Hsia and Neil P. King and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2024/04/Expanding-protein-nanocages-through-designed-symmetry-breaking.pdf},
year = {2024},
date = {2024-04-02},
journal = {self published},
abstract = {Polyhedral protein nanocages have had considerable success as vaccine platforms (1–3) and are promising vehicles for biologics delivery (4–7). Hence there is considerable interest in designing larger and more complex structures capable of displaying larger numbers of antigens or packaging larger cargos. However, the regular polyhedra are the largest closed structures in which all subunits have identical local environments (8–11), and thus accessing larger and more complex closed structures requires breaking local symmetry. Viruses solve this problem by placing chemically distinct but structurally similar chains in unique environments (pseudosymmetry) (12) or utilizing identical subunits that adopt different conformations in different environments (quasisymmetry) (13–15) to access higher triangulation (T) number (13) structures with larger numbers of subunits and interior volumes. A promising route to designing larger and more complex nanocages is to start from regular polyhedral nanocages (T=1) constructed from a symmetric homotrimeric building block, isolate cyclic arrangements of these building blocks by substituting in pseudosymmetric heterotrimers, and then build T=4 and larger structures by combining these with additional homo- and heterotrimers. Here we provide a high-level geometric overview of this design approach to illustrate how tradeoffs between design diversity and design economy can be used to achieve different design outcomes, as demonstrated experimentally in two accompanying papers, Lee et al (16) and Dowling et al (17).},
howpublished = {self published},
keywords = {},
pubstate = {published},
tppubtype = {online}
}
Polyhedral protein nanocages have had considerable success as vaccine platforms (1–3) and are promising vehicles for biologics delivery (4–7). Hence there is considerable interest in designing larger and more complex structures capable of displaying larger numbers of antigens or packaging larger cargos. However, the regular polyhedra are the largest closed structures in which all subunits have identical local environments (8–11), and thus accessing larger and more complex closed structures requires breaking local symmetry. Viruses solve this problem by placing chemically distinct but structurally similar chains in unique environments (pseudosymmetry) (12) or utilizing identical subunits that adopt different conformations in different environments (quasisymmetry) (13–15) to access higher triangulation (T) number (13) structures with larger numbers of subunits and interior volumes. A promising route to designing larger and more complex nanocages is to start from regular polyhedral nanocages (T=1) constructed from a symmetric homotrimeric building block, isolate cyclic arrangements of these building blocks by substituting in pseudosymmetric heterotrimers, and then build T=4 and larger structures by combining these with additional homo- and heterotrimers. Here we provide a high-level geometric overview of this design approach to illustrate how tradeoffs between design diversity and design economy can be used to achieve different design outcomes, as demonstrated experimentally in two accompanying papers, Lee et al (16) and Dowling et al (17).
Sanaa Mansoor, Minkyung Baek, Hahnbeom Park, Gyu Rie Lee, David Baker
Protein Ensemble Generation Through Variational Autoencoder Latent Space Sampling Journal Article
In: J. Chem. Theory Comput., 2024.
@article{Mansoor2024,
title = {Protein Ensemble Generation Through Variational Autoencoder Latent Space Sampling},
author = {Sanaa Mansoor and Minkyung Baek and Hahnbeom Park and Gyu Rie Lee and David Baker},
url = {https://pubs.acs.org/doi/10.1021/acs.jctc.3c01057, J. Chem. Theory Comput.
https://www.bakerlab.org/wp-content/uploads/2024/05/mansoor-et-al-2024-protein-ensemble-generation-through-variational-autoencoder-latent-space-sampling.pdf, PDF},
doi = {10.1021/acs.jctc.3c01057},
year = {2024},
date = {2024-03-28},
urldate = {2024-04-09},
journal = {J. Chem. Theory Comput.},
publisher = {American Chemical Society (ACS)},
abstract = {Mapping the ensemble of protein conformations that contribute to function and can be targeted by small molecule drugs remains an outstanding challenge. Here, we explore the use of variational autoencoders for reducing the challenge of dimensionality in the protein structure ensemble generation problem. We convert high-dimensional protein structural data into a continuous, low-dimensional representation, carry out a search in this space guided by a structure quality metric, and then use RoseTTAFold guided by the sampled structural information to generate 3D structures. We use this approach to generate ensembles for the cancer relevant protein K-Ras, train the VAE on a subset of the available K-Ras crystal structures and MD simulation snapshots, and assess the extent of sampling close to crystal structures withheld from training. We find that our latent space sampling procedure rapidly generates ensembles with high structural quality and is able to sample within 1 Å of held-out crystal structures, with a consistency higher than that of MD simulation or AlphaFold2 prediction. The sampled structures sufficiently recapitulate the cryptic pockets in the held-out K-Ras structures to allow for small molecule docking.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mapping the ensemble of protein conformations that contribute to function and can be targeted by small molecule drugs remains an outstanding challenge. Here, we explore the use of variational autoencoders for reducing the challenge of dimensionality in the protein structure ensemble generation problem. We convert high-dimensional protein structural data into a continuous, low-dimensional representation, carry out a search in this space guided by a structure quality metric, and then use RoseTTAFold guided by the sampled structural information to generate 3D structures. We use this approach to generate ensembles for the cancer relevant protein K-Ras, train the VAE on a subset of the available K-Ras crystal structures and MD simulation snapshots, and assess the extent of sampling close to crystal structures withheld from training. We find that our latent space sampling procedure rapidly generates ensembles with high structural quality and is able to sample within 1 Å of held-out crystal structures, with a consistency higher than that of MD simulation or AlphaFold2 prediction. The sampled structures sufficiently recapitulate the cryptic pockets in the held-out K-Ras structures to allow for small molecule docking.
Danny D. Sahtoe, Ewa A. Andrzejewska, Hannah L. Han, Enrico Rennella, Matthias M. Schneider, Georg Meisl, Maggie Ahlrichs, Justin Decarreau, Hannah Nguyen, Alex Kang, Paul Levine, Mila Lamb, Xinting Li, Asim K. Bera, Lewis E. Kay, Tuomas P. J. Knowles, David Baker
Design of amyloidogenic peptide traps Journal Article
In: Nature Chemical Biology, 2024.
@article{Sahtoe2024,
title = {Design of amyloidogenic peptide traps},
author = {Danny D. Sahtoe and Ewa A. Andrzejewska and Hannah L. Han and Enrico Rennella and Matthias M. Schneider and Georg Meisl and Maggie Ahlrichs and Justin Decarreau and Hannah Nguyen and Alex Kang and Paul Levine and Mila Lamb and Xinting Li and Asim K. Bera and Lewis E. Kay and Tuomas P. J. Knowles and David Baker},
url = {https://www.nature.com/articles/s41589-024-01578-5, Nature Chemical Biology [Open Access]},
doi = {10.1038/s41589-024-01578-5},
year = {2024},
date = {2024-03-19},
urldate = {2024-03-19},
journal = {Nature Chemical Biology},
publisher = {Springer Science and Business Media LLC},
abstract = {Segments of proteins with high β-strand propensity can self-associate to form amyloid fibrils implicated in many diseases. We describe a general approach to bind such segments in β-strand and β-hairpin conformations using de novo designed scaffolds that contain deep peptide-binding clefts. The designs bind their cognate peptides in vitro with nanomolar affinities. The crystal structure of a designed protein−peptide complex is close to the design model, and NMR characterization reveals how the peptide-binding cleft is protected in the apo state. We use the approach to design binders to the amyloid-forming proteins transthyretin, tau, serum amyloid A1 and amyloid β1−42 (Aβ42). The Aβ binders block the assembly of Aβ fibrils as effectively as the most potent of the clinically tested antibodies to date and protect cells from toxic Aβ42 species.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Segments of proteins with high β-strand propensity can self-associate to form amyloid fibrils implicated in many diseases. We describe a general approach to bind such segments in β-strand and β-hairpin conformations using de novo designed scaffolds that contain deep peptide-binding clefts. The designs bind their cognate peptides in vitro with nanomolar affinities. The crystal structure of a designed protein−peptide complex is close to the design model, and NMR characterization reveals how the peptide-binding cleft is protected in the apo state. We use the approach to design binders to the amyloid-forming proteins transthyretin, tau, serum amyloid A1 and amyloid β1−42 (Aβ42). The Aβ binders block the assembly of Aβ fibrils as effectively as the most potent of the clinically tested antibodies to date and protect cells from toxic Aβ42 species.
Timothy F. Huddy, Yang Hsia, Ryan D. Kibler, Jinwei Xu, Neville Bethel, Deepesh Nagarajan, Rachel Redler, Philip J. Y. Leung, Connor Weidle, Alexis Courbet, Erin C. Yang, Asim K. Bera, Nicolas Coudray, S. John Calise, Fatima A. Davila-Hernandez, Hannah L. Han, Kenneth D. Carr, Zhe Li, Ryan McHugh, Gabriella Reggiano, Alex Kang, Banumathi Sankaran, Miles S. Dickinson, Brian Coventry, T. J. Brunette, Yulai Liu, Justas Dauparas, Andrew J. Borst, Damian Ekiert, Justin M. Kollman, Gira Bhabha, David Baker
Blueprinting extendable nanomaterials with standardized protein blocks Journal Article
In: Nature, 2024.
@article{Huddy2024,
title = {Blueprinting extendable nanomaterials with standardized protein blocks},
author = {Timothy F. Huddy and Yang Hsia and Ryan D. Kibler and Jinwei Xu and Neville Bethel and Deepesh Nagarajan and Rachel Redler and Philip J. Y. Leung and Connor Weidle and Alexis Courbet and Erin C. Yang and Asim K. Bera and Nicolas Coudray and S. John Calise and Fatima A. Davila-Hernandez and Hannah L. Han and Kenneth D. Carr and Zhe Li and Ryan McHugh and Gabriella Reggiano and Alex Kang and Banumathi Sankaran and Miles S. Dickinson and Brian Coventry and T. J. Brunette and Yulai Liu and Justas Dauparas and Andrew J. Borst and Damian Ekiert and Justin M. Kollman and Gira Bhabha and David Baker},
url = {https://www.nature.com/articles/s41586-024-07188-4, Nature [Open Access]},
doi = {10.1038/s41586-024-07188-4},
year = {2024},
date = {2024-03-13},
urldate = {2024-03-13},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight ‘train track’ assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence–structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to ‘back of an envelope’ architectural blueprints.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight ‘train track’ assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence–structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to ‘back of an envelope’ architectural blueprints.
Rohith Krishna, Jue Wang, Woody Ahern, Pascal Sturmfels, Preetham Venkatesh, Indrek Kalvet, Gyu Rie Lee, Felix S. Morey-Burrows, Ivan Anishchenko, Ian R. Humphreys, Ryan McHugh, Dionne Vafeados, Xinting Li, George A. Sutherland, Andrew Hitchcock, C. Neil Hunter, Alex Kang, Evans Brackenbrough, Asim K. Bera, Minkyung Baek, Frank DiMaio, David Baker
Generalized biomolecular modeling and design with RoseTTAFold All-Atom Journal Article
In: Science, 2024.
@article{Krishna2024,
title = {Generalized biomolecular modeling and design with RoseTTAFold All-Atom},
author = {Rohith Krishna and Jue Wang and Woody Ahern and Pascal Sturmfels and Preetham Venkatesh and Indrek Kalvet and Gyu Rie Lee and Felix S. Morey-Burrows and Ivan Anishchenko and Ian R. Humphreys and Ryan McHugh and Dionne Vafeados and Xinting Li and George A. Sutherland and Andrew Hitchcock and C. Neil Hunter and Alex Kang and Evans Brackenbrough and Asim K. Bera and Minkyung Baek and Frank DiMaio and David Baker},
url = {https://www.science.org/stoken/author-tokens/ST-1739/full, Science [Full Access Link]
https://www.bakerlab.org/wp-content/uploads/2024/03/science.adl2528.pdf, PDF},
doi = {10.1126/science.adl2528},
year = {2024},
date = {2024-03-07},
urldate = {2024-03-07},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {Deep learning methods have revolutionized protein structure prediction and design but are currently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA) which combines a residue-based representation of amino acids and DNA bases with an atomic representation of all other groups to model assemblies containing proteins, nucleic acids, small molecules, metals, and covalent modifications given their sequences and chemical structures. By fine tuning on denoising tasks we obtain RFdiffusionAA, which builds protein structures around small molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we design and experimentally validate, through crystallography and binding measurements, proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and the light harvesting molecule bilin.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Deep learning methods have revolutionized protein structure prediction and design but are currently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA) which combines a residue-based representation of amino acids and DNA bases with an atomic representation of all other groups to model assemblies containing proteins, nucleic acids, small molecules, metals, and covalent modifications given their sequences and chemical structures. By fine tuning on denoising tasks we obtain RFdiffusionAA, which builds protein structures around small molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we design and experimentally validate, through crystallography and binding measurements, proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and the light harvesting molecule bilin.
Rubul Mout, Ross C. Bretherton, Justin Decarreau, Sangmin Lee, Nicole Gregorio, Natasha I. Edman, Maggie Ahlrichs, Yang Hsia, Danny D. Sahtoe, George Ueda, Alee Sharma, Rebecca Schulman, Cole A. DeForest, David Baker
De novo design of modular protein hydrogels with programmable intra- and extracellular viscoelasticity Journal Article
In: Proceedings of the National Academy of Sciences, 2024.
@article{Mout2024,
title = {De novo design of modular protein hydrogels with programmable intra- and extracellular viscoelasticity},
author = {Rubul Mout, Ross C. Bretherton, Justin Decarreau, Sangmin Lee, Nicole Gregorio, Natasha I. Edman, Maggie Ahlrichs, Yang Hsia, Danny D. Sahtoe, George Ueda, Alee Sharma, Rebecca Schulman, Cole A. DeForest, David Baker},
url = {https://www.pnas.org/doi/full/10.1073/pnas.2309457121, PNAS [Open Access]},
doi = {10.1073/pnas.2309457121},
year = {2024},
date = {2024-01-30},
urldate = {2024-01-30},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Relating the macroscopic properties of protein-based materials to their underlying component microstructure is an outstanding challenge. Here, we exploit computational design to specify the size, flexibility, and valency of de novo protein building blocks, as well as the interaction dynamics between them, to investigate how molecular parameters govern the macroscopic viscoelasticity of the resultant protein hydrogels. We construct gel systems from pairs of symmetric protein homo-oligomers, each comprising 2, 5, 24, or 120 individual protein components, that are crosslinked either physically or covalently into idealized step-growth biopolymer networks. Through rheological assessment, we find that the covalent linkage of multifunctional precursors yields hydrogels whose viscoelasticity depends on the crosslink length between the constituent building blocks. In contrast, reversibly crosslinking the homo-oligomeric components with a computationally designed heterodimer results in viscoelastic biomaterials exhibiting fluid-like properties under rest and low shear, but solid-like behavior at higher frequencies. Exploiting the unique genetic encodability of these materials, we demonstrate the assembly of protein networks within living mammalian cells and show via fluorescence recovery after photobleaching (FRAP) that mechanical properties can be tuned intracellularly in a manner similar to formulations formed extracellularly. We anticipate that the ability to modularly construct and systematically program the viscoelastic properties of designer protein-based materials could have broad utility in biomedicine, with applications in tissue engineering, therapeutic delivery, and synthetic biology.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Relating the macroscopic properties of protein-based materials to their underlying component microstructure is an outstanding challenge. Here, we exploit computational design to specify the size, flexibility, and valency of de novo protein building blocks, as well as the interaction dynamics between them, to investigate how molecular parameters govern the macroscopic viscoelasticity of the resultant protein hydrogels. We construct gel systems from pairs of symmetric protein homo-oligomers, each comprising 2, 5, 24, or 120 individual protein components, that are crosslinked either physically or covalently into idealized step-growth biopolymer networks. Through rheological assessment, we find that the covalent linkage of multifunctional precursors yields hydrogels whose viscoelasticity depends on the crosslink length between the constituent building blocks. In contrast, reversibly crosslinking the homo-oligomeric components with a computationally designed heterodimer results in viscoelastic biomaterials exhibiting fluid-like properties under rest and low shear, but solid-like behavior at higher frequencies. Exploiting the unique genetic encodability of these materials, we demonstrate the assembly of protein networks within living mammalian cells and show via fluorescence recovery after photobleaching (FRAP) that mechanical properties can be tuned intracellularly in a manner similar to formulations formed extracellularly. We anticipate that the ability to modularly construct and systematically program the viscoelastic properties of designer protein-based materials could have broad utility in biomedicine, with applications in tissue engineering, therapeutic delivery, and synthetic biology.
David Baker, George Church
Protein design meets biosecurity Journal Article
In: Science, 2024.
@article{Baker2024,
title = {Protein design meets biosecurity},
author = {David Baker and George Church},
url = {https://www.science.org/doi/10.1126/science.ado1671, Science [Open Access]
https://www.bakerlab.org/wp-content/uploads/2024/04/Baker-Church-Protein-design-meets-biosecurity-Science-25-Jan-2024.pdf, PDF},
doi = {10.1126/science.ado1671},
year = {2024},
date = {2024-01-26},
urldate = {2024-01-26},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {The power and accuracy of computational protein design have been increasing rapidly with the incorporation of artificial intelligence (AI) approaches. This promises to transform biotechnology, enabling advances across sustainability and medicine. DNA synthesis plays a critical role in materializing designed proteins. However, as with all major revolutionary changes, this technology is vulnerable to misuse and the production of dangerous biological agents. To enable the full benefits of this revolution while mitigating risks that may emerge, all synthetic gene sequence and synthesis data should be collected and stored in repositories that are only queried in emergencies to ensure that protein design proceeds in a safe, secure, and trustworthy manner.},
howpublished = {Science},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The power and accuracy of computational protein design have been increasing rapidly with the incorporation of artificial intelligence (AI) approaches. This promises to transform biotechnology, enabling advances across sustainability and medicine. DNA synthesis plays a critical role in materializing designed proteins. However, as with all major revolutionary changes, this technology is vulnerable to misuse and the production of dangerous biological agents. To enable the full benefits of this revolution while mitigating risks that may emerge, all synthetic gene sequence and synthesis data should be collected and stored in repositories that are only queried in emergencies to ensure that protein design proceeds in a safe, secure, and trustworthy manner.
Jason Zhang, William Nguyen, Nathan Greenwood, John Rose, Shao-En Ong, Dustin Maly, David Baker
Computationally designed sensors detect endogenous Ras activity and signaling effectors at subcellular resolution Journal Article
In: Nature Biotechnology, 2024.
@article{Zhang2024,
title = {Computationally designed sensors detect endogenous Ras activity and signaling effectors at subcellular resolution},
author = {Jason Zhang, William Nguyen, Nathan Greenwood, John Rose, Shao-En Ong, Dustin Maly, David Baker},
url = {https://www.nature.com/articles/s41587-023-02107-w, Nature Biotechnology [Open Access]},
doi = {10.1038/s41587-023-02107-w},
year = {2024},
date = {2024-01-25},
journal = {Nature Biotechnology},
abstract = {The utility of genetically encoded biosensors for sensing the activity of signaling proteins has been hampered by a lack of strategies for matching sensor sensitivity to the physiological concentration range of the target. Here we used computational protein design to generate intracellular sensors of Ras activity (LOCKR-based Sensor for Ras activity (Ras-LOCKR-S)) and proximity labelers of the Ras signaling environment (LOCKR-based, Ras activity-dependent Proximity Labeler (Ras-LOCKR-PL)). These tools allow the detection of endogenous Ras activity and labeling of the surrounding environment at subcellular resolution. Using these sensors in human cancer cell lines, we identified Ras-interacting proteins in oncogenic EML4-Alk granules and found that Src-Associated in Mitosis 68-kDa (SAM68) protein specifically enhances Ras activity in the granules. The ability to subcellularly localize endogenous Ras activity should deepen our understanding of Ras function in health and disease and may suggest potential therapeutic strategies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The utility of genetically encoded biosensors for sensing the activity of signaling proteins has been hampered by a lack of strategies for matching sensor sensitivity to the physiological concentration range of the target. Here we used computational protein design to generate intracellular sensors of Ras activity (LOCKR-based Sensor for Ras activity (Ras-LOCKR-S)) and proximity labelers of the Ras signaling environment (LOCKR-based, Ras activity-dependent Proximity Labeler (Ras-LOCKR-PL)). These tools allow the detection of endogenous Ras activity and labeling of the surrounding environment at subcellular resolution. Using these sensors in human cancer cell lines, we identified Ras-interacting proteins in oncogenic EML4-Alk granules and found that Src-Associated in Mitosis 68-kDa (SAM68) protein specifically enhances Ras activity in the granules. The ability to subcellularly localize endogenous Ras activity should deepen our understanding of Ras function in health and disease and may suggest potential therapeutic strategies.
Kiera H Sumida, Reyes Núñez-Franco, Indrek Kalvet, Samuel J Pellock, Basile I M Wicky, Lukas F Milles, Justas Dauparas, Jue Wang, Yakov Kipnis, Noel Jameson, Alex Kang, Joshmyn De La Cruz, Banumathi Sankaran, Asim K Bera, Gonzalo Jiménez-Osés, David Baker
Improving Protein Expression, Stability, and Function with ProteinMPNN Journal Article
In: JACS, 2024.
@article{Sumida2024,
title = {Improving Protein Expression, Stability, and Function with ProteinMPNN},
author = {Kiera H Sumida and Reyes Núñez-Franco and Indrek Kalvet and Samuel J Pellock and Basile I M Wicky and Lukas F Milles and Justas Dauparas and Jue Wang and Yakov Kipnis and Noel Jameson and Alex Kang and Joshmyn De La Cruz and Banumathi Sankaran and Asim K Bera and Gonzalo Jiménez-Osés and David Baker},
url = {https://pubs.acs.org/doi/10.1021/jacs.3c10941, JACS [Open Access]},
doi = {10.1021/jacs.3c10941},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {JACS},
abstract = {Natural proteins are highly optimized for function but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here, we show that the deep neural network ProteinMPNN, together with evolutionary and structural information, provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Natural proteins are highly optimized for function but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here, we show that the deep neural network ProteinMPNN, together with evolutionary and structural information, provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins.
COLLABORATOR LED
Brianne R. King, Kiera H. Sumida, Jessica L. Caruso, David Baker, Jesse G. Zalatan
Computational Stabilization of a Non‐Heme Iron Enzyme Enables Efficient Evolution of New Function Journal Article
In: Angew Chem Int Ed, 2024, ISSN: 1521-3773.
@article{King2024,
title = {Computational Stabilization of a Non‐Heme Iron Enzyme Enables Efficient Evolution of New Function},
author = {Brianne R. King and Kiera H. Sumida and Jessica L. Caruso and David Baker and Jesse G. Zalatan},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/anie.202414705, Angew Chem Int Ed
https://www.bakerlab.org/wp-content/uploads/2025/02/Angew-Chem-Int-Ed-2024-King-Computational-Stabilization-of-a-Non‐Heme-Iron-Enzyme-Enables-Efficient-Evolution-of-New.pdf, PDF},
doi = {10.1002/anie.202414705},
issn = {1521-3773},
year = {2024},
date = {2024-10-12},
urldate = {2025-01-10},
journal = {Angew Chem Int Ed},
publisher = {Wiley},
abstract = {Deep learning tools for enzyme design are rapidly emerging, and there is a critical need to evaluate their effectiveness in engineering workflows. Here we show that the deep learning-based tool ProteinMPNN can be used to redesign Fe(II)/αKG superfamily enzymes for greater stability, solubility, and expression while retaining both native activity and industrially relevant non-native functions. This superfamily has diverse catalytic functions and could provide a rich new source of biocatalysts for synthesis and industrial processes. Through systematic comparisons of directed evolution trajectories for a non-native, remote C(sp3)−H hydroxylation reaction, we demonstrate that the stabilized redesign can be evolved more efficiently than the wild-type enzyme. After three rounds of directed evolution, we obtained a 6-fold activity increase from the wild-type parent and an 80-fold increase from the stabilized variant. To generate the initial stabilized variant, we identified multiple structural and sequence constraints to preserve catalytic function. We applied these criteria to produce stabilized, catalytically active variants of a second Fe(II)/αKG enzyme, suggesting that the approach is generalizable to additional members of the Fe(II)/αKG superfamily. ProteinMPNN is user-friendly and widely accessible, and our results provide a framework for the routine implementation of deep learning-based protein stabilization tools in directed evolution workflows for novel biocatalysts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Deep learning tools for enzyme design are rapidly emerging, and there is a critical need to evaluate their effectiveness in engineering workflows. Here we show that the deep learning-based tool ProteinMPNN can be used to redesign Fe(II)/αKG superfamily enzymes for greater stability, solubility, and expression while retaining both native activity and industrially relevant non-native functions. This superfamily has diverse catalytic functions and could provide a rich new source of biocatalysts for synthesis and industrial processes. Through systematic comparisons of directed evolution trajectories for a non-native, remote C(sp3)−H hydroxylation reaction, we demonstrate that the stabilized redesign can be evolved more efficiently than the wild-type enzyme. After three rounds of directed evolution, we obtained a 6-fold activity increase from the wild-type parent and an 80-fold increase from the stabilized variant. To generate the initial stabilized variant, we identified multiple structural and sequence constraints to preserve catalytic function. We applied these criteria to produce stabilized, catalytically active variants of a second Fe(II)/αKG enzyme, suggesting that the approach is generalizable to additional members of the Fe(II)/αKG superfamily. ProteinMPNN is user-friendly and widely accessible, and our results provide a framework for the routine implementation of deep learning-based protein stabilization tools in directed evolution workflows for novel biocatalysts.
Alexandr Baryshev, Alyssa La Fleur, Benjamin Groves, Cirstyn Michel, David Baker, Ajasja Ljubetič, Georg Seelig
Massively parallel measurement of protein–protein interactions by sequencing using MP3-seq Journal Article
In: Nature Chemical Biology, 2024.
@article{Baryshev2024,
title = {Massively parallel measurement of protein–protein interactions by sequencing using MP3-seq},
author = {Alexandr Baryshev and Alyssa La Fleur and Benjamin Groves and Cirstyn Michel and David Baker and Ajasja Ljubetič and Georg Seelig},
url = {https://www.nature.com/articles/s41589-024-01718-x, Nature Chemical Biology [Open Access]},
doi = {10.1038/s41589-024-01718-x},
year = {2024},
date = {2024-08-27},
urldate = {2024-08-27},
journal = {Nature Chemical Biology},
publisher = {Springer Science and Business Media LLC},
abstract = {Protein–protein interactions (PPIs) regulate many cellular processes and engineered PPIs have cell and gene therapy applications. Here, we introduce massively parallel PPI measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Lastly, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics-based energy terms to predict MP3-seq values. We find that AF-M-based models could be valuable for prescreening interactions but experimentally measuring interactions remains necessary to rank their strengths quantitatively.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein–protein interactions (PPIs) regulate many cellular processes and engineered PPIs have cell and gene therapy applications. Here, we introduce massively parallel PPI measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Lastly, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics-based energy terms to predict MP3-seq values. We find that AF-M-based models could be valuable for prescreening interactions but experimentally measuring interactions remains necessary to rank their strengths quantitatively.
Ke Sun, Sicong Li, Bowen Zheng, Yanlei Zhu, Tongyue Wang, Mingfu Liang, Yue Yao, Kairan Zhang, Jizhong Zhang, Hongyong Li, Dongyang Han, Jishen Zheng, Brian Coventry, Longxing Cao, David Baker, Lei Liu, Peilong Lu
Accurate de novo design of heterochiral protein–protein interactions Journal Article
In: Cell Research, 2024.
@article{Sun2024,
title = {Accurate de novo design of heterochiral protein–protein interactions},
author = {Ke Sun and Sicong Li and Bowen Zheng and Yanlei Zhu and Tongyue Wang and Mingfu Liang and Yue Yao and Kairan Zhang and Jizhong Zhang and Hongyong Li and Dongyang Han and Jishen Zheng and Brian Coventry and Longxing Cao and David Baker and Lei Liu and Peilong Lu},
url = {https://www.nature.com/articles/s41422-024-01014-2, Cell Research [Open Access]},
doi = {10.1038/s41422-024-01014-2},
year = {2024},
date = {2024-08-14},
urldate = {2024-08-14},
journal = {Cell Research},
publisher = {Springer Science and Business Media LLC},
abstract = {Abiotic d-proteins that selectively bind to natural l-proteins have gained significant biotechnological interest. However, the underlying structural principles governing such heterochiral protein–protein interactions remain largely unknown. In this study, we present the de novo design of d-proteins consisting of 50–65 residues, aiming to target specific surface regions of l-proteins or l-peptides. Our designer d-protein binders exhibit nanomolar affinity toward an artificial l-peptide, as well as two naturally occurring proteins of therapeutic significance: the D5 domain of human tropomyosin receptor kinase A (TrkA) and human interleukin-6 (IL-6). Notably, these d-protein binders demonstrate high enantiomeric specificity and target specificity. In cell-based experiments, designer d-protein binders effectively inhibited the downstream signaling of TrkA and IL-6 with high potency. Moreover, these binders exhibited remarkable thermal stability and resistance to protease degradation. Crystal structure of the designed heterochiral d-protein–l-peptide complex, obtained at a resolution of 2.0 Å, closely resembled the design model, indicating that the computational method employed is highly accurate. Furthermore, the crystal structure provides valuable information regarding the interactions between helical l-peptides and d-proteins, particularly elucidating a novel mode of heterochiral helix–helix interactions. Leveraging the design of d-proteins specifically targeting l-peptides or l-proteins opens up avenues for systematic exploration of the mirror-image protein universe, paving the way for a diverse range of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abiotic d-proteins that selectively bind to natural l-proteins have gained significant biotechnological interest. However, the underlying structural principles governing such heterochiral protein–protein interactions remain largely unknown. In this study, we present the de novo design of d-proteins consisting of 50–65 residues, aiming to target specific surface regions of l-proteins or l-peptides. Our designer d-protein binders exhibit nanomolar affinity toward an artificial l-peptide, as well as two naturally occurring proteins of therapeutic significance: the D5 domain of human tropomyosin receptor kinase A (TrkA) and human interleukin-6 (IL-6). Notably, these d-protein binders demonstrate high enantiomeric specificity and target specificity. In cell-based experiments, designer d-protein binders effectively inhibited the downstream signaling of TrkA and IL-6 with high potency. Moreover, these binders exhibited remarkable thermal stability and resistance to protease degradation. Crystal structure of the designed heterochiral d-protein–l-peptide complex, obtained at a resolution of 2.0 Å, closely resembled the design model, indicating that the computational method employed is highly accurate. Furthermore, the crystal structure provides valuable information regarding the interactions between helical l-peptides and d-proteins, particularly elucidating a novel mode of heterochiral helix–helix interactions. Leveraging the design of d-proteins specifically targeting l-peptides or l-proteins opens up avenues for systematic exploration of the mirror-image protein universe, paving the way for a diverse range of applications.
Jason Z. Zhang, Shao-En Ong, David Baker, Dustin J. Maly
Single-cell sensor analyses reveal signaling programs enabling Ras-G12C drug resistance Journal Article
In: Nature Chemical Biology, 2024.
@article{Zhang2024b,
title = {Single-cell sensor analyses reveal signaling programs enabling Ras-G12C drug resistance},
author = {Jason Z. Zhang and Shao-En Ong and David Baker and Dustin J. Maly},
url = {https://www.nature.com/articles/s41589-024-01684-4, Nat Chem Biol [Open Access]},
doi = {10.1038/s41589-024-01684-4},
year = {2024},
date = {2024-08-05},
urldate = {2024-08-05},
journal = {Nature Chemical Biology},
publisher = {Springer Science and Business Media LLC},
abstract = {Clinical resistance to rat sarcoma virus (Ras)-G12C inhibitors is a challenge. A subpopulation of cancer cells has been shown to undergo genomic and transcriptional alterations to facilitate drug resistance but the immediate adaptive effects on Ras signaling in response to these drugs at the single-cell level is not well understood. Here, we used Ras biosensors to profile the activity and signaling environment of endogenous Ras at the single-cell level. We found that a subpopulation of KRas-G12C cells treated with Ras-G12C-guanosine-diphosphate inhibitors underwent adaptive signaling and metabolic changes driven by wild-type Ras at the Golgi and mutant KRas at the mitochondria, respectively. Our Ras biosensors identified major vault protein as a mediator of Ras activation through its scaffolding of Ras signaling pathway components and metabolite channels. Overall, methods including ours that facilitate direct analysis on the single-cell level can report the adaptations that subpopulations of cells adopt in response to cancer therapies, thus providing insight into drug resistance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Clinical resistance to rat sarcoma virus (Ras)-G12C inhibitors is a challenge. A subpopulation of cancer cells has been shown to undergo genomic and transcriptional alterations to facilitate drug resistance but the immediate adaptive effects on Ras signaling in response to these drugs at the single-cell level is not well understood. Here, we used Ras biosensors to profile the activity and signaling environment of endogenous Ras at the single-cell level. We found that a subpopulation of KRas-G12C cells treated with Ras-G12C-guanosine-diphosphate inhibitors underwent adaptive signaling and metabolic changes driven by wild-type Ras at the Golgi and mutant KRas at the mitochondria, respectively. Our Ras biosensors identified major vault protein as a mediator of Ras activation through its scaffolding of Ras signaling pathway components and metabolite channels. Overall, methods including ours that facilitate direct analysis on the single-cell level can report the adaptations that subpopulations of cells adopt in response to cancer therapies, thus providing insight into drug resistance.
Justin A. Peruzzi, Taylor F. Gunnels, Hailey I. Edelstein, Peilong Lu, David Baker, Joshua N. Leonard, Neha P. Kamat
Enhancing extracellular vesicle cargo loading and functional delivery by engineering protein-lipid interactions Journal Article
In: Nature Communications, 2024.
@article{Peruzzi2024b,
title = {Enhancing extracellular vesicle cargo loading and functional delivery by engineering protein-lipid interactions},
author = {Justin A. Peruzzi and Taylor F. Gunnels and Hailey I. Edelstein and Peilong Lu and David Baker and Joshua N. Leonard and Neha P. Kamat},
url = {https://www.nature.com/articles/s41467-024-49678-z [Nature Communications, Open Access]},
doi = {10.1038/s41467-024-49678-z},
year = {2024},
date = {2024-07-04},
urldate = {2024-12-00},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
abstract = {Naturally generated lipid nanoparticles termed extracellular vesicles (EVs) hold significant promise as engineerable therapeutic delivery vehicles. However, active loading of protein cargo into EVs in a manner that is useful for delivery remains a challenge. Here, we demonstrate that by rationally designing proteins to traffic to the plasma membrane and associate with lipid rafts, we can enhance loading of protein cargo into EVs for a set of structurally diverse transmembrane and peripheral membrane proteins. We then demonstrate the capacity of select lipid tags to mediate increased EV loading and functional delivery of an engineered transcription factor to modulate gene expression in target cells. We envision that this technology could be leveraged to develop new EV-based therapeutics that deliver a wide array of macromolecular cargo.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Naturally generated lipid nanoparticles termed extracellular vesicles (EVs) hold significant promise as engineerable therapeutic delivery vehicles. However, active loading of protein cargo into EVs in a manner that is useful for delivery remains a challenge. Here, we demonstrate that by rationally designing proteins to traffic to the plasma membrane and associate with lipid rafts, we can enhance loading of protein cargo into EVs for a set of structurally diverse transmembrane and peripheral membrane proteins. We then demonstrate the capacity of select lipid tags to mediate increased EV loading and functional delivery of an engineered transcription factor to modulate gene expression in target cells. We envision that this technology could be leveraged to develop new EV-based therapeutics that deliver a wide array of macromolecular cargo.
Casper A. Goverde, Martin Pacesa, Nicolas Goldbach, Lars J. Dornfeld, Petra E. M. Balbi, Sandrine Georgeon, Stéphane Rosset, Srajan Kapoor, Jagrity Choudhury, Justas Dauparas, Christian Schellhaas, Simon Kozlov, David Baker, Sergey Ovchinnikov, Alex J. Vecchio, Bruno E. Correia
Computational design of soluble and functional membrane protein analogues Journal Article
In: Nature, 2024, ISSN: 1476-4687.
@article{Goverde2024,
title = {Computational design of soluble and functional membrane protein analogues},
author = {Casper A. Goverde and Martin Pacesa and Nicolas Goldbach and Lars J. Dornfeld and Petra E. M. Balbi and Sandrine Georgeon and Stéphane Rosset and Srajan Kapoor and Jagrity Choudhury and Justas Dauparas and Christian Schellhaas and Simon Kozlov and David Baker and Sergey Ovchinnikov and Alex J. Vecchio and Bruno E. Correia},
url = {https://www.nature.com/articles/s41586-024-07601-y, Nature [Open Access]
},
doi = {10.1038/s41586-024-07601-y},
issn = {1476-4687},
year = {2024},
date = {2024-06-19},
urldate = {2024-06-19},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {De novo design of complex protein folds using solely computational means remains a substantial challenge. Here we use a robust deep learning pipeline to design complex folds and soluble analogues of integral membrane proteins. Unique membrane topologies, such as those from G-protein-coupled receptors, are not found in the soluble proteome, and we demonstrate that their structural features can be recapitulated in solution. Biophysical analyses demonstrate the high thermal stability of the designs, and experimental structures show remarkable design accuracy. The soluble analogues were functionalized with native structural motifs, as a proof of concept for bringing membrane protein functions to the soluble proteome, potentially enabling new approaches in drug discovery. In summary, we have designed complex protein topologies and enriched them with functionalities from membrane proteins, with high experimental success rates, leading to a de facto expansion of the functional soluble fold space.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
De novo design of complex protein folds using solely computational means remains a substantial challenge. Here we use a robust deep learning pipeline to design complex folds and soluble analogues of integral membrane proteins. Unique membrane topologies, such as those from G-protein-coupled receptors, are not found in the soluble proteome, and we demonstrate that their structural features can be recapitulated in solution. Biophysical analyses demonstrate the high thermal stability of the designs, and experimental structures show remarkable design accuracy. The soluble analogues were functionalized with native structural motifs, as a proof of concept for bringing membrane protein functions to the soluble proteome, potentially enabling new approaches in drug discovery. In summary, we have designed complex protein topologies and enriched them with functionalities from membrane proteins, with high experimental success rates, leading to a de facto expansion of the functional soluble fold space.
Sarah J. Wait, Marc Expòsit, Sophia Lin, Michael Rappleye, Justin Daho Lee, Samuel A. Colby, Lily Torp, Anthony Asencio, Annette Smith, Michael Regnier, Farid Moussavi-Harami, David Baker, Christina K. Kim, Andre Berndt
Machine learning-guided engineering of genetically encoded fluorescent calcium indicators Journal Article
In: Nature Computational Science, 2024.
@article{Wait2024,
title = {Machine learning-guided engineering of genetically encoded fluorescent calcium indicators},
author = {Sarah J. Wait and Marc Expòsit and Sophia Lin and Michael Rappleye and Justin Daho Lee and Samuel A. Colby and Lily Torp and Anthony Asencio and Annette Smith and Michael Regnier and Farid Moussavi-Harami and David Baker and Christina K. Kim and Andre Berndt},
url = {https://www.nature.com/articles/s43588-024-00611-w, Nat Comp Sci
https://www.bakerlab.org/wp-content/uploads/2024/03/s43588-024-00611-w.pdf, PDF},
doi = {10.1038/s43588-024-00611-w},
year = {2024},
date = {2024-03-21},
urldate = {2024-03-00},
journal = {Nature Computational Science},
publisher = {Springer Science and Business Media LLC},
abstract = {Here we used machine learning to engineer genetically encoded fluorescent indicators, protein-based sensors critical for real-time monitoring of biological activity. We used machine learning to predict the outcomes of sensor mutagenesis by analyzing established libraries that link sensor sequences to functions. Using the GCaMP calcium indicator as a scaffold, we developed an ensemble of three regression models trained on experimentally derived GCaMP mutation libraries. The trained ensemble performed an in silico functional screen on 1,423 novel, uncharacterized GCaMP variants. As a result, we identified the ensemble-derived GCaMP (eGCaMP) variants, eGCaMP and eGCaMP+, which achieve both faster kinetics and larger ∆F/F0 responses upon stimulation than previously published fast variants. Furthermore, we identified a combinatorial mutation with extraordinary dynamic range, eGCaMP2+, which outperforms the tested sixth-, seventh- and eighth-generation GCaMPs. These findings demonstrate the value of machine learning as a tool to facilitate the efficient engineering of proteins for desired biophysical characteristics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Here we used machine learning to engineer genetically encoded fluorescent indicators, protein-based sensors critical for real-time monitoring of biological activity. We used machine learning to predict the outcomes of sensor mutagenesis by analyzing established libraries that link sensor sequences to functions. Using the GCaMP calcium indicator as a scaffold, we developed an ensemble of three regression models trained on experimentally derived GCaMP mutation libraries. The trained ensemble performed an in silico functional screen on 1,423 novel, uncharacterized GCaMP variants. As a result, we identified the ensemble-derived GCaMP (eGCaMP) variants, eGCaMP and eGCaMP+, which achieve both faster kinetics and larger ∆F/F0 responses upon stimulation than previously published fast variants. Furthermore, we identified a combinatorial mutation with extraordinary dynamic range, eGCaMP2+, which outperforms the tested sixth-, seventh- and eighth-generation GCaMPs. These findings demonstrate the value of machine learning as a tool to facilitate the efficient engineering of proteins for desired biophysical characteristics.
Diego Lopez Mateos, Adam M. Murray, Hai M. Nguyen, Preetham Venkatesh, Brian Koepnick, David Baker, Heike Wulff, Vladimir Yarov-Yarovoy
Computational design of binders targeting the VSDIV from NaV1.7 sodium channel Journal Article
In: Biophysical Journal, 2024.
@article{Mateos2024,
title = {Computational design of binders targeting the VSDIV from NaV1.7 sodium channel},
author = {Diego Lopez Mateos and Adam M. Murray and Hai M. Nguyen and Preetham Venkatesh and Brian Koepnick and David Baker and Heike Wulff and Vladimir Yarov-Yarovoy},
url = {https://www.cell.com/biophysj/abstract/S0006-3495(23)01470-4, Biophysical Journal},
doi = {10.1016/j.bpj.2023.11.770},
year = {2024},
date = {2024-02-08},
urldate = {2024-02-00},
journal = {Biophysical Journal},
publisher = {Elsevier BV},
abstract = {Chronic pain affects about 20% of the US population, but safe treatments are limited. There is an urgent need for effective and non-addictive therapies for chronic pan conditions. Voltage-gated sodium (NaV) channel, NaV1.7, is a key player in pain signaling pathway, making it a promising target for novel pain therapeutics. Achieving high subtype selectivity when targeting NaV channels is of primary importance to avoid impairing vital physiological functions mediated by off-target channels. Efforts to selectively target NaV1.7 have been hindered by the difficulties in targeting NaV1.7 over other NaV channel subtypes. Peptidic gating modifier toxins (GMTs), such as Protoxin-II (ProTx2), are promising scaffolds for novel peptide design targeting ion channels with high potency and subtype selectivity. ProTx2 binds to the second and fourth voltage-sensing domains (VSDII and VSDIV) from NaV1.7 with moderate subtype selectivity and can modulate channel activation and inactivation. In this project, we modeled ProTx2 bound to human NaV1.7 VSDIV in an activated state. We used RoseTTAFold Diffusion and Protein MPNN protein design methods to generate protein binders inspired by ProTx2 binding motif with increased predicted binding affinity for human NaV1.7 VSDIV in an activated state. Additionally, we applied these protein design methods to create de novo binders targeting human NaV1.7 VSDIV in an activated state. We anticipate that trapping the VSDIV in an activated conformation will stabilize an inactivated state of the channel, as activation of VSDIV is coupled with channel fast inactivation. Initial electrophysiological screening of our top in silico binders identified promising candidates that inhibited NaV1.7 in the micromolar range. These binders will undergo further testing and optimization against NaV1.7 to create novel molecular tools to study NaV channel activity and effective and safe therapies for chronic pain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Chronic pain affects about 20% of the US population, but safe treatments are limited. There is an urgent need for effective and non-addictive therapies for chronic pan conditions. Voltage-gated sodium (NaV) channel, NaV1.7, is a key player in pain signaling pathway, making it a promising target for novel pain therapeutics. Achieving high subtype selectivity when targeting NaV channels is of primary importance to avoid impairing vital physiological functions mediated by off-target channels. Efforts to selectively target NaV1.7 have been hindered by the difficulties in targeting NaV1.7 over other NaV channel subtypes. Peptidic gating modifier toxins (GMTs), such as Protoxin-II (ProTx2), are promising scaffolds for novel peptide design targeting ion channels with high potency and subtype selectivity. ProTx2 binds to the second and fourth voltage-sensing domains (VSDII and VSDIV) from NaV1.7 with moderate subtype selectivity and can modulate channel activation and inactivation. In this project, we modeled ProTx2 bound to human NaV1.7 VSDIV in an activated state. We used RoseTTAFold Diffusion and Protein MPNN protein design methods to generate protein binders inspired by ProTx2 binding motif with increased predicted binding affinity for human NaV1.7 VSDIV in an activated state. Additionally, we applied these protein design methods to create de novo binders targeting human NaV1.7 VSDIV in an activated state. We anticipate that trapping the VSDIV in an activated conformation will stabilize an inactivated state of the channel, as activation of VSDIV is coupled with channel fast inactivation. Initial electrophysiological screening of our top in silico binders identified promising candidates that inhibited NaV1.7 in the micromolar range. These binders will undergo further testing and optimization against NaV1.7 to create novel molecular tools to study NaV channel activity and effective and safe therapies for chronic pain.
2023
FROM THE LAB
Susana Vázquez Torres, Philip J Y Leung, Preetham Venkatesh, Isaac D Lutz, Fabian Hink, Huu-Hien Huynh, Jessica Becker, Andy Hsien-Wei Yeh, David Juergens, Nathaniel R Bennett, Andrew N Hoofnagle, Eric Huang, Michael J MacCoss, Marc Expòsit, Gyu Rie Lee, Asim K Bera, Alex Kang, Joshmyn De La Cruz, Paul M Levine, Xinting Li, Mila Lamb, Stacey R Gerben, Analisa Murray, Piper Heine, Elif Nihal Korkmaz, Jeff Nivala, Lance Stewart, Joseph L Watson, Joseph M Rogers, David Baker
De novo design of high-affinity binders of bioactive helical peptides Journal Article
In: Nature, 2023, ISSN: 1476-4687.
@article{pmid38109936,
title = {De novo design of high-affinity binders of bioactive helical peptides},
author = {Susana Vázquez Torres and Philip J Y Leung and Preetham Venkatesh and Isaac D Lutz and Fabian Hink and Huu-Hien Huynh and Jessica Becker and Andy Hsien-Wei Yeh and David Juergens and Nathaniel R Bennett and Andrew N Hoofnagle and Eric Huang and Michael J MacCoss and Marc Expòsit and Gyu Rie Lee and Asim K Bera and Alex Kang and Joshmyn De La Cruz and Paul M Levine and Xinting Li and Mila Lamb and Stacey R Gerben and Analisa Murray and Piper Heine and Elif Nihal Korkmaz and Jeff Nivala and Lance Stewart and Joseph L Watson and Joseph M Rogers and David Baker},
url = {https://www.nature.com/articles/s41586-023-06953-1, Nature [Open Access]},
doi = {10.1038/s41586-023-06953-1},
issn = {1476-4687},
year = {2023},
date = {2023-12-01},
urldate = {2023-12-01},
journal = {Nature},
abstract = {Many peptide hormones form an alpha-helix upon binding their receptors, and sensitive detection methods for them could contribute to better clinical management of disease. De novo protein design can now generate binders with high affinity and specificity to structured proteins. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here, we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar affinity binders can be generated to helical peptide targets both by refining designs generated with other methods, or completely de novo starting from random noise distributions. To our knowledge these are the highest affinity designed binding proteins against any protein or small molecule target generated directly by computation without any experimental optimisation. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimise by partial diffusion both natural and designed proteins, should be broadly useful.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many peptide hormones form an alpha-helix upon binding their receptors, and sensitive detection methods for them could contribute to better clinical management of disease. De novo protein design can now generate binders with high affinity and specificity to structured proteins. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here, we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar affinity binders can be generated to helical peptide targets both by refining designs generated with other methods, or completely de novo starting from random noise distributions. To our knowledge these are the highest affinity designed binding proteins against any protein or small molecule target generated directly by computation without any experimental optimisation. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimise by partial diffusion both natural and designed proteins, should be broadly useful.
Fatima A Davila-Hernandez, Biao Jin, Harley Pyles, Shuai Zhang, Zheming Wang, Timothy F Huddy, Asim K Bera, Alex Kang, Chun-Long Chen, James J De Yoreo, David Baker
Directing polymorph specific calcium carbonate formation with de novo protein templates Journal Article
In: Nature Communications, vol. 14, no. 1, pp. 8191, 2023, ISSN: 2041-1723.
@article{Davila-Hernandez2023,
title = {Directing polymorph specific calcium carbonate formation with de novo protein templates},
author = {Fatima A Davila-Hernandez and Biao Jin and Harley Pyles and Shuai Zhang and Zheming Wang and Timothy F Huddy and Asim K Bera and Alex Kang and Chun-Long Chen and James J De Yoreo and David Baker},
url = {https://www.nature.com/articles/s41467-023-43608-1, Nature Communications (Open Access)},
doi = {10.1038/s41467-023-43608-1},
issn = {2041-1723},
year = {2023},
date = {2023-12-01},
urldate = {2023-12-01},
journal = {Nature Communications},
volume = {14},
number = {1},
pages = {8191},
abstract = {Biomolecules modulate inorganic crystallization to generate hierarchically structured biominerals, but the atomic structure of the organic-inorganic interfaces that regulate mineralization remain largely unknown. We hypothesized that heterogeneous nucleation of calcium carbonate could be achieved by a structured flat molecular template that pre-organizes calcium ions on its surface. To test this hypothesis, we design helical repeat proteins (DHRs) displaying regularly spaced carboxylate arrays on their surfaces and find that both protein monomers and protein-Ca supramolecular assemblies directly nucleate nano-calcite with non-natural {110} or {202} faces while vaterite, which forms first in the absence of the proteins, is bypassed. These protein-stabilized nanocrystals then assemble by oriented attachment into calcite mesocrystals. We find further that nanocrystal size and polymorph can be tuned by varying the length and surface chemistry of the designed protein templates. Thus, bio-mineralization can be programmed using de novo protein design, providing a route to next-generation hybrid materials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Biomolecules modulate inorganic crystallization to generate hierarchically structured biominerals, but the atomic structure of the organic-inorganic interfaces that regulate mineralization remain largely unknown. We hypothesized that heterogeneous nucleation of calcium carbonate could be achieved by a structured flat molecular template that pre-organizes calcium ions on its surface. To test this hypothesis, we design helical repeat proteins (DHRs) displaying regularly spaced carboxylate arrays on their surfaces and find that both protein monomers and protein-Ca supramolecular assemblies directly nucleate nano-calcite with non-natural {110} or {202} faces while vaterite, which forms first in the absence of the proteins, is bypassed. These protein-stabilized nanocrystals then assemble by oriented attachment into calcite mesocrystals. We find further that nanocrystal size and polymorph can be tuned by varying the length and surface chemistry of the designed protein templates. Thus, bio-mineralization can be programmed using de novo protein design, providing a route to next-generation hybrid materials.
Edin Muratspahić, Kristine Deibler, Jianming Han, Nataša Tomašević, Kirtikumar B Jadhav, Aina-Leonor Olivé-Marti, Nadine Hochrainer, Roland Hellinger, Johannes Koehbach, Jonathan F Fay, Mohammad Homaidur Rahman, Lamees Hegazy, Timothy W Craven, Balazs R Varga, Gaurav Bhardwaj, Kevin Appourchaux, Susruta Majumdar, Markus Muttenthaler, Parisa Hosseinzadeh, David J Craik, Mariana Spetea, Tao Che, David Baker, Christian W Gruber
Design and structural validation of peptide-drug conjugate ligands of the kappa-opioid receptor Journal Article
In: Nature Communications, 2023.
@article{Muratspahić2023,
title = {Design and structural validation of peptide-drug conjugate ligands of the kappa-opioid receptor},
author = {Edin Muratspahić and Kristine Deibler and Jianming Han and Nataša Tomašević and Kirtikumar B Jadhav and Aina-Leonor Olivé-Marti and Nadine Hochrainer and Roland Hellinger and Johannes Koehbach and Jonathan F Fay and Mohammad Homaidur Rahman and Lamees Hegazy and Timothy W Craven and Balazs R Varga and Gaurav Bhardwaj and Kevin Appourchaux and Susruta Majumdar and Markus Muttenthaler and Parisa Hosseinzadeh and David J Craik and Mariana Spetea and Tao Che and David Baker and Christian W Gruber},
url = {https://www.nature.com/articles/s41467-023-43718-w, Nature Communications [Open Access]},
doi = {10.1038/s41467-023-43718-w},
year = {2023},
date = {2023-12-01},
urldate = {2023-12-01},
journal = {Nature Communications},
abstract = {Despite the increasing number of GPCR structures and recent advances in peptide design, the development of efficient technologies allowing rational design of high-affinity peptide ligands for single GPCRs remains an unmet challenge. Here, we develop a computational approach for designing conjugates of lariat-shaped macrocyclized peptides and a small molecule opioid ligand. We demonstrate its feasibility by discovering chemical scaffolds for the kappa-opioid receptor (KOR) with desired pharmacological activities. The designed De Novo Cyclic Peptide (DNCP)-β-naloxamine (NalA) exhibit in vitro potent mixed KOR agonism/mu-opioid receptor (MOR) antagonism, nanomolar binding affinity, selectivity, and efficacy bias at KOR. Proof-of-concept in vivo efficacy studies demonstrate that DNCP-β-NalA(1) induces a potent KOR-mediated antinociception in male mice. The high-resolution cryo-EM structure (2.6 Å) of the DNCP-β-NalA-KOR-Gi1 complex and molecular dynamics simulations are harnessed to validate the computational design model. This reveals a network of residues in ECL2/3 and TM6/7 controlling the intrinsic efficacy of KOR. In general, our computational de novo platform overcomes extensive lead optimization encountered in ultra-large library docking and virtual small molecule screening campaigns and offers innovation for GPCR ligand discovery. This may drive the development of next-generation therapeutics for medical applications such as pain conditions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Despite the increasing number of GPCR structures and recent advances in peptide design, the development of efficient technologies allowing rational design of high-affinity peptide ligands for single GPCRs remains an unmet challenge. Here, we develop a computational approach for designing conjugates of lariat-shaped macrocyclized peptides and a small molecule opioid ligand. We demonstrate its feasibility by discovering chemical scaffolds for the kappa-opioid receptor (KOR) with desired pharmacological activities. The designed De Novo Cyclic Peptide (DNCP)-β-naloxamine (NalA) exhibit in vitro potent mixed KOR agonism/mu-opioid receptor (MOR) antagonism, nanomolar binding affinity, selectivity, and efficacy bias at KOR. Proof-of-concept in vivo efficacy studies demonstrate that DNCP-β-NalA(1) induces a potent KOR-mediated antinociception in male mice. The high-resolution cryo-EM structure (2.6 Å) of the DNCP-β-NalA-KOR-Gi1 complex and molecular dynamics simulations are harnessed to validate the computational design model. This reveals a network of residues in ECL2/3 and TM6/7 controlling the intrinsic efficacy of KOR. In general, our computational de novo platform overcomes extensive lead optimization encountered in ultra-large library docking and virtual small molecule screening campaigns and offers innovation for GPCR ligand discovery. This may drive the development of next-generation therapeutics for medical applications such as pain conditions.
Minkyung Baek, Ryan McHugh, Ivan Anishchenko, Hanlun Jiang, David Baker, Frank DiMaio
Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA Journal Article
In: Nature Methods, 2023.
@article{Baek2023,
title = {Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA},
author = {Minkyung Baek and Ryan McHugh and Ivan Anishchenko and Hanlun Jiang and David Baker and Frank DiMaio},
url = {https://www.nature.com/articles/s41592-023-02086-5, Nature Methods [Open Access]},
doi = {10.1038/s41592-023-02086-5},
year = {2023},
date = {2023-11-23},
urldate = {2023-11-23},
journal = {Nature Methods},
publisher = {Springer Science and Business Media LLC},
abstract = {Protein–RNA and protein–DNA complexes play critical roles in biology. Despite considerable recent advances in protein structure prediction, the prediction of the structures of protein–nucleic acid complexes without homology to known complexes is a largely unsolved problem. Here we extend the RoseTTAFold machine learning protein-structure-prediction approach to additionally predict nucleic acid and protein–nucleic acid complexes. We develop a single trained network, RoseTTAFoldNA, that rapidly produces three-dimensional structure models with confidence estimates for protein–DNA and protein–RNA complexes. Here we show that confident predictions have considerably higher accuracy than current state-of-the-art methods. RoseTTAFoldNA should be broadly useful for modeling the structure of naturally occurring protein–nucleic acid complexes, and for designing sequence-specific RNA and DNA-binding proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein–RNA and protein–DNA complexes play critical roles in biology. Despite considerable recent advances in protein structure prediction, the prediction of the structures of protein–nucleic acid complexes without homology to known complexes is a largely unsolved problem. Here we extend the RoseTTAFold machine learning protein-structure-prediction approach to additionally predict nucleic acid and protein–nucleic acid complexes. We develop a single trained network, RoseTTAFoldNA, that rapidly produces three-dimensional structure models with confidence estimates for protein–DNA and protein–RNA complexes. Here we show that confident predictions have considerably higher accuracy than current state-of-the-art methods. RoseTTAFoldNA should be broadly useful for modeling the structure of naturally occurring protein–nucleic acid complexes, and for designing sequence-specific RNA and DNA-binding proteins.
Zhe Li, Shunzhi Wang, Una Nattermann, Asim K Bera, Andrew J Borst, Muammer Y Yaman, Matthew J Bick, Erin C Yang, William Sheffler, Byeongdu Lee, Soenke Seifert, Greg L Hura, Hannah Nguyen, Alex Kang, Radhika Dalal, Joshua M Lubner, Yang Hsia, Hugh Haddox, Alexis Courbet, Quinton Dowling, Marcos Miranda, Andrew Favor, Ali Etemadi, Natasha I Edman, Wei Yang, Connor Weidle, Banumathi Sankaran, Babak Negahdari, Michael B Ross, David S Ginger, David Baker
Accurate computational design of three-dimensional protein crystals Journal Article
In: Nature Materials, 2023.
@article{Li2023,
title = {Accurate computational design of three-dimensional protein crystals},
author = {Zhe Li and Shunzhi Wang and Una Nattermann and Asim K Bera and Andrew J Borst and Muammer Y Yaman and Matthew J Bick and Erin C Yang and William Sheffler and Byeongdu Lee and Soenke Seifert and Greg L Hura and Hannah Nguyen and Alex Kang and Radhika Dalal and Joshua M Lubner and Yang Hsia and Hugh Haddox and Alexis Courbet and Quinton Dowling and Marcos Miranda and Andrew Favor and Ali Etemadi and Natasha I Edman and Wei Yang and Connor Weidle and Banumathi Sankaran and Babak Negahdari and Michael B Ross and David S Ginger and David Baker},
url = {https://rdcu.be/doHL5, Nature Methods},
doi = {10.1038/s41563-023-01683-1},
year = {2023},
date = {2023-10-16},
urldate = {2023-10-01},
journal = {Nature Materials},
abstract = {Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain–side-chain interactions across protein–protein interfaces is an outstanding challenge. Here we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein–protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain–side-chain interactions across protein–protein interfaces is an outstanding challenge. Here we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein–protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.
An L, Hicks DR, Zorine D, Dauparas J, Wicky BIM, Milles LF, Courbet A, Bera AK, Nguyen H, Kang A, Carter L, Baker D
Hallucination of closed repeat proteins containing central pockets Journal Article
In: Nature Structural & Molecular Biology, 2023.
@article{An2023,
title = {Hallucination of closed repeat proteins containing central pockets},
author = {An L, Hicks DR, Zorine D, Dauparas J, Wicky BIM, Milles LF, Courbet A, Bera AK, Nguyen H, Kang A, Carter L, Baker D},
url = {https://www.nature.com/articles/s41594-023-01112-6, Nature Structural & Molecular Biology [Open Access] },
doi = {10.1038/s41594-023-01112-6},
year = {2023},
date = {2023-09-28},
urldate = {2023-09-28},
journal = {Nature Structural & Molecular Biology},
abstract = {In pseudocyclic proteins, such as TIM barrels, β barrels, and some helical transmembrane channels, a single subunit is repeated in a cyclic pattern, giving rise to a central cavity that can serve as a pocket for ligand binding or enzymatic activity. Inspired by these proteins, we devised a deep-learning-based approach to broadly exploring the space of closed repeat proteins starting from only a specification of the repeat number and length. Biophysical data for 38 structurally diverse pseudocyclic designs produced in Escherichia coli are consistent with the design models, and the three crystal structures we were able to obtain are very close to the designed structures. Docking studies suggest the diversity of folds and central pockets provide effective starting points for designing small-molecule binders and enzymes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In pseudocyclic proteins, such as TIM barrels, β barrels, and some helical transmembrane channels, a single subunit is repeated in a cyclic pattern, giving rise to a central cavity that can serve as a pocket for ligand binding or enzymatic activity. Inspired by these proteins, we devised a deep-learning-based approach to broadly exploring the space of closed repeat proteins starting from only a specification of the repeat number and length. Biophysical data for 38 structurally diverse pseudocyclic designs produced in Escherichia coli are consistent with the design models, and the three crystal structures we were able to obtain are very close to the designed structures. Docking studies suggest the diversity of folds and central pockets provide effective starting points for designing small-molecule binders and enzymes.
Anindya Roy, Lei Shi, Ashley Chang, Xianchi Dong, Andres Fernandez, John C. Kraft, Jing Li, Viet Q. Le, Rebecca Viazzo Winegar, Gerald Maxwell Cherf, Dean Slocum, P. Daniel Poulson, Garrett E. Casper, Mary L. Vallecillo-Zúniga, Jonard Corpuz Valdoz, Marcos C. Miranda, Hua Bai, Yakov Kipnis, Audrey Olshefsky, Tanu Priya, Lauren Carter, Rashmi Ravichandran, Cameron M. Chow, Max R. Johnson, Suna Cheng, McKaela Smith, Catherine Overed-Sayer, Donna K. Finch, David Lowe, Asim K. Bera, Gustavo Matute-Bello, Timothy P. Birkland, Frank DiMaio, Ganesh Raghu, Jennifer R. Cochran, Lance J. Stewart, Melody G. Campbell, Pam M. Van Ry, Timothy Springer, David Baker
De novo design of highly selective miniprotein inhibitors of integrins αvβ6 and αvβ8 Journal Article
In: Nature Communications, 2023.
@article{Roy2023,
title = {De novo design of highly selective miniprotein inhibitors of integrins αvβ6 and αvβ8},
author = {Anindya Roy and Lei Shi and Ashley Chang and Xianchi Dong and Andres Fernandez and John C. Kraft and Jing Li and Viet Q. Le and Rebecca Viazzo Winegar and Gerald Maxwell Cherf and Dean Slocum and P. Daniel Poulson and Garrett E. Casper and Mary L. Vallecillo-Zúniga and Jonard Corpuz Valdoz and Marcos C. Miranda and Hua Bai and Yakov Kipnis and Audrey Olshefsky and Tanu Priya and Lauren Carter and Rashmi Ravichandran and Cameron M. Chow and Max R. Johnson and Suna Cheng and McKaela Smith and Catherine Overed-Sayer and Donna K. Finch and David Lowe and Asim K. Bera and Gustavo Matute-Bello and Timothy P. Birkland and Frank DiMaio and Ganesh Raghu and Jennifer R. Cochran and Lance J. Stewart and Melody G. Campbell and Pam M. Van Ry and Timothy Springer and David Baker},
url = {https://www.nature.com/articles/s41467-023-41272-z, Nature Communications [Open Access]},
doi = {10.1038/s41467-023-41272-z},
year = {2023},
date = {2023-09-13},
urldate = {2023-12-00},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
abstract = {The RGD (Arg-Gly-Asp)-binding integrins αvβ6 and αvβ8 are clinically validated cancer and fibrosis targets of considerable therapeutic importance. Compounds that can discriminate between homologous αvβ6 and αvβ8 and other RGD integrins, stabilize specific conformational states, and have high thermal stability could have considerable therapeutic utility. Existing small molecule and antibody inhibitors do not have all these properties, and hence new approaches are needed. Here we describe a generalized method for computationally designing RGD-containing miniproteins selective for a single RGD integrin heterodimer and conformational state. We design hyperstable, selective αvβ6 and αvβ8 inhibitors that bind with picomolar affinity. CryoEM structures of the designed inhibitor-integrin complexes are very close to the computational design models, and show that the inhibitors stabilize specific conformational states of the αvβ6 and the αvβ8 integrins. In a lung fibrosis mouse model, the αvβ6 inhibitor potently reduced fibrotic burden and improved overall lung mechanics, demonstrating the therapeutic potential of de novo designed integrin binding proteins with high selectivity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The RGD (Arg-Gly-Asp)-binding integrins αvβ6 and αvβ8 are clinically validated cancer and fibrosis targets of considerable therapeutic importance. Compounds that can discriminate between homologous αvβ6 and αvβ8 and other RGD integrins, stabilize specific conformational states, and have high thermal stability could have considerable therapeutic utility. Existing small molecule and antibody inhibitors do not have all these properties, and hence new approaches are needed. Here we describe a generalized method for computationally designing RGD-containing miniproteins selective for a single RGD integrin heterodimer and conformational state. We design hyperstable, selective αvβ6 and αvβ8 inhibitors that bind with picomolar affinity. CryoEM structures of the designed inhibitor-integrin complexes are very close to the computational design models, and show that the inhibitors stabilize specific conformational states of the αvβ6 and the αvβ8 integrins. In a lung fibrosis mouse model, the αvβ6 inhibitor potently reduced fibrotic burden and improved overall lung mechanics, demonstrating the therapeutic potential of de novo designed integrin binding proteins with high selectivity.
Sanaa Mansoor, Minkyung Baek, David Juergens, Joseph L. Watson, David Baker
Zero‐shot Mutation Effect Prediction on Protein Stability and Function using RoseTTAFold Journal Article
In: Protein Science, 2023.
@article{Mansoor2023,
title = {Zero‐shot Mutation Effect Prediction on Protein Stability and Function using RoseTTAFold},
author = {Sanaa Mansoor and Minkyung Baek and David Juergens and Joseph L. Watson and David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pro.4780, Protein Science
https://www.bakerlab.org/wp-content/uploads/2023/09/Protein-Science-2023-Mansoor.pdf, PDF},
doi = {10.1002/pro.4780},
year = {2023},
date = {2023-09-11},
urldate = {2023-09-11},
journal = {Protein Science},
publisher = {Wiley},
abstract = {Predicting the effects of mutations on protein function and stability is an outstanding challenge. Here, we assess the performance of a variant of RoseTTAFold jointly trained for sequence and structure recovery, RFjoint, for mutation effect prediction. Without any further training, we achieve comparable accuracy in predicting mutation effects for a diverse set of protein families using RFjoint to both another zero‐shot model (MSA Transformer) and a model which requires specific training on a particular protein family for mutation effect prediction (DeepSequence). Thus, although the architecture of RFjoint was developed to address the protein design problem of scaffolding functional motifs, RFjoint acquired an understanding of the mutational landscapes of proteins during model training that is equivalent to that of recently developed large protein language models. The ability to simultaneously reason over protein structure and sequence could enable even more precise mutation effect predictions following supervised training on the task. These results suggest that RFjoint has a quite broad understanding of protein sequence‐structure landscapes, and can be viewed as a joint model for protein sequence and structure which could be broadly useful for protein modeling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Predicting the effects of mutations on protein function and stability is an outstanding challenge. Here, we assess the performance of a variant of RoseTTAFold jointly trained for sequence and structure recovery, RFjoint, for mutation effect prediction. Without any further training, we achieve comparable accuracy in predicting mutation effects for a diverse set of protein families using RFjoint to both another zero‐shot model (MSA Transformer) and a model which requires specific training on a particular protein family for mutation effect prediction (DeepSequence). Thus, although the architecture of RFjoint was developed to address the protein design problem of scaffolding functional motifs, RFjoint acquired an understanding of the mutational landscapes of proteins during model training that is equivalent to that of recently developed large protein language models. The ability to simultaneously reason over protein structure and sequence could enable even more precise mutation effect predictions following supervised training on the task. These results suggest that RFjoint has a quite broad understanding of protein sequence‐structure landscapes, and can be viewed as a joint model for protein sequence and structure which could be broadly useful for protein modeling.
Neville P. Bethel, Andrew J. Borst, Fabio Parmeggiani, Matthew J. Bick, TJ Brunette, Hannah Nguyen, Alex Kang, Asim K. Bera, Lauren Carter, Marcos C. Miranda, Ryan D. Kibler, Mila Lamb, Xinting Li, Banumathi Sankaran, David Baker
Precisely patterned nanofibres made from extendable protein multiplexes Journal Article
In: Nature Chemistry, 2023.
@article{Bethel2023,
title = {Precisely patterned nanofibres made from extendable protein multiplexes},
author = {Neville P. Bethel and Andrew J. Borst and Fabio Parmeggiani and Matthew J. Bick and TJ Brunette and Hannah Nguyen and Alex Kang and Asim K. Bera and Lauren Carter and Marcos C. Miranda and Ryan D. Kibler and Mila Lamb and Xinting Li and Banumathi Sankaran and David Baker},
url = {https://rdcu.be/dloEi, Nature Chemistry [Open Access]},
doi = {10.1038/s41557-023-01314-x},
year = {2023},
date = {2023-09-04},
urldate = {2023-09-04},
journal = {Nature Chemistry},
publisher = {Springer Science and Business Media LLC},
abstract = {Molecular systems with coincident cyclic and superhelical symmetry axes have considerable advantages for materials design as they can be readily lengthened or shortened by changing the length of the constituent monomers. Among proteins, alpha-helical coiled coils have such symmetric, extendable architectures, but are limited by the relatively fixed geometry and flexibility of the helical protomers. Here we describe a systematic approach to generating modular and rigid repeat protein oligomers with coincident C2 to C8 and superhelical symmetry axes that can be readily extended by repeat propagation. From these building blocks, we demonstrate that a wide range of unbounded fibres can be systematically designed by introducing hydrophilic surface patches that force staggering of the monomers; the geometry of such fibres can be precisely tuned by varying the number of repeat units in the monomer and the placement of the hydrophilic patches.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Molecular systems with coincident cyclic and superhelical symmetry axes have considerable advantages for materials design as they can be readily lengthened or shortened by changing the length of the constituent monomers. Among proteins, alpha-helical coiled coils have such symmetric, extendable architectures, but are limited by the relatively fixed geometry and flexibility of the helical protomers. Here we describe a systematic approach to generating modular and rigid repeat protein oligomers with coincident C2 to C8 and superhelical symmetry axes that can be readily extended by repeat propagation. From these building blocks, we demonstrate that a wide range of unbounded fibres can be systematically designed by introducing hydrophilic surface patches that force staggering of the monomers; the geometry of such fibres can be precisely tuned by varying the number of repeat units in the monomer and the placement of the hydrophilic patches.
Nicolas Goldbach, Issa Benna, Basile I. M. Wicky, Jacob T. Croft, Lauren Carter, Asim K. Bera, Hannah Nguyen, Alex Kang, Banumathi Sankaran, Erin C. Yang, Kelly K. Lee, David Baker
De novo design of monomeric helical bundles for pH-controlled membrane lysis Journal Article
In: Protein Science, 2023.
@article{Goldbach2023,
title = {De novo design of monomeric helical bundles for pH-controlled membrane lysis},
author = {Nicolas Goldbach and Issa Benna and Basile I. M. Wicky and Jacob T. Croft and Lauren Carter and Asim K. Bera and Hannah Nguyen and Alex Kang and Banumathi Sankaran and Erin C. Yang and Kelly K. Lee and David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pro.4769, Protein Science
https://www.bakerlab.org/wp-content/uploads/2023/08/Protein-Science-2023-Goldbach.pdf, PDF},
doi = {https://doi.org/10.1002/pro.4769},
year = {2023},
date = {2023-08-26},
urldate = {2023-08-26},
journal = {Protein Science},
abstract = {Targeted intracellular delivery via receptor-mediated endocytosis requires the delivered cargo to escape the endosome to prevent lysosomal degradation. This can in principle be achieved by membrane lysis tightly restricted to endosomal membranes upon internalization to avoid general membrane insertion and lysis. Here we describe the design of small monomeric proteins with buried histidine containing pH-responsive hydrogen bond networks and membrane permeating amphipathic helices. Of 30 designs that were experimentally tested, all expressed in E. coli, 13 were monomeric with the expected secondary structure, and 4 designs disrupted artificial liposomes in a pH-dependent manner. Mutational analysis showed that the buried histidine hydrogen bond networks mediate pH-responsiveness and control lysis of model membranes within a very narrow range of pH (6.0 - 5.5) with almost no lysis occurring at neutral pH. These tightly controlled lytic monomers could help mediate endosomal escape in designed targeted delivery platforms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Targeted intracellular delivery via receptor-mediated endocytosis requires the delivered cargo to escape the endosome to prevent lysosomal degradation. This can in principle be achieved by membrane lysis tightly restricted to endosomal membranes upon internalization to avoid general membrane insertion and lysis. Here we describe the design of small monomeric proteins with buried histidine containing pH-responsive hydrogen bond networks and membrane permeating amphipathic helices. Of 30 designs that were experimentally tested, all expressed in E. coli, 13 were monomeric with the expected secondary structure, and 4 designs disrupted artificial liposomes in a pH-dependent manner. Mutational analysis showed that the buried histidine hydrogen bond networks mediate pH-responsiveness and control lysis of model membranes within a very narrow range of pH (6.0 – 5.5) with almost no lysis occurring at neutral pH. These tightly controlled lytic monomers could help mediate endosomal escape in designed targeted delivery platforms.
Florian Praetorius, Philip J. Y. Leung, Maxx H. Tessmer, Adam Broerman, Cullen Demakis, Acacia F. Dishman, Arvind Pillai, Abbas Idris, David Juergens, Justas Dauparas, Xinting Li, Paul M. Levine, Mila Lamb, Ryanne K. Ballard, Stacey R. Gerben, Hannah Nguyen, Alex Kang, Banumathi Sankaran, Asim K. Bera, Brian F. Volkman, Jeff Nivala, Stefan Stoll, David Baker
Design of stimulus-responsive two-state hinge proteins Journal Article
In: Science, 2023.
@article{Praetorius2023,
title = {Design of stimulus-responsive two-state hinge proteins},
author = {Florian Praetorius and Philip J. Y. Leung and Maxx H. Tessmer and Adam Broerman and Cullen Demakis and Acacia F. Dishman and Arvind Pillai and Abbas Idris and David Juergens and Justas Dauparas and Xinting Li and Paul M. Levine and Mila Lamb and Ryanne K. Ballard and Stacey R. Gerben and Hannah Nguyen and Alex Kang and Banumathi Sankaran and Asim K. Bera and Brian F. Volkman and Jeff Nivala and Stefan Stoll and David Baker},
url = {https://www.science.org/stoken/author-tokens/ST-1381/full, Science (Free Access)},
doi = {10.1126/science.adg7731},
year = {2023},
date = {2023-08-17},
urldate = {2023-08-17},
journal = {Science},
abstract = {In nature, proteins that switch between two conformations in response to environmental stimuli structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Designing proteins with two distinct but fully structured conformations is a challenge for protein design as it requires sculpting an energy landscape with two distinct minima. Here we describe the design of “hinge” proteins that populate one designed state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, double electron-electron resonance spectroscopy, and binding measurements demonstrate that despite the significant structural differences the two states are designed with atomic level accuracy and that the conformational and binding equilibria are closely coupled. Natural proteins often adopt multiple conformational states, thereby changing their activity or binding partners in response to another protein, small molecule, or other stimulus. It has been difficult to engineer such conformational switching between two folded states in human-designed proteins. Praetorius et al. developed a hinge-like protein by simultaneously considering both desired states in the design process. The successful designs exhibited a large shift in conformation upon binding to a target peptide helix, which could be tailored for specificity. The authors characterized the protein structures, binding kinetics, and conformational equilibrium of the designs. This work provides the groundwork for generating protein switches that respond to biological triggers and can produce conformational changes that modulate protein assemblies. —Michael A. Funk A two-state design of protein switches that couple effector binding to a conformational change is discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In nature, proteins that switch between two conformations in response to environmental stimuli structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Designing proteins with two distinct but fully structured conformations is a challenge for protein design as it requires sculpting an energy landscape with two distinct minima. Here we describe the design of “hinge” proteins that populate one designed state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, double electron-electron resonance spectroscopy, and binding measurements demonstrate that despite the significant structural differences the two states are designed with atomic level accuracy and that the conformational and binding equilibria are closely coupled. Natural proteins often adopt multiple conformational states, thereby changing their activity or binding partners in response to another protein, small molecule, or other stimulus. It has been difficult to engineer such conformational switching between two folded states in human-designed proteins. Praetorius et al. developed a hinge-like protein by simultaneously considering both desired states in the design process. The successful designs exhibited a large shift in conformation upon binding to a target peptide helix, which could be tailored for specificity. The authors characterized the protein structures, binding kinetics, and conformational equilibrium of the designs. This work provides the groundwork for generating protein switches that respond to biological triggers and can produce conformational changes that modulate protein assemblies. —Michael A. Funk A two-state design of protein switches that couple effector binding to a conformational change is discussed.
Watson, Joseph L. and Juergens, David and Bennett, Nathaniel R. and Trippe, Brian L. and Yim, Jason and Eisenach, Helen E. and Ahern, Woody and Borst, Andrew J. and Ragotte, Robert J. and Milles, Lukas F. and Wicky, Basile I. M. and Hanikel, Nikita and Pellock, Samuel J. and Courbet, Alexis and Sheffler, William and Wang, Jue and Venkatesh, Preetham and Sappington, Isaac and Torres, Susana Vázquez and Lauko, Anna and De Bortoli, Valentin and Mathieu, Emile and Ovchinnikov, Sergey and Barzilay, Regina and Jaakkola, Tommi S. and DiMaio, Frank and Baek, Minkyung and Baker, David
De novo design of protein structure and function with RFdiffusion Journal Article
In: Nature, 2023.
@article{Watson2023,
title = {De novo design of protein structure and function with RFdiffusion},
author = {Watson, Joseph L.
and Juergens, David
and Bennett, Nathaniel R.
and Trippe, Brian L.
and Yim, Jason
and Eisenach, Helen E.
and Ahern, Woody
and Borst, Andrew J.
and Ragotte, Robert J.
and Milles, Lukas F.
and Wicky, Basile I. M.
and Hanikel, Nikita
and Pellock, Samuel J.
and Courbet, Alexis
and Sheffler, William
and Wang, Jue
and Venkatesh, Preetham
and Sappington, Isaac
and Torres, Susana Vázquez
and Lauko, Anna
and De Bortoli, Valentin
and Mathieu, Emile
and Ovchinnikov, Sergey
and Barzilay, Regina
and Jaakkola, Tommi S.
and DiMaio, Frank
and Baek, Minkyung
and Baker, David},
url = {https://www.nature.com/articles/s41586-023-06415-8, Nature
https://www.bakerlab.org/wp-content/uploads/2023/07/s41586-023-06415-8_reference.pdf, PDF (29MB)},
doi = {10.1038/s41586-023-06415-8},
year = {2023},
date = {2023-07-11},
journal = {Nature},
abstract = {There has been considerable recent progress in designing new proteins using deep learning methods1–9. Despite this progress, a general deep learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher order symmetric architectures, has yet to be described. Diffusion models10,11 have had considerable success in image and language generative modeling but limited success when applied to protein modeling, likely due to the complexity of protein backbone geometry and sequence-structure relationships. Here we show that by fine tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding, and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold Diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryo-EM structure of a designed binder in complex with Influenza hemagglutinin which is nearly identical to the design model. In a manner analogous to networks which produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
There has been considerable recent progress in designing new proteins using deep learning methods1–9. Despite this progress, a general deep learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher order symmetric architectures, has yet to be described. Diffusion models10,11 have had considerable success in image and language generative modeling but limited success when applied to protein modeling, likely due to the complexity of protein backbone geometry and sequence-structure relationships. Here we show that by fine tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding, and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold Diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryo-EM structure of a designed binder in complex with Influenza hemagglutinin which is nearly identical to the design model. In a manner analogous to networks which produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.
Kalvet, Indrek and Ortmayer, Mary and Zhao, Jingming and Crawshaw, Rebecca and Ennist, Nathan M. and Levy, Colin and Roy, Anindya and Green, Anthony P. and Baker, David
Design of Heme Enzymes with a Tunable Substrate Binding Pocket Adjacent to an Open Metal Coordination Site Journal Article
In: J. Am. Chem. Soc., 2023.
@article{nokey,
title = {Design of Heme Enzymes with a Tunable Substrate Binding Pocket Adjacent to an Open Metal Coordination Site},
author = {Kalvet, Indrek
and Ortmayer, Mary
and Zhao, Jingming
and Crawshaw, Rebecca
and Ennist, Nathan M.
and Levy, Colin
and Roy, Anindya
and Green, Anthony P.
and Baker, David},
url = {https://pubs.acs.org/doi/full/10.1021/jacs.3c02742, ACS (Open Access)},
doi = {10.1021/jacs.3c02742},
year = {2023},
date = {2023-07-05},
urldate = {2023-07-05},
journal = {J. Am. Chem. Soc.},
abstract = {The catalytic versatility of pentacoordinated iron is highlighted by the broad range of natural and engineered activities of heme enzymes such as cytochrome P450s, which position a porphyrin cofactor coordinating a central iron atom below an open substrate binding pocket. This catalytic prowess has inspired efforts to design de novo helical bundle scaffolds that bind porphyrin cofactors. However, such designs lack the large open substrate binding pocket of P450s, and hence, the range of chemical transformations accessible is limited. Here, with the goal of combining the advantages of the P450 catalytic site geometry with the almost unlimited customizability of de novo protein design, we design a high-affinity heme-binding protein, dnHEM1, with an axial histidine ligand, a vacant coordination site for generating reactive intermediates, and a tunable distal pocket for substrate binding. A 1.6 Å X-ray crystal structure of dnHEM1 reveals excellent agreement to the design model with key features programmed as intended. The incorporation of distal pocket substitutions converted dnHEM1 into a proficient peroxidase with a stable neutral ferryl intermediate. In parallel, dnHEM1 was redesigned to generate enantiocomplementary carbene transferases for styrene cyclopropanation (up to 93% isolated yield, 5000 turnovers, 97:3 e.r.) by reconfiguring the distal pocket to accommodate calculated transition state models. Our approach now enables the custom design of enzymes containing cofactors adjacent to binding pockets with an almost unlimited variety of shapes and functionalities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The catalytic versatility of pentacoordinated iron is highlighted by the broad range of natural and engineered activities of heme enzymes such as cytochrome P450s, which position a porphyrin cofactor coordinating a central iron atom below an open substrate binding pocket. This catalytic prowess has inspired efforts to design de novo helical bundle scaffolds that bind porphyrin cofactors. However, such designs lack the large open substrate binding pocket of P450s, and hence, the range of chemical transformations accessible is limited. Here, with the goal of combining the advantages of the P450 catalytic site geometry with the almost unlimited customizability of de novo protein design, we design a high-affinity heme-binding protein, dnHEM1, with an axial histidine ligand, a vacant coordination site for generating reactive intermediates, and a tunable distal pocket for substrate binding. A 1.6 Å X-ray crystal structure of dnHEM1 reveals excellent agreement to the design model with key features programmed as intended. The incorporation of distal pocket substitutions converted dnHEM1 into a proficient peroxidase with a stable neutral ferryl intermediate. In parallel, dnHEM1 was redesigned to generate enantiocomplementary carbene transferases for styrene cyclopropanation (up to 93% isolated yield, 5000 turnovers, 97:3 e.r.) by reconfiguring the distal pocket to accommodate calculated transition state models. Our approach now enables the custom design of enzymes containing cofactors adjacent to binding pockets with an almost unlimited variety of shapes and functionalities.
Bennett, Nathaniel R. and Coventry, Brian and Goreshnik, Inna and Huang, Buwei and Allen, Aza and Vafeados, Dionne and Peng, Ying Po and Dauparas, Justas and Baek, Minkyung and Stewart, Lance and DiMaio, Frank and De Munck, Steven and Savvides, Savvas N. and Baker, David
Improving de novo protein binder design with deep learning Journal Article
In: Nature Communications, 2023.
@article{Bennett2023,
title = {Improving de novo protein binder design with deep learning},
author = {Bennett, Nathaniel R.
and Coventry, Brian
and Goreshnik, Inna
and Huang, Buwei
and Allen, Aza
and Vafeados, Dionne
and Peng, Ying Po
and Dauparas, Justas
and Baek, Minkyung
and Stewart, Lance
and DiMaio, Frank
and De Munck, Steven
and Savvides, Savvas N.
and Baker, David},
url = {https://www.nature.com/articles/s41467-023-38328-5, Nature Communications (Open Access)},
doi = {10.1038/s41467-023-38328-5},
year = {2023},
date = {2023-05-06},
journal = {Nature Communications},
abstract = {Recently it has become possible to de novo design high affinity protein binding proteins from target structural information alone. There is, however, considerable room for improvement as the overall design success rate is low. Here, we explore the augmentation of energy-based protein binder design using deep learning. We find that using AlphaFold2 or RoseTTAFold to assess the probability that a designed sequence adopts the designed monomer structure, and the probability that this structure binds the target as designed, increases design success rates nearly 10-fold. We find further that sequence design using ProteinMPNN rather than Rosetta considerably increases computational efficiency.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recently it has become possible to de novo design high affinity protein binding proteins from target structural information alone. There is, however, considerable room for improvement as the overall design success rate is low. Here, we explore the augmentation of energy-based protein binder design using deep learning. We find that using AlphaFold2 or RoseTTAFold to assess the probability that a designed sequence adopts the designed monomer structure, and the probability that this structure binds the target as designed, increases design success rates nearly 10-fold. We find further that sequence design using ProteinMPNN rather than Rosetta considerably increases computational efficiency.
Lutz, Isaac D. and Wang, Shunzhi and Norn, Christoffer and Courbet, Alexis and Borst, Andrew J. and Zhao, Yan Ting and Dosey, Annie and Cao, Longxing and Xu, Jinwei and Leaf, Elizabeth M. and Treichel, Catherine and Litvicov, Patrisia and Li, Zhe and Goodson, Alexander D. and Rivera-Sánchez, Paula and Bratovianu, Ana-Maria and Baek, Minkyung and King, Neil P. and Ruohola-Baker, Hannele and Baker, David
Top-down design of protein architectures with reinforcement learning Journal Article
In: Science, 2023.
@article{Lutz2023,
title = {Top-down design of protein architectures with reinforcement learning},
author = {Lutz, Isaac D.
and Wang, Shunzhi
and Norn, Christoffer
and Courbet, Alexis
and Borst, Andrew J.
and Zhao, Yan Ting
and Dosey, Annie
and Cao, Longxing
and Xu, Jinwei
and Leaf, Elizabeth M.
and Treichel, Catherine
and Litvicov, Patrisia
and Li, Zhe
and Goodson, Alexander D.
and Rivera-Sánchez, Paula
and Bratovianu, Ana-Maria
and Baek, Minkyung
and King, Neil P.
and Ruohola-Baker, Hannele
and Baker, David},
url = {https://www.science.org/doi/10.1126/science.adf6591, Science
https://www.ipd.uw.edu/wp-content/uploads/2023/04/science.adf6591.pdf, PDF},
doi = {10.1126/science.adf6591},
year = {2023},
date = {2023-04-20},
journal = {Science},
abstract = {As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a “top-down” reinforcement learning–based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo–electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a “top-down” reinforcement learning–based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo–electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.
Wu, Kejia and Bai, Hua and Chang, Ya-Ting and Redler, Rachel and McNally, Kerrie E. and Sheffler, William and Brunette, T. J. and Hicks, Derrick R. and Morgan, Tomos E. and Stevens, Tim J. and Broerman, Adam and Goreshnik, Inna and DeWitt, Michelle and Chow, Cameron M. and Shen, Yihang and Stewart, Lance and Derivery, Emmanuel and Silva, Daniel Adriano and Bhabha, Gira and Ekiert, Damian C. and Baker, David
De novo design of modular peptide-binding proteins by superhelical matching Journal Article
In: Nature, 2023.
@article{Wu2023,
title = {De novo design of modular peptide-binding proteins by superhelical matching},
author = {Wu, Kejia
and Bai, Hua
and Chang, Ya-Ting
and Redler, Rachel
and McNally, Kerrie E.
and Sheffler, William
and Brunette, T. J.
and Hicks, Derrick R.
and Morgan, Tomos E.
and Stevens, Tim J.
and Broerman, Adam
and Goreshnik, Inna
and DeWitt, Michelle
and Chow, Cameron M.
and Shen, Yihang
and Stewart, Lance
and Derivery, Emmanuel
and Silva, Daniel Adriano
and Bhabha, Gira
and Ekiert, Damian C.
and Baker, David},
url = {https://www.nature.com/articles/s41586-023-05909-9, Nature (Open-access)},
doi = {10.1038/s41586-023-05909-9},
year = {2023},
date = {2023-04-05},
urldate = {2023-04-05},
journal = {Nature},
abstract = {General approaches for designing sequence-specific peptide-binding proteins would have wide utility in proteomics and synthetic biology. However, designing peptide-binding proteins is challenging, as most peptides do not have defined structures in isolation, and hydrogen bonds must be made to the buried polar groups in the peptide backbone1–3. Here, inspired by natural and re-engineered protein–peptide systems4–11, we set out to design proteins made out of repeating units that bind peptides with repeating sequences, with a one-to-one correspondence between the repeat units of the protein and those of the peptide. We use geometric hashing to identify protein backbones and peptide-docking arrangements that are compatible with bidentate hydrogen bonds between the side chains of the protein and the peptide backbone12. The remainder of the protein sequence is then optimized for folding and peptide binding. We design repeat proteins to bind to six different tripeptide-repeat sequences in polyproline II conformations. The proteins are hyperstable and bind to four to six tandem repeats of their tripeptide targets with nanomolar to picomolar affinities in vitro and in living cells. Crystal structures reveal repeating interactions between protein and peptide interactions as designed, including ladders of hydrogen bonds from protein side chains to peptide backbones. By redesigning the binding interfaces of individual repeat units, specificity can be achieved for non-repeating peptide sequences and for disordered regions of native proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
General approaches for designing sequence-specific peptide-binding proteins would have wide utility in proteomics and synthetic biology. However, designing peptide-binding proteins is challenging, as most peptides do not have defined structures in isolation, and hydrogen bonds must be made to the buried polar groups in the peptide backbone1–3. Here, inspired by natural and re-engineered protein–peptide systems4–11, we set out to design proteins made out of repeating units that bind peptides with repeating sequences, with a one-to-one correspondence between the repeat units of the protein and those of the peptide. We use geometric hashing to identify protein backbones and peptide-docking arrangements that are compatible with bidentate hydrogen bonds between the side chains of the protein and the peptide backbone12. The remainder of the protein sequence is then optimized for folding and peptide binding. We design repeat proteins to bind to six different tripeptide-repeat sequences in polyproline II conformations. The proteins are hyperstable and bind to four to six tandem repeats of their tripeptide targets with nanomolar to picomolar affinities in vitro and in living cells. Crystal structures reveal repeating interactions between protein and peptide interactions as designed, including ladders of hydrogen bonds from protein side chains to peptide backbones. By redesigning the binding interfaces of individual repeat units, specificity can be achieved for non-repeating peptide sequences and for disordered regions of native proteins.
Kim, David E. and Jensen, Davin R. and Feldman, David and Tischer, Doug and Saleem, Ayesha and Chow, Cameron M. and Li, Xinting and Carter, Lauren and Milles, Lukas and Nguyen, Hannah and Kang, Alex and Bera, Asim K. and Peterson, Francis C. and Volkman, Brian F. and Ovchinnikov, Sergey and Baker, David
De novo design of small beta barrel proteins Journal Article
In: Proceedings of the National Academy of Sciences, 2023.
@article{Kim2023,
title = {De novo design of small beta barrel proteins},
author = {Kim, David E.
and Jensen, Davin R.
and Feldman, David
and Tischer, Doug
and Saleem, Ayesha
and Chow, Cameron M.
and Li, Xinting
and Carter, Lauren
and Milles, Lukas
and Nguyen, Hannah
and Kang, Alex
and Bera, Asim K.
and Peterson, Francis C.
and Volkman, Brian F.
and Ovchinnikov, Sergey
and Baker, David},
url = {https://www.pnas.org/doi/10.1073/pnas.2207974120, PNAS (Open Access)},
doi = {10.1073/pnas.2207974120},
year = {2023},
date = {2023-03-10},
urldate = {2023-03-10},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Small beta barrel proteins are attractive targets for computational design because of their considerable functional diversity despite their very small size (<70 amino acids). However, there are considerable challenges to designing such structures, and there has been little success thus far. Because of the small size, the hydrophobic core stabilizing the fold is necessarily very small, and the conformational strain of barrel closure can oppose folding; also intermolecular aggregation through free beta strand edges can compete with proper monomer folding. Here, we explore the de novo design of small beta barrel topologies using both Rosetta energy–based methods and deep learning approaches to design four small beta barrel folds: Src homology 3 (SH3) and oligonucleotide/oligosaccharide-binding (OB) topologies found in nature and five and six up-and-down-stranded barrels rarely if ever seen in nature. Both approaches yielded successful designs with high thermal stability and experimentally determined structures with less than 2.4 Å rmsd from the designed models. Using deep learning for backbone generation and Rosetta for sequence design yielded higher design success rates and increased structural diversity than Rosetta alone. The ability to design a large and structurally diverse set of small beta barrel proteins greatly increases the protein shape space available for designing binders to protein targets of interest.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Small beta barrel proteins are attractive targets for computational design because of their considerable functional diversity despite their very small size (<70 amino acids). However, there are considerable challenges to designing such structures, and there has been little success thus far. Because of the small size, the hydrophobic core stabilizing the fold is necessarily very small, and the conformational strain of barrel closure can oppose folding; also intermolecular aggregation through free beta strand edges can compete with proper monomer folding. Here, we explore the de novo design of small beta barrel topologies using both Rosetta energy–based methods and deep learning approaches to design four small beta barrel folds: Src homology 3 (SH3) and oligonucleotide/oligosaccharide-binding (OB) topologies found in nature and five and six up-and-down-stranded barrels rarely if ever seen in nature. Both approaches yielded successful designs with high thermal stability and experimentally determined structures with less than 2.4 Å rmsd from the designed models. Using deep learning for backbone generation and Rosetta for sequence design yielded higher design success rates and increased structural diversity than Rosetta alone. The ability to design a large and structurally diverse set of small beta barrel proteins greatly increases the protein shape space available for designing binders to protein targets of interest.
Yeh, Andy Hsien-Wei Norn, Christoffer Kipnis, Yakov Tischer, Doug Pellock, Samuel J. Evans, Declan Ma, Pengchen Lee, Gyu Rie Zhang, Jason Z. Anishchenko, Ivan Coventry, Brian Cao, Longxing Dauparas, Justas Halabiya, Samer DeWitt, Michelle Carter, Lauren Houk, K. N. Baker, David
De novo design of luciferases using deep learning Journal Article
In: Nature, 2023.
@article{Yeh2023,
title = {De novo design of luciferases using deep learning},
author = {Yeh, Andy Hsien-Wei
Norn, Christoffer
Kipnis, Yakov
Tischer, Doug
Pellock, Samuel J.
Evans, Declan
Ma, Pengchen
Lee, Gyu Rie
Zhang, Jason Z.
Anishchenko, Ivan
Coventry, Brian
Cao, Longxing
Dauparas, Justas
Halabiya, Samer
DeWitt, Michelle
Carter, Lauren
Houk, K. N.
Baker, David},
url = {https://www.nature.com/articles/s41586-023-05696-3, Nature (Open Access)},
doi = {10.1038/s41586-023-05696-3},
year = {2023},
date = {2023-02-22},
journal = {Nature},
abstract = {De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds1,2, but has been limited by a lack of suitable protein structures and the complexity of native protein sequence–structure relationships. Here we describe a deep-learning-based ‘family-wide hallucination’ approach that generates large numbers of idealized protein structures containing diverse pocket shapes and designed sequences that encode them. We use these scaffolds to design artificial luciferases that selectively catalyse the oxidative chemiluminescence of the synthetic luciferin substrates diphenylterazine3 and 2-deoxycoelenterazine. The designed active sites position an arginine guanidinium group adjacent to an anion that develops during the reaction in a binding pocket with high shape complementarity. For both luciferin substrates, we obtain designed luciferases with high selectivity; the most active of these is a small (13.9 kDa) and thermostable (with a melting temperature higher than 95 °C) enzyme that has a catalytic efficiency on diphenylterazine (kcat/Km = 106 M−1 s−1) comparable to that of native luciferases, but a much higher substrate specificity. The creation of highly active and specific biocatalysts from scratch with broad applications in biomedicine is a key milestone for computational enzyme design, and our approach should enable generation of a wide range of luciferases and other enzymes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds1,2, but has been limited by a lack of suitable protein structures and the complexity of native protein sequence–structure relationships. Here we describe a deep-learning-based ‘family-wide hallucination’ approach that generates large numbers of idealized protein structures containing diverse pocket shapes and designed sequences that encode them. We use these scaffolds to design artificial luciferases that selectively catalyse the oxidative chemiluminescence of the synthetic luciferin substrates diphenylterazine3 and 2-deoxycoelenterazine. The designed active sites position an arginine guanidinium group adjacent to an anion that develops during the reaction in a binding pocket with high shape complementarity. For both luciferin substrates, we obtain designed luciferases with high selectivity; the most active of these is a small (13.9 kDa) and thermostable (with a melting temperature higher than 95 °C) enzyme that has a catalytic efficiency on diphenylterazine (kcat/Km = 106 M−1 s−1) comparable to that of native luciferases, but a much higher substrate specificity. The creation of highly active and specific biocatalysts from scratch with broad applications in biomedicine is a key milestone for computational enzyme design, and our approach should enable generation of a wide range of luciferases and other enzymes.
Amir Motmaen, Justas Dauparas, Minkyung Baek, Mohamad H. Abedi, David Baker, Philip Bradley
Peptide-binding specificity prediction using fine-tuned protein structure prediction networks Journal Article
In: Proceedings of the National Academy of Sciences, 2023.
@article{nokey,
title = {Peptide-binding specificity prediction using fine-tuned protein structure prediction networks},
author = {Amir Motmaen, Justas Dauparas, Minkyung Baek, Mohamad H. Abedi, David Baker, Philip Bradley},
url = {https://www.pnas.org/doi/10.1073/pnas.2216697120, PNAS (Open Access)},
doi = {10.1073/pnas.2216697120},
year = {2023},
date = {2023-02-21},
urldate = {2023-02-21},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Peptide-binding proteins play key roles in biology, and predicting their binding specificity is a long-standing challenge. While considerable protein structural information is available, the most successful current methods use sequence information alone, in part because it has been a challenge to model the subtle structural changes accompanying sequence substitutions. Protein structure prediction networks such as AlphaFold model sequence-structure relationships very accurately, and we reasoned that if it were possible to specifically train such networks on binding data, more generalizable models could be created. We show that placing a classifier on top of the AlphaFold network and fine-tuning the combined network parameters for both classification and structure prediction accuracy leads to a model with strong generalizable performance on a wide range of Class I and Class II peptide-MHC interactions that approaches the overall performance of the state-of-the-art NetMHCpan sequence-based method. The peptide-MHC optimized model shows excellent performance in distinguishing binding and non-binding peptides to SH3 and PDZ domains. This ability to generalize well beyond the training set far exceeds that of sequence-only models and should be particularly powerful for systems where less experimental data are available.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Peptide-binding proteins play key roles in biology, and predicting their binding specificity is a long-standing challenge. While considerable protein structural information is available, the most successful current methods use sequence information alone, in part because it has been a challenge to model the subtle structural changes accompanying sequence substitutions. Protein structure prediction networks such as AlphaFold model sequence-structure relationships very accurately, and we reasoned that if it were possible to specifically train such networks on binding data, more generalizable models could be created. We show that placing a classifier on top of the AlphaFold network and fine-tuning the combined network parameters for both classification and structure prediction accuracy leads to a model with strong generalizable performance on a wide range of Class I and Class II peptide-MHC interactions that approaches the overall performance of the state-of-the-art NetMHCpan sequence-based method. The peptide-MHC optimized model shows excellent performance in distinguishing binding and non-binding peptides to SH3 and PDZ domains. This ability to generalize well beyond the training set far exceeds that of sequence-only models and should be particularly powerful for systems where less experimental data are available.
Gerben, Stacey R and Borst, Andrew J and Hicks, Derrick R and Moczygemba, Isabelle and Feldman, David and Coventry, Brian and Yang, Wei and Bera, Asim K. and Miranda, Marcos and Kang, Alex and Nguyen, Hannah and Baker, David
Design of Diverse Asymmetric Pockets in De Novo Homo-oligomeric Proteins Journal Article
In: Biochemistry, 2023.
@article{Gerben2023,
title = {Design of Diverse Asymmetric Pockets in De Novo Homo-oligomeric Proteins},
author = {Gerben, Stacey R
and Borst, Andrew J
and Hicks, Derrick R
and Moczygemba, Isabelle
and Feldman, David
and Coventry, Brian
and Yang, Wei
and Bera, Asim K.
and Miranda, Marcos
and Kang, Alex
and Nguyen, Hannah
and Baker, David},
url = {https://pubs.acs.org/doi/full/10.1021/acs.biochem.2c00497, Biochemistry
https://www.bakerlab.org/wp-content/uploads/2023/01/Gerben_Biochemistry2023.pdf, PDF},
doi = {10.1021/acs.biochem.2c00497},
year = {2023},
date = {2023-01-17},
journal = {Biochemistry},
abstract = {A challenge for design of protein–small-molecule recognition is that incorporation of cavities with size, shape, and composition suitable for specific recognition can considerably destabilize protein monomers. This challenge can be overcome through binding pockets formed at homo-oligomeric interfaces between folded monomers. Interfaces surrounding the central homo-oligomer symmetry axes necessarily have the same symmetry and so may not be well suited to binding asymmetric molecules. To enable general recognition of arbitrary asymmetric substrates and small molecules, we developed an approach to designing asymmetric interfaces at off-axis sites on homo-oligomers, analogous to those found in native homo-oligomeric proteins such as glutamine synthetase. We symmetrically dock curved helical repeat proteins such that they form pockets at the asymmetric interface of the oligomer with sizes ranging from several angstroms, appropriate for binding a single ion, to up to more than 20 Å across. Of the 133 proteins tested, 84 had soluble expression in E. coli, 47 had correct oligomeric states in solution, 35 had small-angle X-ray scattering (SAXS) data largely consistent with design models, and 8 had negative-stain electron microscopy (nsEM) 2D class averages showing the structures coming together as designed. Both an X-ray crystal structure and a cryogenic electron microscopy (cryoEM) structure are close to the computational design models. The nature of these proteins as homo-oligomers allows them to be readily built into higher-order structures such as nanocages, and the asymmetric pockets of these structures open rich possibilities for small-molecule binder design free from the constraints associated with monomer destabilization.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A challenge for design of protein–small-molecule recognition is that incorporation of cavities with size, shape, and composition suitable for specific recognition can considerably destabilize protein monomers. This challenge can be overcome through binding pockets formed at homo-oligomeric interfaces between folded monomers. Interfaces surrounding the central homo-oligomer symmetry axes necessarily have the same symmetry and so may not be well suited to binding asymmetric molecules. To enable general recognition of arbitrary asymmetric substrates and small molecules, we developed an approach to designing asymmetric interfaces at off-axis sites on homo-oligomers, analogous to those found in native homo-oligomeric proteins such as glutamine synthetase. We symmetrically dock curved helical repeat proteins such that they form pockets at the asymmetric interface of the oligomer with sizes ranging from several angstroms, appropriate for binding a single ion, to up to more than 20 Å across. Of the 133 proteins tested, 84 had soluble expression in E. coli, 47 had correct oligomeric states in solution, 35 had small-angle X-ray scattering (SAXS) data largely consistent with design models, and 8 had negative-stain electron microscopy (nsEM) 2D class averages showing the structures coming together as designed. Both an X-ray crystal structure and a cryogenic electron microscopy (cryoEM) structure are close to the computational design models. The nature of these proteins as homo-oligomers allows them to be readily built into higher-order structures such as nanocages, and the asymmetric pockets of these structures open rich possibilities for small-molecule binder design free from the constraints associated with monomer destabilization.
COLLABORATOR LED
Audrey Olshefsky, Halli Benasutti, Meilyn Sylvestre, Gabriel L Butterfield, Gabriel J Rocklin, Christian Richardson, Derrick R Hicks, Marc J Lajoie, Kefan Song, Elizabeth Leaf, Catherine Treichel, Justin Decarreau, Sharon Ke, Gargi Kher, Lauren Carter, Jeffrey S Chamberlain, David Baker, Neil P King, Suzie H Pun
In vivo selection of synthetic nucleocapsids for tissue targeting Journal Article
In: PNAS, 2023.
@article{Olshefsky2023,
title = {In vivo selection of synthetic nucleocapsids for tissue targeting},
author = {Audrey Olshefsky and Halli Benasutti and Meilyn Sylvestre and Gabriel L Butterfield and Gabriel J Rocklin and Christian Richardson and Derrick R Hicks and Marc J Lajoie and Kefan Song and Elizabeth Leaf and Catherine Treichel and Justin Decarreau and Sharon Ke and Gargi Kher and Lauren Carter and Jeffrey S Chamberlain and David Baker and Neil P King and Suzie H Pun},
url = {https://www.pnas.org/doi/abs/10.1073/pnas.2306129120, PNAS [Open Access]},
doi = {10.1073/pnas.2306129120},
year = {2023},
date = {2023-11-01},
urldate = {2023-11-01},
journal = {PNAS},
abstract = {Controlling the biodistribution of protein- and nanoparticle-based therapeutic formulations remains challenging. In vivo library selection is an effective method for identifying constructs that exhibit desired distribution behavior; library variants can be selected based on their ability to localize to the tissue or compartment of interest despite complex physiological challenges. Here, we describe further development of an in vivo library selection platform based on self-assembling protein nanoparticles encapsulating their own mRNA genomes (synthetic nucleocapsids or synNCs). We tested two distinct libraries: a low-diversity library composed of synNC surface mutations (45 variants) and a high-diversity library composed of synNCs displaying miniproteins with binder-like properties (6.2 million variants). While we did not identify any variants from the low-diversity surface library that yielded therapeutically relevant changes in biodistribution, the high-diversity miniprotein display library yielded variants that shifted accumulation toward lungs or muscles in just two rounds of in vivo selection. Our approach should contribute to achieving specific tissue homing patterns and identifying targeting ligands for diseases of interest.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Controlling the biodistribution of protein- and nanoparticle-based therapeutic formulations remains challenging. In vivo library selection is an effective method for identifying constructs that exhibit desired distribution behavior; library variants can be selected based on their ability to localize to the tissue or compartment of interest despite complex physiological challenges. Here, we describe further development of an in vivo library selection platform based on self-assembling protein nanoparticles encapsulating their own mRNA genomes (synthetic nucleocapsids or synNCs). We tested two distinct libraries: a low-diversity library composed of synNC surface mutations (45 variants) and a high-diversity library composed of synNCs displaying miniproteins with binder-like properties (6.2 million variants). While we did not identify any variants from the low-diversity surface library that yielded therapeutically relevant changes in biodistribution, the high-diversity miniprotein display library yielded variants that shifted accumulation toward lungs or muscles in just two rounds of in vivo selection. Our approach should contribute to achieving specific tissue homing patterns and identifying targeting ligands for diseases of interest.
Hutchinson, Geoffrey B. and Abiona, Olubukola M. and Ziwawo, Cynthia T. and Werner, Anne P. and Ellis, Daniel and Tsybovsky, Yaroslav and Leist, Sarah R. and Palandjian, Charis and West, Ande and Fritch, Ethan J. and Wang, Nianshuang and Wrapp, Daniel and Boyoglu-Barnum, Seyhan and Ueda, George and Baker, David and Kanekiyo, Masaru and McLellan, Jason S. and Baric, Ralph S. and King, Neil P. and Graham, Barney S. and Corbett-Helaire, Kizzmekia S.
Nanoparticle display of prefusion coronavirus spike elicits S1-focused cross-reactive antibody response against diverse coronavirus subgenera Journal Article
In: Nature Communications, 2023.
@article{Hutchinson2023,
title = {Nanoparticle display of prefusion coronavirus spike elicits S1-focused cross-reactive antibody response against diverse coronavirus subgenera},
author = {Hutchinson, Geoffrey B.
and Abiona, Olubukola M.
and Ziwawo, Cynthia T.
and Werner, Anne P.
and Ellis, Daniel
and Tsybovsky, Yaroslav
and Leist, Sarah R.
and Palandjian, Charis
and West, Ande
and Fritch, Ethan J.
and Wang, Nianshuang
and Wrapp, Daniel
and Boyoglu-Barnum, Seyhan
and Ueda, George
and Baker, David
and Kanekiyo, Masaru
and McLellan, Jason S.
and Baric, Ralph S.
and King, Neil P.
and Graham, Barney S.
and Corbett-Helaire, Kizzmekia S.},
url = {https://www.nature.com/articles/s41467-023-41661-4, Nature Communications (Open Access)},
doi = {10.1038/s41467-023-41661-4},
year = {2023},
date = {2023-10-04},
journal = {Nature Communications},
abstract = {Multivalent antigen display is a fast-growing area of interest toward broadly protective vaccines. Current nanoparticle-based vaccine candidates demonstrate the ability to confer antibody-mediated immunity against divergent strains of notably mutable viruses. In coronaviruses, this work is predominantly aimed at targeting conserved epitopes of the receptor binding domain. However, targeting conserved non-RBD epitopes could limit the potential for antigenic escape. To explore new potential targets, we engineered protein nanoparticles displaying coronavirus prefusion-stabilized spike (CoV_S-2P) trimers derived from MERS-CoV, SARS-CoV-1, SARS-CoV-2, hCoV-HKU1, and hCoV-OC43 and assessed their immunogenicity in female mice. Monotypic SARS-1 nanoparticles elicit cross-neutralizing antibodies against MERS-CoV and protect against MERS-CoV challenge. MERS and SARS nanoparticles elicit S1-focused antibodies, revealing a conserved site on the S N-terminal domain. Moreover, mosaic nanoparticles co-displaying distinct CoV_S-2P trimers elicit antibody responses to distant cross-group antigens and protect male and female mice against MERS-CoV challenge. Our findings will inform further efforts toward the development of pan-coronavirus vaccines.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Multivalent antigen display is a fast-growing area of interest toward broadly protective vaccines. Current nanoparticle-based vaccine candidates demonstrate the ability to confer antibody-mediated immunity against divergent strains of notably mutable viruses. In coronaviruses, this work is predominantly aimed at targeting conserved epitopes of the receptor binding domain. However, targeting conserved non-RBD epitopes could limit the potential for antigenic escape. To explore new potential targets, we engineered protein nanoparticles displaying coronavirus prefusion-stabilized spike (CoV_S-2P) trimers derived from MERS-CoV, SARS-CoV-1, SARS-CoV-2, hCoV-HKU1, and hCoV-OC43 and assessed their immunogenicity in female mice. Monotypic SARS-1 nanoparticles elicit cross-neutralizing antibodies against MERS-CoV and protect against MERS-CoV challenge. MERS and SARS nanoparticles elicit S1-focused antibodies, revealing a conserved site on the S N-terminal domain. Moreover, mosaic nanoparticles co-displaying distinct CoV_S-2P trimers elicit antibody responses to distant cross-group antigens and protect male and female mice against MERS-CoV challenge. Our findings will inform further efforts toward the development of pan-coronavirus vaccines.
Joseph L. Watson, Lara K. Kruger, Ariel J. Ben-Sasson, Alice Bittleston, Marta N. Shahbazi, Vicente Jose Planelles-Herrero, Joseph E. Chambers, James D. Manton, David Baker,, Emmanuel Derivery
Synthetic Par polarity induces cytoskeleton asymmetry in unpolarized mammalian cells Journal Article
In: Cell, 2023.
@article{Watson2023b,
title = {Synthetic Par polarity induces cytoskeleton asymmetry in unpolarized mammalian cells},
author = {Joseph L. Watson, Lara K. Kruger, Ariel J. Ben-Sasson, Alice Bittleston, Marta N. Shahbazi, Vicente Jose Planelles-Herrero, Joseph E. Chambers, James D. Manton, David Baker, and Emmanuel Derivery},
url = {https://www.cell.com/cell/fulltext/S0092-8674(23)00968-6, Cell [Open Access]},
year = {2023},
date = {2023-09-28},
journal = {Cell},
abstract = {Polarized cells rely on a polarized cytoskeleton to function. Yet, how cortical polarity cues induce cytoskeleton polarization remains elusive. Here, we capitalized on recently established designed 2D protein arrays to ectopically engineer cortical polarity of virtually any protein of interest during mitosis in various cell types. This enables direct manipulation of polarity signaling and the identification of the cortical cues sufficient for cytoskeleton polarization. Using this assay, we dissected the logic of the Par complex pathway, a key regulator of cytoskeleton polarity during asymmetric cell division. We show that cortical clustering of any Par complex subunit is sufficient to trigger complex assembly and that the primary kinetic barrier to complex assembly is the relief of Par6 autoinhibition. Further, we found that inducing cortical Par complex polarity induces two hallmarks of asymmetric cell division in unpolarized mammalian cells: spindle orientation, occurring via Par3, and central spindle asymmetry, depending on aPKC activity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Polarized cells rely on a polarized cytoskeleton to function. Yet, how cortical polarity cues induce cytoskeleton polarization remains elusive. Here, we capitalized on recently established designed 2D protein arrays to ectopically engineer cortical polarity of virtually any protein of interest during mitosis in various cell types. This enables direct manipulation of polarity signaling and the identification of the cortical cues sufficient for cytoskeleton polarization. Using this assay, we dissected the logic of the Par complex pathway, a key regulator of cytoskeleton polarity during asymmetric cell division. We show that cortical clustering of any Par complex subunit is sufficient to trigger complex assembly and that the primary kinetic barrier to complex assembly is the relief of Par6 autoinhibition. Further, we found that inducing cortical Par complex polarity induces two hallmarks of asymmetric cell division in unpolarized mammalian cells: spindle orientation, occurring via Par3, and central spindle asymmetry, depending on aPKC activity.
Ammar Alghadeer, Sesha Hanson-Drury, Anjali P. Patni, Devon D. Ehnes, Yan Ting Zhao, Zicong Li, Ashish Phal, Thomas Vincent, Yen C. Lim, Diana O’Day, Cailyn H. Spurrell, Aishwarya A. Gogate, Hai Zhang, Arikketh Devi, Yuliang Wang, Lea Starita, Dan Doherty, Ian A. Glass, Jay Shendure, Benjamin S. Freedman, David Baker, Mary C. Regier, Julie Mathieu, Hannele Ruohola-Baker
Single-cell census of human tooth development enables generation of human enamel Journal Article
In: Developmental Cell, 2023.
@article{ALGHADEER2023,
title = {Single-cell census of human tooth development enables generation of human enamel},
author = {Ammar Alghadeer and Sesha Hanson-Drury and Anjali P. Patni and Devon D. Ehnes and Yan Ting Zhao and Zicong Li and Ashish Phal and Thomas Vincent and Yen C. Lim and Diana O’Day and Cailyn H. Spurrell and Aishwarya A. Gogate and Hai Zhang and Arikketh Devi and Yuliang Wang and Lea Starita and Dan Doherty and Ian A. Glass and Jay Shendure and Benjamin S. Freedman and David Baker and Mary C. Regier and Julie Mathieu and Hannele Ruohola-Baker},
url = {https://www.cell.com/developmental-cell/fulltext/S1534-5807(23)00360-X, Developmental Cell
https://www.bakerlab.org/wp-content/uploads/2023/08/PIIS153458072300360X.pdf, PDF},
doi = {https://doi.org/10.1016/j.devcel.2023.07.013},
year = {2023},
date = {2023-08-14},
urldate = {2023-08-14},
journal = {Developmental Cell},
abstract = {Summary
Tooth enamel secreted by ameloblasts (AMs) is the hardest material in the human body, acting as a shield to protect the teeth. However, the enamel is gradually damaged or partially lost in over 90% of adults and cannot be regenerated due to a lack of ameloblasts in erupted teeth. Here, we use single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) to establish a spatiotemporal single-cell census for the developing human tooth and identify regulatory mechanisms controlling the differentiation process of human ameloblasts. We identify key signaling pathways involved between the support cells and ameloblasts during fetal development and recapitulate those findings in human ameloblast in vitro differentiation from induced pluripotent stem cells (iPSCs). We furthermore develop a disease model of amelogenesis imperfecta in a three-dimensional (3D) organoid system and show AM maturation to mineralized structure in vivo. These studies pave the way for future regenerative dentistry.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Summary
Tooth enamel secreted by ameloblasts (AMs) is the hardest material in the human body, acting as a shield to protect the teeth. However, the enamel is gradually damaged or partially lost in over 90% of adults and cannot be regenerated due to a lack of ameloblasts in erupted teeth. Here, we use single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) to establish a spatiotemporal single-cell census for the developing human tooth and identify regulatory mechanisms controlling the differentiation process of human ameloblasts. We identify key signaling pathways involved between the support cells and ameloblasts during fetal development and recapitulate those findings in human ameloblast in vitro differentiation from induced pluripotent stem cells (iPSCs). We furthermore develop a disease model of amelogenesis imperfecta in a three-dimensional (3D) organoid system and show AM maturation to mineralized structure in vivo. These studies pave the way for future regenerative dentistry.
Tooth enamel secreted by ameloblasts (AMs) is the hardest material in the human body, acting as a shield to protect the teeth. However, the enamel is gradually damaged or partially lost in over 90% of adults and cannot be regenerated due to a lack of ameloblasts in erupted teeth. Here, we use single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) to establish a spatiotemporal single-cell census for the developing human tooth and identify regulatory mechanisms controlling the differentiation process of human ameloblasts. We identify key signaling pathways involved between the support cells and ameloblasts during fetal development and recapitulate those findings in human ameloblast in vitro differentiation from induced pluripotent stem cells (iPSCs). We furthermore develop a disease model of amelogenesis imperfecta in a three-dimensional (3D) organoid system and show AM maturation to mineralized structure in vivo. These studies pave the way for future regenerative dentistry.
Enrico Rennella, Danny D. Sahtoe, David Baker,, Lewis E. Kay
Exploiting conformational dynamics to modulate the function of designed proteins Journal Article
In: Proceedings of the National Academy of Sciences, 2023.
@article{nokey,
title = {Exploiting conformational dynamics to modulate the function of designed proteins},
author = {Enrico Rennella, Danny D. Sahtoe, David Baker, and Lewis E. Kay
},
url = {https://www.pnas.org/doi/10.1073/pnas.2303149120, PNAS},
doi = {10.1073/pnas.2303149120},
year = {2023},
date = {2023-04-24},
journal = {Proceedings of the National Academy of Sciences},
abstract = {With the recent success in calculating protein structures from amino acid sequences using artificial intelligence-based algorithms, an important next step is to decipher how dynamics is encoded by the primary protein sequence so as to better predict function. Such dynamics information is critical for protein design, where strategies could then focus not only on sequences that fold into particular structures that perform a given task, but would also include low-lying excited protein states that could influence the function of the designed protein. Herein, we illustrate the importance of dynamics in modulating the function of C34, a designed α/β protein that captures β-strands of target ligands and is a member of a family of proteins designed to sequester β-strands and β hairpins of aggregation-prone molecules that lead to a variety of pathologies. Using a strategy to “see” regions of apo C34 that are invisible to NMR spectroscopy as a result of pervasive conformational exchange, as well as a mutagenesis approach whereby C34 molecules are stabilized into a single conformer, we determine the structures of the predominant conformations that are sampled by C34 and show that these attenuate the affinity for cognate peptide. Subsequently, the observed motion is exploited to develop an allosterically regulated peptide binder whose binding affinity can be controlled through the addition of a second molecule. Our study emphasizes the unique role that NMR can play in directing the design process and in the construction of new molecules with more complex functionality.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
With the recent success in calculating protein structures from amino acid sequences using artificial intelligence-based algorithms, an important next step is to decipher how dynamics is encoded by the primary protein sequence so as to better predict function. Such dynamics information is critical for protein design, where strategies could then focus not only on sequences that fold into particular structures that perform a given task, but would also include low-lying excited protein states that could influence the function of the designed protein. Herein, we illustrate the importance of dynamics in modulating the function of C34, a designed α/β protein that captures β-strands of target ligands and is a member of a family of proteins designed to sequester β-strands and β hairpins of aggregation-prone molecules that lead to a variety of pathologies. Using a strategy to “see” regions of apo C34 that are invisible to NMR spectroscopy as a result of pervasive conformational exchange, as well as a mutagenesis approach whereby C34 molecules are stabilized into a single conformer, we determine the structures of the predominant conformations that are sampled by C34 and show that these attenuate the affinity for cognate peptide. Subsequently, the observed motion is exploited to develop an allosterically regulated peptide binder whose binding affinity can be controlled through the addition of a second molecule. Our study emphasizes the unique role that NMR can play in directing the design process and in the construction of new molecules with more complex functionality.
Watson, Paris R. and Gupta, Suchetana and Hosseinzadeh, Parisa and Brown, Benjamin P. and Baker, David and Christianson, David W.
Macrocyclic Octapeptide Binding and Inferences on Protein Substrate Binding to Histone Deacetylase 6 Journal Article
In: ACS Chemical Biology, 2023.
@article{Watson0000,
title = {Macrocyclic Octapeptide Binding and Inferences on Protein Substrate Binding to Histone Deacetylase 6},
author = {Watson, Paris R.
and Gupta, Suchetana
and Hosseinzadeh, Parisa
and Brown, Benjamin P.
and Baker, David
and Christianson, David W.},
url = {https://pubs.acs.org/doi/full/10.1021/acschembio.3c00113, ACS Chem. Biol.
https://www.bakerlab.org/wp-content/uploads/2023/04/acschembio.3c00113.pdf, PDF},
doi = {10.1021/acschembio.3c00113},
year = {2023},
date = {2023-04-07},
urldate = {2023-04-07},
journal = {ACS Chemical Biology},
abstract = {Histone deacetylases (HDACs) are essential for the regulation of myriad biological processes, and their aberrant function is implicated in cancer, neurodegeneration, and other diseases. The cytosolic isozyme HDAC6 is unique among the greater family of deacetylases in that it contains two catalytic domains, CD1 and CD2. HDAC6 CD2 is responsible for tubulin deacetylase and tau deacetylase activities, inhibition of which is a key goal as new therapeutic approaches are explored. Of particular interest as HDAC inhibitors are naturally occurring cyclic tetrapeptides such as Trapoxin A or HC Toxin, or the cyclic depsipeptides Largazole and Romidepsin. Even more intriguing are larger, computationally designed macrocyclic peptide inhibitors. Here, we report the 2.0 Å resolution crystal structure of HDAC6 CD2 complexed with macrocyclic octapeptide 1. Comparison with the previously reported structure of the complex with macrocyclic octapeptide 2 reveals that a potent thiolate–zinc interaction made by the unnatural amino acid (S)-2-amino-7-sulfanylheptanoic acid contributes to nanomolar inhibitory potency for each inhibitor. Apart from this zinc-binding residue, octapeptides adopt strikingly different overall conformations and make few direct hydrogen bonds with the protein. Intermolecular interactions are dominated by water-mediated hydrogen bonds; in essence, water molecules appear to cushion the enzyme–octapeptide interface. In view of the broad specificity observed for protein substrates of HDAC6 CD2, we suggest that the binding of macrocyclic octapeptides may mimic certain features of the binding of macromolecular protein substrates.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Histone deacetylases (HDACs) are essential for the regulation of myriad biological processes, and their aberrant function is implicated in cancer, neurodegeneration, and other diseases. The cytosolic isozyme HDAC6 is unique among the greater family of deacetylases in that it contains two catalytic domains, CD1 and CD2. HDAC6 CD2 is responsible for tubulin deacetylase and tau deacetylase activities, inhibition of which is a key goal as new therapeutic approaches are explored. Of particular interest as HDAC inhibitors are naturally occurring cyclic tetrapeptides such as Trapoxin A or HC Toxin, or the cyclic depsipeptides Largazole and Romidepsin. Even more intriguing are larger, computationally designed macrocyclic peptide inhibitors. Here, we report the 2.0 Å resolution crystal structure of HDAC6 CD2 complexed with macrocyclic octapeptide 1. Comparison with the previously reported structure of the complex with macrocyclic octapeptide 2 reveals that a potent thiolate–zinc interaction made by the unnatural amino acid (S)-2-amino-7-sulfanylheptanoic acid contributes to nanomolar inhibitory potency for each inhibitor. Apart from this zinc-binding residue, octapeptides adopt strikingly different overall conformations and make few direct hydrogen bonds with the protein. Intermolecular interactions are dominated by water-mediated hydrogen bonds; in essence, water molecules appear to cushion the enzyme–octapeptide interface. In view of the broad specificity observed for protein substrates of HDAC6 CD2, we suggest that the binding of macrocyclic octapeptides may mimic certain features of the binding of macromolecular protein substrates.
Yang, Huilin and Ulge, Umut Y. and Quijano-Rubio, Alfredo and Bernstein, Zachary J. and Maestas, David R. and Chun, Jung-Ho and Wang, Wentao and Lin, Jian-Xin and Jude, Kevin M. and Singh, Srujan and Orcutt-Jahns, Brian T. and Li, Peng and Mou, Jody and Chung, Liam and Kuo, Yun-Huai and Ali, Yasmin H. and Meyer, Aaron S. and Grayson, Warren L. and Heller, Nicola M. and Garcia, K. Christopher and Leonard, Warren J. and Silva, Daniel-Adriano and Elisseeff, Jennifer H. and Baker, David and Spangler, Jamie B.
Design of cell-type-specific hyperstable IL-4 mimetics via modular de novo scaffolds Journal Article
In: Nature Chemical Biology, 2023.
@article{Yang2023,
title = {Design of cell-type-specific hyperstable IL-4 mimetics via modular de novo scaffolds},
author = {Yang, Huilin
and Ulge, Umut Y.
and Quijano-Rubio, Alfredo
and Bernstein, Zachary J.
and Maestas, David R.
and Chun, Jung-Ho
and Wang, Wentao
and Lin, Jian-Xin
and Jude, Kevin M.
and Singh, Srujan
and Orcutt-Jahns, Brian T.
and Li, Peng
and Mou, Jody
and Chung, Liam
and Kuo, Yun-Huai
and Ali, Yasmin H.
and Meyer, Aaron S.
and Grayson, Warren L.
and Heller, Nicola M.
and Garcia, K. Christopher
and Leonard, Warren J.
and Silva, Daniel-Adriano
and Elisseeff, Jennifer H.
and Baker, David
and Spangler, Jamie B.},
url = {https://www.nature.com/articles/s41589-023-01313-6, Nature Chemical Biology
https://www.bakerlab.org/wp-content/uploads/2023/05/s41589-023-01313-6-1.pdf, PDF},
doi = {10.1038/s41589-023-01313-6},
year = {2023},
date = {2023-04-06},
journal = {Nature Chemical Biology},
abstract = {The interleukin-4 (IL-4) cytokine plays a critical role in modulating immune homeostasis. Although there is great interest in harnessing this cytokine as a therapeutic in natural or engineered formats, the clinical potential of native IL-4 is limited by its instability and pleiotropic actions. Here, we design IL-4 cytokine mimetics (denoted Neo-4) based on a de novo engineered IL-2 mimetic scaffold and demonstrate that these cytokines can recapitulate physiological functions of IL-4 in cellular and animal models. In contrast with natural IL-4, Neo-4 is hyperstable and signals exclusively through the type I IL-4 receptor complex, providing previously inaccessible insights into differential IL-4 signaling through type I versus type II receptors. Because of their hyperstability, our computationally designed mimetics can directly incorporate into sophisticated biomaterials that require heat processing, such as three-dimensional-printed scaffolds. Neo-4 should be broadly useful for interrogating IL-4 biology, and the design workflow will inform targeted cytokine therapeutic development.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The interleukin-4 (IL-4) cytokine plays a critical role in modulating immune homeostasis. Although there is great interest in harnessing this cytokine as a therapeutic in natural or engineered formats, the clinical potential of native IL-4 is limited by its instability and pleiotropic actions. Here, we design IL-4 cytokine mimetics (denoted Neo-4) based on a de novo engineered IL-2 mimetic scaffold and demonstrate that these cytokines can recapitulate physiological functions of IL-4 in cellular and animal models. In contrast with natural IL-4, Neo-4 is hyperstable and signals exclusively through the type I IL-4 receptor complex, providing previously inaccessible insights into differential IL-4 signaling through type I versus type II receptors. Because of their hyperstability, our computationally designed mimetics can directly incorporate into sophisticated biomaterials that require heat processing, such as three-dimensional-printed scaffolds. Neo-4 should be broadly useful for interrogating IL-4 biology, and the design workflow will inform targeted cytokine therapeutic development.
Wang, Jing Yang (John) and Khmelinskaia, Alena and Sheffler, William and Miranda, Marcos C. and Antanasijevic, Aleksandar and Borst, Andrew J. and Torres, Susana V. and Shu, Chelsea and Hsia, Yang and Nattermann, Una and Ellis, Daniel and Walkey, Carl and Ahlrichs, Maggie and Chan, Sidney and Kang, Alex and Nguyen, Hannah and Sydeman, Claire and Sankaran, Banumathi and Wu, Mengyu and Bera, Asim K. and Carter, Lauren and Fiala, Brooke and Murphy, Michael and Baker, David and Ward, Andrew B. and King, Neil P.
Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains Journal Article
In: Proceedings of the National Academy of Sciences, 2023.
@article{Wang2023,
title = {Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains},
author = {Wang, Jing Yang (John)
and Khmelinskaia, Alena
and Sheffler, William
and Miranda, Marcos C.
and Antanasijevic, Aleksandar
and Borst, Andrew J.
and Torres, Susana V.
and Shu, Chelsea
and Hsia, Yang
and Nattermann, Una
and Ellis, Daniel
and Walkey, Carl
and Ahlrichs, Maggie
and Chan, Sidney
and Kang, Alex
and Nguyen, Hannah
and Sydeman, Claire
and Sankaran, Banumathi
and Wu, Mengyu
and Bera, Asim K.
and Carter, Lauren
and Fiala, Brooke
and Murphy, Michael
and Baker, David
and Ward, Andrew B.
and King, Neil P.},
url = {https://www.pnas.org/doi/10.1073/pnas.2214556120, PNAS (Open Access)},
doi = {10.1073/pnas.2214556120},
year = {2023},
date = {2023-03-08},
urldate = {2023-03-08},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Computationally designed protein nanoparticles have recently emerged as a promising platform for the development of new vaccines and biologics. For many applications, secretion of designed nanoparticles from eukaryotic cells would be advantageous, but in practice, they often secrete poorly. Here we show that designed hydrophobic interfaces that drive nanoparticle assembly are often predicted to form cryptic transmembrane domains, suggesting that interaction with the membrane insertion machinery could limit efficient secretion. We develop a general computational protocol, the Degreaser, to design away cryptic transmembrane domains without sacrificing protein stability. The retroactive application of the Degreaser to previously designed nanoparticle components and nanoparticles considerably improves secretion, and modular integration of the Degreaser into design pipelines results in new nanoparticles that secrete as robustly as naturally occurring protein assemblies. Both the Degreaser protocol and the nanoparticles we describe may be broadly useful in biotechnological applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computationally designed protein nanoparticles have recently emerged as a promising platform for the development of new vaccines and biologics. For many applications, secretion of designed nanoparticles from eukaryotic cells would be advantageous, but in practice, they often secrete poorly. Here we show that designed hydrophobic interfaces that drive nanoparticle assembly are often predicted to form cryptic transmembrane domains, suggesting that interaction with the membrane insertion machinery could limit efficient secretion. We develop a general computational protocol, the Degreaser, to design away cryptic transmembrane domains without sacrificing protein stability. The retroactive application of the Degreaser to previously designed nanoparticle components and nanoparticles considerably improves secretion, and modular integration of the Degreaser into design pipelines results in new nanoparticles that secrete as robustly as naturally occurring protein assemblies. Both the Degreaser protocol and the nanoparticles we describe may be broadly useful in biotechnological applications.
Lin, Dingchang and Li, Xiuyuan and Moult, Eric and Park, Pojeong and Tang, Benjamin and Shen, Hao and Grimm, Jonathan B. and Falco, Natalie and Jia, Bill Z. and Baker, David and Lavis, Luke D. and Cohen, Adam E.
Time-tagged ticker tapes for intracellular recordings Journal Article
In: Nature Biotechnology, 2023.
@article{Lin2023,
title = {Time-tagged ticker tapes for intracellular recordings},
author = {Lin, Dingchang
and Li, Xiuyuan
and Moult, Eric
and Park, Pojeong
and Tang, Benjamin
and Shen, Hao
and Grimm, Jonathan B.
and Falco, Natalie
and Jia, Bill Z.
and Baker, David
and Lavis, Luke D.
and Cohen, Adam E.},
url = {https://www.nature.com/articles/s41587-022-01524-7, Nature Biotechnology
https://www.bakerlab.org/wp-content/uploads/2023/01/s41587-022-01524-7.pdf, PDF},
doi = {10.1038/s41587-022-01524-7},
year = {2023},
date = {2023-01-02},
journal = {Nature Biotechnology},
abstract = {Recording transcriptional histories of a cell would enable deeper understanding of cellular developmental trajectories and responses to external perturbations. Here we describe an engineered protein fiber that incorporates diverse fluorescent marks during its growth to store a ticker tape-like history. An embedded HaloTag reporter incorporates user-supplied dyes, leading to colored stripes that map the growth of each individual fiber to wall clock time. A co-expressed eGFP tag driven by a promoter of interest records a history of transcriptional activation. High-resolution multi-spectral imaging on fixed samples reads the cellular histories, and interpolation of eGFP marks relative to HaloTag timestamps provides accurate absolute timing. We demonstrate recordings of doxycycline-induced transcription in HEK cells and cFos promoter activation in cultured neurons, with a single-cell absolute accuracy of 30–40 minutes over a 12-hour recording. The protein-based ticker tape design we present here could be generalized to achieve massively parallel single-cell recordings of diverse physiological modalities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recording transcriptional histories of a cell would enable deeper understanding of cellular developmental trajectories and responses to external perturbations. Here we describe an engineered protein fiber that incorporates diverse fluorescent marks during its growth to store a ticker tape-like history. An embedded HaloTag reporter incorporates user-supplied dyes, leading to colored stripes that map the growth of each individual fiber to wall clock time. A co-expressed eGFP tag driven by a promoter of interest records a history of transcriptional activation. High-resolution multi-spectral imaging on fixed samples reads the cellular histories, and interpolation of eGFP marks relative to HaloTag timestamps provides accurate absolute timing. We demonstrate recordings of doxycycline-induced transcription in HEK cells and cFos promoter activation in cultured neurons, with a single-cell absolute accuracy of 30–40 minutes over a 12-hour recording. The protein-based ticker tape design we present here could be generalized to achieve massively parallel single-cell recordings of diverse physiological modalities.
Florian Praetorius, Philip J. Y. Leung, Maxx H. Tessmer, Adam Broerman, Cullen Demakis, Acacia F. Dishman, Arvind Pillai, Abbas Idris, David Juergens, Justas Dauparas, Xinting Li, Paul M. Levine, Mila Lamb, Ryanne K. Ballard, Stacey R. Gerben, Hannah Nguyen, Alex Kang, Banumathi Sankaran, Asim K. Bera, Brian F. Volkman, Jeff Nivala, Stefan Stoll, David Baker
Design of stimulus-responsive two-state hinge proteins Journal Article
In: Science, vol. 381, no. 6659, pp. 754-760, 2023.
@article{doi:10.1126/science.adg7731b,
title = {Design of stimulus-responsive two-state hinge proteins},
author = {Florian Praetorius and Philip J. Y. Leung and Maxx H. Tessmer and Adam Broerman and Cullen Demakis and Acacia F. Dishman and Arvind Pillai and Abbas Idris and David Juergens and Justas Dauparas and Xinting Li and Paul M. Levine and Mila Lamb and Ryanne K. Ballard and Stacey R. Gerben and Hannah Nguyen and Alex Kang and Banumathi Sankaran and Asim K. Bera and Brian F. Volkman and Jeff Nivala and Stefan Stoll and David Baker},
url = {https://www.science.org/doi/abs/10.1126/science.adg7731},
doi = {10.1126/science.adg7731},
year = {2023},
date = {2023-01-01},
journal = {Science},
volume = {381},
number = {6659},
pages = {754-760},
abstract = {In nature, proteins that switch between two conformations in response to environmental stimuli structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Designing proteins with two distinct but fully structured conformations is a challenge for protein design as it requires sculpting an energy landscape with two distinct minima. Here we describe the design of “hinge” proteins that populate one designed state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, double electron-electron resonance spectroscopy, and binding measurements demonstrate that despite the significant structural differences the two states are designed with atomic level accuracy and that the conformational and binding equilibria are closely coupled. Natural proteins often adopt multiple conformational states, thereby changing their activity or binding partners in response to another protein, small molecule, or other stimulus. It has been difficult to engineer such conformational switching between two folded states in human-designed proteins. Praetorius et al. developed a hinge-like protein by simultaneously considering both desired states in the design process. The successful designs exhibited a large shift in conformation upon binding to a target peptide helix, which could be tailored for specificity. The authors characterized the protein structures, binding kinetics, and conformational equilibrium of the designs. This work provides the groundwork for generating protein switches that respond to biological triggers and can produce conformational changes that modulate protein assemblies. —Michael A. Funk A two-state design of protein switches that couple effector binding to a conformational change is discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In nature, proteins that switch between two conformations in response to environmental stimuli structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Designing proteins with two distinct but fully structured conformations is a challenge for protein design as it requires sculpting an energy landscape with two distinct minima. Here we describe the design of “hinge” proteins that populate one designed state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, double electron-electron resonance spectroscopy, and binding measurements demonstrate that despite the significant structural differences the two states are designed with atomic level accuracy and that the conformational and binding equilibria are closely coupled. Natural proteins often adopt multiple conformational states, thereby changing their activity or binding partners in response to another protein, small molecule, or other stimulus. It has been difficult to engineer such conformational switching between two folded states in human-designed proteins. Praetorius et al. developed a hinge-like protein by simultaneously considering both desired states in the design process. The successful designs exhibited a large shift in conformation upon binding to a target peptide helix, which could be tailored for specificity. The authors characterized the protein structures, binding kinetics, and conformational equilibrium of the designs. This work provides the groundwork for generating protein switches that respond to biological triggers and can produce conformational changes that modulate protein assemblies. —Michael A. Funk A two-state design of protein switches that couple effector binding to a conformational change is discussed.
2022
FROM THE LAB
Bermeo, Sherry and Favor, Andrew and Chang, Ya-Ting and Norris, Andrew and Boyken, Scott E. and Hsia, Yang and Haddox, Hugh K. and Xu, Chunfu and Brunette, T. J. and Wysocki, Vicki H. and Bhabha, Gira and Ekiert, Damian C. and Baker, David
De novo design of obligate ABC-type heterotrimeric proteins Journal Article
In: Nature Structural & Molecular Biology, 2022.
@article{Bermeo2022,
title = {De novo design of obligate ABC-type heterotrimeric proteins},
author = {Bermeo, Sherry
and Favor, Andrew
and Chang, Ya-Ting
and Norris, Andrew
and Boyken, Scott E.
and Hsia, Yang
and Haddox, Hugh K.
and Xu, Chunfu
and Brunette, T. J.
and Wysocki, Vicki H.
and Bhabha, Gira
and Ekiert, Damian C.
and Baker, David},
url = {https://www.nature.com/articles/s41594-022-00879-4, Nature Structural & Molecular Biology (Open Access)},
doi = {10.1038/s41594-022-00879-4},
year = {2022},
date = {2022-12-15},
journal = {Nature Structural & Molecular Biology},
abstract = {The de novo design of three protein chains that associate to form a heterotrimer (but not any of the possible two-chain heterodimers) and that can drive the assembly of higher-order branching structures is an important challenge for protein design. We designed helical heterotrimers with specificity conferred by buried hydrogen bond networks and large aromatic residues to enhance shape complementary packing. We obtained ten designs for which all three chains cooperatively assembled into heterotrimers with few or no other species present. Crystal structures of a helical bundle heterotrimer and extended versions, with helical repeat proteins fused to individual subunits, showed all three chains assembling in the designed orientation. We used these heterotrimers as building blocks to construct larger cyclic oligomers, which were structurally validated by electron microscopy. Our three-way junction designs provide new routes to complex protein nanostructures and enable the scaffolding of three distinct ligands for modulation of cell signaling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The de novo design of three protein chains that associate to form a heterotrimer (but not any of the possible two-chain heterodimers) and that can drive the assembly of higher-order branching structures is an important challenge for protein design. We designed helical heterotrimers with specificity conferred by buried hydrogen bond networks and large aromatic residues to enhance shape complementary packing. We obtained ten designs for which all three chains cooperatively assembled into heterotrimers with few or no other species present. Crystal structures of a helical bundle heterotrimer and extended versions, with helical repeat proteins fused to individual subunits, showed all three chains assembling in the designed orientation. We used these heterotrimers as building blocks to construct larger cyclic oligomers, which were structurally validated by electron microscopy. Our three-way junction designs provide new routes to complex protein nanostructures and enable the scaffolding of three distinct ligands for modulation of cell signaling.
Kipnis, Yakov and Chaib, Anissa Ouald and Vorobieva, Anastassia A. and Cai, Guangyang and Reggiano, Gabriella and Basanta, Benjamin and Kumar, Eshan and Mittl, Peer R.E. and Hilvert, Donald and Baker, David
Design and optimization of enzymatic activity in a de novo β-barrel scaffold Journal Article
In: Protein Science, 2022.
@article{Kipnis2022,
title = {Design and optimization of enzymatic activity in a de novo β-barrel scaffold},
author = {Kipnis, Yakov
and Chaib, Anissa Ouald
and Vorobieva, Anastassia A.
and Cai, Guangyang
and Reggiano, Gabriella
and Basanta, Benjamin
and Kumar, Eshan
and Mittl, Peer R.E.
and Hilvert, Donald
and Baker, David},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/pro.4405, Protein Science
https://www.bakerlab.org/wp-content/uploads/2022/10/Protein-Science-2022-Kipnis-Design-and-optimization-of-enzymatic-activity-in-a-de-novo-‐barrel-scaffold.pdf, PDF},
doi = {10.1002/pro.4405},
year = {2022},
date = {2022-11-01},
urldate = {2022-11-01},
journal = {Protein Science},
abstract = {While native scaffolds offer a large diversity of shapes and topologies for enzyme engineering, their often unpredictable behavior in response to sequence modification makes de novo generated scaffolds an exciting alternative. Here we explore the customization of the backbone and sequence of a de novo designed eight stranded ?-barrel protein to create catalysts for a retro-aldolase model reaction. We show that active and specific catalysts can be designed in this fold and use directed evolution to further optimize activity and stereoselectivity. Our results support previous suggestions that different folds have different inherent amenability to evolution and this property could account, in part, for the distribution of natural enzymes among different folds.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
While native scaffolds offer a large diversity of shapes and topologies for enzyme engineering, their often unpredictable behavior in response to sequence modification makes de novo generated scaffolds an exciting alternative. Here we explore the customization of the backbone and sequence of a de novo designed eight stranded ?-barrel protein to create catalysts for a retro-aldolase model reaction. We show that active and specific catalysts can be designed in this fold and use directed evolution to further optimize activity and stereoselectivity. Our results support previous suggestions that different folds have different inherent amenability to evolution and this property could account, in part, for the distribution of natural enzymes among different folds.
Quijano-Rubio, Alfredo and Bhuiyan, Aladdin M. and Yang, Huilin and Leung, Isabel and Bello, Elisa and Ali, Lestat R. and Zhangxu, Kevin and Perkins, Jilliane and Chun, Jung-Ho and Wang, Wentao and Lajoie, Marc J. and Ravichandran, Rashmi and Kuo, Yun-Huai and Dougan, Stephanie K. and Riddell, Stanley R. and Spangler, Jamie B. and Dougan, Michael and Silva, Daniel-Adriano and Baker, David
A split, conditionally active mimetic of IL-2 reduces the toxicity of systemic cytokine therapy Journal Article
In: Nature Biotechnology, 2022.
@article{Quijano-Rubio2022,
title = {A split, conditionally active mimetic of IL-2 reduces the toxicity of systemic cytokine therapy},
author = {Quijano-Rubio, Alfredo
and Bhuiyan, Aladdin M.
and Yang, Huilin
and Leung, Isabel
and Bello, Elisa
and Ali, Lestat R.
and Zhangxu, Kevin
and Perkins, Jilliane
and Chun, Jung-Ho
and Wang, Wentao
and Lajoie, Marc J.
and Ravichandran, Rashmi
and Kuo, Yun-Huai
and Dougan, Stephanie K.
and Riddell, Stanley R.
and Spangler, Jamie B.
and Dougan, Michael
and Silva, Daniel-Adriano
and Baker, David},
url = {https://www.nature.com/articles/s41587-022-01510-z, Nature Biotechnology
https://www.bakerlab.org/wp-content/uploads/2022/11/s41587-022-01510-z.pdf, PDF},
doi = {10.1038/s41587-022-01510-z},
year = {2022},
date = {2022-10-31},
journal = {Nature Biotechnology},
abstract = {The therapeutic potential of recombinant cytokines has been limited by the severe side effects of systemic administration. We describe a strategy to reduce the dose-limiting toxicities of monomeric cytokines by designing two components that require colocalization for activity and that can be independently targeted to restrict activity to cells expressing two surface markers. We demonstrate the approach with a previously designed mimetic of cytokines interleukin-2 and interleukin-15—Neoleukin-2/15 (Neo-2/15)—both for trans-activating immune cells surrounding targeted tumor cells and for cis-activating directly targeted immune cells. In trans-activation mode, tumor antigen targeting of the two components enhanced antitumor activity and attenuated toxicity compared with systemic treatment in syngeneic mouse melanoma models. In cis-activation mode, immune cell targeting of the two components selectively expanded CD8+ T cells in a syngeneic mouse melanoma model and promoted chimeric antigen receptor T cell activation in a lymphoma xenograft model, enhancing antitumor efficacy in both cases.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The therapeutic potential of recombinant cytokines has been limited by the severe side effects of systemic administration. We describe a strategy to reduce the dose-limiting toxicities of monomeric cytokines by designing two components that require colocalization for activity and that can be independently targeted to restrict activity to cells expressing two surface markers. We demonstrate the approach with a previously designed mimetic of cytokines interleukin-2 and interleukin-15—Neoleukin-2/15 (Neo-2/15)—both for trans-activating immune cells surrounding targeted tumor cells and for cis-activating directly targeted immune cells. In trans-activation mode, tumor antigen targeting of the two components enhanced antitumor activity and attenuated toxicity compared with systemic treatment in syngeneic mouse melanoma models. In cis-activation mode, immune cell targeting of the two components selectively expanded CD8+ T cells in a syngeneic mouse melanoma model and promoted chimeric antigen receptor T cell activation in a lymphoma xenograft model, enhancing antitumor efficacy in both cases.
Said, Meerit Y., Kang, Christine S., Wang, Shunzhi, Sheffler, William, Salveson, Patrick J., Bera, Asim K., Kang, Alex, Nguyen, Hannah, Ballard, Ryanne, Li, Xinting, Bai, Hua, Stewart, Lance, Levine, Paul, Baker, David
Exploration of Structured Symmetric Cyclic Peptides as Ligands for Metal-Organic Frameworks Journal Article
In: Chemistry of Materials, 2022.
@article{Said2022,
title = {Exploration of Structured Symmetric Cyclic Peptides as Ligands for Metal-Organic Frameworks},
author = {Said, Meerit Y. and Kang, Christine S. and Wang, Shunzhi and Sheffler, William and Salveson, Patrick J. and Bera, Asim K. and Kang, Alex and Nguyen, Hannah and Ballard, Ryanne and Li, Xinting and Bai, Hua and Stewart, Lance and Levine, Paul and Baker, David},
url = {https://pubs.acs.org/doi/10.1021/acs.chemmater.2c02597, Chem. Mater.
https://www.bakerlab.org/wp-content/uploads/2022/10/Said_etal_ChemMater2022_CyclicPeptideMOFs.pdf, PDF},
doi = {/10.1021/acs.chemmater.2c02597},
year = {2022},
date = {2022-10-25},
urldate = {2022-10-25},
journal = {Chemistry of Materials},
abstract = {Despite remarkable advances in the assembly of highly structured coordination polymers and metal–organic frameworks, the rational design of such materials using more conformationally flexible organic ligands such as peptides remains challenging. In an effort to make the design of such materials fully programmable, we first developed a computational design method for generating metal-mediated 3D frameworks using rigid and symmetric peptide macrocycles with metal-coordinating sidechains. We solved the structures of six crystalline networks involving conformationally constrained 6 to 12 residue cyclic peptides with C2, C3, and S2 internal symmetry and three different types of metals (Zn2+, Co2+, or Cu2+) by single-crystal X-ray diffraction, which reveals how the peptide sequences, backbone symmetries, and metal coordination preferences drive the assembly of the resulting structures. In contrast to smaller ligands, these peptides associate through peptide–peptide interactions without full coordination of the metals, contrary to one of the assumptions underlying our computational design method. The cyclic peptides are the largest peptidic ligands reported to form crystalline coordination polymers with transition metals to date, and while more work is required to develop methods for fully programming their crystal structures, the combination of high chemical diversity with synthetic accessibility makes them attractive building blocks for engineering a broader set of new crystalline materials for use in applications such as sensing, asymmetric catalysis, and chiral separation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Despite remarkable advances in the assembly of highly structured coordination polymers and metal–organic frameworks, the rational design of such materials using more conformationally flexible organic ligands such as peptides remains challenging. In an effort to make the design of such materials fully programmable, we first developed a computational design method for generating metal-mediated 3D frameworks using rigid and symmetric peptide macrocycles with metal-coordinating sidechains. We solved the structures of six crystalline networks involving conformationally constrained 6 to 12 residue cyclic peptides with C2, C3, and S2 internal symmetry and three different types of metals (Zn2+, Co2+, or Cu2+) by single-crystal X-ray diffraction, which reveals how the peptide sequences, backbone symmetries, and metal coordination preferences drive the assembly of the resulting structures. In contrast to smaller ligands, these peptides associate through peptide–peptide interactions without full coordination of the metals, contrary to one of the assumptions underlying our computational design method. The cyclic peptides are the largest peptidic ligands reported to form crystalline coordination polymers with transition metals to date, and while more work is required to develop methods for fully programming their crystal structures, the combination of high chemical diversity with synthetic accessibility makes them attractive building blocks for engineering a broader set of new crystalline materials for use in applications such as sensing, asymmetric catalysis, and chiral separation.
Chidyausiku, Tamuka M. and Mendes, Soraia R. and Klima, Jason C. and Nadal, Marta and Eckhard, Ulrich and Roel-Touris, Jorge and Houliston, Scott and Guevara, Tibisay and Haddox, Hugh K. and Moyer, Adam and Arrowsmith, Cheryl H. and Gomis-Rüth, F. Xavier and Baker, David and Marcos, Enrique
De novo design of immunoglobulin-like domains Journal Article
In: Nature Communications, 2022.
@article{Chidyausiku2022,
title = {De novo design of immunoglobulin-like domains},
author = {Chidyausiku, Tamuka M.
and Mendes, Soraia R.
and Klima, Jason C.
and Nadal, Marta
and Eckhard, Ulrich
and Roel-Touris, Jorge
and Houliston, Scott
and Guevara, Tibisay
and Haddox, Hugh K.
and Moyer, Adam
and Arrowsmith, Cheryl H.
and Gomis-Rüth, F. Xavier
and Baker, David
and Marcos, Enrique},
url = {https://www.nature.com/articles/s41467-022-33004-6, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2022/10/Chidyausiku_etal_NatComm_Design_of_innunoglobulin-like_domains.pdf, PDF},
year = {2022},
date = {2022-10-03},
urldate = {2022-10-03},
journal = {Nature Communications},
abstract = {Antibodies, and antibody derivatives such as nanobodies, contain immunoglobulin-like (Ig) β-sandwich scaffolds which anchor the hypervariable antigen-binding loops and constitute the largest growing class of drugs. Current engineering strategies for this class of compounds rely on naturally existing Ig frameworks, which can be hard to modify and have limitations in manufacturability, designability and range of action. Here, we develop design rules for the central feature of the Ig fold architecture—the non-local cross-β structure connecting the two β-sheets—and use these to design highly stable Ig domains de novo, confirm their structures through X-ray crystallography, and show they can correctly scaffold functional loops. Our approach opens the door to the design of antibody-like scaffolds with tailored structures and superior biophysical properties.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Antibodies, and antibody derivatives such as nanobodies, contain immunoglobulin-like (Ig) β-sandwich scaffolds which anchor the hypervariable antigen-binding loops and constitute the largest growing class of drugs. Current engineering strategies for this class of compounds rely on naturally existing Ig frameworks, which can be hard to modify and have limitations in manufacturability, designability and range of action. Here, we develop design rules for the central feature of the Ig fold architecture—the non-local cross-β structure connecting the two β-sheets—and use these to design highly stable Ig domains de novo, confirm their structures through X-ray crystallography, and show they can correctly scaffold functional loops. Our approach opens the door to the design of antibody-like scaffolds with tailored structures and superior biophysical properties.
B. I. M. Wicky, L. F. Milles, A. Courbet, R. J. Ragotte, J. Dauparas, E. Kinfu, S. Tipps, R. D. Kibler, M. Baek, F. DiMaio, X. Li, L. Carter, A. Kang, H. Nguyen, A. K. Bera, D. Baker
Hallucinating symmetric protein assemblies Journal Article
In: Science, 2022.
@article{Wicky2022,
title = {Hallucinating symmetric protein assemblies},
author = {B. I. M. Wicky and L. F. Milles and A. Courbet and R. J. Ragotte and J. Dauparas and E. Kinfu and S. Tipps and R. D. Kibler and M. Baek and F. DiMaio and X. Li and L. Carter and A. Kang and H. Nguyen and A. K. Bera and D. Baker},
url = {https://www.science.org/doi/abs/10.1126/science.add1964, Science
https://www.bakerlab.org/wp-content/uploads/2022/09/Wicky_etal_Science2022_Hallucinating_symmetric_protein_assemblies.pdf, PDF
},
doi = {10.1126/science.add1964},
year = {2022},
date = {2022-09-15},
journal = {Science},
abstract = {Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of 7 designs are very close to the computational models (median RMSD: 0.6 Å), as are 3 cryoEM structures of giant 10 nanometer rings with up to 1550 residues and C33 symmetry; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be generated using deep learning, and pave the way for the design of increasingly complex components for nanomachines and biomaterials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of 7 designs are very close to the computational models (median RMSD: 0.6 Å), as are 3 cryoEM structures of giant 10 nanometer rings with up to 1550 residues and C33 symmetry; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be generated using deep learning, and pave the way for the design of increasingly complex components for nanomachines and biomaterials.
Dauparas, J. and Anishchenko, I. and Bennett, N. and Bai, H. and Ragotte, R. J. and Milles, L. F. and Wicky, B. I. M. and Courbet, A. and de Haas, R. J. and Bethel, N. and Leung, P. J. Y. and Huddy, T. F. and Pellock, S. and Tischer, D. and Chan, F. and Koepnick, B. and Nguyen, H. and Kang, A. and Sankaran, B. and Bera, A. K. and King, N. P. and Baker, D.
Robust deep learning–based protein sequence design using ProteinMPNN Journal Article
In: Science, 2022.
@article{Dauparas2022,
title = {Robust deep learning–based protein sequence design using ProteinMPNN},
author = {Dauparas, J.
and Anishchenko, I.
and Bennett, N.
and Bai, H.
and Ragotte, R. J.
and Milles, L. F.
and Wicky, B. I. M.
and Courbet, A.
and de Haas, R. J.
and Bethel, N.
and Leung, P. J. Y.
and Huddy, T. F.
and Pellock, S.
and Tischer, D.
and Chan, F.
and Koepnick, B.
and Nguyen, H.
and Kang, A.
and Sankaran, B.
and Bera, A. K.
and King, N. P.
and Baker, D.},
url = {https://www.science.org/doi/abs/10.1126/science.add2187, Science
https://www.bakerlab.org/wp-content/uploads/2022/09/Dauparas_etal_Science2022_Sequence_design_via_ProteinMPNN.pdf, PDF},
doi = {10.1126/science.add2187},
year = {2022},
date = {2022-09-15},
journal = {Science},
abstract = {While deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here we describe a deep learning–based protein sequence design method, ProteinMPNN, with outstanding performance in both in silico and experimental tests. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4%, compared to 32.9% for Rosetta. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. We demonstrate the broad utility and high accuracy of ProteinMPNN using X-ray crystallography, cryoEM and functional studies by rescuing previously failed designs, made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target binding proteins},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
While deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here we describe a deep learning–based protein sequence design method, ProteinMPNN, with outstanding performance in both in silico and experimental tests. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4%, compared to 32.9% for Rosetta. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. We demonstrate the broad utility and high accuracy of ProteinMPNN using X-ray crystallography, cryoEM and functional studies by rescuing previously failed designs, made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target binding proteins
Gaurav Bhardwaj, Jacob O’Connor, Stephen Rettie, Yen-Hua Huang, Theresa A. Ramelot, Vikram Khipple Mulligan, Gizem Gokce Alpkilic, Jonathan Palmer, Asim K. Bera, Matthew J. Bick, Maddalena Di Piazza, Xinting Li, Parisa Hosseinzadeh, Timothy W. Craven, Roberto Tejero, Anna Lauko, Ryan Choi, Calina Glynn, Linlin Dong, Robert Griffin, Wesley C. van Voorhis, Jose Rodriguez, Lance Stewart, Gaetano T. Montelione, David Craik, David Baker
Accurate de novo design of membrane-traversing macrocycles Journal Article
In: Cell, 2022.
@article{Bhardwaj2022,
title = {Accurate de novo design of membrane-traversing macrocycles},
author = {Gaurav Bhardwaj and Jacob O’Connor and Stephen Rettie and Yen-Hua Huang and Theresa A. Ramelot and Vikram Khipple Mulligan and Gizem Gokce Alpkilic and Jonathan Palmer and Asim K. Bera and Matthew J. Bick and Maddalena {Di Piazza} and Xinting Li and Parisa Hosseinzadeh and Timothy W. Craven and Roberto Tejero and Anna Lauko and Ryan Choi and Calina Glynn and Linlin Dong and Robert Griffin and Wesley C. {van Voorhis} and Jose Rodriguez and Lance Stewart and Gaetano T. Montelione and David Craik and David Baker},
url = {https://www.sciencedirect.com/science/article/pii/S0092867422009229?via%3Dihub, Cell
https://www.bakerlab.org/wp-content/uploads/2022/08/1-s2.0-S0092867422009229-main.pdf, PDF},
doi = {10.1016/j.cell.2022.07.019},
year = {2022},
date = {2022-08-29},
urldate = {2022-08-29},
journal = {Cell},
abstract = {We use computational design coupled with experimental characterization to systematically investigate the design principles for macrocycle membrane permeability and oral bioavailability. We designed 184 6–12 residue macrocycles with a wide range of predicted structures containing noncanonical backbone modifications and experimentally determined structures of 35; 29 are very close to the computational models. With such control, we show that membrane permeability can be systematically achieved by ensuring all amide (NH) groups are engaged in internal hydrogen bonding interactions. 84 designs over the 6–12 residue size range cross membranes with an apparent permeability greater than 1 × 10−6 cm/s. Designs with exposed NH groups can be made membrane permeable through the design of an alternative isoenergetic fully hydrogen-bonded state favored in the lipid membrane. The ability to robustly design membrane-permeable and orally bioavailable peptides with high structural accuracy should contribute to the next generation of designed macrocycle therapeutics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We use computational design coupled with experimental characterization to systematically investigate the design principles for macrocycle membrane permeability and oral bioavailability. We designed 184 6–12 residue macrocycles with a wide range of predicted structures containing noncanonical backbone modifications and experimentally determined structures of 35; 29 are very close to the computational models. With such control, we show that membrane permeability can be systematically achieved by ensuring all amide (NH) groups are engaged in internal hydrogen bonding interactions. 84 designs over the 6–12 residue size range cross membranes with an apparent permeability greater than 1 × 10−6 cm/s. Designs with exposed NH groups can be made membrane permeable through the design of an alternative isoenergetic fully hydrogen-bonded state favored in the lipid membrane. The ability to robustly design membrane-permeable and orally bioavailable peptides with high structural accuracy should contribute to the next generation of designed macrocycle therapeutics.
Yang, Erin C. and Divine, Robby and Kang, Christine S. and Chan, Sidney and Arenas, Elijah and Subol, Zoe and Tinker, Peter and Manninen, Hayden and Feichtenbiner, Alicia and Mustafa, Talal and Hallowell, Julia and Orr, Isiac and Haddox, Hugh and Koepnick, Brian and O’Connor, Jacob and Haydon, Ian C. and Herpoldt, Karla-Luise and Wormer, Kandise Van and Abell, Celine and Baker, David and Khmelinskaia, Alena and King, Neil P.
Increasing Computational Protein Design Literacy through Cohort-Based Learning for Undergraduate Students Journal Article
In: Journal of Chemical Education, 2022.
@article{Yang2022,
title = {Increasing Computational Protein Design Literacy through Cohort-Based Learning for Undergraduate Students},
author = {Yang, Erin C.
and Divine, Robby
and Kang, Christine S.
and Chan, Sidney
and Arenas, Elijah
and Subol, Zoe
and Tinker, Peter
and Manninen, Hayden
and Feichtenbiner, Alicia
and Mustafa, Talal
and Hallowell, Julia
and Orr, Isiac
and Haddox, Hugh
and Koepnick, Brian
and O’Connor, Jacob
and Haydon, Ian C.
and Herpoldt, Karla-Luise
and Wormer, Kandise Van
and Abell, Celine
and Baker, David
and Khmelinskaia, Alena
and King, Neil P.},
url = {https://pubs.acs.org/doi/full/10.1021/acs.jchemed.2c00500, Journal of Chemical Education
https://www.bakerlab.org/wp-content/uploads/2022/08/Yang2022acs.jchemed.2c00500.pdf, PDF},
year = {2022},
date = {2022-08-05},
urldate = {2022-08-05},
journal = {Journal of Chemical Education},
abstract = {Undergraduate research experiences can improve student success in graduate education and STEM careers. During the COVID-19 pandemic, undergraduate researchers at our institution and many others lost their work–study research positions due to interruption of in-person research activities. This imposed a financial burden on the students and eliminated an important learning opportunity. To address these challenges, we created a paid, fully remote, cohort-based research curriculum in computational protein design. Our curriculum used existing protein design methods as a platform to first educate and train undergraduate students and then to test research hypotheses. In the first phase, students learned computational methods to assess the stability of designed protein assemblies. In the second phase, students used a larger data set to identify factors that could improve the accuracy of current protein design algorithms. This cohort-based program created valuable new research opportunities for undergraduates at our institute and enhanced the undergraduates’ feeling of connection with the lab. Students learned transferable and useful skills such as literature review, programming basics, data analysis, hypothesis testing, and scientific communication. Our program provides a model of structured computational research training opportunities for undergraduate researchers in any field for organizations looking to expand educational access.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Undergraduate research experiences can improve student success in graduate education and STEM careers. During the COVID-19 pandemic, undergraduate researchers at our institution and many others lost their work–study research positions due to interruption of in-person research activities. This imposed a financial burden on the students and eliminated an important learning opportunity. To address these challenges, we created a paid, fully remote, cohort-based research curriculum in computational protein design. Our curriculum used existing protein design methods as a platform to first educate and train undergraduate students and then to test research hypotheses. In the first phase, students learned computational methods to assess the stability of designed protein assemblies. In the second phase, students used a larger data set to identify factors that could improve the accuracy of current protein design algorithms. This cohort-based program created valuable new research opportunities for undergraduates at our institute and enhanced the undergraduates’ feeling of connection with the lab. Students learned transferable and useful skills such as literature review, programming basics, data analysis, hypothesis testing, and scientific communication. Our program provides a model of structured computational research training opportunities for undergraduate researchers in any field for organizations looking to expand educational access.
Derrick R. Hicks, Madison A. Kennedy, Kirsten A. Thompson, Michelle DeWitt, Brian Coventry, Alex Kang, Asim K. Bera, T. J. Brunette, Banumathi Sankaran, Barry Stoddard, David Baker
De novo design of protein homodimers containing tunable symmetric protein pockets Journal Article
In: Proceedings of the National Academy of Sciences, 2022.
@article{Hicks2022,
title = {De novo design of protein homodimers containing tunable symmetric protein pockets},
author = {Derrick R. Hicks and Madison A. Kennedy and Kirsten A. Thompson and Michelle DeWitt and Brian Coventry and Alex Kang and Asim K. Bera and T. J. Brunette and Banumathi Sankaran and Barry Stoddard and David Baker},
url = {https://www.pnas.org/doi/abs/10.1073/pnas.2113400119, PNAS
https://www.bakerlab.org/wp-content/uploads/2022/07/pnas.2113400119.pdf, Download PDF},
doi = {10.1073/pnas.2113400119},
year = {2022},
date = {2022-07-21},
urldate = {2022-07-21},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Proteins capable of binding arbitrary small molecules could enable the generation of new biosensors or medicines. While considerable progress has been made in recent years to design proteins from scratch capable of binding asymmetric molecules, little work has been done to facilitate the binding of symmetric molecules. Here, we present a method for generating libraries of C2 symmetric proteins with diverse central cavities that could be functionalized in the future to bind a range of C2 symmetric small molecules for applications such as ligand controllable cell engineering. We show that 31% of our designed proteins fold to the desired quaternary state, when experimentally characterized, and are hyperstable. Function follows form in biology, and the binding of small molecules requires proteins with pockets that match the shape of the ligand. For design of binding to symmetric ligands, protein homo-oligomers with matching symmetry are advantageous as each protein subunit can make identical interactions with the ligand. Here, we describe a general approach to designing hyperstable C2 symmetric proteins with pockets of diverse size and shape. We first designed repeat proteins that sample a continuum of curvatures but have low helical rise, then docked these into C2 symmetric homodimers to generate an extensive range of C2 symmetric cavities. We used this approach to design thousands of C2 symmetric homodimers, and characterized 101 of them experimentally. Of these, the geometry of 31 were confirmed by small angle X-ray scattering and 2 were shown by crystallographic analyses to be in close agreement with the computational design models. These scaffolds provide a rich set of starting points for binding a wide range of C2 symmetric compounds.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Proteins capable of binding arbitrary small molecules could enable the generation of new biosensors or medicines. While considerable progress has been made in recent years to design proteins from scratch capable of binding asymmetric molecules, little work has been done to facilitate the binding of symmetric molecules. Here, we present a method for generating libraries of C2 symmetric proteins with diverse central cavities that could be functionalized in the future to bind a range of C2 symmetric small molecules for applications such as ligand controllable cell engineering. We show that 31% of our designed proteins fold to the desired quaternary state, when experimentally characterized, and are hyperstable. Function follows form in biology, and the binding of small molecules requires proteins with pockets that match the shape of the ligand. For design of binding to symmetric ligands, protein homo-oligomers with matching symmetry are advantageous as each protein subunit can make identical interactions with the ligand. Here, we describe a general approach to designing hyperstable C2 symmetric proteins with pockets of diverse size and shape. We first designed repeat proteins that sample a continuum of curvatures but have low helical rise, then docked these into C2 symmetric homodimers to generate an extensive range of C2 symmetric cavities. We used this approach to design thousands of C2 symmetric homodimers, and characterized 101 of them experimentally. Of these, the geometry of 31 were confirmed by small angle X-ray scattering and 2 were shown by crystallographic analyses to be in close agreement with the computational design models. These scaffolds provide a rich set of starting points for binding a wide range of C2 symmetric compounds.
Jue Wang, Sidney Lisanza, David Juergens, Doug Tischer, Joseph L. Watson, Karla M. Castro, Robert Ragotte, Amijai Saragovi, Lukas F. Milles, Minkyung Baek, Ivan Anishchenko, Wei Yang, Derrick R. Hicks, Marc Expòsit, Thomas Schlichthaerle, Jung-Ho Chun, Justas Dauparas, Nathaniel Bennett, Basile I. M. Wicky, Andrew Muenks, Frank DiMaio, Bruno Correia, Sergey Ovchinnikov, David Baker
Scaffolding protein functional sites using deep learning Journal Article
In: Science, 2022.
@article{Wang2022,
title = {Scaffolding protein functional sites using deep learning},
author = {Jue Wang and Sidney Lisanza and David Juergens and Doug Tischer and Joseph L. Watson and Karla M. Castro and Robert Ragotte and Amijai Saragovi and Lukas F. Milles and Minkyung Baek and Ivan Anishchenko and Wei Yang and Derrick R. Hicks and Marc Expòsit and Thomas Schlichthaerle and Jung-Ho Chun and Justas Dauparas and Nathaniel Bennett and Basile I. M. Wicky and Andrew Muenks and Frank DiMaio and Bruno Correia and Sergey Ovchinnikov and David Baker },
url = {https://www.science.org/doi/abs/10.1126/science.abn2100, Science
https://www.ipd.uw.edu/wp-content/uploads/2022/07/science.abn2100.pdf, Download PDF},
doi = {10.1126/science.abn2100},
year = {2022},
date = {2022-07-21},
urldate = {2022-07-21},
journal = {Science},
abstract = {The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing to prespecify the fold or secondary structure of the scaffold. The first approach, “constrained hallucination,” optimizes sequences such that their predicted structures contain the desired functional site. The second approach, “inpainting,” starts from the functional site and fills in additional sequence and structure to create a viable protein scaffold in a single forward pass through a specifically trained RoseTTAFold network. We use these two methods to design candidate immunogens, receptor traps, metalloproteins, enzymes, and protein-binding proteins and validate the designs using a combination of in silico and experimental tests. Protein design has had success in finding sequences that fold into a desired conformation, but designing functional proteins remains challenging. Wang et al. describe two deep-learning methods to design proteins that contain prespecified functional sites. In the first, they found sequences predicted to fold into stable structures that contain the functional site. In the second, they retrained a structure prediction network to recover the sequence and full structure of a protein given only the functional site. The authors demonstrate their methods by designing proteins containing a variety of functional motifs. —VV Deep-learning methods enable the scaffolding of desired functional residues within a well-folded designed protein.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing to prespecify the fold or secondary structure of the scaffold. The first approach, “constrained hallucination,” optimizes sequences such that their predicted structures contain the desired functional site. The second approach, “inpainting,” starts from the functional site and fills in additional sequence and structure to create a viable protein scaffold in a single forward pass through a specifically trained RoseTTAFold network. We use these two methods to design candidate immunogens, receptor traps, metalloproteins, enzymes, and protein-binding proteins and validate the designs using a combination of in silico and experimental tests. Protein design has had success in finding sequences that fold into a desired conformation, but designing functional proteins remains challenging. Wang et al. describe two deep-learning methods to design proteins that contain prespecified functional sites. In the first, they found sequences predicted to fold into stable structures that contain the functional site. In the second, they retrained a structure prediction network to recover the sequence and full structure of a protein given only the functional site. The authors demonstrate their methods by designing proteins containing a variety of functional motifs. —VV Deep-learning methods enable the scaffolding of desired functional residues within a well-folded designed protein.
Zhang, Jason Z. and Yeh, Hsien-Wei and Walls, Alexandra C. and Wicky, Basile I. M. and Sprouse, Kaitlin R. and VanBlargan, Laura A. and Treger, Rebecca and Quijano-Rubio, Alfredo and Pham, Minh N. and Kraft, John C. and Haydon, Ian C. and Yang, Wei and DeWitt, Michelle and Bowen, John E. and Chow, Cameron M. and Carter, Lauren and Ravichandran, Rashmi and Wener, Mark H. and Stewart, Lance and Veesler, David and Diamond, Michael S. and Greninger, Alexander L. and Koelle, David M. and Baker, David
Thermodynamically coupled biosensors for detecting neutralizing antibodies against SARS-CoV-2 variants Journal Article
In: Nature Biotechnology, 2022.
@article{Zhang2022,
title = {Thermodynamically coupled biosensors for detecting neutralizing antibodies against SARS-CoV-2 variants},
author = {Zhang, Jason Z.
and Yeh, Hsien-Wei
and Walls, Alexandra C.
and Wicky, Basile I. M.
and Sprouse, Kaitlin R.
and VanBlargan, Laura A.
and Treger, Rebecca
and Quijano-Rubio, Alfredo
and Pham, Minh N.
and Kraft, John C.
and Haydon, Ian C.
and Yang, Wei
and DeWitt, Michelle
and Bowen, John E.
and Chow, Cameron M.
and Carter, Lauren
and Ravichandran, Rashmi
and Wener, Mark H.
and Stewart, Lance
and Veesler, David
and Diamond, Michael S.
and Greninger, Alexander L.
and Koelle, David M.
and Baker, David},
url = {https://www.nature.com/articles/s41587-022-01280-8, Nature Biotechnology
https://www.bakerlab.org/wp-content/uploads/2022/04/Zhang_etal_NatureBiotech_Thermodynamically_coupled_biosensors_for_detecting_nAbs_against_SARSCoV2_variants.pdf, Download PDF},
year = {2022},
date = {2022-04-28},
urldate = {2022-04-28},
journal = {Nature Biotechnology},
abstract = {We designed a protein biosensor that uses thermodynamic coupling for sensitive and rapid detection of neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in serum. The biosensor is a switchable, caged luciferase–receptor-binding domain (RBD) construct that detects serum-antibody interference with the binding of virus RBD to angiotensin-converting enzyme 2 (ACE-2) as a proxy for neutralization. Our coupling approach does not require target modification and can better distinguish sample-to-sample differences in analyte binding affinity and abundance than traditional competition-based assays.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We designed a protein biosensor that uses thermodynamic coupling for sensitive and rapid detection of neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in serum. The biosensor is a switchable, caged luciferase–receptor-binding domain (RBD) construct that detects serum-antibody interference with the binding of virus RBD to angiotensin-converting enzyme 2 (ACE-2) as a proxy for neutralization. Our coupling approach does not require target modification and can better distinguish sample-to-sample differences in analyte binding affinity and abundance than traditional competition-based assays.
A. Courbet, J. Hansen, Y. Hsia, N. Bethel, Y.-J. Park, C. Xu, A. Moyer, S. E. Boyken, G. Ueda, U. Nattermann, D. Nagarajan, D. Silva, W. Sheffler, J. Quispe, A. Nord, N. King, P. Bradley, D. Veesler, J. Kollman, D. Baker
Computational design of mechanically coupled axle-rotor protein assemblies Journal Article
In: Science, 2022.
@article{Courbet2022,
title = {Computational design of mechanically coupled axle-rotor protein assemblies},
author = {A. Courbet and J. Hansen and Y. Hsia and N. Bethel and Y.-J. Park and C. Xu and A. Moyer and S. E. Boyken and G. Ueda and U. Nattermann and D. Nagarajan and D. Silva and W. Sheffler and J. Quispe and A. Nord and N. King and P. Bradley and D. Veesler and J. Kollman and D. Baker},
url = {https://www.science.org/doi/abs/10.1126/science.abm1183, Science
https://www.bakerlab.org/wp-content/uploads/2022/04/science.abm1183.pdf, Download PDF},
year = {2022},
date = {2022-04-21},
urldate = {2022-04-21},
journal = {Science},
abstract = {Natural molecular machines contain protein components that undergo motion relative to each other. Designing such mechanically constrained nanoscale protein architectures with internal degrees of freedom is an outstanding challenge for computational protein design. Here we explore the de novo construction of protein machinery from designed axle and rotor components with internal cyclic or dihedral symmetry. We find that the axle-rotor systems assemble in vitro and in vivo as designed. Using cryo–electron microscopy, we find that these systems populate conformationally variable relative orientations reflecting the symmetry of the coupled components and the computationally designed interface energy landscape. These mechanical systems with internal degrees of freedom are a step toward the design of genetically encodable nanomachines. Protein rotary machines such as ATP synthase contain axle-like and ring-like components and couple biochemical energy to the mechanical work of rotating the components relative to each other. Courbet et al. have taken a step toward designing such axel-rotor nanomachines. A structural requirement is that interactions between the components must be strong enough to allow assembly but still allow different rotational states to be populated. The authors met this design challenge and computationally designed ring-like protein topologies (rotors) with a range of inner diameters that accommodate designed axle-like binding partners. The systems assemble and populate the different rotational states anticipated by the designs. These rotational energy landscapes provide one of two needed elements for a directional motor. —VV Computationally designed self-assembling axle-rotor protein systems populate multiple rotational states.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Natural molecular machines contain protein components that undergo motion relative to each other. Designing such mechanically constrained nanoscale protein architectures with internal degrees of freedom is an outstanding challenge for computational protein design. Here we explore the de novo construction of protein machinery from designed axle and rotor components with internal cyclic or dihedral symmetry. We find that the axle-rotor systems assemble in vitro and in vivo as designed. Using cryo–electron microscopy, we find that these systems populate conformationally variable relative orientations reflecting the symmetry of the coupled components and the computationally designed interface energy landscape. These mechanical systems with internal degrees of freedom are a step toward the design of genetically encodable nanomachines. Protein rotary machines such as ATP synthase contain axle-like and ring-like components and couple biochemical energy to the mechanical work of rotating the components relative to each other. Courbet et al. have taken a step toward designing such axel-rotor nanomachines. A structural requirement is that interactions between the components must be strong enough to allow assembly but still allow different rotational states to be populated. The authors met this design challenge and computationally designed ring-like protein topologies (rotors) with a range of inner diameters that accommodate designed axle-like binding partners. The systems assemble and populate the different rotational states anticipated by the designs. These rotational energy landscapes provide one of two needed elements for a directional motor. —VV Computationally designed self-assembling axle-rotor protein systems populate multiple rotational states.
Andrew C. Hunt, James Brett Case, Young-Jun Park, Longxing Cao, Kejia Wu, Alexandra C. Walls, Zhuoming Liu, John E. Bowen, Hsien-Wei Yeh, Shally Saini, Louisa Helms, Yan Ting Zhao, Tien-Ying Hsiang, Tyler N. Starr, Inna Goreshnik, Lisa Kozodoy, Lauren Carter, Rashmi Ravichandran, Lydia B. Green, Wadim L. Matochko, Christy A. Thomson, Bastian Vögeli, Antje Krüger, Laura A. VanBlargan, Rita E. Chen, Baoling Ying, Adam L. Bailey, Natasha M. Kafai, Scott E. Boyken, Ajasja Ljubetič, Natasha Edman, George Ueda, Cameron M. Chow, Max Johnson, Amin Addetia, Mary Jane Navarro, Nuttada Panpradist, Michael Gale, Benjamin S. Freedman, Jesse D. Bloom, Hannele Ruohola-Baker, Sean P. J. Whelan, Lance Stewart, Michael S. Diamond, David Veesler, Michael C. Jewett, David Baker
Multivalent designed proteins neutralize SARS-CoV-2 variants of concern and confer protection against infection in mice Journal Article
In: Science Translational Medicine, 2022.
@article{Hunt2022,
title = {Multivalent designed proteins neutralize SARS-CoV-2 variants of concern and confer protection against infection in mice},
author = {Andrew C. Hunt and James Brett Case and Young-Jun Park and Longxing Cao and Kejia Wu and Alexandra C. Walls and Zhuoming Liu and John E. Bowen and Hsien-Wei Yeh and Shally Saini and Louisa Helms and Yan Ting Zhao and Tien-Ying Hsiang and Tyler N. Starr and Inna Goreshnik and Lisa Kozodoy and Lauren Carter and Rashmi Ravichandran and Lydia B. Green and Wadim L. Matochko and Christy A. Thomson and Bastian Vögeli and Antje Krüger and Laura A. VanBlargan and Rita E. Chen and Baoling Ying and Adam L. Bailey and Natasha M. Kafai and Scott E. Boyken and Ajasja Ljubetič and Natasha Edman and George Ueda and Cameron M. Chow and Max Johnson and Amin Addetia and Mary Jane Navarro and Nuttada Panpradist and Michael Gale and Benjamin S. Freedman and Jesse D. Bloom and Hannele Ruohola-Baker and Sean P. J. Whelan and Lance Stewart and Michael S. Diamond and David Veesler and Michael C. Jewett and David Baker},
url = {https://www.science.org/doi/abs/10.1126/scitranslmed.abn1252, Science Translational Medicine
https://www.bakerlab.org/wp-content/uploads/2022/04/scitranslmed.abn1252.pdf, Download PDF},
doi = {10.1126/scitranslmed.abn1252},
year = {2022},
date = {2022-04-12},
urldate = {2022-04-12},
journal = {Science Translational Medicine},
abstract = {New variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to arise and prolong the coronavirus disease 2019 (COVID-19) pandemic. Here we used a cell-free expression workflow to rapidly screen and optimize constructs containing multiple computationally designed miniprotein inhibitors of SARS-CoV-2. We found the broadest efficacy with a homo-trimeric version of the 75-residue angiotensin converting enzyme 2 (ACE2) mimic AHB2 (TRI2-2) designed to geometrically match the trimeric spike architecture. In the cryo-electron microscopy structure, TRI2 formed a tripod on top of the spike protein which engaged all three receptor binding domains (RBDs) simultaneously as in the design model. TRI2-2 neutralized Omicron (B.1.1.529), Delta (B.1.617.2), and all other variants tested with greater potency than that of monoclonal antibodies used clinically for the treatment of COVID-19. TRI2-2 also conferred prophylactic and therapeutic protection against SARS-CoV-2 challenge when administered intranasally in mice. Designed miniprotein receptor mimics geometrically arrayed to match pathogen receptor binding sites could be a widely applicable antiviral therapeutic strategy with advantages over antibodies and native receptor traps. By comparison, the designed proteins have resistance to viral escape and antigenic drift by construction, precisely tuned avidity, and greatly reduced chance of autoimmune responses. Computationally designed trivalent minibinders provide therapeutic protection in mice against emerging SARS-CoV-2 variants of concern.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
New variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to arise and prolong the coronavirus disease 2019 (COVID-19) pandemic. Here we used a cell-free expression workflow to rapidly screen and optimize constructs containing multiple computationally designed miniprotein inhibitors of SARS-CoV-2. We found the broadest efficacy with a homo-trimeric version of the 75-residue angiotensin converting enzyme 2 (ACE2) mimic AHB2 (TRI2-2) designed to geometrically match the trimeric spike architecture. In the cryo-electron microscopy structure, TRI2 formed a tripod on top of the spike protein which engaged all three receptor binding domains (RBDs) simultaneously as in the design model. TRI2-2 neutralized Omicron (B.1.1.529), Delta (B.1.617.2), and all other variants tested with greater potency than that of monoclonal antibodies used clinically for the treatment of COVID-19. TRI2-2 also conferred prophylactic and therapeutic protection against SARS-CoV-2 challenge when administered intranasally in mice. Designed miniprotein receptor mimics geometrically arrayed to match pathogen receptor binding sites could be a widely applicable antiviral therapeutic strategy with advantages over antibodies and native receptor traps. By comparison, the designed proteins have resistance to viral escape and antigenic drift by construction, precisely tuned avidity, and greatly reduced chance of autoimmune responses. Computationally designed trivalent minibinders provide therapeutic protection in mice against emerging SARS-CoV-2 variants of concern.
Cao, Longxing, Coventry, Brian, Goreshnik, Inna, Huang, Buwei, Park, Joon Sung, Jude, Kevin M., Marković, Iva, Kadam, Rameshwar U., Verschueren, Koen H. G., Verstraete, Kenneth, Walsh, Scott Thomas Russell, Bennett, Nathaniel, Phal, Ashish, Yang, Aerin, Kozodoy, Lisa, DeWitt, Michelle, Picton, Lora, Miller, Lauren, Strauch, Eva-Maria, DeBouver, Nicholas D., Pires, Allison, Bera, Asim K., Halabiya, Samer, Hammerson, Bradley, Yang, Wei, Bernard, Steffen, Stewart, Lance, Wilson, Ian A., Ruohola-Baker, Hannele, Schlessinger, Joseph, Lee, Sangwon, Savvides, Savvas N., Garcia, K. Christopher, Baker, David
Design of protein binding proteins from target structure alone Journal Article
In: Nature, 2022.
@article{Cao2022,
title = {Design of protein binding proteins from target structure alone},
author = {Cao, Longxing and Coventry, Brian and Goreshnik, Inna and Huang, Buwei and Park, Joon Sung and Jude, Kevin M. and Marković, Iva and Kadam, Rameshwar U. and Verschueren, Koen H. G. and Verstraete, Kenneth and Walsh, Scott Thomas Russell and Bennett, Nathaniel and Phal, Ashish and Yang, Aerin and Kozodoy, Lisa and DeWitt, Michelle and Picton, Lora and Miller, Lauren and Strauch, Eva-Maria and DeBouver, Nicholas D. and Pires, Allison and Bera, Asim K. and Halabiya, Samer and Hammerson, Bradley and Yang, Wei and Bernard, Steffen and Stewart, Lance and Wilson, Ian A. and Ruohola-Baker, Hannele and Schlessinger, Joseph and Lee, Sangwon and Savvides, Savvas N. and Garcia, K. Christopher and Baker, David},
url = {https://www.nature.com/articles/s41586-022-04654-9, Nature
https://www.bakerlab.org/wp-content/uploads/2022/03/Cao_etal_Nature2022_Design_of_binders_from_target_structure_alone.pdf, Download PDF},
doi = {10.1038/s41586-022-04654-9},
year = {2022},
date = {2022-03-24},
urldate = {2022-03-24},
journal = {Nature},
abstract = {The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains an outstanding challenge1–5. We describe a general solution to this problem which starts with a broad exploration of the very large space of possible binding modes to a selected region of a protein surface, and then intensifies the search in the vicinity of the most promising binding modes. We demonstrate its very broad applicability by de novo design of binding proteins to 12 diverse protein targets with very different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and following experimental optimization bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of five of the binder-target complexes, and all five are very close to the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein-protein interactions, and should guide improvement of both. Our approach now enables targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains an outstanding challenge1–5. We describe a general solution to this problem which starts with a broad exploration of the very large space of possible binding modes to a selected region of a protein surface, and then intensifies the search in the vicinity of the most promising binding modes. We demonstrate its very broad applicability by de novo design of binding proteins to 12 diverse protein targets with very different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and following experimental optimization bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of five of the binder-target complexes, and all five are very close to the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein-protein interactions, and should guide improvement of both. Our approach now enables targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.
Levine, Paul M., Craven, Timothy W., Li, Xinting, Balana, Aaron T., Bird, Gregory H., Godes, Marina, Salveson, Patrick J., Erickson, Patrick W., Lamb, Mila, Ahlrichs, Maggie, Murphy, Michael, Ogohara, Cassandra, Said, Meerit Y., Walensky, Loren D., Pratt, Matthew R., Baker, David
Generation of Potent and Stable GLP-1 Analogues Via “Serine Ligation” Journal Article
In: ACS Chemical Biology, 2022.
@article{nokey,
title = {Generation of Potent and Stable GLP-1 Analogues Via “Serine Ligation”},
author = {Levine, Paul M. and Craven, Timothy W. and Li, Xinting and Balana, Aaron T. and Bird, Gregory H. and Godes, Marina and Salveson, Patrick J. and Erickson, Patrick W. and Lamb, Mila and Ahlrichs, Maggie and Murphy, Michael and Ogohara, Cassandra and Said, Meerit Y. and Walensky, Loren D. and Pratt, Matthew R. and Baker, David},
url = {https://pubs.acs.org/doi/abs/10.1021/acschembio.2c00075, ACS Chemical Biology
https://www.bakerlab.org/wp-content/uploads/2022/03/Levine_etal_ACSChemBio2022_GLP-1_ananlogues_by_serine_ligation.pdf, Download PDF},
doi = {10.1021/acschembio.2c00075},
year = {2022},
date = {2022-03-23},
journal = {ACS Chemical Biology},
abstract = {Peptide and protein bioconjugation technologies have revolutionized our ability to site-specifically or chemoselectively install a variety of functional groups for applications in chemical biology and medicine, including the enhancement of bioavailability. Here, we introduce a site-specific bioconjugation strategy inspired by chemical ligation at serine that relies on a noncanonical amino acid containing a 1-amino-2-hydroxy functional group and a salicylaldehyde ester. More specifically, we harness this technology to generate analogues of glucagon-like peptide-1 that resemble Semaglutide, a long-lasting blockbuster drug currently used in the clinic to regulate glucose levels in the blood. We identify peptides that are more potent than unmodified peptide and equipotent to Semaglutide in a cell-based activation assay, improve the stability in human serum, and increase glucose disposal efficiency in vivo. This approach demonstrates the potential of “serine ligation” for various applications in chemical biology, with a particular focus on generating stabilized peptide therapeutics.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Peptide and protein bioconjugation technologies have revolutionized our ability to site-specifically or chemoselectively install a variety of functional groups for applications in chemical biology and medicine, including the enhancement of bioavailability. Here, we introduce a site-specific bioconjugation strategy inspired by chemical ligation at serine that relies on a noncanonical amino acid containing a 1-amino-2-hydroxy functional group and a salicylaldehyde ester. More specifically, we harness this technology to generate analogues of glucagon-like peptide-1 that resemble Semaglutide, a long-lasting blockbuster drug currently used in the clinic to regulate glucose levels in the blood. We identify peptides that are more potent than unmodified peptide and equipotent to Semaglutide in a cell-based activation assay, improve the stability in human serum, and increase glucose disposal efficiency in vivo. This approach demonstrates the potential of “serine ligation” for various applications in chemical biology, with a particular focus on generating stabilized peptide therapeutics.
Minkyung Baek, David Baker
Deep learning and protein structure modeling Journal Article
In: Nature Methods, 2022.
@article{Baek2022,
title = {Deep learning and protein structure modeling},
author = {Minkyung Baek and David Baker},
url = {https://www.nature.com/articles/s41592-021-01360-8, Nature Methods
https://www.bakerlab.org/wp-content/uploads/2022/01/Baek_Baker_NatureMethods2022_Deep_Learning_and_Protein_Structure_Modeling.pdf, Download PDF
},
doi = {10.1038/s41592-021-01360-8},
year = {2022},
date = {2022-01-22},
urldate = {2022-01-22},
journal = {Nature Methods},
abstract = {Deep learning has transformed protein structure modeling. Here we relate AlphaFold and RoseTTAFold to classical physically based approaches to protein structure prediction, and discuss the many areas of structural biology that are likely to be affected by further advances in deep learning.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Deep learning has transformed protein structure modeling. Here we relate AlphaFold and RoseTTAFold to classical physically based approaches to protein structure prediction, and discuss the many areas of structural biology that are likely to be affected by further advances in deep learning.
Danny D. Sahtoe, Florian Praetorius, Alexis Courbet, Yang Hsia, Basile I. M. Wicky, Natasha I. Edman, Lauren M. Miller, Bart J. R. Timmermans, Justin Decarreau, Hana M. Morris, Alex Kang, Asim K. Bera, David Baker
Reconfigurable asymmetric protein assemblies through implicit negative design Journal Article
In: Science, 2022.
@article{Sahtoe2022,
title = {Reconfigurable asymmetric protein assemblies through implicit negative design},
author = {Danny D. Sahtoe and Florian Praetorius and Alexis Courbet and Yang Hsia and Basile I. M. Wicky and Natasha I. Edman and Lauren M. Miller and Bart J. R. Timmermans and Justin Decarreau and Hana M. Morris and Alex Kang and Asim K. Bera and David Baker},
url = {https://www.science.org/doi/pdf/10.1126/science.abj7662
https://www.bakerlab.org/wp-content/uploads/2022/01/Sahtoe_etal_Science2022_Diverse_protein_assemblies_by_implicit_negative_design.pdf},
doi = {10.1126/science.abj7662},
year = {2022},
date = {2022-01-21},
urldate = {2022-01-21},
journal = {Science},
abstract = {Asymmetric multiprotein complexes that undergo subunit exchange play central roles in biology but present a challenge for design because the components must not only contain interfaces that enable reversible association but also be stable and well behaved in isolation. We use implicit negative design to generate β sheet–mediated heterodimers that can be assembled into a wide variety of complexes. The designs are stable, folded, and soluble in isolation and rapidly assemble upon mixing, and crystal structures are close to the computational models. We construct linearly arranged hetero-oligomers with up to six different components, branched hetero-oligomers, closed C4-symmetric two-component rings, and hetero-oligomers assembled on a cyclic homo-oligomeric central hub and demonstrate that such complexes can readily reconfigure through subunit exchange. Our approach provides a general route to designing asymmetric reconfigurable protein systems. Protein complexes play important roles in biological processes, and many complexes are dynamic, with subunits exchanging to facilitate different functions. It has been challenging to design stable and soluble monomeric proteins that reversibly associate into hetero-oligomers. Sahtoe et al. used a strategy called implicit negative design to construct proteins with interaction interfaces that drive association with a selected partner but not self-association. The resulting designs are stably folded in solution and provide the modules for assembly into a wide variety of complexes. They can be functionalized, allowing target proteins to be displayed in defined geometries, and complex subunits can be exchanged by varying the available concentrations of components. —VV De novo designed protein building blocks can be modularly combined to create customized protein assemblies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Asymmetric multiprotein complexes that undergo subunit exchange play central roles in biology but present a challenge for design because the components must not only contain interfaces that enable reversible association but also be stable and well behaved in isolation. We use implicit negative design to generate β sheet–mediated heterodimers that can be assembled into a wide variety of complexes. The designs are stable, folded, and soluble in isolation and rapidly assemble upon mixing, and crystal structures are close to the computational models. We construct linearly arranged hetero-oligomers with up to six different components, branched hetero-oligomers, closed C4-symmetric two-component rings, and hetero-oligomers assembled on a cyclic homo-oligomeric central hub and demonstrate that such complexes can readily reconfigure through subunit exchange. Our approach provides a general route to designing asymmetric reconfigurable protein systems. Protein complexes play important roles in biological processes, and many complexes are dynamic, with subunits exchanging to facilitate different functions. It has been challenging to design stable and soluble monomeric proteins that reversibly associate into hetero-oligomers. Sahtoe et al. used a strategy called implicit negative design to construct proteins with interaction interfaces that drive association with a selected partner but not self-association. The resulting designs are stably folded in solution and provide the modules for assembly into a wide variety of complexes. They can be functionalized, allowing target proteins to be displayed in defined geometries, and complex subunits can be exchanged by varying the available concentrations of components. —VV De novo designed protein building blocks can be modularly combined to create customized protein assemblies.
COLLABORATOR LED
Joon Sung Park, Jungyuen Choi, Longxing Cao, Jyotidarsini Mohanty, Yoshihisa Suzuki, Andy Park, David Baker, Joseph Schlessinger, Sangwon Lee
Isoform-specific inhibition of FGFR signaling achieved by a de-novo-designed mini-protein Journal Article
In: Cell Reports, 2022.
@article{nokey,
title = {Isoform-specific inhibition of FGFR signaling achieved by a de-novo-designed mini-protein},
author = {Joon Sung Park and Jungyuen Choi and Longxing Cao and Jyotidarsini Mohanty and Yoshihisa Suzuki and Andy Park and David Baker and Joseph Schlessinger and Sangwon Lee},
url = {https://www.sciencedirect.com/science/article/pii/S2211124722014012#!, Cell Reports
https://www.bakerlab.org/wp-content/uploads/2022/10/1-s2.0-S2211124722014012-main.pdf, PDF},
doi = {10.1016/j.celrep.2022.111545},
year = {2022},
date = {2022-10-25},
journal = {Cell Reports},
abstract = {Cellular signaling by fibroblast growth factor receptors (FGFRs) is a highly regulated process mediated by specific interactions between distinct subsets of fibroblast growth factor (FGF) ligands and two FGFR isoforms generated by alternative splicing: an epithelial b- and mesenchymal c-isoforms. Here, we investigate the properties of a mini-protein, mb7, developed by an in silico design strategy to bind to the ligand-binding region of FGFR2. We describe structural, biophysical, and cellular analyses demonstrating that mb7 binds with high affinity to the c-isoforms of FGFR, resulting in inhibition of cellular signaling induced by a subset of FGFs that preferentially activate c-isoforms of FGFR. Notably, as mb7 blocks interaction between FGFR with Klotho proteins, it functions as an antagonist of the metabolic hormones FGF19 and FGF21, providing mechanistic insights and strategies for the development of therapeutics for diseases driven by aberrantly activated FGFRs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cellular signaling by fibroblast growth factor receptors (FGFRs) is a highly regulated process mediated by specific interactions between distinct subsets of fibroblast growth factor (FGF) ligands and two FGFR isoforms generated by alternative splicing: an epithelial b- and mesenchymal c-isoforms. Here, we investigate the properties of a mini-protein, mb7, developed by an in silico design strategy to bind to the ligand-binding region of FGFR2. We describe structural, biophysical, and cellular analyses demonstrating that mb7 binds with high affinity to the c-isoforms of FGFR, resulting in inhibition of cellular signaling induced by a subset of FGFs that preferentially activate c-isoforms of FGFR. Notably, as mb7 blocks interaction between FGFR with Klotho proteins, it functions as an antagonist of the metabolic hormones FGF19 and FGF21, providing mechanistic insights and strategies for the development of therapeutics for diseases driven by aberrantly activated FGFRs.
Sen, Neeladri and Anishchenko, Ivan and Bordin N and Sillitoe, Ian and Velankar, Sameer and Baker, David and Orengo, Christine
Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs Journal Article
In: Briefings in Bioinformatics, 2022.
@article{Sen2022,
title = {Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs},
author = {Sen, Neeladri
and Anishchenko, Ivan
and Bordin N
and Sillitoe, Ian
and Velankar, Sameer
and Baker, David
and Orengo, Christine},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294430/},
doi = {10.1093/bib/bbac187},
year = {2022},
date = {2022-07-18},
journal = {Briefings in Bioinformatics},
abstract = {Mutations in human proteins lead to diseases. The structure of these proteins can help understand the mechanism of such diseases and develop therapeutics against them. With improved deep learning techniques, such as RoseTTAFold and AlphaFold, we can predict the structure of proteins even in the absence of structural homologs. We modeled and extracted the domains from 553 disease-associated human proteins without known protein structures or close homologs in the Protein Databank. We noticed that the model quality was higher and the Root mean square deviation (RMSD) lower between AlphaFold and RoseTTAFold models for domains that could be assigned to CATH families as compared to those which could only be assigned to Pfam families of unknown structure or could not be assigned to either. We predicted ligand-binding sites, protein-protein interfaces and conserved residues in these predicted structures. We then explored whether the disease-associated missense mutations were in the proximity of these predicted functional sites, whether they destabilized the protein structure based on ddG calculations or whether they were predicted to be pathogenic. We could explain 80% of these disease-associated mutations based on proximity to functional sites, structural destabilization or pathogenicity. When compared to polymorphisms, a larger percentage of disease-associated missense mutations were buried, closer to predicted functional sites, predicted as destabilizing and pathogenic. Usage of models from the two state-of-the-art techniques provide better confidence in our predictions, and we explain 93 additional mutations based on RoseTTAFold models which could not be explained based solely on AlphaFold models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mutations in human proteins lead to diseases. The structure of these proteins can help understand the mechanism of such diseases and develop therapeutics against them. With improved deep learning techniques, such as RoseTTAFold and AlphaFold, we can predict the structure of proteins even in the absence of structural homologs. We modeled and extracted the domains from 553 disease-associated human proteins without known protein structures or close homologs in the Protein Databank. We noticed that the model quality was higher and the Root mean square deviation (RMSD) lower between AlphaFold and RoseTTAFold models for domains that could be assigned to CATH families as compared to those which could only be assigned to Pfam families of unknown structure or could not be assigned to either. We predicted ligand-binding sites, protein-protein interfaces and conserved residues in these predicted structures. We then explored whether the disease-associated missense mutations were in the proximity of these predicted functional sites, whether they destabilized the protein structure based on ddG calculations or whether they were predicted to be pathogenic. We could explain 80% of these disease-associated mutations based on proximity to functional sites, structural destabilization or pathogenicity. When compared to polymorphisms, a larger percentage of disease-associated missense mutations were buried, closer to predicted functional sites, predicted as destabilizing and pathogenic. Usage of models from the two state-of-the-art techniques provide better confidence in our predictions, and we explain 93 additional mutations based on RoseTTAFold models which could not be explained based solely on AlphaFold models.
Macé, Kévin and Vadakkepat, Abhinav K. and Redzej, Adam and Lukoyanova, Natalya and Oomen, Clasien and Braun, Nathalie and Ukleja, Marta and Lu, Fang and Costa, Tiago R. D. and Orlova, Elena V. and Baker, David and Cong, Qian and Waksman, Gabriel
Cryo-EM structure of a type IV secretion system Journal Article
In: Nature, 2022.
@article{Macé2022,
title = {Cryo-EM structure of a type IV secretion system},
author = {Macé, Kévin
and Vadakkepat, Abhinav K.
and Redzej, Adam
and Lukoyanova, Natalya
and Oomen, Clasien
and Braun, Nathalie
and Ukleja, Marta
and Lu, Fang
and Costa, Tiago R. D.
and Orlova, Elena V.
and Baker, David
and Cong, Qian
and Waksman, Gabriel},
url = {https://www.nature.com/articles/s41586-022-04859-y, Nature
https://www.bakerlab.org/wp-content/uploads/2022/08/Mace2022s41586-022-04859-y.pdf, PDF},
doi = {10.1038/s41586-022-04859-y},
year = {2022},
date = {2022-07-01},
urldate = {2022-07-01},
journal = {Nature},
abstract = {Bacterial conjugation is the fundamental process of unidirectional transfer of DNAs, often plasmid DNAs, from a donor cell to a recipient cell1. It is the primary means by which antibiotic resistance genes spread among bacterial populations2,3. In Gram-negative bacteria, conjugation is mediated by a large transport apparatus—the conjugative type IV secretion system (T4SS)—produced by the donor cell and embedded in both its outer and inner membranes. The T4SS also elaborates a long extracellular filament—the conjugative pilus—that is essential for DNA transfer4,5. Here we present a high-resolution cryo-electron microscopy (cryo-EM) structure of a 2.8 megadalton T4SS complex composed of 92 polypeptides representing 8 of the 10 essential T4SS components involved in pilus biogenesis. We added the two remaining components to the structural model using co-evolution analysis of protein interfaces, to enable the reconstitution of the entire system including the pilus. This structure describes the exceptionally large protein–protein interaction network required to assemble the many components that constitute a T4SS and provides insights on the unique mechanism by which they elaborate pili.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Bacterial conjugation is the fundamental process of unidirectional transfer of DNAs, often plasmid DNAs, from a donor cell to a recipient cell1. It is the primary means by which antibiotic resistance genes spread among bacterial populations2,3. In Gram-negative bacteria, conjugation is mediated by a large transport apparatus—the conjugative type IV secretion system (T4SS)—produced by the donor cell and embedded in both its outer and inner membranes. The T4SS also elaborates a long extracellular filament—the conjugative pilus—that is essential for DNA transfer4,5. Here we present a high-resolution cryo-electron microscopy (cryo-EM) structure of a 2.8 megadalton T4SS complex composed of 92 polypeptides representing 8 of the 10 essential T4SS components involved in pilus biogenesis. We added the two remaining components to the structural model using co-evolution analysis of protein interfaces, to enable the reconstitution of the entire system including the pilus. This structure describes the exceptionally large protein–protein interaction network required to assemble the many components that constitute a T4SS and provides insights on the unique mechanism by which they elaborate pili.
Agarwal, Dilip Kumar and Hunt, Andrew C. and Shekhawat, Gajendra S. and Carter, Lauren and Chan, Sidney and Wu, Kejia and Cao, Longxing and Baker, David and Lorenzo-Redondo, Ramon and Ozer, Egon A. and Simons, Lacy M. and Hultquist, Judd F. and Jewett, Michael C. and Dravid, Vinayak P.
Rapid and Sensitive Detection of Antigen from SARS-CoV-2 Variants of Concern by a Multivalent Minibinder-Functionalized Nanomechanical Sensor Journal Article
In: Analytical Chemistry, 2022.
@article{Agarwal2022,
title = {Rapid and Sensitive Detection of Antigen from SARS-CoV-2 Variants of Concern by a Multivalent Minibinder-Functionalized Nanomechanical Sensor},
author = {Agarwal, Dilip Kumar
and Hunt, Andrew C.
and Shekhawat, Gajendra S.
and Carter, Lauren
and Chan, Sidney
and Wu, Kejia
and Cao, Longxing
and Baker, David
and Lorenzo-Redondo, Ramon
and Ozer, Egon A.
and Simons, Lacy M.
and Hultquist, Judd F.
and Jewett, Michael C.
and Dravid, Vinayak P.},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9211039/, Analytical Chemistry},
year = {2022},
date = {2022-06-06},
urldate = {2022-06-06},
journal = {Analytical Chemistry},
abstract = {New platforms for the rapid and sensitive detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern are urgently needed. Here we report the development of a nanomechanical sensor based on the deflection of a microcantilever capable of detecting the SARS-CoV-2 spike (S) glycoprotein antigen using computationally designed multivalent minibinders immobilized on a microcantilever surface. The sensor exhibits rapid (<5 min) detection of the target antigens down to concentrations of 0.05 ng/mL (362 fM) and is more than an order of magnitude more sensitive than an antibody-based cantilever sensor. Validation of the sensor with clinical samples from 33 patients, including 9 patients infected with the Omicron (BA.1) variant observed detection of antigen from nasopharyngeal swabs with cycle threshold (Ct) values as high as 39, suggesting a limit of detection similar to that of the quantitative reverse transcription polymerase chain reaction (RT-qPCR). Our findings demonstrate the use of minibinders and nanomechanical sensors for the rapid and sensitive detection of SARS-CoV-2 and potentially other disease markers.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
New platforms for the rapid and sensitive detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern are urgently needed. Here we report the development of a nanomechanical sensor based on the deflection of a microcantilever capable of detecting the SARS-CoV-2 spike (S) glycoprotein antigen using computationally designed multivalent minibinders immobilized on a microcantilever surface. The sensor exhibits rapid (<5 min) detection of the target antigens down to concentrations of 0.05 ng/mL (362 fM) and is more than an order of magnitude more sensitive than an antibody-based cantilever sensor. Validation of the sensor with clinical samples from 33 patients, including 9 patients infected with the Omicron (BA.1) variant observed detection of antigen from nasopharyngeal swabs with cycle threshold (Ct) values as high as 39, suggesting a limit of detection similar to that of the quantitative reverse transcription polymerase chain reaction (RT-qPCR). Our findings demonstrate the use of minibinders and nanomechanical sensors for the rapid and sensitive detection of SARS-CoV-2 and potentially other disease markers.
Sarah L. Lovelock, Rebecca Crawshaw, Sophie Basler, Colin Levy, David Baker, Donald Hilvert, Anthony P. Green
The road to fully programmable protein catalysis Journal Article
In: Nature, 2022.
@article{Lovelock2022,
title = {The road to fully programmable protein catalysis},
author = {Sarah L. Lovelock and Rebecca Crawshaw and Sophie Basler and Colin Levy and David Baker and Donald Hilvert and Anthony P. Green
},
url = {https://www.nature.com/articles/s41586-022-04456-z, Nature
https://www.bakerlab.org/wp-content/uploads/2022/06/s41586-022-04456-z.pdf, Download PDF},
doi = {10.1038/s41586-022-04456-z},
year = {2022},
date = {2022-06-01},
journal = {Nature},
abstract = {The ability to design efficient enzymes from scratch would have a profound effect on chemistry, biotechnology and medicine. Rapid progress in protein engineering over the past decade makes us optimistic that this ambition is within reach. The development of artificial enzymes containing metal cofactors and noncanonical organocatalytic groups shows how protein structure can be optimized to harness the reactivity of nonproteinogenic elements. In parallel, computational methods have been used to design protein catalysts for diverse reactions on the basis of fundamental principles of transition state stabilization. Although the activities of designed catalysts have been quite low, extensive laboratory evolution has been used to generate efficient enzymes. Structural analysis of these systems has revealed the high degree of precision that will be needed to design catalysts with greater activity. To this end, emerging protein design methods, including deep learning, hold particular promise for improving model accuracy. Here we take stock of key developments in the field and highlight new opportunities for innovation that should allow us to transition beyond the current state of the art and enable the robust design of biocatalysts to address societal needs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ability to design efficient enzymes from scratch would have a profound effect on chemistry, biotechnology and medicine. Rapid progress in protein engineering over the past decade makes us optimistic that this ambition is within reach. The development of artificial enzymes containing metal cofactors and noncanonical organocatalytic groups shows how protein structure can be optimized to harness the reactivity of nonproteinogenic elements. In parallel, computational methods have been used to design protein catalysts for diverse reactions on the basis of fundamental principles of transition state stabilization. Although the activities of designed catalysts have been quite low, extensive laboratory evolution has been used to generate efficient enzymes. Structural analysis of these systems has revealed the high degree of precision that will be needed to design catalysts with greater activity. To this end, emerging protein design methods, including deep learning, hold particular promise for improving model accuracy. Here we take stock of key developments in the field and highlight new opportunities for innovation that should allow us to transition beyond the current state of the art and enable the robust design of biocatalysts to address societal needs.
Yao, Sicong, Moyer, Adam, Zheng, Yiwu, Shen, Yang, Meng, Xiaoting, Yuan, Chong, Zhao, Yibing, Yao, Hongwei, Baker, David, Wu, Chuanliu
De novo design and directed folding of disulfide-bridged peptide heterodimers Journal Article
In: Nature Communications, 2022.
@article{Yao2022,
title = {De novo design and directed folding of disulfide-bridged peptide heterodimers},
author = {Yao, Sicong and Moyer, Adam and Zheng, Yiwu and Shen, Yang and Meng, Xiaoting and Yuan, Chong and Zhao, Yibing and Yao, Hongwei and Baker, David and Wu, Chuanliu},
url = {https://www.nature.com/articles/s41467-022-29210-x, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2022/03/Yao_etal_NatComms2022_Design_of_directed_folding_of_disulfile_bridged_peptide_heterodimers.pdf, Download PDF},
year = {2022},
date = {2022-03-22},
urldate = {2022-03-22},
journal = {Nature Communications},
abstract = {Peptide heterodimers are prevalent in nature, which are not only functional macromolecules but molecular tools for chemical and synthetic biology. Computational methods have also been developed to design heterodimers of advanced functions. However, these peptide heterodimers are usually formed through noncovalent interactions, which are prone to dissociate and subject to concentration-dependent nonspecific aggregation. Heterodimers crosslinked with interchain disulfide bonds are more stable, but it represents a formidable challenge for both the computational design of heterodimers and the manipulation of disulfide pairing for heterodimer synthesis and applications. Here, we report the design, synthesis and application of interchain disulfide-bridged peptide heterodimers with mutual orthogonality by combining computational de novo designs with a directed disulfide pairing strategy. These heterodimers can be used as not only scaffolds for generating functional molecules but chemical tools or building blocks for protein labeling and construction of crosslinking hybrids. This study thus opens the door for using this unexplored dimeric structure space for many biological applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Peptide heterodimers are prevalent in nature, which are not only functional macromolecules but molecular tools for chemical and synthetic biology. Computational methods have also been developed to design heterodimers of advanced functions. However, these peptide heterodimers are usually formed through noncovalent interactions, which are prone to dissociate and subject to concentration-dependent nonspecific aggregation. Heterodimers crosslinked with interchain disulfide bonds are more stable, but it represents a formidable challenge for both the computational design of heterodimers and the manipulation of disulfide pairing for heterodimer synthesis and applications. Here, we report the design, synthesis and application of interchain disulfide-bridged peptide heterodimers with mutual orthogonality by combining computational de novo designs with a directed disulfide pairing strategy. These heterodimers can be used as not only scaffolds for generating functional molecules but chemical tools or building blocks for protein labeling and construction of crosslinking hybrids. This study thus opens the door for using this unexplored dimeric structure space for many biological applications.
Singer, Jedediah M., Novotney, Scott, Strickland, Devin, Haddox, Hugh K., Leiby, Nicholas, Rocklin, Gabriel J., Chow, Cameron M., Roy, Anindya, Bera, Asim K., Motta, Francis C., Cao, Longxing, Strauch, Eva-Maria, Chidyausiku, Tamuka M., Ford, Alex, Ho, Ethan, Zaitzeff, Alexander, Mackenzie, Craig O., Eramian, Hamed, DiMaio, Frank, Grigoryan, Gevorg, Vaughn, Matthew, Stewart, Lance J., Baker, David, Klavins, Eric
Large-scale design and refinement of stable proteins using sequence-only models Journal Article
In: PLoS ONE, 2022.
@article{Singer2022,
title = {Large-scale design and refinement of stable proteins using sequence-only models},
author = {Singer, Jedediah M. and Novotney, Scott and Strickland, Devin and Haddox, Hugh K. and Leiby, Nicholas and Rocklin, Gabriel J. and Chow, Cameron M. and Roy, Anindya and Bera, Asim K. and Motta, Francis C. and Cao, Longxing and Strauch, Eva-Maria and Chidyausiku, Tamuka M. and Ford, Alex and Ho, Ethan and Zaitzeff, Alexander and Mackenzie, Craig O. and Eramian, Hamed and DiMaio, Frank and Grigoryan, Gevorg and Vaughn, Matthew and Stewart, Lance J. and Baker, David and Klavins, Eric
},
doi = {doi.org/10.1371/journal.pone.0265020},
year = {2022},
date = {2022-03-14},
urldate = {2022-03-14},
journal = {PLoS ONE},
abstract = {Engineered proteins generally must possess a stable structure in order to achieve their designed function. Stable designs, however, are astronomically rare within the space of all possible amino acid sequences. As a consequence, many designs must be tested computationally and experimentally in order to find stable ones, which is expensive in terms of time and resources. Here we use a high-throughput, low-fidelity assay to experimentally evaluate the stability of approximately 200,000 novel proteins. These include a wide range of sequence perturbations, providing a baseline for future work in the field. We build a neural network model that predicts protein stability given only sequences of amino acids, and compare its performance to the assayed values. We also report another network model that is able to generate the amino acid sequences of novel stable proteins given requested secondary sequences. Finally, we show that the predictive model—despite weaknesses including a noisy data set—can be used to substantially increase the stability of both expert-designed and model-generated proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Engineered proteins generally must possess a stable structure in order to achieve their designed function. Stable designs, however, are astronomically rare within the space of all possible amino acid sequences. As a consequence, many designs must be tested computationally and experimentally in order to find stable ones, which is expensive in terms of time and resources. Here we use a high-throughput, low-fidelity assay to experimentally evaluate the stability of approximately 200,000 novel proteins. These include a wide range of sequence perturbations, providing a baseline for future work in the field. We build a neural network model that predicts protein stability given only sequences of amino acids, and compare its performance to the assayed values. We also report another network model that is able to generate the amino acid sequences of novel stable proteins given requested secondary sequences. Finally, we show that the predictive model—despite weaknesses including a noisy data set—can be used to substantially increase the stability of both expert-designed and model-generated proteins.
Shiri Levy, Logeshwaran Somasundaram, Infencia Xavier Raj, Diego Ic-Mex, Ashish Phal, Sven Schmidt, Weng I. Ng, Daniel Mar, Justin Decarreau, Nicholas Moss, Ammar Alghadeer, Henrik Honkanen, Jay Sarthy, Nicholas Vitanza, R. David Hawkins, Julie Mathieu, Yuliang Wang, David Baker, Karol Bomsztyk, Hannele Ruohola-Baker
dCas9 fusion to computer-designed PRC2 inhibitor reveals functional TATA box in distal promoter region Journal Article
In: Cell Reports, 2022.
@article{Levy2022,
title = {dCas9 fusion to computer-designed PRC2 inhibitor reveals functional TATA box in distal promoter region},
author = {Shiri Levy and Logeshwaran Somasundaram and Infencia Xavier Raj and Diego Ic-Mex and Ashish Phal and Sven Schmidt and Weng I. Ng and Daniel Mar and Justin Decarreau and Nicholas Moss and Ammar Alghadeer and Henrik Honkanen and Jay Sarthy and Nicholas Vitanza and R. David Hawkins and Julie Mathieu and Yuliang Wang and David Baker and Karol Bomsztyk and Hannele Ruohola-Baker},
url = {https://www.sciencedirect.com/science/article/pii/S221112472200184X, Cell Reports
https://www.bakerlab.org/wp-content/uploads/2022/03/1-s2.0-S221112472200184X-main.pdf, Download PDF},
doi = {10.1016/j.celrep.2022.110457},
year = {2022},
date = {2022-03-01},
journal = {Cell Reports},
abstract = {Bifurcation of cellular fates, a critical process in development, requires histone 3 lysine 27 methylation (H3K27me3) marks propagated by the polycomb repressive complex 2 (PRC2). However, precise chromatin loci of functional H3K27me3 marks are not yet known. Here, we identify critical PRC2 functional sites at high resolution. We fused a computationally designed protein, EED binder (EB), which competes with EZH2 and thereby inhibits PRC2 function, to dCas9 (EBdCas9) to allow for PRC2 inhibition at a precise locus using gRNA. Targeting EBdCas9 to four different genes (TBX18, p16, CDX2, and GATA3) results in precise H3K27me3 and EZH2 reduction, gene activation, and functional outcomes in the cell cycle (p16) or trophoblast transdifferentiation (CDX2 and GATA3). In the case of TBX18, we identify a PRC2-controlled, functional TATA box >500 bp upstream of the TBX18 transcription start site (TSS) using EBdCas9. Deletion of this TATA box eliminates EBdCas9-dependent TATA binding protein (TBP) recruitment and transcriptional activation. EBdCas9 technology may provide a broadly applicable tool for epigenomic control of gene regulation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Bifurcation of cellular fates, a critical process in development, requires histone 3 lysine 27 methylation (H3K27me3) marks propagated by the polycomb repressive complex 2 (PRC2). However, precise chromatin loci of functional H3K27me3 marks are not yet known. Here, we identify critical PRC2 functional sites at high resolution. We fused a computationally designed protein, EED binder (EB), which competes with EZH2 and thereby inhibits PRC2 function, to dCas9 (EBdCas9) to allow for PRC2 inhibition at a precise locus using gRNA. Targeting EBdCas9 to four different genes (TBX18, p16, CDX2, and GATA3) results in precise H3K27me3 and EZH2 reduction, gene activation, and functional outcomes in the cell cycle (p16) or trophoblast transdifferentiation (CDX2 and GATA3). In the case of TBX18, we identify a PRC2-controlled, functional TATA box >500 bp upstream of the TBX18 transcription start site (TSS) using EBdCas9. Deletion of this TATA box eliminates EBdCas9-dependent TATA binding protein (TBP) recruitment and transcriptional activation. EBdCas9 technology may provide a broadly applicable tool for epigenomic control of gene regulation.
Mike T. Veling, Dan T. Nguyen, Nicole N. Thadani, Michela E. Oster, Nathan J. Rollins, Kelly P. Brock, Neville P. Bethel, Samuel Lim, David Baker, Jeffrey C. Way, Debora S. Marks, Roger L. Chang, and Pamela A. Silver
Natural and Designed Proteins Inspired by Extremotolerant Organisms Can Form Condensates and Attenuate Apoptosis in Human Cells Journal Article
In: ACS Synthetic Biology, 2022.
@article{Veling2022,
title = {Natural and Designed Proteins Inspired by Extremotolerant Organisms Can Form Condensates and Attenuate Apoptosis in Human Cells},
author = {Mike T. Veling and Dan T. Nguyen and Nicole N. Thadani and Michela E. Oster and Nathan J. Rollins and Kelly P. Brock and Neville P. Bethel and Samuel Lim, David Baker and Jeffrey C. Way and Debora S. Marks and Roger L. Chang and and Pamela A. Silver},
url = {https://pubs.acs.org/doi/abs/10.1021/acssynbio.1c00572, ACS Synthetic Biology
https://www.bakerlab.org/wp-content/uploads/2022/02/Veling_etal_ACSSynBio_Feb2022.pdf, Download PDF},
doi = {10.1021/acssynbio.1c00572},
year = {2022},
date = {2022-02-18},
journal = {ACS Synthetic Biology},
abstract = {Many organisms can survive extreme conditions and successfully recover to normal life. This extremotolerant behavior has been attributed in part to repetitive, amphipathic, and intrinsically disordered proteins that are upregulated in the protected state. Here, we assemble a library of approximately 300 naturally occurring and designed extremotolerance-associated proteins to assess their ability to protect human cells from chemically induced apoptosis. We show that several proteins from tardigrades, nematodes, and the Chinese giant salamander are apoptosis-protective. Notably, we identify a region of the human ApoE protein with similarity to extremotolerance-associated proteins that also protects against apoptosis. This region mirrors the phase separation behavior seen with such proteins, like the tardigrade protein CAHS2. Moreover, we identify a synthetic protein, DHR81, that shares this combination of elevated phase separation propensity and apoptosis protection. Finally, we demonstrate that driving protective proteins into the condensate state increases apoptosis protection, and highlights the ability of DHR81 condensates to sequester caspase-7. Taken together, this work draws a link between extremotolerance-associated proteins, condensate formation, and designing human cellular protection.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many organisms can survive extreme conditions and successfully recover to normal life. This extremotolerant behavior has been attributed in part to repetitive, amphipathic, and intrinsically disordered proteins that are upregulated in the protected state. Here, we assemble a library of approximately 300 naturally occurring and designed extremotolerance-associated proteins to assess their ability to protect human cells from chemically induced apoptosis. We show that several proteins from tardigrades, nematodes, and the Chinese giant salamander are apoptosis-protective. Notably, we identify a region of the human ApoE protein with similarity to extremotolerance-associated proteins that also protects against apoptosis. This region mirrors the phase separation behavior seen with such proteins, like the tardigrade protein CAHS2. Moreover, we identify a synthetic protein, DHR81, that shares this combination of elevated phase separation propensity and apoptosis protection. Finally, we demonstrate that driving protective proteins into the condensate state increases apoptosis protection, and highlights the ability of DHR81 condensates to sequester caspase-7. Taken together, this work draws a link between extremotolerance-associated proteins, condensate formation, and designing human cellular protection.
Taylor H. Nguyen, Galen Dods, Mariana Gomez-Schiavon, Muziyue Wu, Zibo Chen, Ryan Kibler, David Baker, Hana El-Samad, Andrew H. Ng
In: GEN Biotechnology, 2022.
@article{Nguyen2022,
title = {Competitive Displacement of De Novo Designed HeteroDimers Can Reversibly Control Protein–Protein Interactions and Implement Feedback in Synthetic Circuits},
author = {Taylor H. Nguyen and Galen Dods and Mariana Gomez-Schiavon and Muziyue Wu and Zibo Chen and Ryan Kibler and David Baker and Hana El-Samad and Andrew H. Ng},
url = {https://www.liebertpub.com/doi/10.1089/genbio.2021.0011, GEN Biotechnology
},
doi = {10.1089/genbio.2021.0011},
year = {2022},
date = {2022-02-16},
urldate = {2022-02-16},
journal = {GEN Biotechnology},
abstract = {Dynamic dimerization is a common regulatory interaction between biological molecules, underpinning many signaling functions. Because of its ubiquity, many biological engineering efforts have focused on building dimerizing proteins, such as the SYNZIPs and de novo Designed HeteroDimers (DHDs). Using the DHDs as a model system, we show that low-affinity protein interactions can be competitively displaced by a high-affinity “dominant negative” heterodimer. We demonstrate the utility of this signaling motif by using competitive displacement to implement negative feedback in a synthetic circuit. Competitive displacement could be extended to other heterodimer systems to expand the functionality of protein circuits and enable new biotechnology applications.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dynamic dimerization is a common regulatory interaction between biological molecules, underpinning many signaling functions. Because of its ubiquity, many biological engineering efforts have focused on building dimerizing proteins, such as the SYNZIPs and de novo Designed HeteroDimers (DHDs). Using the DHDs as a model system, we show that low-affinity protein interactions can be competitively displaced by a high-affinity “dominant negative” heterodimer. We demonstrate the utility of this signaling motif by using competitive displacement to implement negative feedback in a synthetic circuit. Competitive displacement could be extended to other heterodimer systems to expand the functionality of protein circuits and enable new biotechnology applications.
Linder, Johannes, La Fleur, Alyssa, Chen, Zibo, Ljubetič, Ajasja, Baker, David, Kannan, Sreeram, Seelig, Georg
Interpreting neural networks for biological sequences by learning stochastic masks Journal Article
In: Nature Machine Intelligence, 2022.
@article{Linder2022,
title = {Interpreting neural networks for biological sequences by learning stochastic masks},
author = {Linder, Johannes and La Fleur, Alyssa and Chen, Zibo and Ljubetič, Ajasja and Baker, David and Kannan, Sreeram and Seelig, Georg},
url = {https://www.nature.com/articles/s42256-021-00428-6, Nature Machine Intelligence},
doi = {10.1038/s42256-021-00428-6},
year = {2022},
date = {2022-01-25},
urldate = {2022-01-25},
journal = {Nature Machine Intelligence},
abstract = {Sequence-based neural networks can learn to make accurate predictions from large biological datasets, but model interpretation remains challenging. Many existing feature attribution methods are optimized for continuous rather than discrete input patterns and assess individual feature importance in isolation, making them ill-suited for interpreting nonlinear interactions in molecular sequences. Here, building on work in computer vision and natural language processing, we developed an approach based on deep learning—scrambler networks—wherein the most important sequence positions are identified with learned input masks. Scramblers learn to predict position-specific scoring matrices where unimportant nucleotides or residues are scrambled by raising their entropy. We apply scramblers to interpret the effects of genetic variants, uncover nonlinear interactions between cis-regulatory elements, explain binding specificity for protein–protein interactions, and identify structural determinants of de novo-designed proteins. We show that scramblers enable efficient attribution across large datasets and result in high-quality explanations, often outperforming state-of-the-art methods.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sequence-based neural networks can learn to make accurate predictions from large biological datasets, but model interpretation remains challenging. Many existing feature attribution methods are optimized for continuous rather than discrete input patterns and assess individual feature importance in isolation, making them ill-suited for interpreting nonlinear interactions in molecular sequences. Here, building on work in computer vision and natural language processing, we developed an approach based on deep learning—scrambler networks—wherein the most important sequence positions are identified with learned input masks. Scramblers learn to predict position-specific scoring matrices where unimportant nucleotides or residues are scrambled by raising their entropy. We apply scramblers to interpret the effects of genetic variants, uncover nonlinear interactions between cis-regulatory elements, explain binding specificity for protein–protein interactions, and identify structural determinants of de novo-designed proteins. We show that scramblers enable efficient attribution across large datasets and result in high-quality explanations, often outperforming state-of-the-art methods.
Toshifumi Fujioka, Nobutaka Numoto, Hiroyuki Akama, Kola Shilpa, Michiko Oka, Prodip K. Roy, Yarkali Krishna, Nobutoshi Ito, David Baker, Masayuki Oda, Fujie Tanaka
Varying the Directionality of Protein Catalysts for Aldol and Retro-Aldol Reactions Journal Article
In: ChemBioChem, vol. 23, no. 2, pp. e202100435, 2022.
@article{https://doi.org/10.1002/cbic.202100435,
title = {Varying the Directionality of Protein Catalysts for Aldol and Retro-Aldol Reactions},
author = {Toshifumi Fujioka and Nobutaka Numoto and Hiroyuki Akama and Kola Shilpa and Michiko Oka and Prodip K. Roy and Yarkali Krishna and Nobutoshi Ito and David Baker and Masayuki Oda and Fujie Tanaka},
url = {https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cbic.202100435},
doi = {https://doi.org/10.1002/cbic.202100435},
year = {2022},
date = {2022-01-01},
journal = {ChemBioChem},
volume = {23},
number = {2},
pages = {e202100435},
abstract = {Abstract Natural aldolase enzymes and created retro-aldolase protein catalysts often catalyze both aldol and retro-aldol reactions depending on the concentrations of the reactants and the products. Here, we report that the directionality of protein catalysts can be altered by replacing one amino acid. The protein catalyst derived from a scaffold of a previously reported retro-aldolase catalyst, catalyzed aldol reactions more efficiently than the previously reported retro-aldolase catalyst. The retro-aldolase catalyst efficiently catalyzed the retro-aldol reaction but was less efficient in catalyzing the aldol reaction. The results indicate that protein catalysts with varying levels of directionality in usually reversibly catalyzed aldol and retro-aldol reactions can be generated from the same protein scaffold.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Natural aldolase enzymes and created retro-aldolase protein catalysts often catalyze both aldol and retro-aldol reactions depending on the concentrations of the reactants and the products. Here, we report that the directionality of protein catalysts can be altered by replacing one amino acid. The protein catalyst derived from a scaffold of a previously reported retro-aldolase catalyst, catalyzed aldol reactions more efficiently than the previously reported retro-aldolase catalyst. The retro-aldolase catalyst efficiently catalyzed the retro-aldol reaction but was less efficient in catalyzing the aldol reaction. The results indicate that protein catalysts with varying levels of directionality in usually reversibly catalyzed aldol and retro-aldol reactions can be generated from the same protein scaffold.
Brian L. Trippe, Buwei Huang, Erika A. DeBenedictis, Brian Coventry, Nicholas Bhattacharya, Kevin K. Yang, David Baker, Lorin Crawford
Randomized gates eliminate bias in sort-seq assays Journal Article
In: Protein Science, vol. 31, no. 9, pp. e4401, 2022.
@article{https://doi.org/10.1002/pro.4401,
title = {Randomized gates eliminate bias in sort-seq assays},
author = {Brian L. Trippe and Buwei Huang and Erika A. DeBenedictis and Brian Coventry and Nicholas Bhattacharya and Kevin K. Yang and David Baker and Lorin Crawford},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pro.4401},
doi = {https://doi.org/10.1002/pro.4401},
year = {2022},
date = {2022-01-01},
journal = {Protein Science},
volume = {31},
number = {9},
pages = {e4401},
abstract = {Abstract Sort-seq assays are a staple of the biological engineering toolkit, allowing researchers to profile many groups of cells based on any characteristic that can be tied to fluorescence. However, current approaches, which segregate cells into bins deterministically based on their measured fluorescence, introduce systematic bias. We describe a surprising result: one can obtain unbiased estimates by incorporating randomness into sorting. We validate this approach in simulation and experimentally, and describe extensions for both estimating group level variances and for using multi-bin sorters.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Sort-seq assays are a staple of the biological engineering toolkit, allowing researchers to profile many groups of cells based on any characteristic that can be tied to fluorescence. However, current approaches, which segregate cells into bins deterministically based on their measured fluorescence, introduce systematic bias. We describe a surprising result: one can obtain unbiased estimates by incorporating randomness into sorting. We validate this approach in simulation and experimentally, and describe extensions for both estimating group level variances and for using multi-bin sorters.
2021
FROM THE LAB
Anishchenko, Ivan and Pellock, Samuel J. and Chidyausiku, Tamuka M. and Ramelot, Theresa A. and Ovchinnikov, Sergey and Hao, Jingzhou and Bafna, Khushboo and Norn, Christoffer and Kang, Alex and Bera, Asim K. and DiMaio, Frank and Carter, Lauren and Chow, Cameron M. and Montelione, Gaetano T. and Baker, David
De novo protein design by deep network hallucination Journal Article
In: Nature, 2021.
@article{Anishchenko2021,
title = {De novo protein design by deep network hallucination},
author = {Anishchenko, Ivan
and Pellock, Samuel J.
and Chidyausiku, Tamuka M.
and Ramelot, Theresa A.
and Ovchinnikov, Sergey
and Hao, Jingzhou
and Bafna, Khushboo
and Norn, Christoffer
and Kang, Alex
and Bera, Asim K.
and DiMaio, Frank
and Carter, Lauren
and Chow, Cameron M.
and Montelione, Gaetano T.
and Baker, David},
url = {https://www.nature.com/articles/s41586-021-04184-w
https://www.bakerlab.org/wp-content/uploads/2022/01/Anishchenko_etal_Nature2021_DeepNetworkHallucination.pdf},
doi = {10.1038/s41586-021-04184-w},
year = {2021},
date = {2021-12-01},
urldate = {2021-12-01},
journal = {Nature},
abstract = {There has been considerable recent progress in protein structure prediction using deep neural networks to predict inter-residue distances from amino acid sequences1–3. Here we investigate whether the information captured by such networks is sufficiently rich to generate new folded proteins with sequences unrelated to those of the naturally occurring proteins used in training the models. We generate random amino acid sequences, and input them into the trRosetta structure prediction network to predict starting residue–residue distance maps, which, as expected, are quite featureless. We then carry out Monte Carlo sampling in amino acid sequence space, optimizing the contrast (Kullback–Leibler divergence) between the inter-residue distance distributions predicted by the network and background distributions averaged over all proteins. Optimization from different random starting points resulted in novel proteins spanning a wide range of sequences and predicted structures. We obtained synthetic genes encoding 129 of the network-‘hallucinated’ sequences, and expressed and purified the proteins in Escherichia coli; 27 of the proteins yielded monodisperse species with circular dichroism spectra consistent with the hallucinated structures. We determined the three-dimensional structures of three of the hallucinated proteins, two by X-ray crystallography and one by NMR, and these closely matched the hallucinated models. Thus, deep networks trained to predict native protein structures from their sequences can be inverted to design new proteins, and such networks and methods should contribute alongside traditional physics-based models to the de novo design of proteins with new functions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
There has been considerable recent progress in protein structure prediction using deep neural networks to predict inter-residue distances from amino acid sequences1–3. Here we investigate whether the information captured by such networks is sufficiently rich to generate new folded proteins with sequences unrelated to those of the naturally occurring proteins used in training the models. We generate random amino acid sequences, and input them into the trRosetta structure prediction network to predict starting residue–residue distance maps, which, as expected, are quite featureless. We then carry out Monte Carlo sampling in amino acid sequence space, optimizing the contrast (Kullback–Leibler divergence) between the inter-residue distance distributions predicted by the network and background distributions averaged over all proteins. Optimization from different random starting points resulted in novel proteins spanning a wide range of sequences and predicted structures. We obtained synthetic genes encoding 129 of the network-‘hallucinated’ sequences, and expressed and purified the proteins in Escherichia coli; 27 of the proteins yielded monodisperse species with circular dichroism spectra consistent with the hallucinated structures. We determined the three-dimensional structures of three of the hallucinated proteins, two by X-ray crystallography and one by NMR, and these closely matched the hallucinated models. Thus, deep networks trained to predict native protein structures from their sequences can be inverted to design new proteins, and such networks and methods should contribute alongside traditional physics-based models to the de novo design of proteins with new functions.
Ian R. Humphreys, Jimin Pei, Minkyung Baek, Aditya Krishnakumar, Ivan Anishchenko, Sergey Ovchinnikov, Jing Zhang, Travis J. Ness, Sudeep Banjade, Saket R. Bagde, Viktoriya G. Stancheva, Xiao-Han Li, Kaixian Liu, Zhi Zheng, Daniel J. Barrero, Upasana Roy, Jochen Kuper, Israel S. Fernández, Barnabas Szakal, Dana Branzei, Josep Rizo, Caroline Kisker, Eric C. Greene, Sue Biggins, Scott Keeney, Elizabeth A. Miller, J. Christopher Fromme, Tamara L. Hendrickson, Qian Cong, David Baker
Computed structures of core eukaryotic protein complexes Journal Article
In: Science, 2021.
@article{Humphreys2012,
title = {Computed structures of core eukaryotic protein complexes},
author = {Ian R. Humphreys and Jimin Pei and Minkyung Baek and Aditya Krishnakumar and Ivan Anishchenko and Sergey Ovchinnikov and Jing Zhang and Travis J. Ness and Sudeep Banjade and Saket R. Bagde and Viktoriya G. Stancheva and Xiao-Han Li and Kaixian Liu and Zhi Zheng and Daniel J. Barrero and Upasana Roy and Jochen Kuper and Israel S. Fernández and Barnabas Szakal and Dana Branzei and Josep Rizo and Caroline Kisker and Eric C. Greene and Sue Biggins and Scott Keeney and Elizabeth A. Miller and J. Christopher Fromme and Tamara L. Hendrickson and Qian Cong and David Baker},
url = {https://www.science.org/doi/10.1126/science.abm4805, Science
https://www.bakerlab.org/wp-content/uploads/2022/06/science.abm4805.pdf, Download PDF},
doi = {10.1126/science.abm4805},
year = {2021},
date = {2021-11-11},
urldate = {2021-11-11},
journal = {Science},
abstract = {Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coevolution analysis and deep-learning-based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes within the Saccharomyces cerevisiae proteome. We use a combination of RoseTTAFold and AlphaFold to screen through paired multiple sequence alignments for 8.3 million pairs of yeast proteins, identify 1,505 likely to interact, and build structure models for 106 previously unidentified assemblies and 806 that have not been structurally characterized. These complexes, which have as many as 5 subunits, play roles in almost all key processes in eukaryotic cells and provide broad insights into biological function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coevolution analysis and deep-learning-based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes within the Saccharomyces cerevisiae proteome. We use a combination of RoseTTAFold and AlphaFold to screen through paired multiple sequence alignments for 8.3 million pairs of yeast proteins, identify 1,505 likely to interact, and build structure models for 106 previously unidentified assemblies and 806 that have not been structurally characterized. These complexes, which have as many as 5 subunits, play roles in almost all key processes in eukaryotic cells and provide broad insights into biological function.
Woodall, Nicholas B. and Weinberg, Zara and Park, Jesslyn and Busch, Florian and Johnson, Richard S. and Feldbauer, Mikayla J. and Murphy, Michael and Ahlrichs, Maggie and Yousif, Issa and MacCoss, Michael J. and Wysocki, Vicki H. and El-Samad, Hana and Baker, David
De novo design of tyrosine and serine kinase-driven protein switches Journal Article
In: Nature Structural & Molecular Biology, 2021.
@article{Woodall2021,
title = {De novo design of tyrosine and serine kinase-driven protein switches},
author = {Woodall, Nicholas B.
and Weinberg, Zara
and Park, Jesslyn
and Busch, Florian
and Johnson, Richard S.
and Feldbauer, Mikayla J.
and Murphy, Michael
and Ahlrichs, Maggie
and Yousif, Issa
and MacCoss, Michael J.
and Wysocki, Vicki H.
and El-Samad, Hana
and Baker, David},
url = {https://www.nature.com/articles/s41594-021-00649-8, Nature Structural & Molecular Biology
https://www.bakerlab.org/wp-content/uploads/2021/09/De-novo-design-of-tyrosine-and-serine-kinase-driven-protein-switches.pdf, Download PDF},
doi = {10.1038/s41594-021-00649-8},
year = {2021},
date = {2021-09-13},
urldate = {2021-09-13},
journal = {Nature Structural & Molecular Biology},
abstract = {Kinases play central roles in signaling cascades, relaying information from the outside to the inside of mammalian cells. De novo designed protein switches capable of interfacing with tyrosine kinase signaling pathways would open new avenues for controlling cellular behavior, but, so far, no such systems have been described. Here we describe the de novo design of two classes of protein switch that link phosphorylation by tyrosine and serine kinases to protein-protein association. In the first class, protein-protein association is required for phosphorylation by the kinase, while in the second class, kinase activity drives protein-protein association. We design systems that couple protein binding to kinase activity on the immunoreceptor tyrosine-based activation motif central to T-cell signaling, and kinase activity to reconstitution of green fluorescent protein fluorescence from fragments and the inhibition of the protease calpain. The designed switches are reversible and function in vitro and in cells with up to 40-fold activation of switching by phosphorylation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kinases play central roles in signaling cascades, relaying information from the outside to the inside of mammalian cells. De novo designed protein switches capable of interfacing with tyrosine kinase signaling pathways would open new avenues for controlling cellular behavior, but, so far, no such systems have been described. Here we describe the de novo design of two classes of protein switch that link phosphorylation by tyrosine and serine kinases to protein-protein association. In the first class, protein-protein association is required for phosphorylation by the kinase, while in the second class, kinase activity drives protein-protein association. We design systems that couple protein binding to kinase activity on the immunoreceptor tyrosine-based activation motif central to T-cell signaling, and kinase activity to reconstitution of green fluorescent protein fluorescence from fragments and the inhibition of the protease calpain. The designed switches are reversible and function in vitro and in cells with up to 40-fold activation of switching by phosphorylation.
Minkyung Baek, Ivan Anishchenko, Hahnbeom Park, Ian R. Humphreys, David Baker
Protein oligomer modeling guided by predicted inter-chain contacts in CASP14 Journal Article
In: Proteins, 2021.
@article{Baek2021b,
title = {Protein oligomer modeling guided by predicted inter-chain contacts in CASP14},
author = {Minkyung Baek and Ivan Anishchenko and Hahnbeom Park and Ian R. Humphreys and David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.26197, Proteins},
doi = {10.1002/prot.26197},
year = {2021},
date = {2021-07-29},
urldate = {2021-07-29},
journal = {Proteins},
abstract = {For CASP14, we developed deep learning-based methods for predicting homo-oligomeric and hetero-oligomeric contacts and used them for oligomer modeling. To build structure models, we developed an oligomer structure generation method that utilizes predicted inter-chain contacts to guide iterative restrained minimization from random backbone structures. We supplemented this gradient-based fold-and-dock method with template-based and ab initio docking approaches using deep learning-based subunit predictions on 29 assembly targets. These methods produced oligomer models with summed Z-scores 5.5 units higher than the next best group, with the fold-and-dock method having the best relative performance. Over the eight targets for which this method was used, the best of the five submitted models had average oligomer TM-score of 0.71 (average oligomer TM-score of the next best group: 0.64), and explicit modeling of inter-subunit interactions improved modeling of six out of 40 individual domains (ΔGDT-TS > 2.0).
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
For CASP14, we developed deep learning-based methods for predicting homo-oligomeric and hetero-oligomeric contacts and used them for oligomer modeling. To build structure models, we developed an oligomer structure generation method that utilizes predicted inter-chain contacts to guide iterative restrained minimization from random backbone structures. We supplemented this gradient-based fold-and-dock method with template-based and ab initio docking approaches using deep learning-based subunit predictions on 29 assembly targets. These methods produced oligomer models with summed Z-scores 5.5 units higher than the next best group, with the fold-and-dock method having the best relative performance. Over the eight targets for which this method was used, the best of the five submitted models had average oligomer TM-score of 0.71 (average oligomer TM-score of the next best group: 0.64), and explicit modeling of inter-subunit interactions improved modeling of six out of 40 individual domains (ΔGDT-TS > 2.0).
Baek, Minkyung and DiMaio, Frank and Anishchenko, Ivan and Dauparas, Justas and Ovchinnikov, Sergey and Lee, Gyu Rie and Wang, Jue and Cong, Qian and Kinch, Lisa N. and Schaeffer, R. Dustin and Millán, Claudia and Park, Hahnbeom and Adams, Carson and Glassman, Caleb R. and DeGiovanni, Andy and Pereira, Jose H. and Rodrigues, Andria V. and van Dijk, Alberdina A. and Ebrecht, Ana C. and Opperman, Diederik J. and Sagmeister, Theo and Buhlheller, Christoph and Pavkov-Keller, Tea and Rathinaswamy, Manoj K. and Dalwadi, Udit and Yip, Calvin K. and Burke, John E. and Garcia, K. Christopher and Grishin, Nick V. and Adams, Paul D. and Read, Randy J. and Baker, David
Accurate prediction of protein structures and interactions using a three-track neural network Journal Article
In: Science, 2021.
@article{Baek2021,
title = {Accurate prediction of protein structures and interactions using a three-track neural network},
author = {Baek, Minkyung
and DiMaio, Frank
and Anishchenko, Ivan
and Dauparas, Justas
and Ovchinnikov, Sergey
and Lee, Gyu Rie
and Wang, Jue
and Cong, Qian
and Kinch, Lisa N.
and Schaeffer, R. Dustin
and Millán, Claudia
and Park, Hahnbeom
and Adams, Carson
and Glassman, Caleb R.
and DeGiovanni, Andy
and Pereira, Jose H.
and Rodrigues, Andria V.
and van Dijk, Alberdina A.
and Ebrecht, Ana C.
and Opperman, Diederik J.
and Sagmeister, Theo
and Buhlheller, Christoph
and Pavkov-Keller, Tea
and Rathinaswamy, Manoj K.
and Dalwadi, Udit
and Yip, Calvin K.
and Burke, John E.
and Garcia, K. Christopher
and Grishin, Nick V.
and Adams, Paul D.
and Read, Randy J.
and Baker, David},
url = {http://science.sciencemag.org/content/early/2021/07/14/science.abj8754, Science
https://www.ipd.uw.edu/wp-content/uploads/2021/07/Baek_etal_Science2021_RoseTTAFold.pdf, Download PDF},
doi = {10.1126/science.abj8754},
year = {2021},
date = {2021-07-15},
urldate = {2021-07-15},
journal = {Science},
abstract = {DeepMind presented remarkably accurate predictions at the recent CASP14 protein structure prediction assessment conference. We explored network architectures incorporating related ideas and obtained the best performance with a three-track network in which information at the 1D sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging X-ray crystallography and cryo-EM structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches which require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
DeepMind presented remarkably accurate predictions at the recent CASP14 protein structure prediction assessment conference. We explored network architectures incorporating related ideas and obtained the best performance with a three-track network in which information at the 1D sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging X-ray crystallography and cryo-EM structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches which require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.
Nobuyasu Koga, Rie Koga, Gaohua Liu, Javier Castellanos, Gaetano T. Montelione, David Baker
Role of backbone strain in de novo design of complex α/β protein structures Journal Article
In: Nature Communications, 2021.
@article{Koga2021,
title = {Role of backbone strain in de novo design of complex α/β protein structures},
author = {Nobuyasu Koga and Rie Koga and Gaohua Liu and Javier Castellanos and Gaetano T. Montelione and David Baker
},
url = {https://www.nature.com/articles/s41467-021-24050-7, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2021/07/Koga_NatComm2021.pdf, Download PDF},
doi = {10.1038/s41467-021-24050-7},
year = {2021},
date = {2021-06-24},
urldate = {2021-06-24},
journal = {Nature Communications},
abstract = {We previously elucidated principles for designing ideal proteins with completely consistent local and non-local interactions which have enabled the design of a wide range of new αβ-proteins with four or fewer β-strands. The principles relate local backbone structures to supersecondary-structure packing arrangements of α-helices and β-strands. Here, we test the generality of the principles by employing them to design larger proteins with five- and six- stranded β-sheets flanked by α-helices. The initial designs were monomeric in solution with high thermal stability, and the nuclear magnetic resonance (NMR) structure of one was close to the design model, but for two others the order of strands in the β-sheet was swapped. Investigation into the origins of this strand swapping suggested that the global structures of the design models were more strained than the NMR structures. We incorporated explicit consideration of global backbone strain into the design methodology, and succeeded in designing proteins with the intended unswapped strand arrangements. These results illustrate the value of experimental structure determination in guiding improvement of de novo design, and the importance of consistency between local, supersecondary, and global tertiary interactions in determining protein topology. The augmented set of principles should inform the design of larger functional proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We previously elucidated principles for designing ideal proteins with completely consistent local and non-local interactions which have enabled the design of a wide range of new αβ-proteins with four or fewer β-strands. The principles relate local backbone structures to supersecondary-structure packing arrangements of α-helices and β-strands. Here, we test the generality of the principles by employing them to design larger proteins with five- and six- stranded β-sheets flanked by α-helices. The initial designs were monomeric in solution with high thermal stability, and the nuclear magnetic resonance (NMR) structure of one was close to the design model, but for two others the order of strands in the β-sheet was swapped. Investigation into the origins of this strand swapping suggested that the global structures of the design models were more strained than the NMR structures. We incorporated explicit consideration of global backbone strain into the design methodology, and succeeded in designing proteins with the intended unswapped strand arrangements. These results illustrate the value of experimental structure determination in guiding improvement of de novo design, and the importance of consistency between local, supersecondary, and global tertiary interactions in determining protein topology. The augmented set of principles should inform the design of larger functional proteins.
Case, James Brett and Chen, Rita E. and Cao, Longxing and Ying, Baoling and Winkler, Emma S. and Johnson, Max and Goreshnik, Inna and Pham, Minh N. and Shrihari, Swathi and Kafai, Natasha M. and Bailey, Adam L. and Xie, Xuping and Shi, Pei-Yong and Ravichandran, Rashmi and Carter, Lauren and Stewart, Lance and Baker, David and Diamond, Michael S.
Ultrapotent miniproteins targeting the SARS-CoV-2 receptor-binding domain protect against infection and disease Journal Article
In: Cell Host & Microbe, 2021.
@article{Case2021,
title = {Ultrapotent miniproteins targeting the SARS-CoV-2 receptor-binding domain protect against infection and disease},
author = {Case, James Brett
and Chen, Rita E.
and Cao, Longxing
and Ying, Baoling
and Winkler, Emma S.
and Johnson, Max
and Goreshnik, Inna
and Pham, Minh N.
and Shrihari, Swathi
and Kafai, Natasha M.
and Bailey, Adam L.
and Xie, Xuping
and Shi, Pei-Yong
and Ravichandran, Rashmi
and Carter, Lauren
and Stewart, Lance
and Baker, David
and Diamond, Michael S.},
url = {https://www.cell.com/cell-host-microbe/fulltext/S1931-3128(21)00286-9, Cell Host & Microbe
https://www.bakerlab.org/wp-content/uploads/2021/07/Case_etal_CellHostMicrobe_Ultrapotent-miniproteins-targeting-the-SARS-CoV-2-receptor-binding-domain-protect-against-infection-and-disease.pdf, Download PDF},
doi = {10.1016/j.chom.2021.06.008},
year = {2021},
date = {2021-06-18},
urldate = {2021-06-18},
journal = {Cell Host & Microbe},
abstract = {Despite the introduction of public health measures and spike protein-based vaccines to mitigate the COVID-19 pandemic, SARS-CoV-2 infections and deaths continue to have a global impact. Previously, we used a structural design approach to develop picomolar range miniproteins targeting the SARS-CoV-2 spike receptor binding domain. Here, we investigated the capacity of modified versions of one lead miniprotein, LCB1, to protect against SARS-CoV-2-mediated lung disease in mice. Systemic administration of LCB1-Fc reduced viral burden, diminished immune cell infiltration and inflammation, and completely prevented lung disease and pathology. A single intranasal dose of LCB1v1.3 reduced SARS-CoV-2 infection in the lung when given as many as five days before or two days after virus inoculation. Importantly, LCB1v1.3 protected in vivo against a historical strain (WA1/2020), an emerging B.1.1.7 strain, and a strain encoding key E484K and N501Y spike protein substitutions. These data support development of LCB1v1.3 for prevention or treatment of SARS-CoV-2 infection.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Despite the introduction of public health measures and spike protein-based vaccines to mitigate the COVID-19 pandemic, SARS-CoV-2 infections and deaths continue to have a global impact. Previously, we used a structural design approach to develop picomolar range miniproteins targeting the SARS-CoV-2 spike receptor binding domain. Here, we investigated the capacity of modified versions of one lead miniprotein, LCB1, to protect against SARS-CoV-2-mediated lung disease in mice. Systemic administration of LCB1-Fc reduced viral burden, diminished immune cell infiltration and inflammation, and completely prevented lung disease and pathology. A single intranasal dose of LCB1v1.3 reduced SARS-CoV-2 infection in the lung when given as many as five days before or two days after virus inoculation. Importantly, LCB1v1.3 protected in vivo against a historical strain (WA1/2020), an emerging B.1.1.7 strain, and a strain encoding key E484K and N501Y spike protein substitutions. These data support development of LCB1v1.3 for prevention or treatment of SARS-CoV-2 infection.
Bryan, Cassie M. and Rocklin, Gabriel J. and Bick, Matthew J. and Ford, Alex and Majri-Morrison, Sonia and Kroll, Ashley V. and Miller, Chad J. and Carter, Lauren and Goreshnik, Inna and Kang, Alex and DiMaio, Frank and Tarbell, Kristin V. and Baker, David
Computational design of a synthetic PD-1 agonist Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 29, 2021.
@article{Bryan2021,
title = {Computational design of a synthetic PD-1 agonist},
author = {Bryan, Cassie M.
and Rocklin, Gabriel J.
and Bick, Matthew J.
and Ford, Alex
and Majri-Morrison, Sonia
and Kroll, Ashley V.
and Miller, Chad J.
and Carter, Lauren
and Goreshnik, Inna
and Kang, Alex
and DiMaio, Frank
and Tarbell, Kristin V.
and Baker, David},
url = {https://www.pnas.org/content/118/29/e2102164118, PNAS
https://www.bakerlab.org/wp-content/uploads/2021/07/Bryan_etal_PNAS2021_DeNovo_PD1_agonist.pdf, Download PDF},
year = {2021},
date = {2021-06-11},
urldate = {2021-06-11},
journal = {Proceedings of the National Academy of Sciences},
volume = {118},
number = {29},
abstract = {Programmed cell death protein-1 (PD-1) expressed on activated T cells inhibits T cell function and proliferation to prevent an excessive immune response, and disease can result if this delicate balance is shifted in either direction. Tumor cells often take advantage of this pathway by overexpressing the PD-1 ligand PD-L1 to evade destruction by the immune system. Alternatively, if there is a decrease in function of the PD-1 pathway, unchecked activation of the immune system and autoimmunity can result. Using a combination of computation and experiment, we designed a hyperstable 40-residue miniprotein, PD-MP1, that specifically binds murine and human PD-1 at the PD-L1 interface with a Kd of ∼100 nM. The apo crystal structure shows that the binder folds as designed with a backbone RMSD of 1.3 Å to the design model. Trimerization of PD-MP1 resulted in a PD-1 agonist that strongly inhibits murine T cell activation. This small, hyperstable PD-1 binding protein was computationally designed with an all-beta interface, and the trimeric agonist could contribute to treatments for autoimmune and inflammatory diseases.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Programmed cell death protein-1 (PD-1) expressed on activated T cells inhibits T cell function and proliferation to prevent an excessive immune response, and disease can result if this delicate balance is shifted in either direction. Tumor cells often take advantage of this pathway by overexpressing the PD-1 ligand PD-L1 to evade destruction by the immune system. Alternatively, if there is a decrease in function of the PD-1 pathway, unchecked activation of the immune system and autoimmunity can result. Using a combination of computation and experiment, we designed a hyperstable 40-residue miniprotein, PD-MP1, that specifically binds murine and human PD-1 at the PD-L1 interface with a Kd of ∼100 nM. The apo crystal structure shows that the binder folds as designed with a backbone RMSD of 1.3 Å to the design model. Trimerization of PD-MP1 resulted in a PD-1 agonist that strongly inhibits murine T cell activation. This small, hyperstable PD-1 binding protein was computationally designed with an all-beta interface, and the trimeric agonist could contribute to treatments for autoimmune and inflammatory diseases.
Vulovic, Ivan, Yao, Qing, Park, Young-Jun, Courbet, Alexis, Norris, Andrew, Busch, Florian, Sahasrabuddhe, Aniruddha, Merten, Hannes, Sahtoe, Danny D., Ueda, George, Fallas, Jorge A., Weaver, Sara J., Hsia, Yang, Langan, Robert A., Pl"uckthun, Andreas, Wysocki, Vicki H., Veesler, David, Jensen, Grant J., Baker, David
Generation of ordered protein assemblies using rigid three-body fusion Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 23, 2021.
@article{Vulovic2021,
title = {Generation of ordered protein assemblies using rigid three-body fusion},
author = {Vulovic, Ivan and Yao, Qing and Park, Young-Jun and Courbet, Alexis and Norris, Andrew and Busch, Florian and Sahasrabuddhe, Aniruddha and Merten, Hannes and Sahtoe, Danny D. and Ueda, George and Fallas, Jorge A. and Weaver, Sara J. and Hsia, Yang and Langan, Robert A. and Pl{"u}ckthun, Andreas and Wysocki, Vicki H. and Veesler, David and Jensen, Grant J. and Baker, David},
url = {https://www.pnas.org/content/118/23/e2015037118, PNAS
},
doi = {10.1073/pnas.2015037118},
year = {2021},
date = {2021-06-08},
urldate = {2021-06-08},
journal = {Proceedings of the National Academy of Sciences},
volume = {118},
number = {23},
abstract = {Protein nanomaterial design is an emerging discipline with applications in medicine and beyond. A long-standing design approach uses genetic fusion to join protein homo-oligomer subunits via α-helical linkers to form more complex symmetric assemblies, but this method is hampered by linker flexibility and a dearth of geometric solutions. Here, we describe a general computational method for rigidly fusing homo-oligomer and spacer building blocks to generate user-defined architectures that generates far more geometric solutions than previous approaches. The fusion junctions are then optimized using Rosetta to minimize flexibility. We apply this method to design and test 92 dihedral symmetric protein assemblies using a set of designed homodimers and repeat protein building blocks. Experimental validation by native mass spectrometry, small-angle X-ray scattering, and negative-stain single-particle electron microscopy confirms the assembly states for 11 designs. Most of these assemblies are constructed from designed ankyrin repeat proteins (DARPins), held in place on one end by α-helical fusion and on the other by a designed homodimer interface, and we explored their use for cryogenic electron microscopy (cryo-EM) structure determination by incorporating DARPin variants selected to bind targets of interest. Although the target resolution was limited by preferred orientation effects and small scaffold size, we found that the dual anchoring strategy reduced the flexibility of the target-DARPIN complex with respect to the overall assembly, suggesting that multipoint anchoring of binding domains could contribute to cryo-EM structure determination of small proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein nanomaterial design is an emerging discipline with applications in medicine and beyond. A long-standing design approach uses genetic fusion to join protein homo-oligomer subunits via α-helical linkers to form more complex symmetric assemblies, but this method is hampered by linker flexibility and a dearth of geometric solutions. Here, we describe a general computational method for rigidly fusing homo-oligomer and spacer building blocks to generate user-defined architectures that generates far more geometric solutions than previous approaches. The fusion junctions are then optimized using Rosetta to minimize flexibility. We apply this method to design and test 92 dihedral symmetric protein assemblies using a set of designed homodimers and repeat protein building blocks. Experimental validation by native mass spectrometry, small-angle X-ray scattering, and negative-stain single-particle electron microscopy confirms the assembly states for 11 designs. Most of these assemblies are constructed from designed ankyrin repeat proteins (DARPins), held in place on one end by α-helical fusion and on the other by a designed homodimer interface, and we explored their use for cryogenic electron microscopy (cryo-EM) structure determination by incorporating DARPin variants selected to bind targets of interest. Although the target resolution was limited by preferred orientation effects and small scaffold size, we found that the dual anchoring strategy reduced the flexibility of the target-DARPIN complex with respect to the overall assembly, suggesting that multipoint anchoring of binding domains could contribute to cryo-EM structure determination of small proteins.
Hosseinzadeh, Parisa and Watson, Paris R. and Craven, Timothy W. and Li, Xinting and Rettie, Stephen and Pardo-Avila, Fátima and Bera, Asim K. and Mulligan, Vikram Khipple and Lu, Peilong and Ford, Alexander S. and Weitzner, Brian D. and Stewart, Lance J. and Moyer, Adam P. and Di Piazza, Maddalena and Whalen, Joshua G. and Greisen, Per Jr. and Christianson, David W. and Baker, David
Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites Journal Article
In: Nature Communications, 2021.
@article{Hosseinzadeh2021,
title = {Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites},
author = {Hosseinzadeh, Parisa
and Watson, Paris R.
and Craven, Timothy W.
and Li, Xinting
and Rettie, Stephen
and Pardo-Avila, Fátima
and Bera, Asim K.
and Mulligan, Vikram Khipple
and Lu, Peilong
and Ford, Alexander S.
and Weitzner, Brian D.
and Stewart, Lance J.
and Moyer, Adam P.
and Di Piazza, Maddalena
and Whalen, Joshua G.
and Greisen, Per Jr.
and Christianson, David W.
and Baker, David},
url = {https://www.nature.com/articles/s41467-021-23609-8, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2021/06/Hosseinzadeh_etal_NatureComms2021_AnchorExtention.pdf, Download PDF},
doi = {10.1038/s41467-021-23609-8},
year = {2021},
date = {2021-06-07},
urldate = {2021-06-07},
journal = {Nature Communications},
abstract = {Despite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational “anchor extension” methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC50 values of 9.1 and 4.4 nM for the best binders compared to 5.4 and 0.6 µM for the anchor, respectively). The HDAC6 inhibitor is among the most potent reported so far. These results highlight the potential for de novo design of high-affinity protein-peptide interfaces, as well as the challenges that remain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Despite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational “anchor extension” methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC50 values of 9.1 and 4.4 nM for the best binders compared to 5.4 and 0.6 µM for the anchor, respectively). The HDAC6 inhibitor is among the most potent reported so far. These results highlight the potential for de novo design of high-affinity protein-peptide interfaces, as well as the challenges that remain.
Sahtoe, Danny D., Coscia, Adrian, Mustafaoglu, Nur, Miller, Lauren M., Olal, Daniel, Vulovic, Ivan, Yu, Ta-Yi, Goreshnik, Inna, Lin, Yu-Ru, Clark, Lars, Busch, Florian, Stewart, Lance, Wysocki, Vicki H., Ingber, Donald E., Abraham, Jonathan, Baker, David
Transferrin receptor targeting by de novo sheet extension Journal Article
In: Proceedings of the National Academy of Sciences, 2021.
@article{Sahtoe2021,
title = {Transferrin receptor targeting by de novo sheet extension},
author = {Sahtoe, Danny D. and Coscia, Adrian and Mustafaoglu, Nur and Miller, Lauren M. and Olal, Daniel and Vulovic, Ivan and Yu, Ta-Yi and Goreshnik, Inna and Lin, Yu-Ru and Clark, Lars and Busch, Florian and Stewart, Lance and Wysocki, Vicki H. and Ingber, Donald E. and Abraham, Jonathan and Baker, David},
url = {https://www.pnas.org/content/118/17/e2021569118, PNAS
},
doi = {10.1073/pnas.2021569118},
year = {2021},
date = {2021-04-27},
urldate = {2021-04-27},
journal = {Proceedings of the National Academy of Sciences},
abstract = {The de novo design of proteins that bind natural target proteins is useful for a variety of biomedical and biotechnological applications. We describe a design strategy to target proteins containing an exposed beta edge strand. We use the approach to design binders to the human transferrin receptor which shuttles back and forth across the blood{textendash}brain barrier. Such binders could be useful for the delivery of therapeutics into the brain.The de novo design of polar protein{textendash}protein interactions is challenging because of the thermodynamic cost of stripping water away from the polar groups. Here, we describe a general approach for designing proteins which complement exposed polar backbone groups at the edge of beta sheets with geometrically matched beta strands. We used this approach to computationally design small proteins that bind to an exposed beta sheet on the human transferrin receptor (hTfR), which shuttles interacting proteins across the blood{textendash}brain barrier (BBB), opening up avenues for drug delivery into the brain. We describe a design which binds hTfR with a 20 nM Kd, is hyperstable, and crosses an in vitro microfluidic organ-on-a-chip model of the human BBB. Our design approach provides a general strategy for creating binders to protein targets with exposed surface beta edge strands.Crystal structures have been deposited in the RCSB PDB with the accession nos. 6WRX, 6WRW, and 6WRV. Additional supporting data has been deposited in the online Zenodo repository (https://zenodo.org/record/4594115) (47). All other study data are included in the article and/or supporting information.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The de novo design of proteins that bind natural target proteins is useful for a variety of biomedical and biotechnological applications. We describe a design strategy to target proteins containing an exposed beta edge strand. We use the approach to design binders to the human transferrin receptor which shuttles back and forth across the blood{textendash}brain barrier. Such binders could be useful for the delivery of therapeutics into the brain.The de novo design of polar protein{textendash}protein interactions is challenging because of the thermodynamic cost of stripping water away from the polar groups. Here, we describe a general approach for designing proteins which complement exposed polar backbone groups at the edge of beta sheets with geometrically matched beta strands. We used this approach to computationally design small proteins that bind to an exposed beta sheet on the human transferrin receptor (hTfR), which shuttles interacting proteins across the blood{textendash}brain barrier (BBB), opening up avenues for drug delivery into the brain. We describe a design which binds hTfR with a 20 nM Kd, is hyperstable, and crosses an in vitro microfluidic organ-on-a-chip model of the human BBB. Our design approach provides a general strategy for creating binders to protein targets with exposed surface beta edge strands.Crystal structures have been deposited in the RCSB PDB with the accession nos. 6WRX, 6WRW, and 6WRV. Additional supporting data has been deposited in the online Zenodo repository (https://zenodo.org/record/4594115) (47). All other study data are included in the article and/or supporting information.
Hsia, Yang and Mout, Rubul and Sheffler, William and Edman, Natasha I. and Vulovic, Ivan and Park, Young-Jun and Redler, Rachel L. and Bick, Matthew J. and Bera, Asim K. and Courbet, Alexis and Kang, Alex and Brunette, T. J. and Nattermann, Una and Tsai, Evelyn and Saleem, Ayesha and Chow, Cameron M. and Ekiert, Damian and Bhabha, Gira and Veesler, David and Baker, David
Design of multi-scale protein complexes by hierarchical building block fusion Journal Article
In: Nature Communications, 2021.
@article{Hsia2012,
title = {Design of multi-scale protein complexes by hierarchical building block fusion},
author = {Hsia, Yang
and Mout, Rubul
and Sheffler, William
and Edman, Natasha I.
and Vulovic, Ivan
and Park, Young-Jun
and Redler, Rachel L.
and Bick, Matthew J.
and Bera, Asim K.
and Courbet, Alexis
and Kang, Alex
and Brunette, T. J.
and Nattermann, Una
and Tsai, Evelyn
and Saleem, Ayesha
and Chow, Cameron M.
and Ekiert, Damian
and Bhabha, Gira
and Veesler, David
and Baker, David},
url = {https://www.nature.com/articles/s41467-021-22276-z, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2021/04/Hsia_etal_NatComms_WORMS.pdf, Download PDF},
doi = {10.1038/s41467-021-22276-z},
year = {2021},
date = {2021-04-16},
urldate = {2021-04-16},
journal = {Nature Communications},
abstract = {A systematic and robust approach to generating complex protein nanomaterials would have broad utility. We develop a hierarchical approach to designing multi-component protein assemblies from two classes of modular building blocks: designed helical repeat proteins (DHRs) and helical bundle oligomers (HBs). We first rigidly fuse DHRs to HBs to generate a large library of oligomeric building blocks. We then generate assemblies with cyclic, dihedral, and point group symmetries from these building blocks using architecture guided rigid helical fusion with new software named WORMS. X-ray crystallography and cryo-electron microscopy characterization show that the hierarchical design approach can accurately generate a wide range of assemblies, including a 43 nm diameter icosahedral nanocage. The computational methods and building block sets described here provide a very general route to de novo designed protein nanomaterials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A systematic and robust approach to generating complex protein nanomaterials would have broad utility. We develop a hierarchical approach to designing multi-component protein assemblies from two classes of modular building blocks: designed helical repeat proteins (DHRs) and helical bundle oligomers (HBs). We first rigidly fuse DHRs to HBs to generate a large library of oligomeric building blocks. We then generate assemblies with cyclic, dihedral, and point group symmetries from these building blocks using architecture guided rigid helical fusion with new software named WORMS. X-ray crystallography and cryo-electron microscopy characterization show that the hierarchical design approach can accurately generate a wide range of assemblies, including a 43 nm diameter icosahedral nanocage. The computational methods and building block sets described here provide a very general route to de novo designed protein nanomaterials.
Divine, Robby, Dang, Ha V., Ueda, George, Fallas, Jorge A., Vulovic, Ivan, Sheffler, William, Saini, Shally, Zhao, Yan Ting, Raj, Infencia Xavier, Morawski, Peter A., Jennewein, Madeleine F., Homad, Leah J., Wan, Yu-Hsin, Tooley, Marti R., Seeger, Franziska, Etemadi, Ali, Fahning, Mitchell L., Lazarovits, James, Roederer, Alex, Walls, Alexandra C., Stewart, Lance, Mazloomi, Mohammadali, King, Neil P., Campbell, Daniel J., McGuire, Andrew T., Stamatatos, Leonidas, Ruohola-Baker, Hannele, Mathieu, Julie, Veesler, David, Baker, David
Designed proteins assemble antibodies into modular nanocages Journal Article
In: Science, vol. 372, no. 6537, 2021.
@article{Divine2021,
title = {Designed proteins assemble antibodies into modular nanocages},
author = {Divine, Robby and Dang, Ha V. and Ueda, George and Fallas, Jorge A. and Vulovic, Ivan and Sheffler, William and Saini, Shally and Zhao, Yan Ting and Raj, Infencia Xavier and Morawski, Peter A. and Jennewein, Madeleine F. and Homad, Leah J. and Wan, Yu-Hsin and Tooley, Marti R. and Seeger, Franziska and Etemadi, Ali and Fahning, Mitchell L. and Lazarovits, James and Roederer, Alex and Walls, Alexandra C. and Stewart, Lance and Mazloomi, Mohammadali and King, Neil P. and Campbell, Daniel J. and McGuire, Andrew T. and Stamatatos, Leonidas and Ruohola-Baker, Hannele and Mathieu, Julie and Veesler, David and Baker, David},
url = {https://science.sciencemag.org/content/372/6537/eabd9994.full.pdf, Science
https://www.bakerlab.org/wp-content/uploads/2021/04/Divine_etal_Science2021_Antibody_nanocages.pdf, Download PDF},
doi = {10.1126/science.abd9994},
year = {2021},
date = {2021-04-02},
urldate = {2021-04-02},
journal = {Science},
volume = {372},
number = {6537},
abstract = {Antibodies are broadly used in therapies and as research tools because they can be generated against a wide range of targets. Efficacy can often be increased by clustering antibodies in multivalent assemblies. Divine et al. designed antibody nanocages from two components: One is an antibody-binding homo-oligomic protein and the other is the antibody itself. Computationally designed proteins drive the assembly of antibody nanocages in a range of architectures, allowing control of the symmetry and the antibody valency. The multivalent display enhances antibody-dependent signaling, and nanocages displaying antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein effectively neutralize pseudovirus.Science, this issue p. eabd9994INTRODUCTIONAntibodies that bind tightly to targets of interest play central roles in biological research and medicine. Clusters of antibodies, typically generated by fusing antibodies to polymers or genetically linking antibody fragments together, can enhance signaling. Currently lacking are approaches for making antibody assemblies with a range of precisely specified architectures and valencies.RATIONALEWe set out to computationally design proteins that assemble antibodies into precise architectures with different valencies and symmetries. We developed an approach to designing proteins that position antibodies or Fc-fusions on the twofold symmetry axes of regular dihedral and polyhedral architectures. We hypothesized that such designs could robustly drive arbitrary antibodies into homogeneous and structurally well-defined nanocages and that such assemblies could have pronounced effects on cell signaling.RESULTSAntibody cage (AbC){textendash}forming designs were created by rigidly fusing antibody constant domain{textendash}binding modules to cyclic oligomers through helical spacer domains such that the symmetry axes of the dimeric antibody and cyclic oligomer are at orientations that generate different dihedral or polyhedral (e.g., tetrahedral, octahedral, or icosahedral) architectures. The junction regions between the connected building blocks were optimized to fold to the designed structures. Synthetic genes encoding the designs were expressed in bacterial cultures; of 48 structurally characterized designs, eight assemblies matched the design models. Successful designs encompass D2 dihedral (three designs), T32 tetrahedral (two designs), O42 octahedral (one design), and I52 icosahedral (two designs) architectures; these contain 2, 6, 12, or 30 antibodies, respectively.We investigated the effects of AbCs on cell signaling. AbCs formed with a death receptor{textendash}targeting antibody induced apoptosis of tumor cell lines that were unaffected by the soluble antibody or the native ligand. Angiopoietin pathway signaling, CD40 signaling, and T cell proliferation were all enhanced by assembling Fc-fusions or antibodies in AbCs. AbC formation also enhanced in vitro viral neutralization of a severe acute respiratory syndrome coronavirus 2 pseudovirus.CONCLUSIONWe have designed multiple antibody cage{textendash}forming proteins that precisely cluster any protein A{textendash}binding antibody into nanocages with controlled valency and geometry. AbCs can be formed with 2, 6, 12, or 30 antibodies simply by mixing the antibody with the corresponding designed protein, without the need for any covalent modification of the antibody. Incorporating receptor binding or virus-neutralizing antibodies into AbCs enhanced their biological activity across a range of cell systems. We expect that our rapid and robust approach for assembling antibodies into homogeneous and ordered nanocages without the need for covalent modification will have broad utility in research and medicine.Designed proteins assemble antibodies into large symmetric architectures.Designed antibody-clustering proteins (light gray) assemble antibodies (purple) into diverse nanocage architectures (top). Antibody nanocages enhance cell signaling compared with free antibodies (bottom).IMAGE: IAN HAYDON, INSTITUTE FOR PROTEIN DESIGNMultivalent display of receptor-engaging antibodies or ligands can enhance their activity. Instead of achieving multivalency by attachment to preexisting scaffolds, here we unite form and function by the computational design of nanocages in which one structural component is an antibody or Fc-ligand fusion and the second is a designed antibody-binding homo-oligomer that drives nanocage assembly. Structures of eight nanocages determined by electron microscopy spanning dihedral, tetrahedral, octahedral, and icosahedral architectures with 2, 6, 12, and 30 antibodies per nanocage, respectively, closely match the corresponding computational models. Antibody nanocages targeting cell surface receptors enhance signaling compared with free antibodies or Fc-fusions in death receptor 5 (DR5){textendash}mediated apoptosis, angiopoietin-1 receptor (Tie2){textendash}mediated angiogenesis, CD40 activation, and T cell proliferation. Nanocage assembly also increases severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pseudovirus neutralization by α-SARS-CoV-2 monoclonal antibodies and Fc{textendash}angiotensin-converting enzyme 2 (ACE2) fusion proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Antibodies are broadly used in therapies and as research tools because they can be generated against a wide range of targets. Efficacy can often be increased by clustering antibodies in multivalent assemblies. Divine et al. designed antibody nanocages from two components: One is an antibody-binding homo-oligomic protein and the other is the antibody itself. Computationally designed proteins drive the assembly of antibody nanocages in a range of architectures, allowing control of the symmetry and the antibody valency. The multivalent display enhances antibody-dependent signaling, and nanocages displaying antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein effectively neutralize pseudovirus.Science, this issue p. eabd9994INTRODUCTIONAntibodies that bind tightly to targets of interest play central roles in biological research and medicine. Clusters of antibodies, typically generated by fusing antibodies to polymers or genetically linking antibody fragments together, can enhance signaling. Currently lacking are approaches for making antibody assemblies with a range of precisely specified architectures and valencies.RATIONALEWe set out to computationally design proteins that assemble antibodies into precise architectures with different valencies and symmetries. We developed an approach to designing proteins that position antibodies or Fc-fusions on the twofold symmetry axes of regular dihedral and polyhedral architectures. We hypothesized that such designs could robustly drive arbitrary antibodies into homogeneous and structurally well-defined nanocages and that such assemblies could have pronounced effects on cell signaling.RESULTSAntibody cage (AbC){textendash}forming designs were created by rigidly fusing antibody constant domain{textendash}binding modules to cyclic oligomers through helical spacer domains such that the symmetry axes of the dimeric antibody and cyclic oligomer are at orientations that generate different dihedral or polyhedral (e.g., tetrahedral, octahedral, or icosahedral) architectures. The junction regions between the connected building blocks were optimized to fold to the designed structures. Synthetic genes encoding the designs were expressed in bacterial cultures; of 48 structurally characterized designs, eight assemblies matched the design models. Successful designs encompass D2 dihedral (three designs), T32 tetrahedral (two designs), O42 octahedral (one design), and I52 icosahedral (two designs) architectures; these contain 2, 6, 12, or 30 antibodies, respectively.We investigated the effects of AbCs on cell signaling. AbCs formed with a death receptor{textendash}targeting antibody induced apoptosis of tumor cell lines that were unaffected by the soluble antibody or the native ligand. Angiopoietin pathway signaling, CD40 signaling, and T cell proliferation were all enhanced by assembling Fc-fusions or antibodies in AbCs. AbC formation also enhanced in vitro viral neutralization of a severe acute respiratory syndrome coronavirus 2 pseudovirus.CONCLUSIONWe have designed multiple antibody cage{textendash}forming proteins that precisely cluster any protein A{textendash}binding antibody into nanocages with controlled valency and geometry. AbCs can be formed with 2, 6, 12, or 30 antibodies simply by mixing the antibody with the corresponding designed protein, without the need for any covalent modification of the antibody. Incorporating receptor binding or virus-neutralizing antibodies into AbCs enhanced their biological activity across a range of cell systems. We expect that our rapid and robust approach for assembling antibodies into homogeneous and ordered nanocages without the need for covalent modification will have broad utility in research and medicine.Designed proteins assemble antibodies into large symmetric architectures.Designed antibody-clustering proteins (light gray) assemble antibodies (purple) into diverse nanocage architectures (top). Antibody nanocages enhance cell signaling compared with free antibodies (bottom).IMAGE: IAN HAYDON, INSTITUTE FOR PROTEIN DESIGNMultivalent display of receptor-engaging antibodies or ligands can enhance their activity. Instead of achieving multivalency by attachment to preexisting scaffolds, here we unite form and function by the computational design of nanocages in which one structural component is an antibody or Fc-ligand fusion and the second is a designed antibody-binding homo-oligomer that drives nanocage assembly. Structures of eight nanocages determined by electron microscopy spanning dihedral, tetrahedral, octahedral, and icosahedral architectures with 2, 6, 12, and 30 antibodies per nanocage, respectively, closely match the corresponding computational models. Antibody nanocages targeting cell surface receptors enhance signaling compared with free antibodies or Fc-fusions in death receptor 5 (DR5){textendash}mediated apoptosis, angiopoietin-1 receptor (Tie2){textendash}mediated angiogenesis, CD40 activation, and T cell proliferation. Nanocage assembly also increases severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pseudovirus neutralization by α-SARS-CoV-2 monoclonal antibodies and Fc{textendash}angiotensin-converting enzyme 2 (ACE2) fusion proteins.
Mulligan, Vikram Khipple, Workman, Sean, Sun, Tianjun, Rettie, Stephen, Li, Xinting, Worrall, Liam J., Craven, Timothy W., King, Dustin T., Hosseinzadeh, Parisa, Watkins, Andrew M., Renfrew, P. Douglas, Guffy, Sharon, Labonte, Jason W., Moretti, Rocco, Bonneau, Richard, Strynadka, Natalie C. J., Baker, David
Computationally designed peptide macrocycle inhibitors of New Delhi metallo-β-lactamase 1 Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 12, 2021.
@article{Mulligan2021,
title = {Computationally designed peptide macrocycle inhibitors of New Delhi metallo-β-lactamase 1},
author = {Mulligan, Vikram Khipple and Workman, Sean and Sun, Tianjun and Rettie, Stephen and Li, Xinting and Worrall, Liam J. and Craven, Timothy W. and King, Dustin T. and Hosseinzadeh, Parisa and Watkins, Andrew M. and Renfrew, P. Douglas and Guffy, Sharon and Labonte, Jason W. and Moretti, Rocco and Bonneau, Richard and Strynadka, Natalie C. J. and Baker, David},
url = {https://www.pnas.org/content/118/12/e2012800118.full, PNAS
https://www.bakerlab.org/wp-content/uploads/2021/03/Mulligen_etal_PNAS2021_Macrocycle_inhibitors.pdf, Download PDF},
doi = {10.1073/pnas.2012800118},
year = {2021},
date = {2021-03-23},
urldate = {2021-03-23},
journal = {Proceedings of the National Academy of Sciences},
volume = {118},
number = {12},
abstract = {The rise of antibiotic resistance calls for new therapeutics targeting resistance factors such as the New Delhi metallo-β-lactamase 1 (NDM-1), a bacterial enzyme that degrades β-lactam antibiotics. We present structure-guided computational methods for designing peptide macrocycles built from mixtures of L- and D-amino acids that are able to bind to and inhibit targets of therapeutic interest. Our methods explicitly consider the propensity of a peptide to favor a binding-competent conformation, which we found to predict rank order of experimentally observed IC50 values across seven designed NDM-1- inhibiting peptides. We were able to determine X-ray crystal structures of three of the designed inhibitors in complex with NDM-1, and in all three the conformation of the peptide is very close to the computationally designed model. In two of the three structures, the binding mode with NDM-1 is also very similar to the design model, while in the third, we observed an alternative binding mode likely arising from internal symmetry in the shape of the design combined with flexibility of the target. Although challenges remain in robustly predicting target backbone changes, binding mode, and the effects of mutations on binding affinity, our methods for designing ordered, binding-competent macrocycles should have broad applicability to a wide range of therapeutic targets.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The rise of antibiotic resistance calls for new therapeutics targeting resistance factors such as the New Delhi metallo-β-lactamase 1 (NDM-1), a bacterial enzyme that degrades β-lactam antibiotics. We present structure-guided computational methods for designing peptide macrocycles built from mixtures of L- and D-amino acids that are able to bind to and inhibit targets of therapeutic interest. Our methods explicitly consider the propensity of a peptide to favor a binding-competent conformation, which we found to predict rank order of experimentally observed IC50 values across seven designed NDM-1- inhibiting peptides. We were able to determine X-ray crystal structures of three of the designed inhibitors in complex with NDM-1, and in all three the conformation of the peptide is very close to the computationally designed model. In two of the three structures, the binding mode with NDM-1 is also very similar to the design model, while in the third, we observed an alternative binding mode likely arising from internal symmetry in the shape of the design combined with flexibility of the target. Although challenges remain in robustly predicting target backbone changes, binding mode, and the effects of mutations on binding affinity, our methods for designing ordered, binding-competent macrocycles should have broad applicability to a wide range of therapeutic targets.
Norn, Christoffer, Wicky, Basile I. M., Juergens, David, Liu, Sirui, Kim, David, Tischer, Doug, Koepnick, Brian, Anishchenko, Ivan, Baker, David, Ovchinnikov, Sergey
Protein sequence design by conformational landscape optimization Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 11, 2021.
@article{Norn2021,
title = {Protein sequence design by conformational landscape optimization},
author = {Norn, Christoffer and Wicky, Basile I. M. and Juergens, David and Liu, Sirui and Kim, David and Tischer, Doug and Koepnick, Brian and Anishchenko, Ivan and Baker, David and Ovchinnikov, Sergey},
url = {https://www.pnas.org/content/118/11/e2017228118, PNAS
https://www.bakerlab.org/wp-content/uploads/2021/03/Norn_etal_PNAS2021_LandscapeOptimization.pdf, Download PDF},
doi = {10.1073/pnas.2017228118},
year = {2021},
date = {2021-03-16},
urldate = {2021-03-16},
journal = {Proceedings of the National Academy of Sciences},
volume = {118},
number = {11},
abstract = {Almost all proteins fold to their lowest free energy state, which is determined by their amino acid sequence. Computational protein design has primarily focused on finding sequences that have very low energy in the target designed structure. However, what is most relevant during folding is not the absolute energy of the folded state but the energy difference between the folded state and the lowest-lying alternative states. We describe a deep learning approach that captures aspects of the folding landscape, in particular the presence of structures in alternative energy minima, and show that it can enhance current protein design methods.The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen{textquoteright}s thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowest energy state. As this calculation involves not only all possible amino acid sequences but also, all possible structures, most current approaches focus instead on the more tractable problem of finding the lowest-energy amino acid sequence for the desired structure, often checking by protein structure prediction in a second step that the desired structure is indeed the lowest-energy conformation for the designed sequence, and typically discarding a large fraction of designed sequences for which this is not the case. Here, we show that by backpropagating gradients through the transform-restrained Rosetta (trRosetta) structure prediction network from the desired structure to the input amino acid sequence, we can directly optimize over all possible amino acid sequences and all possible structures in a single calculation. We find that trRosetta calculations, which consider the full conformational landscape, can be more effective than Rosetta single-point energy estimations in predicting folding and stability of de novo designed proteins. We compare sequence design by conformational landscape optimization with the standard energy-based sequence design methodology in Rosetta and show that the former can result in energy landscapes with fewer alternative energy minima. We show further that more funneled energy landscapes can be designed by combining the strengths of the two approaches: the low-resolution trRosetta model serves to disfavor alternative states, and the high-resolution Rosetta model serves to create a deep energy minimum at the design target structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Almost all proteins fold to their lowest free energy state, which is determined by their amino acid sequence. Computational protein design has primarily focused on finding sequences that have very low energy in the target designed structure. However, what is most relevant during folding is not the absolute energy of the folded state but the energy difference between the folded state and the lowest-lying alternative states. We describe a deep learning approach that captures aspects of the folding landscape, in particular the presence of structures in alternative energy minima, and show that it can enhance current protein design methods.The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen{textquoteright}s thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowest energy state. As this calculation involves not only all possible amino acid sequences but also, all possible structures, most current approaches focus instead on the more tractable problem of finding the lowest-energy amino acid sequence for the desired structure, often checking by protein structure prediction in a second step that the desired structure is indeed the lowest-energy conformation for the designed sequence, and typically discarding a large fraction of designed sequences for which this is not the case. Here, we show that by backpropagating gradients through the transform-restrained Rosetta (trRosetta) structure prediction network from the desired structure to the input amino acid sequence, we can directly optimize over all possible amino acid sequences and all possible structures in a single calculation. We find that trRosetta calculations, which consider the full conformational landscape, can be more effective than Rosetta single-point energy estimations in predicting folding and stability of de novo designed proteins. We compare sequence design by conformational landscape optimization with the standard energy-based sequence design methodology in Rosetta and show that the former can result in energy landscapes with fewer alternative energy minima. We show further that more funneled energy landscapes can be designed by combining the strengths of the two approaches: the low-resolution trRosetta model serves to disfavor alternative states, and the high-resolution Rosetta model serves to create a deep energy minimum at the design target structure.
Coventry B, Baker D
Protein sequence optimization with a pairwise decomposable penalty for buried unsatisfied hydrogen bonds Journal Article
In: PLoS Computational Biology, 2021.
@article{Coventry2021,
title = {Protein sequence optimization with a pairwise decomposable penalty for buried unsatisfied hydrogen bonds},
author = {Coventry B and Baker D},
url = {https://doi.org/10.1371/journal.pcbi.1008061, PLoS Computational Biology
https://www.bakerlab.org/wp-content/uploads/2021/03/journal.pcbi_.1008061.pdf, Download PDF},
year = {2021},
date = {2021-03-08},
urldate = {2021-03-08},
journal = {PLoS Computational Biology},
abstract = {In aqueous solution, polar groups make hydrogen bonds with water, and hence burial of such groups in the interior of a protein is unfavorable unless the loss of hydrogen bonds with water is compensated by formation of new ones with other protein groups. For this reason, buried “unsatisfied” polar groups making no hydrogen bonds are very rare in proteins. Efficiently representing the energetic cost of unsatisfied hydrogen bonds with a pairwise-decomposable energy term during protein design is challenging since whether or not a group is satisfied depends on all of its neighbors. Here we describe a method for assigning a pairwise-decomposable energy to sidechain rotamers such that following combinatorial sidechain packing, buried unsaturated polar atoms are penalized. The penalty can be any quadratic function of the number of unsatisfied polar groups, and can be computed very rapidly. We show that inclusion of this term in Rosetta sidechain packing calculations substantially reduces the number of buried unsatisfied polar groups.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In aqueous solution, polar groups make hydrogen bonds with water, and hence burial of such groups in the interior of a protein is unfavorable unless the loss of hydrogen bonds with water is compensated by formation of new ones with other protein groups. For this reason, buried “unsatisfied” polar groups making no hydrogen bonds are very rare in proteins. Efficiently representing the energetic cost of unsatisfied hydrogen bonds with a pairwise-decomposable energy term during protein design is challenging since whether or not a group is satisfied depends on all of its neighbors. Here we describe a method for assigning a pairwise-decomposable energy to sidechain rotamers such that following combinatorial sidechain packing, buried unsaturated polar atoms are penalized. The penalty can be any quadratic function of the number of unsatisfied polar groups, and can be computed very rapidly. We show that inclusion of this term in Rosetta sidechain packing calculations substantially reduces the number of buried unsatisfied polar groups.
Vorobieva, Anastassia A., White, Paul, Liang, Binyong, Horne, Jim E., Bera, Asim K., Chow, Cameron M., Gerben, Stacey, Marx, Sinduja, Kang, Alex, Stiving, Alyssa Q., Harvey, Sophie R., Marx, Dagan C., Khan, G. Nasir, Fleming, Karen G., Wysocki, Vicki H., Brockwell, David J., Tamm, Lukas K., Radford, Sheena E., Baker, David
De novo design of transmembrane beta barrels Journal Article
In: Science, vol. 371, no. 6531, 2021.
@article{Vorobieva2021,
title = {De novo design of transmembrane beta barrels},
author = {Vorobieva, Anastassia A. and White, Paul and Liang, Binyong and Horne, Jim E. and Bera, Asim K. and Chow, Cameron M. and Gerben, Stacey and Marx, Sinduja and Kang, Alex and Stiving, Alyssa Q. and Harvey, Sophie R. and Marx, Dagan C. and Khan, G. Nasir and Fleming, Karen G. and Wysocki, Vicki H. and Brockwell, David J. and Tamm, Lukas K. and Radford, Sheena E. and Baker, David},
url = {https://science.sciencemag.org/content/371/6531/eabc8182, Science
https://www.bakerlab.org/wp-content/uploads/2021/02/Vorobieva_etal_Science2021_De_Novo_Transmembrane_beta_barrels.pdf, Download PDF},
doi = {10.1126/science.abc8182},
year = {2021},
date = {2021-02-19},
urldate = {2021-02-19},
journal = {Science},
volume = {371},
number = {6531},
abstract = {Computational design offers the possibility of making proteins with customized structures and functions. The range of accessible protein scaffolds has expanded with the design of increasingly complex cytoplasmic proteins and, recently, helical membrane proteins. Vorobieva et al. describe the successful computational design of eight-stranded transmembrane β-barrel proteins (TMBs). Using an iterative approach, they show the importance of negative design to prevent off-target structures and gain insight into the sequence determinants of TMB folding. Twenty-three designs satisfied biochemical screens for a TMB structure, and two structures were experimentally validated by nuclear magnetic resonance spectroscopy or x-ray crystallography. This is a step toward the custom design of pores for applications such as single-molecule sequencing.Science, this issue p. eabc8182INTRODUCTIONDespite their key biological roles, only a few proteins that fold into lipid membranes have been designed de novo. A class of membrane proteins{textemdash}transmembrane β barrels (TMBs){textemdash}forms a continuous sheet that closes on itself in lipid membranes. In addition to the challenge of designing β-sheet proteins, which are prone to misfolding and aggregation if folding is not properly controlled, the computational design of TMBs is complicated by limited understanding of TMB folding. As a result, no TMB has been designed de novo to date.Although the folding of TMBs in vivo is catalyzed by the β-barrel assembly machinery (BAM), many TMBs can also fold spontaneously in synthetic membranes to form stable pores, making them attractive for biotechnology and single-molecule analytical applications. Hence, de novo design of TMBs has potential both for understanding the determinants of TMB folding and membrane insertion and for the custom engineering of TMB nanopores.RATIONALEWe used de novo protein design to distill key principles of TMB folding through several design-build-test cycles. We iterated between hypothesis formulation, its implementation into computational design methods, and experimental characterization of the resulting proteins. To focus on the fundamental principles of TMB folding in the absence of complications due to interactions with chaperones and BAM in vivo, we focused on the challenge of de novo design of eight-stranded TMBs, which can fold and assemble into synthetic lipid membranes.RESULTSWe used a combination of purely geometric models and explicit Rosetta protein structure simulations to determine the constraints that β-strand connectivity and membrane embedding place on the TMB architecture. Through a series of design-build-test cycles, we found that, unlike almost all other classes of proteins, locally destabilizing sequences are critical for expression and folding of TMBs, and that the β-turns that translocate through the bilayer during folding have to be destabilized to enable correct assembly in the membrane. Our results suggest that premature formation of β hairpins may result in off-target β-sheet structures that compete with proper membrane insertion and folding, and hence the β hairpins of TMBs must be designed such that they are only transiently formed prior to membrane insertion, when the protein is in an aqueous environment. In the hydrophobic environment of the lipid bilayer, the full TMB can assemble because the membrane-facing nonpolar residues, which would tend to cluster nonspecifically in an aqueous environment, instead make favorable interactions with the lipids. As the TMB assembles, the β hairpins are stabilized by interactions with the neighboring β strands.Using computational methods that incorporate the above insights, we designed TMB sequences that successfully fold and assemble into both detergent micelles and lipid bilayers. Two of the designs were highly stable and could fold into liposomes more rapidly and reversibly than the transmembrane domain of the model outer membrane protein A (tOmpA) of Escherichia coli. A nuclear magnetic resonance solution structure and a high-resolution crystal structure for two different designs closely match the design models, showing that the TMB design method developed here can generate new structures with atomic-level accuracy.CONCLUSIONThis study elucidates key principles for de novo design of transmembrane β barrels, ranging from constraints on β-barrel architecture and β-hairpin design, as well as local and global sequence features. Our designs provide starting points for the bottom-up elucidation of the molecular mechanisms underlying TMB folding and interactions with the cellular outer membrane folding and insertion machinery. More generally, our work demonstrates that TMBs can be designed with atomic-level accuracy and opens the door to custom design of nanopores tailored for applications such as single-molecule sensing and sequencing.De novo{textendash}designed eight-stranded transmembrane β barrels fold spontaneously and reversibly into synthetic lipid membranes.The illustration shows the crystal structure of the protein TMB2.17 designed in this study, which adopts a structure identical to the design model.Credit: Ian Haydon.Transmembrane β-barrel proteins (TMBs) are of great interest for single-molecule analytical technologies because they can spontaneously fold and insert into membranes and form stable pores, but the range of pore properties that can be achieved by repurposing natural TMBs is limited. We leverage the power of de novo computational design coupled with a {textquotedblleft}hypothesis, design, and test{textquotedblright} approach to determine TMB design principles, notably, the importance of negative design to slow β-sheet assembly. We design new eight-stranded TMBs, with no homology to known TMBs, that insert and fold reversibly into synthetic lipid membranes and have nuclear magnetic resonance and x-ray crystal structures very similar to the computational models. These advances should enable the custom design of pores for a wide range of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational design offers the possibility of making proteins with customized structures and functions. The range of accessible protein scaffolds has expanded with the design of increasingly complex cytoplasmic proteins and, recently, helical membrane proteins. Vorobieva et al. describe the successful computational design of eight-stranded transmembrane β-barrel proteins (TMBs). Using an iterative approach, they show the importance of negative design to prevent off-target structures and gain insight into the sequence determinants of TMB folding. Twenty-three designs satisfied biochemical screens for a TMB structure, and two structures were experimentally validated by nuclear magnetic resonance spectroscopy or x-ray crystallography. This is a step toward the custom design of pores for applications such as single-molecule sequencing.Science, this issue p. eabc8182INTRODUCTIONDespite their key biological roles, only a few proteins that fold into lipid membranes have been designed de novo. A class of membrane proteins{textemdash}transmembrane β barrels (TMBs){textemdash}forms a continuous sheet that closes on itself in lipid membranes. In addition to the challenge of designing β-sheet proteins, which are prone to misfolding and aggregation if folding is not properly controlled, the computational design of TMBs is complicated by limited understanding of TMB folding. As a result, no TMB has been designed de novo to date.Although the folding of TMBs in vivo is catalyzed by the β-barrel assembly machinery (BAM), many TMBs can also fold spontaneously in synthetic membranes to form stable pores, making them attractive for biotechnology and single-molecule analytical applications. Hence, de novo design of TMBs has potential both for understanding the determinants of TMB folding and membrane insertion and for the custom engineering of TMB nanopores.RATIONALEWe used de novo protein design to distill key principles of TMB folding through several design-build-test cycles. We iterated between hypothesis formulation, its implementation into computational design methods, and experimental characterization of the resulting proteins. To focus on the fundamental principles of TMB folding in the absence of complications due to interactions with chaperones and BAM in vivo, we focused on the challenge of de novo design of eight-stranded TMBs, which can fold and assemble into synthetic lipid membranes.RESULTSWe used a combination of purely geometric models and explicit Rosetta protein structure simulations to determine the constraints that β-strand connectivity and membrane embedding place on the TMB architecture. Through a series of design-build-test cycles, we found that, unlike almost all other classes of proteins, locally destabilizing sequences are critical for expression and folding of TMBs, and that the β-turns that translocate through the bilayer during folding have to be destabilized to enable correct assembly in the membrane. Our results suggest that premature formation of β hairpins may result in off-target β-sheet structures that compete with proper membrane insertion and folding, and hence the β hairpins of TMBs must be designed such that they are only transiently formed prior to membrane insertion, when the protein is in an aqueous environment. In the hydrophobic environment of the lipid bilayer, the full TMB can assemble because the membrane-facing nonpolar residues, which would tend to cluster nonspecifically in an aqueous environment, instead make favorable interactions with the lipids. As the TMB assembles, the β hairpins are stabilized by interactions with the neighboring β strands.Using computational methods that incorporate the above insights, we designed TMB sequences that successfully fold and assemble into both detergent micelles and lipid bilayers. Two of the designs were highly stable and could fold into liposomes more rapidly and reversibly than the transmembrane domain of the model outer membrane protein A (tOmpA) of Escherichia coli. A nuclear magnetic resonance solution structure and a high-resolution crystal structure for two different designs closely match the design models, showing that the TMB design method developed here can generate new structures with atomic-level accuracy.CONCLUSIONThis study elucidates key principles for de novo design of transmembrane β barrels, ranging from constraints on β-barrel architecture and β-hairpin design, as well as local and global sequence features. Our designs provide starting points for the bottom-up elucidation of the molecular mechanisms underlying TMB folding and interactions with the cellular outer membrane folding and insertion machinery. More generally, our work demonstrates that TMBs can be designed with atomic-level accuracy and opens the door to custom design of nanopores tailored for applications such as single-molecule sensing and sequencing.De novo{textendash}designed eight-stranded transmembrane β barrels fold spontaneously and reversibly into synthetic lipid membranes.The illustration shows the crystal structure of the protein TMB2.17 designed in this study, which adopts a structure identical to the design model.Credit: Ian Haydon.Transmembrane β-barrel proteins (TMBs) are of great interest for single-molecule analytical technologies because they can spontaneously fold and insert into membranes and form stable pores, but the range of pore properties that can be achieved by repurposing natural TMBs is limited. We leverage the power of de novo computational design coupled with a {textquotedblleft}hypothesis, design, and test{textquotedblright} approach to determine TMB design principles, notably, the importance of negative design to slow β-sheet assembly. We design new eight-stranded TMBs, with no homology to known TMBs, that insert and fold reversibly into synthetic lipid membranes and have nuclear magnetic resonance and x-ray crystal structures very similar to the computational models. These advances should enable the custom design of pores for a wide range of applications.
Klima, Jason C. and Doyle, Lindsey A. and Lee, Justin Daho and Rappleye, Michael and Gagnon, Lauren A. and Lee, Min Yen and Barros, Emilia P. and Vorobieva, Anastassia A. and Dou, Jiayi and Bremner, Samantha and Quon, Jacob S. and Chow, Cameron M. and Carter, Lauren and Mack, David L. and Amaro, Rommie E. and Vaughan, Joshua C. and Berndt, Andre and Stoddard, Barry L. and Baker, David
Incorporation of sensing modalities into de novo designed fluorescence-activating proteins Journal Article
In: Nature Communications, vol. 856, no. 12, pp. 2041–1723, 2021.
@article{Klima2021,
title = {Incorporation of sensing modalities into de novo designed fluorescence-activating proteins},
author = {Klima, Jason C.
and Doyle, Lindsey A.
and Lee, Justin Daho
and Rappleye, Michael
and Gagnon, Lauren A.
and Lee, Min Yen
and Barros, Emilia P.
and Vorobieva, Anastassia A.
and Dou, Jiayi
and Bremner, Samantha
and Quon, Jacob S.
and Chow, Cameron M.
and Carter, Lauren
and Mack, David L.
and Amaro, Rommie E.
and Vaughan, Joshua C.
and Berndt, Andre
and Stoddard, Barry L.
and Baker, David},
url = {https://www.nature.com/articles/s41467-020-18911-w, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2021/02/Klima_etal_NatComm2021_Sensing_modalities_in_fluorescent_proteins.pdf, Download PDF},
doi = {10.1038/s41467-020-18911-w},
year = {2021},
date = {2021-02-08},
urldate = {2021-02-08},
journal = {Nature Communications},
volume = {856},
number = {12},
pages = {2041–1723},
abstract = {Through the efforts of many groups, a wide range of fluorescent protein reporters and sensors based on green fluorescent protein and its relatives have been engineered in recent years. Here we explore the incorporation of sensing modalities into de novo designed fluorescence-activating proteins, called mini-fluorescence-activating proteins (mFAPs), that bind and stabilize the fluorescent cis-planar state of the fluorogenic compound DFHBI. We show through further design that the fluorescence intensity and specificity of mFAPs for different chromophores can be tuned, and the fluorescence made sensitive to pH and Ca2+ for real-time fluorescence reporting. Bipartite split mFAPs enable real-time monitoring of protein–protein association and (unlike widely used split GFP reporter systems) are fully reversible, allowing direct readout of association and dissociation events. The relative ease with which sensing modalities can be incorporated and advantages in smaller size and photostability make de novo designed fluorescence-activating proteins attractive candidates for optical sensor engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Through the efforts of many groups, a wide range of fluorescent protein reporters and sensors based on green fluorescent protein and its relatives have been engineered in recent years. Here we explore the incorporation of sensing modalities into de novo designed fluorescence-activating proteins, called mini-fluorescence-activating proteins (mFAPs), that bind and stabilize the fluorescent cis-planar state of the fluorogenic compound DFHBI. We show through further design that the fluorescence intensity and specificity of mFAPs for different chromophores can be tuned, and the fluorescence made sensitive to pH and Ca2+ for real-time fluorescence reporting. Bipartite split mFAPs enable real-time monitoring of protein–protein association and (unlike widely used split GFP reporter systems) are fully reversible, allowing direct readout of association and dissociation events. The relative ease with which sensing modalities can be incorporated and advantages in smaller size and photostability make de novo designed fluorescence-activating proteins attractive candidates for optical sensor engineering.
Quijano-Rubio, Alfredo and Yeh, Hsien-Wei and Park, Jooyoung and Lee, Hansol and Langan, Robert A. and Boyken, Scott E. and Lajoie, Marc J. and Cao, Longxing and Chow, Cameron M. and Miranda, Marcos C. and Wi, Jimin and Hong, Hyo Jeong and Stewart, Lance and Oh, Byung-Ha and Baker, David
De novo design of modular and tunable protein biosensors Journal Article
In: Nature, 2021.
@article{Quijano-Rubio2021,
title = {De novo design of modular and tunable protein biosensors},
author = {Quijano-Rubio, Alfredo
and Yeh, Hsien-Wei
and Park, Jooyoung
and Lee, Hansol
and Langan, Robert A.
and Boyken, Scott E.
and Lajoie, Marc J.
and Cao, Longxing
and Chow, Cameron M.
and Miranda, Marcos C.
and Wi, Jimin
and Hong, Hyo Jeong
and Stewart, Lance
and Oh, Byung-Ha
and Baker, David},
url = {https://www.nature.com/articles/s41586-021-03258-z, Nature
https://www.bakerlab.org/wp-content/uploads/2021/02/Rubio_et_al_Nature_COVID_LOCKR_sensors.pdf, Download PDF},
doi = {10.1038/s41586-021-03258-z},
year = {2021},
date = {2021-01-27},
urldate = {2021-01-27},
journal = {Nature},
abstract = {Naturally occurring protein switches have been repurposed for developing novel biosensors and reporters for cellular and clinical applications1, but the number of such switches is limited, and engineering them is often challenging as each is different. Here, we show that a very general class of protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which binding of a peptide key triggers biological outputs of interest2. The designed sensors are modular molecular devices with a closed dark state and an open luminescent state; binding of the analyte of interest drives switching from the closed to the open state. Because the sensor is based purely on thermodynamic coupling of analyte binding to sensor activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We demonstrate the modularity of this platform by creating biosensors that, with little optimization, sensitively detect the anti-apoptosis protein Bcl-2, the IgG1 Fc domain, the Her2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac Troponin I and an anti-Hepatitis B virus (HBV) antibody that achieve the sub-nanomolar sensitivity necessary to detect clinically relevant concentrations of these molecules. Given the current need for diagnostic tools for tracking COVID-193, we used the approach to design sensors of antibodies against SARS-CoV-2 protein epitopes and of the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. The latter, which incorporates a de novo designed RBD binder4, has a limit of detection of 15 pM and a signal over background of over 50-fold. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Naturally occurring protein switches have been repurposed for developing novel biosensors and reporters for cellular and clinical applications1, but the number of such switches is limited, and engineering them is often challenging as each is different. Here, we show that a very general class of protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which binding of a peptide key triggers biological outputs of interest2. The designed sensors are modular molecular devices with a closed dark state and an open luminescent state; binding of the analyte of interest drives switching from the closed to the open state. Because the sensor is based purely on thermodynamic coupling of analyte binding to sensor activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We demonstrate the modularity of this platform by creating biosensors that, with little optimization, sensitively detect the anti-apoptosis protein Bcl-2, the IgG1 Fc domain, the Her2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac Troponin I and an anti-Hepatitis B virus (HBV) antibody that achieve the sub-nanomolar sensitivity necessary to detect clinically relevant concentrations of these molecules. Given the current need for diagnostic tools for tracking COVID-193, we used the approach to design sensors of antibodies against SARS-CoV-2 protein epitopes and of the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. The latter, which incorporates a de novo designed RBD binder4, has a limit of detection of 15 pM and a signal over background of over 50-fold. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.
Ben-Sasson, Ariel J., Watson, Joseph L., Sheffler, William, Johnson, Matthew Camp, Bittleston, Alice, Somasundaram, Logeshwaran, Decarreau, Justin, Jiao, Fang, Chen, Jiajun, Mela, Ioanna, Drabek, Andrew A., Jarrett, Sanchez M., Blacklow, Stephen C., Kaminski, Clemens F., Hura, Greg L., De Yoreo, James J., Kollman, Justin M., Ruohola-Baker, Hannele, Derivery, Emmanuel, Baker, David
Design of biologically active binary protein 2D materials Journal Article
In: Nature, 2021.
@article{Ben-Sasson2020,
title = {Design of biologically active binary protein 2D materials},
author = {Ben-Sasson, Ariel J. and Watson, Joseph L. and Sheffler, William and Johnson, Matthew Camp and Bittleston, Alice and Somasundaram, Logeshwaran and Decarreau, Justin and Jiao, Fang and Chen, Jiajun and Mela, Ioanna and Drabek, Andrew A. and Jarrett, Sanchez M. and Blacklow, Stephen C. and Kaminski, Clemens F. and Hura, Greg L. and De Yoreo, James J. and Kollman, Justin M. and Ruohola-Baker, Hannele and Derivery, Emmanuel and Baker, David},
url = {https://www.nature.com/articles/s41586-020-03120-8, Nature
https://www.bakerlab.org/wp-content/uploads/2021/02/Ben-Sasson_Nature2021_Binary_2D_arrays.pdf, Download PDF},
doi = {10.1038/s41586-020-03120-8},
year = {2021},
date = {2021-01-06},
urldate = {2021-01-06},
journal = {Nature},
abstract = {Ordered two-dimensional arrays such as S-layers1,2 and designed analogues3–5 have intrigued bioengineers6,7, but with the exception of a single lattice formed with flexible linkers8, they are constituted from just one protein component. Materials composed of two components have considerable potential advantages for modulating assembly dynamics and incorporating more complex functionality9–12. Here we describe a computational method to generate co-assembling binary layers by designing rigid interfaces between pairs of dihedral protein building blocks, and use it to design a p6m lattice. The designed array components are soluble at millimolar concentrations, but when combined at nanomolar concentrations, they rapidly assemble into nearly crystalline micrometre-scale arrays nearly identical to the computational design model in vitro and in cells without the need for a two-dimensional support. Because the material is designed from the ground up, the components can be readily functionalized and their symmetry reconfigured, enabling formation of ligand arrays with distinguishable surfaces, which we demonstrate can drive extensive receptor clustering, downstream protein recruitment and signalling. Using atomic force microscopy on supported bilayers and quantitative microscopy on living cells, we show that arrays assembled on membranes have component stoichiometry and structure similar to arrays formed in vitro, and that our material can therefore impose order onto fundamentally disordered substrates such as cell membranes. In contrast to previously characterized cell surface receptor binding assemblies such as antibodies and nanocages, which are rapidly endocytosed, we find that large arrays assembled at the cell surface suppress endocytosis in a tunable manner, with potential therapeutic relevance for extending receptor engagement and immune evasion. Our work provides a foundation for a synthetic cell biology in which multi-protein macroscale materials are designed to modulate cell responses and reshape synthetic and living systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ordered two-dimensional arrays such as S-layers1,2 and designed analogues3–5 have intrigued bioengineers6,7, but with the exception of a single lattice formed with flexible linkers8, they are constituted from just one protein component. Materials composed of two components have considerable potential advantages for modulating assembly dynamics and incorporating more complex functionality9–12. Here we describe a computational method to generate co-assembling binary layers by designing rigid interfaces between pairs of dihedral protein building blocks, and use it to design a p6m lattice. The designed array components are soluble at millimolar concentrations, but when combined at nanomolar concentrations, they rapidly assemble into nearly crystalline micrometre-scale arrays nearly identical to the computational design model in vitro and in cells without the need for a two-dimensional support. Because the material is designed from the ground up, the components can be readily functionalized and their symmetry reconfigured, enabling formation of ligand arrays with distinguishable surfaces, which we demonstrate can drive extensive receptor clustering, downstream protein recruitment and signalling. Using atomic force microscopy on supported bilayers and quantitative microscopy on living cells, we show that arrays assembled on membranes have component stoichiometry and structure similar to arrays formed in vitro, and that our material can therefore impose order onto fundamentally disordered substrates such as cell membranes. In contrast to previously characterized cell surface receptor binding assemblies such as antibodies and nanocages, which are rapidly endocytosed, we find that large arrays assembled at the cell surface suppress endocytosis in a tunable manner, with potential therapeutic relevance for extending receptor engagement and immune evasion. Our work provides a foundation for a synthetic cell biology in which multi-protein macroscale materials are designed to modulate cell responses and reshape synthetic and living systems.
COLLABORATOR LED
Crawshaw, Rebecca and Crossley, Amy E. and Johannissen, Linus and Burke, Ashleigh J. and Hay, Sam and Levy, Colin and Baker, David and Lovelock, Sarah L. and Green, Anthony P.
Engineering an efficient and enantioselective enzyme for the Morita-Baylis-Hillman reaction Journal Article
In: Nature Chemistry, 2021.
@article{Crawshaw2021,
title = {Engineering an efficient and enantioselective enzyme for the Morita-Baylis-Hillman reaction},
author = {Crawshaw, Rebecca
and Crossley, Amy E.
and Johannissen, Linus
and Burke, Ashleigh J.
and Hay, Sam
and Levy, Colin
and Baker, David
and Lovelock, Sarah L.
and Green, Anthony P.},
url = {https://www.nature.com/articles/s41557-021-00833-9
https://www.bakerlab.org/wp-content/uploads/2022/01/Crawshaw_etal_NatChem_Engineering_enantioselective_enzyme_Morita-Baylis-Hillman_reaction.pdf},
doi = {10.1038/s41557-021-00833-9},
year = {2021},
date = {2021-12-16},
journal = {Nature Chemistry},
abstract = {The combination of computational design and directed evolution could offer a general strategy to create enzymes with new functions. So far, this approach has delivered enzymes for a handful of model reactions. Here we show that new catalytic mechanisms can be engineered into proteins to accelerate more challenging chemical transformations. Evolutionary optimization of a primitive design afforded an efficient and enantioselective enzyme (BH32.14) for the Morita–Baylis–Hillman (MBH) reaction. BH32.14 is suitable for preparative-scale transformations, accepts a broad range of aldehyde and enone coupling partners and is able to promote selective monofunctionalizations of dialdehydes. Crystallographic, biochemical and computational studies reveal that BH32.14 operates via a sophisticated catalytic mechanism comprising a His23 nucleophile paired with a judiciously positioned Arg124. This catalytic arginine shuttles between conformational states to stabilize multiple oxyanion intermediates and serves as a genetically encoded surrogate of privileged bidentate hydrogen-bonding catalysts (for example, thioureas). This study demonstrates that elaborate catalytic devices can be built from scratch to promote demanding multi-step processes not observed in nature.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The combination of computational design and directed evolution could offer a general strategy to create enzymes with new functions. So far, this approach has delivered enzymes for a handful of model reactions. Here we show that new catalytic mechanisms can be engineered into proteins to accelerate more challenging chemical transformations. Evolutionary optimization of a primitive design afforded an efficient and enantioselective enzyme (BH32.14) for the Morita–Baylis–Hillman (MBH) reaction. BH32.14 is suitable for preparative-scale transformations, accepts a broad range of aldehyde and enone coupling partners and is able to promote selective monofunctionalizations of dialdehydes. Crystallographic, biochemical and computational studies reveal that BH32.14 operates via a sophisticated catalytic mechanism comprising a His23 nucleophile paired with a judiciously positioned Arg124. This catalytic arginine shuttles between conformational states to stabilize multiple oxyanion intermediates and serves as a genetically encoded surrogate of privileged bidentate hydrogen-bonding catalysts (for example, thioureas). This study demonstrates that elaborate catalytic devices can be built from scratch to promote demanding multi-step processes not observed in nature.
Patricia M. Legler and Stephen F. Little and Jeffrey Senft and Rowena Schokman and John H. Carra and Jaimee R. Compton and Donald Chabot and Steven Tobery and David P. Fetterer and Justin B. Siegel and David Baker and Arthur M. Friedlander
Treatment of experimental anthrax with pegylated circularly permuted capsule depolymerase Journal Article
In: Science Translational Medicine, 2021.
@article{Friedlander2021,
title = {Treatment of experimental anthrax with pegylated circularly permuted capsule depolymerase},
author = {Patricia M. Legler
and Stephen F. Little
and Jeffrey Senft
and Rowena Schokman
and John H. Carra
and Jaimee R. Compton
and Donald Chabot
and Steven Tobery
and David P. Fetterer
and Justin B. Siegel
and David Baker
and Arthur M. Friedlander},
url = {https://www.science.org/doi/10.1126/scitranslmed.abh1682
https://www.bakerlab.org/wp-content/uploads/2022/01/Legler_etal_ScienceTransMed2021_Treatment_of_anthrax_by_capsule_depolymerase.pdf},
doi = {10.1126/scitranslmed.abh1682},
year = {2021},
date = {2021-12-08},
journal = {Science Translational Medicine},
abstract = {Anthrax is considered one of the most dangerous bioweapon agents, and concern about multidrug-resistant strains has led to the development of alternative therapeutic approaches that target the antiphagocytic capsule, an essential virulence determinant of Bacillus anthracis, the causative agent. Capsule depolymerase is a γ-glutamyltransferase that anchors the capsule to the cell wall of B. anthracis. Encapsulated strains of B. anthracis can be treated with recombinant capsule depolymerase to enzymatically remove the capsule and promote phagocytosis and killing by human neutrophils. Here, we show that pegylation improved the pharmacokinetic and therapeutic properties of a previously described variant of capsule depolymerase, CapD-CP, when delivered 24 hours after exposure every 8 hours for 2 days for the treatment of mice infected with B. anthracis. Mice infected with 382 LD50 of B. anthracis spores from a nontoxigenic encapsulated strain were completely protected (10 of 10) after treatment with the pegylated PEG-CapD-CPS334C, whereas 10% of control mice (1 of 10) survived with control treatment using bovine serum albumin (P < 0.0001, log-rank analysis). Treatment of mice infected with five LD50 of a fully virulent toxigenic, encapsulated B. anthracis strain with PEG-CapD-CPS334C protected 80% (8 of 10) of the animals, whereas 20% of controls (2 of 10) survived (P = 0.0125, log-rank analysis). This strategy renders B. anthracis susceptible to innate immune responses and does not rely on antibiotics. These findings suggest that enzyme-catalyzed removal of the capsule may be a potential therapeutic strategy for the treatment of multidrug- or vaccine-resistant anthrax and other bacterial infections.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Anthrax is considered one of the most dangerous bioweapon agents, and concern about multidrug-resistant strains has led to the development of alternative therapeutic approaches that target the antiphagocytic capsule, an essential virulence determinant of Bacillus anthracis, the causative agent. Capsule depolymerase is a γ-glutamyltransferase that anchors the capsule to the cell wall of B. anthracis. Encapsulated strains of B. anthracis can be treated with recombinant capsule depolymerase to enzymatically remove the capsule and promote phagocytosis and killing by human neutrophils. Here, we show that pegylation improved the pharmacokinetic and therapeutic properties of a previously described variant of capsule depolymerase, CapD-CP, when delivered 24 hours after exposure every 8 hours for 2 days for the treatment of mice infected with B. anthracis. Mice infected with 382 LD50 of B. anthracis spores from a nontoxigenic encapsulated strain were completely protected (10 of 10) after treatment with the pegylated PEG-CapD-CPS334C, whereas 10% of control mice (1 of 10) survived with control treatment using bovine serum albumin (P < 0.0001, log-rank analysis). Treatment of mice infected with five LD50 of a fully virulent toxigenic, encapsulated B. anthracis strain with PEG-CapD-CPS334C protected 80% (8 of 10) of the animals, whereas 20% of controls (2 of 10) survived (P = 0.0125, log-rank analysis). This strategy renders B. anthracis susceptible to innate immune responses and does not rely on antibiotics. These findings suggest that enzyme-catalyzed removal of the capsule may be a potential therapeutic strategy for the treatment of multidrug- or vaccine-resistant anthrax and other bacterial infections.
Du, Zongyang and Su, Hong and Wang, Wenkai and Ye, Lisha and Wei, Hong and Peng, Zhenling and Anishchenko, Ivan and Baker, David and Yang, Jianyi
The trRosetta server for fast and accurate protein structure prediction Journal Article
In: Nature Protocols, 2021.
@article{Du2021,
title = {The trRosetta server for fast and accurate protein structure prediction},
author = {Du, Zongyang
and Su, Hong
and Wang, Wenkai
and Ye, Lisha
and Wei, Hong
and Peng, Zhenling
and Anishchenko, Ivan
and Baker, David
and Yang, Jianyi},
url = {https://www.nature.com/articles/s41596-021-00628-9
https://www.bakerlab.org/wp-content/uploads/2022/01/Du_etal_NatProt2021_trRosetta_server.pdf},
doi = {10.1038/s41596-021-00628-9},
year = {2021},
date = {2021-12-01},
urldate = {2021-12-01},
journal = {Nature Protocols},
abstract = {The trRosetta (transform-restrained Rosetta) server is a web-based platform for fast and accurate protein structure prediction, powered by deep learning and Rosetta. With the input of a protein’s amino acid sequence, a deep neural network is first used to predict the inter-residue geometries, including distance and orientations. The predicted geometries are then transformed as restraints to guide the structure prediction on the basis of direct energy minimization, which is implemented under the framework of Rosetta. The trRosetta server distinguishes itself from other similar structure prediction servers in terms of rapid and accurate de novo structure prediction. As an illustration, trRosetta was applied to two Pfam families with unknown structures, for which the predicted de novo models were estimated to have high accuracy. Nevertheless, to take advantage of homology modeling, homologous templates are used as additional inputs to the network automatically. In general, it takes ~1 h to predict the final structure for a typical protein with ~300 amino acids, using a maximum of 10 CPU cores in parallel in our cluster system. To enable large-scale structure modeling, a downloadable package of trRosetta with open-source codes is available as well. A detailed guidance for using the package is also available in this protocol. The server and the package are available at https://yanglab.nankai.edu.cn/trRosetta/ and https://yanglab.nankai.edu.cn/trRosetta/download/, respectively.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The trRosetta (transform-restrained Rosetta) server is a web-based platform for fast and accurate protein structure prediction, powered by deep learning and Rosetta. With the input of a protein’s amino acid sequence, a deep neural network is first used to predict the inter-residue geometries, including distance and orientations. The predicted geometries are then transformed as restraints to guide the structure prediction on the basis of direct energy minimization, which is implemented under the framework of Rosetta. The trRosetta server distinguishes itself from other similar structure prediction servers in terms of rapid and accurate de novo structure prediction. As an illustration, trRosetta was applied to two Pfam families with unknown structures, for which the predicted de novo models were estimated to have high accuracy. Nevertheless, to take advantage of homology modeling, homologous templates are used as additional inputs to the network automatically. In general, it takes ~1 h to predict the final structure for a typical protein with ~300 amino acids, using a maximum of 10 CPU cores in parallel in our cluster system. To enable large-scale structure modeling, a downloadable package of trRosetta with open-source codes is available as well. A detailed guidance for using the package is also available in this protocol. The server and the package are available at https://yanglab.nankai.edu.cn/trRosetta/ and https://yanglab.nankai.edu.cn/trRosetta/download/, respectively.
Muammer Y Yaman, Kathryn N Guye, Maxim Ziatdinov, Hao Shen, David Baker, Sergei V Kalinin, David S Ginger
Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis Journal Article
In: Soft Matter, 2021.
@article{Yaman2021,
title = {Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis},
author = {Muammer Y Yaman and Kathryn N Guye and Maxim Ziatdinov and Hao Shen and David Baker and Sergei V Kalinin and David S Ginger
},
url = {https://pubmed.ncbi.nlm.nih.gov/34128040/
https://www.bakerlab.org/wp-content/uploads/2021/06/Muammer_etal_SoftMatter2021_Aisngment_along_nanofibers.pdf},
doi = {10.1039/d1sm00645b},
year = {2021},
date = {2021-06-15},
journal = {Soft Matter},
abstract = {In this study, we focus on exploring the directional assembly of anisotropic Au nanorods along de novo designed 1D protein nanofiber templates. Using machine learning and automated image processing, we analyze scanning electron microscopy (SEM) images to study how the attachment density and alignment fidelity are influenced by variables such as the aspect ratio of the Au nanorods, and the salt concentration of the solution. We find that the Au nanorods prefer to align parallel to the protein nanofibers. This preference decreases with increasing salt concentration, but is only weakly sensitive to the nanorod aspect ratio. While the overall specific Au nanorod attachment density to the protein fibers increases with increasing solution ionic strength, this increase is dominated primarily by non-specific binding to the substrate background, and we find that greater specific attachment (nanorods attached to the nanofiber template as compared to the substrates) occurs at the lower studied salt concentrations, with the maximum ratio of specific to non-specific binding occurring when the protein fiber solutions are prepared in 75 mM NaCl concentration.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this study, we focus on exploring the directional assembly of anisotropic Au nanorods along de novo designed 1D protein nanofiber templates. Using machine learning and automated image processing, we analyze scanning electron microscopy (SEM) images to study how the attachment density and alignment fidelity are influenced by variables such as the aspect ratio of the Au nanorods, and the salt concentration of the solution. We find that the Au nanorods prefer to align parallel to the protein nanofibers. This preference decreases with increasing salt concentration, but is only weakly sensitive to the nanorod aspect ratio. While the overall specific Au nanorod attachment density to the protein fibers increases with increasing solution ionic strength, this increase is dominated primarily by non-specific binding to the substrate background, and we find that greater specific attachment (nanorods attached to the nanofiber template as compared to the substrates) occurs at the lower studied salt concentrations, with the maximum ratio of specific to non-specific binding occurring when the protein fiber solutions are prepared in 75 mM NaCl concentration.
Boyoglu-Barnum, Seyhan and Ellis, Daniel and Gillespie, Rebecca A. and Hutchinson, Geoffrey B. and Park, Young-Jun and Moin, Syed M. and Acton, Oliver J. and Ravichandran, Rashmi and Murphy, Mike and Pettie, Deleah and Matheson, Nick and Carter, Lauren and Creanga, Adrian and Watson, Michael J. and Kephart, Sally and Ataca, Sila and Vaile, John R. and Ueda, George and Crank, Michelle C. and Stewart, Lance and Lee, Kelly K. and Guttman, Miklos and Baker, David and Mascola, John R. and Veesler, David and Graham, Barney S. and King, Neil P. and Kanekiyo, Masaru
Quadrivalent influenza nanoparticle vaccines induce broad protection Journal Article
In: Nature, 2021.
@article{Boyoglu-Barnum2021,
title = {Quadrivalent influenza nanoparticle vaccines induce broad protection},
author = {Boyoglu-Barnum, Seyhan
and Ellis, Daniel
and Gillespie, Rebecca A.
and Hutchinson, Geoffrey B.
and Park, Young-Jun
and Moin, Syed M.
and Acton, Oliver J.
and Ravichandran, Rashmi
and Murphy, Mike
and Pettie, Deleah
and Matheson, Nick
and Carter, Lauren
and Creanga, Adrian
and Watson, Michael J.
and Kephart, Sally
and Ataca, Sila
and Vaile, John R.
and Ueda, George
and Crank, Michelle C.
and Stewart, Lance
and Lee, Kelly K.
and Guttman, Miklos
and Baker, David
and Mascola, John R.
and Veesler, David
and Graham, Barney S.
and King, Neil P.
and Kanekiyo, Masaru},
url = {https://www.nature.com/articles/s41586-021-03365-x
https://www.bakerlab.org/wp-content/uploads/2021/04/Nature2021_NanoparticleFluVaccine.pdf},
doi = {10.1038/s41586-021-03365-x},
year = {2021},
date = {2021-03-24},
journal = {Nature},
abstract = {Influenza vaccines that confer broad and durable protection against diverse viral strains would have a major effect on global health, as they would lessen the need for annual vaccine reformulation and immunization. Here we show that computationally designed, two-component nanoparticle immunogens induce potently neutralizing and broadly protective antibody responses against a wide variety of influenza viruses. The nanoparticle immunogens contain 20 haemagglutinin glycoprotein trimers in an ordered array, and their assembly in vitro enables the precisely controlled co-display of multiple distinct haemagglutinin proteins in defined ratios. Nanoparticle immunogens that co-display the four haemagglutinins of licensed quadrivalent influenza vaccines elicited antibody responses in several animal models against vaccine-matched strains that were equivalent to or better than commercial quadrivalent influenza vaccines, and simultaneously induced broadly protective antibody responses to heterologous viruses by targeting the subdominant yet conserved haemagglutinin stem. The combination of potent receptor-blocking and cross-reactive stem-directed antibodies induced by the nanoparticle immunogens makes them attractive candidates for a supraseasonal influenza vaccine candidate with the potential to replace conventional seasonal vaccines.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Influenza vaccines that confer broad and durable protection against diverse viral strains would have a major effect on global health, as they would lessen the need for annual vaccine reformulation and immunization. Here we show that computationally designed, two-component nanoparticle immunogens induce potently neutralizing and broadly protective antibody responses against a wide variety of influenza viruses. The nanoparticle immunogens contain 20 haemagglutinin glycoprotein trimers in an ordered array, and their assembly in vitro enables the precisely controlled co-display of multiple distinct haemagglutinin proteins in defined ratios. Nanoparticle immunogens that co-display the four haemagglutinins of licensed quadrivalent influenza vaccines elicited antibody responses in several animal models against vaccine-matched strains that were equivalent to or better than commercial quadrivalent influenza vaccines, and simultaneously induced broadly protective antibody responses to heterologous viruses by targeting the subdominant yet conserved haemagglutinin stem. The combination of potent receptor-blocking and cross-reactive stem-directed antibodies induced by the nanoparticle immunogens makes them attractive candidates for a supraseasonal influenza vaccine candidate with the potential to replace conventional seasonal vaccines.
Naozumi Hiranuma, Hahnbeom Park, Minkyung Baek, Ivan Anishchenko, Justas Dauparas, David Baker
Improved protein structure refinement guided by deep learning based accuracy estimation Journal Article
In: Nature Communications, vol. 12, no. 1340, 2021.
@article{Hiranuma2021,
title = {Improved protein structure refinement guided by deep learning based accuracy estimation},
author = {Naozumi Hiranuma and Hahnbeom Park and Minkyung Baek and Ivan Anishchenko and Justas Dauparas and David Baker
},
url = {https://www.nature.com/articles/s41467-021-21511-x, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2021/02/Hiranuma_etal_NatureComms2021_DeepLearningStructureRefinement.pdf, Download PDF},
doi = {10.1038/s41467-021-21511-x},
year = {2021},
date = {2021-02-26},
urldate = {2021-02-26},
journal = {Nature Communications},
volume = {12},
number = {1340},
abstract = {We develop a deep learning framework (DeepAccNet) that estimates per-residue accuracy and residue-residue distance signed error in protein models and uses these predictions to guide Rosetta protein structure refinement. The network uses 3D convolutions to evaluate local atomic environments followed by 2D convolutions to provide their global contexts and outperforms other methods that similarly predict the accuracy of protein structure models. Overall accuracy predictions for X-ray and cryoEM structures in the PDB correlate with their resolution, and the network should be broadly useful for assessing the accuracy of both predicted structure models and experimentally determined structures and identifying specific regions likely to be in error. Incorporation of the accuracy predictions at multiple stages in the Rosetta refinement protocol considerably increased the accuracy of the resulting protein structure models, illustrating how deep learning can improve search for global energy minima of biomolecules.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We develop a deep learning framework (DeepAccNet) that estimates per-residue accuracy and residue-residue distance signed error in protein models and uses these predictions to guide Rosetta protein structure refinement. The network uses 3D convolutions to evaluate local atomic environments followed by 2D convolutions to provide their global contexts and outperforms other methods that similarly predict the accuracy of protein structure models. Overall accuracy predictions for X-ray and cryoEM structures in the PDB correlate with their resolution, and the network should be broadly useful for assessing the accuracy of both predicted structure models and experimentally determined structures and identifying specific regions likely to be in error. Incorporation of the accuracy predictions at multiple stages in the Rosetta refinement protocol considerably increased the accuracy of the resulting protein structure models, illustrating how deep learning can improve search for global energy minima of biomolecules.
Hahnbeom Park, Guangfeng Zhou, Minkyung Baek, David Baker, Frank DiMaio
Force Field Optimization Guided by Small Molecule Crystal Lattice Data Enables Consistent Sub-Angstrom Protein–Ligand Docking Journal Article
In: Journal of Chemical Theory and Computation, 2021.
@article{Park2021,
title = {Force Field Optimization Guided by Small Molecule Crystal Lattice Data Enables Consistent Sub-Angstrom Protein–Ligand Docking},
author = {Hahnbeom Park and Guangfeng Zhou and Minkyung Baek and David Baker and Frank DiMaio},
url = {https://pubs.acs.org/doi/full/10.1021/acs.jctc.0c01184
https://www.bakerlab.org/wp-content/uploads/2021/02/Park_etal_JCTC2021_Small_mol_force_field_optimization.pdf},
doi = {10.1021/acs.jctc.0c01184},
year = {2021},
date = {2021-02-12},
journal = {Journal of Chemical Theory and Computation},
abstract = {Accurate and rapid calculation of protein-small molecule interaction free energies is critical for computational drug discovery. Because of the large chemical space spanned by drug-like molecules, classical force fields contain thousands of parameters describing atom-pair distance and torsional preferences; each parameter is typically optimized independently on simple representative molecules. Here, we describe a new approach in which small molecule force field parameters are jointly optimized guided by the rich source of information contained within thousands of available small molecule crystal structures. We optimize parameters by requiring that the experimentally determined molecular lattice arrangements have lower energy than all alternative lattice arrangements. Thousands of independent crystal lattice-prediction simulations were run on each of 1386 small molecule crystal structures, and energy function parameters of an implicit solvent energy model were optimized, so native crystal lattice arrangements had the lowest energy. The resulting energy model was implemented in Rosetta, together with a rapid genetic algorithm docking method employing grid-based scoring and receptor flexibility. The success rate of bound structure recapitulation in cross-docking on 1112 complexes was improved by more than 10% over previously published methods, with solutions within <1 Å in over half of the cases. Our results demonstrate that small molecule crystal structures are a rich source of information for guiding molecular force field development, and the improved Rosetta energy function should increase accuracy in a wide range of small molecule structure prediction and design studies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Accurate and rapid calculation of protein-small molecule interaction free energies is critical for computational drug discovery. Because of the large chemical space spanned by drug-like molecules, classical force fields contain thousands of parameters describing atom-pair distance and torsional preferences; each parameter is typically optimized independently on simple representative molecules. Here, we describe a new approach in which small molecule force field parameters are jointly optimized guided by the rich source of information contained within thousands of available small molecule crystal structures. We optimize parameters by requiring that the experimentally determined molecular lattice arrangements have lower energy than all alternative lattice arrangements. Thousands of independent crystal lattice-prediction simulations were run on each of 1386 small molecule crystal structures, and energy function parameters of an implicit solvent energy model were optimized, so native crystal lattice arrangements had the lowest energy. The resulting energy model was implemented in Rosetta, together with a rapid genetic algorithm docking method employing grid-based scoring and receptor flexibility. The success rate of bound structure recapitulation in cross-docking on 1112 complexes was improved by more than 10% over previously published methods, with solutions within <1 Å in over half of the cases. Our results demonstrate that small molecule crystal structures are a rich source of information for guiding molecular force field development, and the improved Rosetta energy function should increase accuracy in a wide range of small molecule structure prediction and design studies.
Ziatdinov, Maxim and Zhang, Shuai and Dollar, Orion and Pfaendtner, Jim and Mundy, Christopher J. and Li, Xin and Pyles, Harley and Baker, David and De Yoreo, James J. and Kalinin, Sergei V.
Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data Journal Article
In: Nano Letters, 2021.
@article{Ziatdinov2021,
title = {Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data},
author = {Ziatdinov, Maxim
and Zhang, Shuai
and Dollar, Orion
and Pfaendtner, Jim
and Mundy, Christopher J.
and Li, Xin
and Pyles, Harley
and Baker, David
and De Yoreo, James J.
and Kalinin, Sergei V.},
url = {https://pubs.acs.org/doi/10.1021/acs.nanolett.0c03447},
doi = {10.1021/acs.nanolett.0c03447},
year = {2021},
date = {2021-01-13},
journal = {Nano Letters},
abstract = {The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. The deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. The deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.
2020
FROM THE LAB
Vikram Khipple Mulligan, Christine S. Kang, Michael R. Sawaya, Stephen Rettie, Xinting Li, Inna Antselovich, Timothy W. Craven, Andrew M. Watkins, Jason W. Labonte, Frank DiMaio, Todd O. Yeates, David Baker
Computational design of mixed chirality peptide macrocycles with internal symmetry Journal Article
In: Protein Science, 2020.
@article{Mulligan2020,
title = {Computational design of mixed chirality peptide macrocycles with internal symmetry},
author = {Vikram Khipple Mulligan and Christine S. Kang and Michael R. Sawaya and Stephen Rettie and Xinting Li and Inna Antselovich and Timothy W. Craven and Andrew M. Watkins and Jason W. Labonte and Frank DiMaio and Todd O. Yeates and David Baker},
url = {https://onlinelibrary.wiley.com/doi/epdf/10.1002/pro.3974
https://www.bakerlab.org/wp-content/uploads/2020/10/Mulligan2020-Computational-design-of-mixed-chirality-peptide-macrocycles-with-internal-symmetry.pdf},
doi = {10.1002/pro.3974},
year = {2020},
date = {2020-10-15},
journal = {Protein Science},
abstract = {Cyclic symmetry is frequent in protein and peptide homo‐oligomers, but extremely rare within a single chain, as it is not compatible with free N‐ and C‐termini. Here we describe the computational design of mixed‐chirality peptide macrocycles with rigid structures that feature internal cyclic symmetries or improper rotational symmetries inaccessible to natural proteins. Crystal structures of three C2‐ and C3‐symmetric macrocycles, and of six diverse S2‐symmetric macrocycles, match the computationally‐designed models with backbone heavy‐atom RMSD values of 1 å or better. Crystal structures of an S4‐symmetric macrocycle (consisting of a sequence and structure segment mirrored at each of three successive repeats) designed to bind zinc reveal a large‐scale zinc‐driven conformational change from an S4‐symmetric apo‐state to a nearly inverted S4‐symmetric holo‐state almost identical to the design model. This work demonstrates the power of computational design for exploring symmetries and structures not found in nature, and for creating synthetic switchable systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cyclic symmetry is frequent in protein and peptide homo‐oligomers, but extremely rare within a single chain, as it is not compatible with free N‐ and C‐termini. Here we describe the computational design of mixed‐chirality peptide macrocycles with rigid structures that feature internal cyclic symmetries or improper rotational symmetries inaccessible to natural proteins. Crystal structures of three C2‐ and C3‐symmetric macrocycles, and of six diverse S2‐symmetric macrocycles, match the computationally‐designed models with backbone heavy‐atom RMSD values of 1 å or better. Crystal structures of an S4‐symmetric macrocycle (consisting of a sequence and structure segment mirrored at each of three successive repeats) designed to bind zinc reveal a large‐scale zinc‐driven conformational change from an S4‐symmetric apo‐state to a nearly inverted S4‐symmetric holo‐state almost identical to the design model. This work demonstrates the power of computational design for exploring symmetries and structures not found in nature, and for creating synthetic switchable systems.
Cao, Longxing, Goreshnik, Inna, Coventry, Brian, Case, James Brett, Miller, Lauren, Kozodoy, Lisa, Chen, Rita E., Carter, Lauren, Walls, Alexandra C., Park, Young-Jun, Strauch, Eva-Maria, Stewart, Lance, Diamond, Michael S., Veesler, David, Baker, David
De novo design of picomolar SARS-CoV-2 miniprotein inhibitors Journal Article
In: Science, 2020.
@article{Cao2020,
title = {De novo design of picomolar SARS-CoV-2 miniprotein inhibitors},
author = {Cao, Longxing and Goreshnik, Inna and Coventry, Brian and Case, James Brett and Miller, Lauren and Kozodoy, Lisa and Chen, Rita E. and Carter, Lauren and Walls, Alexandra C. and Park, Young-Jun and Strauch, Eva-Maria and Stewart, Lance and Diamond, Michael S. and Veesler, David and Baker, David},
url = {https://science.sciencemag.org/content/early/2020/09/08/science.abd9909
https://www.bakerlab.org/wp-content/uploads/2020/09/Cao_etal_Science_COVID_spike_binders.pdf},
doi = {10.1126/science.abd9909},
year = {2020},
date = {2020-09-09},
journal = {Science},
abstract = {Targeting the interaction between the SARS-CoV-2 Spike protein and the human ACE2 receptor is a promising therapeutic strategy. We designed inhibitors using two de novo design approaches. Computer generated scaffolds were either built around an ACE2 helix that interacts with the Spike receptor binding domain (RBD), or docked against the RBD to identify new binding modes, and their amino acid sequences designed to optimize target binding, folding and stability. Ten designs bound the RBD with affinities ranging from 100pM to 10nM, and blocked ARS-CoV-2 infection of Vero E6 cells with IC 50 values between 24 pM and 35 nM; The most potent, with new binding modes, are 56 and 64 residue proteins (IC 50 ~ 0.16 ng/ml). Cryo-electron microscopy structures of these minibinders in complex with the SARS-CoV-2 spike ectodomain trimer with all three RBDs bound are nearly identical to the computational models. These hyperstable minibinders provide starting points for SARS-CoV-2 therapeutics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Targeting the interaction between the SARS-CoV-2 Spike protein and the human ACE2 receptor is a promising therapeutic strategy. We designed inhibitors using two de novo design approaches. Computer generated scaffolds were either built around an ACE2 helix that interacts with the Spike receptor binding domain (RBD), or docked against the RBD to identify new binding modes, and their amino acid sequences designed to optimize target binding, folding and stability. Ten designs bound the RBD with affinities ranging from 100pM to 10nM, and blocked ARS-CoV-2 infection of Vero E6 cells with IC 50 values between 24 pM and 35 nM; The most potent, with new binding modes, are 56 and 64 residue proteins (IC 50 ~ 0.16 ng/ml). Cryo-electron microscopy structures of these minibinders in complex with the SARS-CoV-2 spike ectodomain trimer with all three RBDs bound are nearly identical to the computational models. These hyperstable minibinders provide starting points for SARS-CoV-2 therapeutics.
Chunfu Xu, Peilong Lu, Tamer M. Gamal El-Din, Xue Y. Pei, Matthew C. Johnson, Atsuko Uyeda, Matthew J. Bick, Qi Xu, Daohua Jiang, Hua Bai, Gabriella Reggiano, Yang Hsia, T J Brunette, Jiayi Dou, Dan Ma, Eric M. Lynch, Scott E. Boyken, Po-Ssu Huang, Lance Stewart, Frank DiMaio, Justin M. Kollman, Ben F. Luisi, Tomoaki Matsuura, William A. Catterall, David Baker
Computational design of transmembrane pores Journal Article
In: Nature, vol. 585, pp. 129–134, 2020.
@article{Xu2020,
title = {Computational design of transmembrane pores},
author = {Chunfu Xu and Peilong Lu and Tamer M. Gamal El-Din and Xue Y. Pei and Matthew C. Johnson and Atsuko Uyeda and Matthew J. Bick and Qi Xu and Daohua Jiang and Hua Bai and Gabriella Reggiano and Yang Hsia and T J Brunette and Jiayi Dou and Dan Ma and Eric M. Lynch and Scott E. Boyken and Po-Ssu Huang and Lance Stewart and Frank DiMaio and Justin M. Kollman and Ben F. Luisi and Tomoaki Matsuura and William A. Catterall and David Baker },
url = {https://www.bakerlab.org/wp-content/uploads/2020/08/Xuetal_Nature2020_DeNovoPores.pdf
https://www.nature.com/articles/s41586-020-2646-5},
doi = {10.1038/s41586-020-2646-5},
year = {2020},
date = {2020-08-26},
journal = {Nature},
volume = {585},
pages = {129–134},
abstract = {Transmembrane channels and pores have key roles in fundamental biological processes and in biotechnological applications such as DNA nanopore sequencing, resulting in considerable interest in the design of pore-containing proteins. Synthetic amphiphilic peptides have been found to form ion channels, and there have been recent advances in de novo membrane protein design and in redesigning naturally occurring channel-containing proteins. However, the de novo design of stable, well-defined transmembrane protein pores that are capable of conducting ions selectively or are large enough to enable the passage of small-molecule fluorophores remains an outstanding challenge. Here we report the computational design of protein pores formed by two concentric rings of α-helices that are stable and monodisperse in both their water-soluble and their transmembrane forms. Crystal structures of the water-soluble forms of a 12-helical pore and a 16-helical pore closely match the computational design models. Patch-clamp electrophysiology experiments show that, when expressed in insect cells, the transmembrane form of the 12-helix pore enables the passage of ions across the membrane with high selectivity for potassium over sodium; ion passage is blocked by specific chemical modification at the pore entrance. When incorporated into liposomes using in vitro protein synthesis, the transmembrane form of the 16-helix pore—but not the 12-helix pore—enables the passage of biotinylated Alexa Fluor 488. A cryo-electron microscopy structure of the 16-helix transmembrane pore closely matches the design model. The ability to produce structurally and functionally well-defined transmembrane pores opens the door to the creation of designer channels and pores for a wide variety of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Transmembrane channels and pores have key roles in fundamental biological processes and in biotechnological applications such as DNA nanopore sequencing, resulting in considerable interest in the design of pore-containing proteins. Synthetic amphiphilic peptides have been found to form ion channels, and there have been recent advances in de novo membrane protein design and in redesigning naturally occurring channel-containing proteins. However, the de novo design of stable, well-defined transmembrane protein pores that are capable of conducting ions selectively or are large enough to enable the passage of small-molecule fluorophores remains an outstanding challenge. Here we report the computational design of protein pores formed by two concentric rings of α-helices that are stable and monodisperse in both their water-soluble and their transmembrane forms. Crystal structures of the water-soluble forms of a 12-helical pore and a 16-helical pore closely match the computational design models. Patch-clamp electrophysiology experiments show that, when expressed in insect cells, the transmembrane form of the 12-helix pore enables the passage of ions across the membrane with high selectivity for potassium over sodium; ion passage is blocked by specific chemical modification at the pore entrance. When incorporated into liposomes using in vitro protein synthesis, the transmembrane form of the 16-helix pore—but not the 12-helix pore—enables the passage of biotinylated Alexa Fluor 488. A cryo-electron microscopy structure of the 16-helix transmembrane pore closely matches the design model. The ability to produce structurally and functionally well-defined transmembrane pores opens the door to the creation of designer channels and pores for a wide variety of applications.
Lajoie, Marc J. and Boyken, Scott E. and Salter, Alexander I. and Bruffey, Jilliane and Rajan, Anusha and Langan, Robert A. and Olshefsky, Audrey and Muhunthan, Vishaka and Bick, Matthew J. and Gewe, Mesfin and Quijano-Rubio, Alfredo and Johnson, JayLee and Lenz, Garreck and Nguyen, Alisha and Pun, Suzie and Correnti, Colin E. and Riddell, Stanley R. and Baker, David
Designed protein logic to target cells with precise combinations of surface antigens Journal Article
In: Science, 2020.
@article{Lajoie2020,
title = {Designed protein logic to target cells with precise combinations of surface antigens },
author = {Lajoie, Marc J. and
Boyken, Scott E. and
Salter, Alexander I. and
Bruffey, Jilliane and
Rajan, Anusha and
Langan, Robert A. and
Olshefsky, Audrey and
Muhunthan, Vishaka and
Bick, Matthew J. and
Gewe, Mesfin and
Quijano-Rubio, Alfredo and
Johnson, JayLee and
Lenz, Garreck and
Nguyen, Alisha and
Pun, Suzie and
Correnti, Colin E. and
Riddell, Stanley R. and
Baker, David},
url = {https://science.sciencemag.org/content/early/2020/08/19/science.aba6527
https://www.bakerlab.org/wp-content/uploads/2020/08/Lajoie-coLOCKR2020.pdf},
doi = {10.1126/science.aba6527},
year = {2020},
date = {2020-08-20},
journal = {Science},
abstract = {Precise cell targeting is challenging because most mammalian cell types lack a single surface marker that distinguishes them from other cells. A solution would be to target cells based on specific combinations of proteins present on their surfaces. We design colocalization-dependent protein switches (Co-LOCKR) that perform AND, OR, and NOT Boolean logic operations. These switches activate through a conformational change only when all conditions are met, generating rapid, transcription-independent responses at single-cell resolution within complex cell populations. We implement AND gates to redirect T cell specificity against tumor cells expressing two surface antigens while avoiding off-target recognition of single-antigen cells, and 3-input switches that add NOT or OR logic to avoid or include cells expressing a third antigen. Thus, de novo designed proteins can perform computations on the surface of cells, integrating multiple distinct binding interactions into a single output.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Precise cell targeting is challenging because most mammalian cell types lack a single surface marker that distinguishes them from other cells. A solution would be to target cells based on specific combinations of proteins present on their surfaces. We design colocalization-dependent protein switches (Co-LOCKR) that perform AND, OR, and NOT Boolean logic operations. These switches activate through a conformational change only when all conditions are met, generating rapid, transcription-independent responses at single-cell resolution within complex cell populations. We implement AND gates to redirect T cell specificity against tumor cells expressing two surface antigens while avoiding off-target recognition of single-antigen cells, and 3-input switches that add NOT or OR logic to avoid or include cells expressing a third antigen. Thus, de novo designed proteins can perform computations on the surface of cells, integrating multiple distinct binding interactions into a single output.
Basanta, Benjamin, Bick, Matthew J., Bera, Asim K., Norn, Christoffer, Chow, Cameron M., Carter, Lauren P., Goreshnik, Inna, Dimaio, Frank, Baker, David
An enumerative algorithm for de novo design of proteins with diverse pocket structures Journal Article
In: Proceedings of the National Academy of Sciences, vol. 117, no. 36, pp. 22135–22145, 2020, ISBN: 0027-8424.
@article{Basanta2020,
title = {An enumerative algorithm for de novo design of proteins with diverse pocket structures},
author = {Basanta, Benjamin and Bick, Matthew J. and Bera, Asim K. and Norn, Christoffer and Chow, Cameron M. and Carter, Lauren P. and Goreshnik, Inna and Dimaio, Frank and Baker, David},
url = {https://www.pnas.org/content/117/36/22135
https://www.bakerlab.org/wp-content/uploads/2020/12/Basanta_etal_2020_PNAS_enumerative-algorithm-for-de-novo-design-of-proteins-with-diverse-pocket-structures.pdf},
doi = {10.1073/pnas.2005412117},
isbn = {0027-8424},
year = {2020},
date = {2020-08-11},
journal = {Proceedings of the National Academy of Sciences},
volume = {117},
number = {36},
pages = {22135–22145},
abstract = {Reengineering naturally occurring proteins to have new functions has had considerable impact on industrial and biomedical applications, but is limited by the finite number of known proteins. A promise of de novo protein design is to generate a larger and more diverse set of protein structures than is currently available. This vision has not yet been realized for small-molecule binder or enzyme design due to the complexity of pocket-containing structures. Here we present an algorithm that systematically generates NTF2-like protein structures with diverse pocket geometries. The scaffold sets, the insights gained from detailed structural characterization, and the computational method for generating unlimited numbers of structures should contribute to a new generation of de novo small-molecule binding proteins and catalysts.To create new enzymes and biosensors from scratch, precise control over the structure of small-molecule binding sites is of paramount importance, but systematically designing arbitrary protein pocket shapes and sizes remains an outstanding challenge. Using the NTF2-like structural superfamily as a model system, we developed an enumerative algorithm for creating a virtually unlimited number of de novo proteins supporting diverse pocket structures. The enumerative algorithm was tested and refined through feedback from two rounds of large-scale experimental testing, involving in total the assembly of synthetic genes encoding 7,896 designs and assessment of their stability on yeast cell surface, detailed biophysical characterization of 64 designs, and crystal structures of 5 designs. The refined algorithm generates proteins that remain folded at high temperatures and exhibit more pocket diversity than naturally occurring NTF2-like proteins. We expect this approach to transform the design of small-molecule sensors and enzymes by enabling the creation of binding and active site geometries much more optimal for specific design challenges than is accessible by repurposing the limited number of naturally occurring NTF2-like proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Reengineering naturally occurring proteins to have new functions has had considerable impact on industrial and biomedical applications, but is limited by the finite number of known proteins. A promise of de novo protein design is to generate a larger and more diverse set of protein structures than is currently available. This vision has not yet been realized for small-molecule binder or enzyme design due to the complexity of pocket-containing structures. Here we present an algorithm that systematically generates NTF2-like protein structures with diverse pocket geometries. The scaffold sets, the insights gained from detailed structural characterization, and the computational method for generating unlimited numbers of structures should contribute to a new generation of de novo small-molecule binding proteins and catalysts.To create new enzymes and biosensors from scratch, precise control over the structure of small-molecule binding sites is of paramount importance, but systematically designing arbitrary protein pocket shapes and sizes remains an outstanding challenge. Using the NTF2-like structural superfamily as a model system, we developed an enumerative algorithm for creating a virtually unlimited number of de novo proteins supporting diverse pocket structures. The enumerative algorithm was tested and refined through feedback from two rounds of large-scale experimental testing, involving in total the assembly of synthetic genes encoding 7,896 designs and assessment of their stability on yeast cell surface, detailed biophysical characterization of 64 designs, and crystal structures of 5 designs. The refined algorithm generates proteins that remain folded at high temperatures and exhibit more pocket diversity than naturally occurring NTF2-like proteins. We expect this approach to transform the design of small-molecule sensors and enzymes by enabling the creation of binding and active site geometries much more optimal for specific design challenges than is accessible by repurposing the limited number of naturally occurring NTF2-like proteins.
Ueda, George, Antanasijevic, Aleksandar, Fallas, Jorge A, Sheffler, William, Copps, Jeffrey, Ellis, Daniel, Hutchinson, Geoffrey B, Moyer, Adam, Yasmeen, Anila, Tsybovsky, Yaroslav, Park, Young-Jun, Bick, Matthew J, Sankaran, Banumathi, Gillespie, Rebecca A, Brouwer, Philip JM, Zwart, Peter H, Veesler, David, Kanekiyo, Masaru, Graham, Barney S, Sanders, Rogier W, Moore, John P, Klasse, Per Johan, Ward, Andrew B, King, Neil P, Baker, David
Tailored design of protein nanoparticle scaffolds for multivalent presentation of viral glycoprotein antigens Journal Article
In: eLife, vol. 9, pp. e57659, 2020.
@article{Ueda2020,
title = {Tailored design of protein nanoparticle scaffolds for multivalent presentation of viral glycoprotein antigens},
author = {Ueda, George and Antanasijevic, Aleksandar and Fallas, Jorge A and Sheffler, William and Copps, Jeffrey and Ellis, Daniel and Hutchinson, Geoffrey B and Moyer, Adam and Yasmeen, Anila and Tsybovsky, Yaroslav and Park, Young-Jun and Bick, Matthew J and Sankaran, Banumathi and Gillespie, Rebecca A and Brouwer, Philip JM and Zwart, Peter H and Veesler, David and Kanekiyo, Masaru and Graham, Barney S and Sanders, Rogier W and Moore, John P and Klasse, Per Johan and Ward, Andrew B and King, Neil P and Baker, David},
url = {https://elifesciences.org/articles/57659},
doi = {10.7554/eLife.57659},
year = {2020},
date = {2020-08-04},
journal = {eLife},
volume = {9},
pages = {e57659},
abstract = {Multivalent presentation of viral glycoproteins can substantially increase the elicitation of antigen-specific antibodies. To enable a new generation of anti-viral vaccines, we designed self-assembling protein nanoparticles with geometries tailored to present the ectodomains of influenza, HIV, and RSV viral glycoprotein trimers. We first textit{de novo} designed trimers tailored for antigen fusion, featuring N-terminal helices positioned to match the C termini of the viral glycoproteins. Trimers that experimentally adopted their designed configurations were incorporated as components of tetrahedral, octahedral, and icosahedral nanoparticles, which were characterized by cryo-electron microscopy and assessed for their ability to present viral glycoproteins. Electron microscopy and antibody binding experiments demonstrated that the designed nanoparticles presented antigenically intact prefusion HIV-1 Env, influenza hemagglutinin, and RSV F trimers in the predicted geometries. This work demonstrates that antigen-displaying protein nanoparticles can be designed from scratch, and provides a systematic way to investigate the influence of antigen presentation geometry on the immune response to vaccination.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Multivalent presentation of viral glycoproteins can substantially increase the elicitation of antigen-specific antibodies. To enable a new generation of anti-viral vaccines, we designed self-assembling protein nanoparticles with geometries tailored to present the ectodomains of influenza, HIV, and RSV viral glycoprotein trimers. We first textit{de novo} designed trimers tailored for antigen fusion, featuring N-terminal helices positioned to match the C termini of the viral glycoproteins. Trimers that experimentally adopted their designed configurations were incorporated as components of tetrahedral, octahedral, and icosahedral nanoparticles, which were characterized by cryo-electron microscopy and assessed for their ability to present viral glycoproteins. Electron microscopy and antibody binding experiments demonstrated that the designed nanoparticles presented antigenically intact prefusion HIV-1 Env, influenza hemagglutinin, and RSV F trimers in the predicted geometries. This work demonstrates that antigen-displaying protein nanoparticles can be designed from scratch, and provides a systematic way to investigate the influence of antigen presentation geometry on the immune response to vaccination.
Brunette, TJ, Bick, Matthew J., Hansen, Jesse M., Chow, Cameron M., Kollman, Justin M., Baker, David
Modular repeat protein sculpting using rigid helical junctions Journal Article
In: Proceedings of the National Academy of Sciences, 2020.
@article{Brunette2020,
title = {Modular repeat protein sculpting using rigid helical junctions},
author = {Brunette, TJ and Bick, Matthew J. and Hansen, Jesse M. and Chow, Cameron M. and Kollman, Justin M. and Baker, David},
url = {https://www.bakerlab.org/wp-content/uploads/2020/04/Brunette2020_Junctions.pdf
https://www.pnas.org/content/early/2020/04/02/1908768117},
doi = {10.1073/pnas.1908768117},
year = {2020},
date = {2020-04-02},
journal = {Proceedings of the National Academy of Sciences},
abstract = {The ability to precisely design large proteins with diverse shapes would enable applications ranging from the design of protein binders that wrap around their target to the positioning of multiple functional sites in specified orientations. We describe a protein backbone design method for generating a wide range of rigid fusions between helix-containing proteins and use it to design 75,000 structurally unique junctions between monomeric and homo-oligomeric de novo designed and ankyrin repeat proteins (RPs). Of the junction designs that were experimentally characterized, 82% have circular dichroism and solution small-angle X-ray scattering profiles consistent with the design models and are stable at 95 °C. Crystal structures of four designed junctions were in close agreement with the design models with rmsds ranging from 0.9 to 1.6 Å. Electron microscopic images of extended tetrameric structures and ∼10-nm-diameter “L” and “V” shapes generated using the junctions are close to the design models, demonstrating the control the rigid junctions provide for protein shape sculpting over multiple nanometer length scales.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ability to precisely design large proteins with diverse shapes would enable applications ranging from the design of protein binders that wrap around their target to the positioning of multiple functional sites in specified orientations. We describe a protein backbone design method for generating a wide range of rigid fusions between helix-containing proteins and use it to design 75,000 structurally unique junctions between monomeric and homo-oligomeric de novo designed and ankyrin repeat proteins (RPs). Of the junction designs that were experimentally characterized, 82% have circular dichroism and solution small-angle X-ray scattering profiles consistent with the design models and are stable at 95 °C. Crystal structures of four designed junctions were in close agreement with the design models with rmsds ranging from 0.9 to 1.6 Å. Electron microscopic images of extended tetrameric structures and ∼10-nm-diameter “L” and “V” shapes generated using the junctions are close to the design models, demonstrating the control the rigid junctions provide for protein shape sculpting over multiple nanometer length scales.
Wei, Kathy Y., Moschidi, Danai, Bick, Matthew J., Nerli, Santrupti, McShan, Andrew C., Carter, Lauren P., Huang, Po-Ssu, Fletcher, Daniel A., Sgourakis, Nikolaos G., Boyken, Scott E., Baker, David
Computational design of closely related proteins that adopt two well-defined but structurally divergent folds Journal Article
In: Proceedings of the National Academy of Sciences, 2020.
@article{Wei2020,
title = {Computational design of closely related proteins that adopt two well-defined but structurally divergent folds},
author = {Wei, Kathy Y. and Moschidi, Danai and Bick, Matthew J. and Nerli, Santrupti and McShan, Andrew C. and Carter, Lauren P. and Huang, Po-Ssu and Fletcher, Daniel A. and Sgourakis, Nikolaos G. and Boyken, Scott E. and Baker, David
},
url = {https://www.pnas.org/content/early/2020/03/17/1914808117
https://www.ipd.uw.edu/wp-content/uploads/2020/03/Wei_PNAS_2020.pdf},
doi = {10.1073/pnas.1914808117},
year = {2020},
date = {2020-03-17},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Computational protein design has focused primarily on the design of sequences which fold to single stable states, but in biology many proteins adopt multiple states. We used de novo protein design to generate very closely related proteins that adopt two very different states—a short state and a long state, like a viral fusion protein—and then created a single molecule that can be found in both forms. Our proteins, poised between forms, are a starting point for the design of triggered shape changes.The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used for de novo design of proteins that fold to a single state with a deep free-energy minimum, and to reengineer natural proteins to alter their dynamics or fold, the de novo design of closely related sequences which adopt well-defined but structurally divergent structures remains an outstanding challenge. We designed closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations — one short (~66 Å height) and the other long (~100 Å height) — reminiscent of the conformational transition of viral fusion proteins. Crystallographic and NMR spectroscopic characterization shows that both the short- and long-state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large-scale conformational switches between structurally divergent forms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational protein design has focused primarily on the design of sequences which fold to single stable states, but in biology many proteins adopt multiple states. We used de novo protein design to generate very closely related proteins that adopt two very different states—a short state and a long state, like a viral fusion protein—and then created a single molecule that can be found in both forms. Our proteins, poised between forms, are a starting point for the design of triggered shape changes.The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used for de novo design of proteins that fold to a single state with a deep free-energy minimum, and to reengineer natural proteins to alter their dynamics or fold, the de novo design of closely related sequences which adopt well-defined but structurally divergent structures remains an outstanding challenge. We designed closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations — one short (~66 Å height) and the other long (~100 Å height) — reminiscent of the conformational transition of viral fusion proteins. Crystallographic and NMR spectroscopic characterization shows that both the short- and long-state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large-scale conformational switches between structurally divergent forms.
Chen, Zibo, Kibler, Ryan D., Hunt, Andrew, Busch, Florian, Pearl, Jocelynn, Jia, Mengxuan, VanAernum, Zachary L., Wicky, Basile I. M., Dods, Galen, Liao, Hanna, Wilken, Matthew S., Ciarlo, Christie, Green, Shon, El-Samad, Hana, Stamatoyannopoulos, John, Wysocki, Vicki H., Jewett, Michael C., Boyken, Scott E., Baker, David
De novo design of protein logic gates Journal Article
In: Science, vol. 368, no. 6486, pp. 78-84, 2020.
@article{Chen2020,
title = {De novo design of protein logic gates},
author = {Chen, Zibo and Kibler, Ryan D. and Hunt, Andrew and Busch, Florian and Pearl, Jocelynn and Jia, Mengxuan and VanAernum, Zachary L. and Wicky, Basile I. M. and Dods, Galen and Liao, Hanna and Wilken, Matthew S. and Ciarlo, Christie and Green, Shon and El-Samad, Hana and Stamatoyannopoulos, John and Wysocki, Vicki H. and Jewett, Michael C. and Boyken, Scott E. and Baker, David},
url = {https://science.sciencemag.org/content/368/6486/78
https://www.bakerlab.org/wp-content/uploads/2020/04/Chen2020_DeNovoProteinLogicGates.pdf},
doi = {10.1126/science.aay2790},
year = {2020},
date = {2020-03-04},
journal = {Science},
volume = {368},
number = {6486},
pages = {78-84},
abstract = {The design of modular protein logic for regulating protein function at the posttranscriptional level is a challenge for synthetic biology. Here, we describe the design of two-input AND, OR, NAND, NOR, XNOR, and NOT gates built from de novo–designed proteins. These gates regulate the association of arbitrary protein units ranging from split enzymes to transcriptional machinery in vitro, in yeast and in primary human T cells, where they control the expression of the TIM3 gene related to T cell exhaustion. Designed binding interaction cooperativity, confirmed by native mass spectrometry, makes the gates largely insensitive to stoichiometric imbalances in the inputs, and the modularity of the approach enables ready extension to three-input OR, AND, and disjunctive normal form gates. The modularity and cooperativity of the control elements, coupled with the ability to de novo design an essentially unlimited number of protein components, should enable the design of sophisticated posttranslational control logic over a wide range of biological functions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The design of modular protein logic for regulating protein function at the posttranscriptional level is a challenge for synthetic biology. Here, we describe the design of two-input AND, OR, NAND, NOR, XNOR, and NOT gates built from de novo–designed proteins. These gates regulate the association of arbitrary protein units ranging from split enzymes to transcriptional machinery in vitro, in yeast and in primary human T cells, where they control the expression of the TIM3 gene related to T cell exhaustion. Designed binding interaction cooperativity, confirmed by native mass spectrometry, makes the gates largely insensitive to stoichiometric imbalances in the inputs, and the modularity of the approach enables ready extension to three-input OR, AND, and disjunctive normal form gates. The modularity and cooperativity of the control elements, coupled with the ability to de novo design an essentially unlimited number of protein components, should enable the design of sophisticated posttranslational control logic over a wide range of biological functions.
Yang, Jianyi, Anishchenko, Ivan, Park, Hahnbeom, Peng, Zhenling, Ovchinnikov, Sergey, Baker, David
Improved protein structure prediction using predicted interresidue orientations Journal Article
In: Proceedings of the National Academy of Sciences, 2020, ISBN: 0027-8424.
@article{Yang2020,
title = {Improved protein structure prediction using predicted interresidue orientations},
author = {Yang, Jianyi and Anishchenko, Ivan and Park, Hahnbeom and Peng, Zhenling and Ovchinnikov, Sergey and Baker, David},
url = {https://www.pnas.org/content/early/2020/01/01/1914677117
https://www.bakerlab.org/wp-content/uploads/2020/01/Yang2020_ImprovedStructurePredictionInterresidueOrientations.pdf
},
doi = {10.1073/pnas.1914677117},
isbn = {0027-8424},
year = {2020},
date = {2020-01-02},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Protein structure prediction is a longstanding challenge in computational biology. Through extension of deep learning-based prediction to interresidue orientations in addition to distances, and the development of a constrained optimization by Rosetta, we show that more accurate models can be generated. Results on a set of 18 de novo-designed proteins suggests the proposed method should be directly applicable to current challenges in de novo protein design.The prediction of interresidue contacts and distances from coevolutionary data using deep learning has considerably advanced protein structure prediction. Here, we build on these advances by developing a deep residual network for predicting interresidue orientations, in addition to distances, and a Rosetta-constrained energy-minimization protocol for rapidly and accurately generating structure models guided by these restraints. In benchmark tests on 13th Community-Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP13)- and Continuous Automated Model Evaluation (CAMEO)-derived sets, the method outperforms all previously described structure-prediction methods. Although trained entirely on native proteins, the network consistently assigns higher probability to de novo-designed proteins, identifying the key fold-determining residues and providing an independent quantitative measure of the "ideality" of a protein structure. The method promises to be useful for a broad range of protein structure prediction and design problems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein structure prediction is a longstanding challenge in computational biology. Through extension of deep learning-based prediction to interresidue orientations in addition to distances, and the development of a constrained optimization by Rosetta, we show that more accurate models can be generated. Results on a set of 18 de novo-designed proteins suggests the proposed method should be directly applicable to current challenges in de novo protein design.The prediction of interresidue contacts and distances from coevolutionary data using deep learning has considerably advanced protein structure prediction. Here, we build on these advances by developing a deep residual network for predicting interresidue orientations, in addition to distances, and a Rosetta-constrained energy-minimization protocol for rapidly and accurately generating structure models guided by these restraints. In benchmark tests on 13th Community-Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP13)- and Continuous Automated Model Evaluation (CAMEO)-derived sets, the method outperforms all previously described structure-prediction methods. Although trained entirely on native proteins, the network consistently assigns higher probability to de novo-designed proteins, identifying the key fold-determining residues and providing an independent quantitative measure of the "ideality" of a protein structure. The method promises to be useful for a broad range of protein structure prediction and design problems.
COLLABORATOR LED
Caldwell, Shane J., Haydon, Ian C., Piperidou, Nikoletta, Huang, Po-Ssu, Bick, Matthew J., Sjöström, H. Sebastian, Hilvert, Donald, Baker, David, Zeymer, Cathleen
Tight and specific lanthanide binding in a de novo TIM barrel with a large internal cavity designed by symmetric domain fusion Journal Article
In: Proceedings of the National Academy of Sciences, 2020.
@article{Caldwell2020,
title = {Tight and specific lanthanide binding in a de novo TIM barrel with a large internal cavity designed by symmetric domain fusion},
author = {Caldwell, Shane J. and Haydon, Ian C. and Piperidou, Nikoletta and Huang, Po-Ssu and Bick, Matthew J. and Sjöström, H. Sebastian and Hilvert, Donald and Baker, David and Zeymer, Cathleen
},
url = {https://www.bakerlab.org/wp-content/uploads/2020/11/Caldwell_et_al_PNAS_TIM_barrel_metal_binding.pdf
https://www.pnas.org/content/early/2020/11/13/2008535117},
doi = {10.1073/pnas.2008535117},
year = {2020},
date = {2020-11-17},
journal = {Proceedings of the National Academy of Sciences},
abstract = {De novo protein design has succeeded in generating a large variety of globular proteins, but the construction of protein scaffolds with cavities that could accommodate large signaling molecules, cofactors, and substrates remains an outstanding challenge. The long, often flexible loops that form such cavities in many natural proteins are difficult to precisely program and thus challenging for computational protein design. Here we describe an alternative approach to this problem. We fused two stable proteins with C2 symmetry—a de novo designed dimeric ferredoxin fold and a de novo designed TIM barrel—such that their symmetry axes are aligned to create scaffolds with large cavities that can serve as binding pockets or enzymatic reaction chambers. The crystal structures of two such designs confirm the presence of a 420 cubic Ångström chamber defined by the top of the designed TIM barrel and the bottom of the ferredoxin dimer. We functionalized the scaffold by installing a metal-binding site consisting of four glutamate residues close to the symmetry axis. The protein binds lanthanide ions with very high affinity as demonstrated by tryptophan-enhanced terbium luminescence. This approach can be extended to other metals and cofactors, making this scaffold a modular platform for the design of binding proteins and biocatalysts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
De novo protein design has succeeded in generating a large variety of globular proteins, but the construction of protein scaffolds with cavities that could accommodate large signaling molecules, cofactors, and substrates remains an outstanding challenge. The long, often flexible loops that form such cavities in many natural proteins are difficult to precisely program and thus challenging for computational protein design. Here we describe an alternative approach to this problem. We fused two stable proteins with C2 symmetry—a de novo designed dimeric ferredoxin fold and a de novo designed TIM barrel—such that their symmetry axes are aligned to create scaffolds with large cavities that can serve as binding pockets or enzymatic reaction chambers. The crystal structures of two such designs confirm the presence of a 420 cubic Ångström chamber defined by the top of the designed TIM barrel and the bottom of the ferredoxin dimer. We functionalized the scaffold by installing a metal-binding site consisting of four glutamate residues close to the symmetry axis. The protein binds lanthanide ions with very high affinity as demonstrated by tryptophan-enhanced terbium luminescence. This approach can be extended to other metals and cofactors, making this scaffold a modular platform for the design of binding proteins and biocatalysts.
Robin L. Kirkpatrick, Kieran Lewis, Robert A. Langan, Marc J. Lajoie, Scott E. Boyken, Madeleine Eakman, David Baker, Jesse G. Zalatan
Conditional Recruitment to a DNA-Bound CRISPR–Cas Complex Using a Colocalization-Dependent Protein Switch Journal Article
In: ACS Synthetic Biology, 2020.
@article{Kirkpatrick2020,
title = {Conditional Recruitment to a DNA-Bound CRISPR–Cas Complex Using a Colocalization-Dependent Protein Switch},
author = {Robin L. Kirkpatrick and Kieran Lewis and Robert A. Langan and Marc J. Lajoie and Scott E. Boyken and Madeleine Eakman and David Baker and Jesse G. Zalatan},
url = {https://pubs.acs.org/doi/full/10.1021/acssynbio.0c00012
https://www.bakerlab.org/wp-content/uploads/2020/08/Kirkpatrick2020-LOCKR-CRISPR.pdf},
doi = {10.1021/acssynbio.0c00012},
year = {2020},
date = {2020-08-20},
journal = {ACS Synthetic Biology},
abstract = {To spatially control biochemical functions at specific sites within a genome, we have engineered a synthetic switch that activates when bound to its DNA target site. The system uses two CRISPR–Cas complexes to colocalize components of a de novo-designed protein switch (Co-LOCKR) to adjacent sites in the genome. Colocalization triggers a conformational change in the switch from an inactive closed state to an active open state with an exposed functional peptide. We prototype the system in yeast and demonstrate that DNA binding triggers activation of the switch, recruitment of a transcription factor, and expression of a downstream reporter gene. This DNA-triggered Co-LOCKR switch provides a platform to engineer sophisticated functions that should only be executed at a specific target site within the genome, with potential applications in a wide range of synthetic systems including epigenetic regulation, imaging, and genetic logic circuits.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To spatially control biochemical functions at specific sites within a genome, we have engineered a synthetic switch that activates when bound to its DNA target site. The system uses two CRISPR–Cas complexes to colocalize components of a de novo-designed protein switch (Co-LOCKR) to adjacent sites in the genome. Colocalization triggers a conformational change in the switch from an inactive closed state to an active open state with an exposed functional peptide. We prototype the system in yeast and demonstrate that DNA binding triggers activation of the switch, recruitment of a transcription factor, and expression of a downstream reporter gene. This DNA-triggered Co-LOCKR switch provides a platform to engineer sophisticated functions that should only be executed at a specific target site within the genome, with potential applications in a wide range of synthetic systems including epigenetic regulation, imaging, and genetic logic circuits.
2019
FROM THE LAB
Park, Jooyoung, Selvaraj, Brinda, McShan, Andrew C, Boyken, Scott E, Wei, Kathy Y, Oberdorfer, Gustav, DeGrado, William, Sgourakis, Nikolaos G, Cuneo, Matthew J, Myles, Dean AA, Baker, David
De novo design of a homo-trimeric amantadine-binding protein Journal Article
In: eLife, 2019.
@article{Park2019b,
title = {De novo design of a homo-trimeric amantadine-binding protein},
author = {Park, Jooyoung and Selvaraj, Brinda and McShan, Andrew C and Boyken, Scott E and Wei, Kathy Y and Oberdorfer, Gustav and DeGrado, William and Sgourakis, Nikolaos G and Cuneo, Matthew J and Myles, Dean AA and Baker, David
},
editor = {Wolberger, Cynthia and Fleishman, Sarel Jacob and Anderson, Ross},
url = {https://elifesciences.org/articles/47839.pdf},
doi = {10.7554/eLife.47839},
year = {2019},
date = {2019-12-19},
journal = {eLife},
abstract = {The computational design of a symmetric protein homo-oligomer that binds a symmetry-matched small molecule larger than a metal ion has not yet been achieved. We used de novo protein design to create a homo-trimeric protein that binds the Ctextsubscript{3} symmetric small molecule drug amantadine with each protein monomer making identical interactions with each face of the small molecule. Solution NMR data show that the protein has regular three-fold symmetry and undergoes localized structural changes upon ligand binding. A high-resolution X-ray structure reveals a close overall match to the design model with the exception of water molecules in the amantadine binding site not included in the Rosetta design calculations, and a neutron structure provides experimental validation of the computationally designed hydrogen-bond networks. Exploration of approaches to generate a small molecule inducible homo-trimerization system based on the design highlight challenges that must be overcome to computationally design such systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The computational design of a symmetric protein homo-oligomer that binds a symmetry-matched small molecule larger than a metal ion has not yet been achieved. We used de novo protein design to create a homo-trimeric protein that binds the Ctextsubscript{3} symmetric small molecule drug amantadine with each protein monomer making identical interactions with each face of the small molecule. Solution NMR data show that the protein has regular three-fold symmetry and undergoes localized structural changes upon ligand binding. A high-resolution X-ray structure reveals a close overall match to the design model with the exception of water molecules in the amantadine binding site not included in the Rosetta design calculations, and a neutron structure provides experimental validation of the computationally designed hydrogen-bond networks. Exploration of approaches to generate a small molecule inducible homo-trimerization system based on the design highlight challenges that must be overcome to computationally design such systems.
Brian D. Weitzner, Yakov Kipnis, A. Gerard Daniel, Donald Hilvert, David Baker
A computational method for design of connected catalytic networks in proteins Journal Article
In: Protein Science, 2019.
@article{Weitzner2019,
title = {A computational method for design of connected catalytic networks in proteins},
author = {Brian D. Weitzner, Yakov Kipnis, A. Gerard Daniel, Donald Hilvert, David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pro.3757
https://www.bakerlab.org/wp-content/uploads/2020/02/Weitzner_et_al-2019-Protein_Science-1.pdf},
doi = {DOI10.1002/pro .3757},
year = {2019},
date = {2019-10-23},
journal = {Protein Science},
abstract = {Computational design of new active sites has generally proceeded by geometrically defining interactions between the reaction transition state(s) and surrounding side-chain functional groups which maximize transition-state stabilization, and then searching for sites in protein scaffolds where the specified side-chain–transition-state interactions can be realized. A limitation of this approach is that the interactions between the side chains themselves are not constrained. An extensive connected hydrogen bond network involving the catalytic residues was observed in a designed retroaldolase following directed evolution. Such connected networks could increase catalytic activity by preorganizing active site residues in catalytically competent orientations, and enabling concerted interactions between side chains during catalysis, for example proton shuffling. We developed a method for designing active sites in which the catalytic side chains, in addition to making interactions with the transition state, are also involved in extensive hydrogen bond networks. Because of the added constraint of hydrogen-bond connectivity between the catalytic side chains, to find solutions, a wider range of interactions between these side chains and the transition state must be considered. Our new method starts from a ChemDraw-like 2D representation of the transition state with hydrogen-bond donors, acceptors, and covalent interaction sites indicated, and all placements of side-chain functional groups that make the indicated interactions with the transition state, and are fully connected in a single hydrogen-bond network are systematically enumerated. The RosettaMatch method can then be used to identify realizations of these fully-connected active sites in protein scaffolds. The method generates many fully-connected active site solutions for a set of model reactions that are promising starting points for the design of fully-preorganized enzyme catalysts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational design of new active sites has generally proceeded by geometrically defining interactions between the reaction transition state(s) and surrounding side-chain functional groups which maximize transition-state stabilization, and then searching for sites in protein scaffolds where the specified side-chain–transition-state interactions can be realized. A limitation of this approach is that the interactions between the side chains themselves are not constrained. An extensive connected hydrogen bond network involving the catalytic residues was observed in a designed retroaldolase following directed evolution. Such connected networks could increase catalytic activity by preorganizing active site residues in catalytically competent orientations, and enabling concerted interactions between side chains during catalysis, for example proton shuffling. We developed a method for designing active sites in which the catalytic side chains, in addition to making interactions with the transition state, are also involved in extensive hydrogen bond networks. Because of the added constraint of hydrogen-bond connectivity between the catalytic side chains, to find solutions, a wider range of interactions between these side chains and the transition state must be considered. Our new method starts from a ChemDraw-like 2D representation of the transition state with hydrogen-bond donors, acceptors, and covalent interaction sites indicated, and all placements of side-chain functional groups that make the indicated interactions with the transition state, and are fully connected in a single hydrogen-bond network are systematically enumerated. The RosettaMatch method can then be used to identify realizations of these fully-connected active sites in protein scaffolds. The method generates many fully-connected active site solutions for a set of model reactions that are promising starting points for the design of fully-preorganized enzyme catalysts.
Langan, Robert A. , Boyken, Scott E. , Ng, Andrew H. , Samson, Jennifer A. , Dods, Galen , Westbrook, Alexandra M. , Nguyen, Taylor H. , Lajoie, Marc J. , Chen, Zibo , Berger, Stephanie , Mulligan, Vikram Khipple , Dueber, John E. , Novak, Walter R. P. , El-Samad, Hana , Baker, David
De novo design of bioactive protein switches Journal Article
In: Nature, 2019.
@article{Langan2019,
title = {De novo design of bioactive protein switches},
author = {Langan, Robert A.
and Boyken, Scott E.
and Ng, Andrew H.
and Samson, Jennifer A.
and Dods, Galen
and Westbrook, Alexandra M.
and Nguyen, Taylor H.
and Lajoie, Marc J.
and Chen, Zibo
and Berger, Stephanie
and Mulligan, Vikram Khipple
and Dueber, John E.
and Novak, Walter R. P.
and El-Samad, Hana
and Baker, David},
url = {https://doi.org/10.1038/s41586-019-1432-8
https://www.nature.com/articles/s41586-019-1432-8
https://www.bakerlab.org/wp-content/uploads/2019/07/Langan_LOCKR.pdf},
doi = {10.1038/s41586-019-1432-8},
year = {2019},
date = {2019-07-24},
journal = {Nature},
abstract = {Allosteric regulation of protein function is widespread in biology, but is challenging for de novo protein design as it requires the explicit design of multiple states with comparable free energies. Here we explore the possibility of designing switchable protein systems de novo, through the modulation of competing inter- and intramolecular interactions. We design a static, five-helix ‘cage’ with a single interface that can interact either intramolecularly with a terminal ‘latch’ helix or intermolecularly with a peptide ‘key’. Encoded on the latch are functional motifs for binding, degradation or nuclear export that function only when the key displaces the latch from the cage. We describe orthogonal cage–key systems that function in vitro, in yeast and in mammalian cells with up to 40-fold activation of function by key. The ability to design switchable protein functions that are controlled by induced conformational change is a milestone for de novo protein design, and opens up new avenues for synthetic biology and cell engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Allosteric regulation of protein function is widespread in biology, but is challenging for de novo protein design as it requires the explicit design of multiple states with comparable free energies. Here we explore the possibility of designing switchable protein systems de novo, through the modulation of competing inter- and intramolecular interactions. We design a static, five-helix ‘cage’ with a single interface that can interact either intramolecularly with a terminal ‘latch’ helix or intermolecularly with a peptide ‘key’. Encoded on the latch are functional motifs for binding, degradation or nuclear export that function only when the key displaces the latch from the cage. We describe orthogonal cage–key systems that function in vitro, in yeast and in mammalian cells with up to 40-fold activation of function by key. The ability to design switchable protein functions that are controlled by induced conformational change is a milestone for de novo protein design, and opens up new avenues for synthetic biology and cell engineering.
Ng, Andrew H. and Nguyen, Taylor H. and Gómez-Schiavon, Mariana and Dods, Galen and Langan, Robert A. and Boyken, Scott E. and Samson, Jennifer A. and Waldburger, Lucas M. and Dueber, John E. and Baker, David and El-Samad, Hana
Modular and tunable biological feedback control using a de novo protein switch Journal Article
In: Nature, 2019.
@article{Ng2019,
title = {Modular and tunable biological feedback control using a de novo protein switch},
author = {Ng, Andrew H.
and Nguyen, Taylor H.
and Gómez-Schiavon, Mariana
and Dods, Galen
and Langan, Robert A.
and Boyken, Scott E.
and Samson, Jennifer A.
and Waldburger, Lucas M.
and Dueber, John E.
and Baker, David
and El-Samad, Hana},
url = {https://doi.org/10.1038/s41586-019-1425-7
https://www.nature.com/articles/s41586-019-1425-7
https://www.bakerlab.org/wp-content/uploads/2019/07/Ng_LOCKR_circuits.pdf},
doi = {10.1038/s41586-019-1425-7},
year = {2019},
date = {2019-07-24},
journal = {Nature},
abstract = {De novo-designed proteins1–3 hold great promise as building blocks for synthetic circuits, and can complement the use of engineered variants of natural proteins4–7. One such designer protein—degronLOCKR, which is based on ‘latching orthogonal cage–key proteins’ (LOCKR) technology8—is a switch that degrades a protein of interest in vivo upon induction by a genetically encoded small peptide. Here we leverage the plug-and-play nature of degronLOCKR to implement feedback control of endogenous signalling pathways and synthetic gene circuits. We first generate synthetic negative and positive feedback in the yeast mating pathway by fusing degronLOCKR to endogenous signalling molecules, illustrating the ease with which this strategy can be used to rewire complex endogenous pathways. We next evaluate feedback control mediated by degronLOCKR on a synthetic gene circuit9, to quantify the feedback capabilities and operational range of the feedback control circuit. The designed nature of degronLOCKR proteins enables simple and rational modifications to tune feedback behaviour in both the synthetic circuit and the mating pathway. The ability to engineer feedback control into living cells represents an important milestone in achieving the full potential of synthetic biology10,11,12. More broadly, this work demonstrates the large and untapped potential of de novo design of proteins for generating tools that implement complex synthetic functionalities in cells for biotechnological and therapeutic applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
De novo-designed proteins1–3 hold great promise as building blocks for synthetic circuits, and can complement the use of engineered variants of natural proteins4–7. One such designer protein—degronLOCKR, which is based on ‘latching orthogonal cage–key proteins’ (LOCKR) technology8—is a switch that degrades a protein of interest in vivo upon induction by a genetically encoded small peptide. Here we leverage the plug-and-play nature of degronLOCKR to implement feedback control of endogenous signalling pathways and synthetic gene circuits. We first generate synthetic negative and positive feedback in the yeast mating pathway by fusing degronLOCKR to endogenous signalling molecules, illustrating the ease with which this strategy can be used to rewire complex endogenous pathways. We next evaluate feedback control mediated by degronLOCKR on a synthetic gene circuit9, to quantify the feedback capabilities and operational range of the feedback control circuit. The designed nature of degronLOCKR proteins enables simple and rational modifications to tune feedback behaviour in both the synthetic circuit and the mating pathway. The ability to engineer feedback control into living cells represents an important milestone in achieving the full potential of synthetic biology10,11,12. More broadly, this work demonstrates the large and untapped potential of de novo design of proteins for generating tools that implement complex synthetic functionalities in cells for biotechnological and therapeutic applications.
Hahnbeom Park, Gyu Rie Lee, David E. Kim, Ivan Anishchanka, Qian Cong, David Baker
High‐accuracy refinement using Rosetta in CASP13 Journal Article
In: Proteins, 2019.
@article{Park2019,
title = {High‐accuracy refinement using Rosetta in CASP13},
author = {Hahnbeom Park and Gyu Rie Lee and David E. Kim and Ivan Anishchanka and Qian Cong and David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.25784},
doi = {10.1002/prot.25784},
year = {2019},
date = {2019-07-20},
journal = {Proteins},
abstract = {Because proteins generally fold to their lowest free energy states, energy‐guided refinement in principle should be able to systematically improve the quality of protein structure models generated using homologous structure or co‐evolution derived information. However, because of the high dimensionality of the search space, there are far more ways to degrade the quality of a near native model than to improve it, and hence refinement methods are very sensitive to energy function errors. In CASP13, we sought to carry out a thorough search for low energy states in the neighborhood of a starting model using restraints to avoid straying too far. The approach was reasonably successful in improving both regions largely incorrect in the starting models as well core regions that started out closer to the correct structure. Models with GDT‐HA over 70 were obtained for five targets and for one of those, an accuracy of 0.5 å backbone RMSD was achieved. An important current challenge is to improve performance in refining oligomers and/or larger proteins, for which the search problem remains extremely difficult.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Because proteins generally fold to their lowest free energy states, energy‐guided refinement in principle should be able to systematically improve the quality of protein structure models generated using homologous structure or co‐evolution derived information. However, because of the high dimensionality of the search space, there are far more ways to degrade the quality of a near native model than to improve it, and hence refinement methods are very sensitive to energy function errors. In CASP13, we sought to carry out a thorough search for low energy states in the neighborhood of a starting model using restraints to avoid straying too far. The approach was reasonably successful in improving both regions largely incorrect in the starting models as well core regions that started out closer to the correct structure. Models with GDT‐HA over 70 were obtained for five targets and for one of those, an accuracy of 0.5 å backbone RMSD was achieved. An important current challenge is to improve performance in refining oligomers and/or larger proteins, for which the search problem remains extremely difficult.
Qian Cong, Ivan Anishchenko, Sergey Ovchinnikov, David Baker
Protein interaction networks revealed by proteome coevolution Journal Article
In: Science, 2019.
@article{Cong2019,
title = {Protein interaction networks revealed by proteome coevolution},
author = {Qian Cong and Ivan Anishchenko and Sergey Ovchinnikov and David Baker},
url = {https://science.sciencemag.org/content/365/6449/185
https://www.bakerlab.org/wp-content/uploads/2019/07/2019_Cong_ProteomeCoevolution.pdf},
doi = {10.1126/science.aaw6718},
year = {2019},
date = {2019-07-11},
journal = {Science},
abstract = {Residue-residue coevolution has been observed across a number of protein-protein interfaces, but the extent of residue coevolution between protein families on the whole-proteome scale has not been systematically studied. We investigate coevolution between 5.4 million pairs of proteins in Escherichia coli and between 3.9 millions pairs in Mycobacterium tuberculosis. We find strong coevolution for binary complexes involved in metabolism and weaker coevolution for larger complexes playing roles in genetic information processing. We take advantage of this coevolution, in combination with structure modeling, to predict protein-protein interactions (PPIs) with an accuracy that benchmark studies suggest is considerably higher than that of proteome-wide two-hybrid and mass spectrometry screens. We identify hundreds of previously uncharacterized PPIs in E. coli and M. tuberculosis that both add components to known protein complexes and networks and establish the existence of new ones.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Residue-residue coevolution has been observed across a number of protein-protein interfaces, but the extent of residue coevolution between protein families on the whole-proteome scale has not been systematically studied. We investigate coevolution between 5.4 million pairs of proteins in Escherichia coli and between 3.9 millions pairs in Mycobacterium tuberculosis. We find strong coevolution for binary complexes involved in metabolism and weaker coevolution for larger complexes playing roles in genetic information processing. We take advantage of this coevolution, in combination with structure modeling, to predict protein-protein interactions (PPIs) with an accuracy that benchmark studies suggest is considerably higher than that of proteome-wide two-hybrid and mass spectrometry screens. We identify hundreds of previously uncharacterized PPIs in E. coli and M. tuberculosis that both add components to known protein complexes and networks and establish the existence of new ones.
Harley Pyles, Shuai Zhang, James J. De Yoreo, David Baker
Controlling protein assembly on inorganic crystals through designed protein interfaces Journal Article
In: Nature, 2019.
@article{Pyles2019,
title = {Controlling protein assembly on inorganic crystals through designed protein interfaces},
author = {Harley Pyles and Shuai Zhang and James J. De Yoreo and David Baker },
url = {https://www.nature.com/articles/s41586-019-1361-6
https://www.bakerlab.org/wp-content/uploads/2019/07/2019_Pyles_MicaBinder.pdf},
doi = {10.1038/s41586-019-1361-6},
year = {2019},
date = {2019-07-10},
journal = {Nature},
abstract = {The ability of proteins and other macromolecules to interact with inorganic surfaces is essential to biological function. The proteins involved in these interactions are highly charged and often rich in carboxylic acid side chains, but the structures of most protein–inorganic interfaces are unknown. We explored the possibility of systematically designing structured protein–mineral interfaces, guided by the example of ice-binding proteins, which present arrays of threonine residues (matched to the ice lattice) that order clathrate waters into an ice-like structure6. Here we design proteins displaying arrays of up to 54 carboxylate residues geometrically matched to the potassium ion (K+) sublattice on muscovite mica (001). At low K+ concentration, individual molecules bind independently to mica in the designed orientations, whereas at high K+ concentration, the designs form two-dimensional liquid-crystal phases, which accentuate the inherent structural bias in the muscovite lattice to produce protein arrays ordered over tens of millimetres. Incorporation of designed protein–protein interactions preserving the match between the proteins and the K+ lattice led to extended self-assembled structures on mica: designed end-to-end interactions produced micrometre-long single-protein-diameter wires and a designed trimeric interface yielded extensive honeycomb arrays. The nearest-neighbour distances in these hexagonal arrays could be set digitally between 7.5 and 15.9 nanometres with 2.1-nanometre selectivity by changing the number of repeat units in the monomer. These results demonstrate that protein–inorganic lattice interactions can be systematically programmed and set the stage for designing protein–inorganic hybrid materials.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ability of proteins and other macromolecules to interact with inorganic surfaces is essential to biological function. The proteins involved in these interactions are highly charged and often rich in carboxylic acid side chains, but the structures of most protein–inorganic interfaces are unknown. We explored the possibility of systematically designing structured protein–mineral interfaces, guided by the example of ice-binding proteins, which present arrays of threonine residues (matched to the ice lattice) that order clathrate waters into an ice-like structure6. Here we design proteins displaying arrays of up to 54 carboxylate residues geometrically matched to the potassium ion (K+) sublattice on muscovite mica (001). At low K+ concentration, individual molecules bind independently to mica in the designed orientations, whereas at high K+ concentration, the designs form two-dimensional liquid-crystal phases, which accentuate the inherent structural bias in the muscovite lattice to produce protein arrays ordered over tens of millimetres. Incorporation of designed protein–protein interactions preserving the match between the proteins and the K+ lattice led to extended self-assembled structures on mica: designed end-to-end interactions produced micrometre-long single-protein-diameter wires and a designed trimeric interface yielded extensive honeycomb arrays. The nearest-neighbour distances in these hexagonal arrays could be set digitally between 7.5 and 15.9 nanometres with 2.1-nanometre selectivity by changing the number of repeat units in the monomer. These results demonstrate that protein–inorganic lattice interactions can be systematically programmed and set the stage for designing protein–inorganic hybrid materials.
Koepnick, Brian and Flatten, Jeff and Husain, Tamir and Ford, Alex and Silva, Daniel-Adriano and Bick, Matthew J. and Bauer, Aaron and Liu, Gaohua and Ishida, Yojiro and Boykov, Alexander and Estep, Roger D. and Kleinfelter, Susan and Nørgård-Solano, Toke and Wei, Linda and Players, Foldit and Montelione, Gaetano T. and DiMaio, Frank and Popović, Zoran and Khatib, Firas and Cooper, Seth and Baker, David
De novo protein design by citizen scientists Journal Article
In: Nature, 2019.
@article{Koepnick2019,
title = {De novo protein design by citizen scientists},
author = {Koepnick, Brian
and Flatten, Jeff
and Husain, Tamir
and Ford, Alex
and Silva, Daniel-Adriano
and Bick, Matthew J.
and Bauer, Aaron
and Liu, Gaohua
and Ishida, Yojiro
and Boykov, Alexander
and Estep, Roger D.
and Kleinfelter, Susan
and Nørgård-Solano, Toke
and Wei, Linda
and Players, Foldit
and Montelione, Gaetano T.
and DiMaio, Frank
and Popović, Zoran
and Khatib, Firas
and Cooper, Seth
and Baker, David},
url = {https://doi.org/10.1038/s41586-019-1274-4
https://www.bakerlab.org/wp-content/uploads/2019/06/Koepnick_Nature2019_FolditDesign.pdf},
doi = {10.1038/s41586-019-1274-4},
year = {2019},
date = {2019-06-05},
journal = {Nature},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Boyken, Scott E., Benhaim, Mark A., Busch, Florian, Jia, Mengxuan, Bick, Matthew J., Choi, Heejun, Klima, Jason C., Chen, Zibo, Walkey, Carl, Mileant, Alexander, Sahasrabuddhe, Aniruddha, Wei, Kathy Y., Hodge, Edgar A., Byron, Sarah, Quijano-Rubio, Alfredo, Sankaran, Banumathi, King, Neil P., Lippincott-Schwartz, Jennifer, Wysocki, Vicki H., Lee, Kelly K., Baker, David
De novo design of tunable, pH-driven conformational changes Journal Article
In: Science, vol. 364, no. 6441, pp. 658-664, 2019.
@article{Boyken2019,
title = {De novo design of tunable, pH-driven conformational changes},
author = {Boyken, Scott E. and Benhaim, Mark A. and Busch, Florian and Jia, Mengxuan and Bick, Matthew J. and Choi, Heejun and Klima, Jason C. and Chen, Zibo and Walkey, Carl and Mileant, Alexander and Sahasrabuddhe, Aniruddha and Wei, Kathy Y. and Hodge, Edgar A. and Byron, Sarah and Quijano-Rubio, Alfredo and Sankaran, Banumathi and King, Neil P. and Lippincott-Schwartz, Jennifer and Wysocki, Vicki H. and Lee, Kelly K. and Baker, David
},
url = {https://science.sciencemag.org/content/364/6441/658
https://www.bakerlab.org/wp-content/uploads/2019/06/Boyken_etal2019_pH_conformational_changes.pdf},
doi = {10.1126/science.aav7897},
year = {2019},
date = {2019-05-17},
journal = {Science},
volume = {364},
number = {6441},
pages = {658-664},
abstract = {The ability of naturally occurring proteins to change conformation in response to environmental changes is critical to biological function. Although there have been advances in the de novo design of stable proteins with a single, deep free-energy minimum, the design of conformational switches remains challenging. We present a general strategy to design pH-responsive protein conformational changes by precisely preorganizing histidine residues in buried hydrogen-bond networks. We design homotrimers and heterodimers that are stable above pH 6.5 but undergo cooperative, large-scale conformational changes when the pH is lowered and electrostatic and steric repulsion builds up as the network histidine residues become protonated. The transition pH and cooperativity can be controlled through the number of histidine-containing networks and the strength of the surrounding hydrophobic interactions. Upon disassembly, the designed proteins disrupt lipid membranes both in vitro and after being endocytosed in mammalian cells. Our results demonstrate that environmentally triggered conformational changes can now be programmed by de novo protein design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ability of naturally occurring proteins to change conformation in response to environmental changes is critical to biological function. Although there have been advances in the de novo design of stable proteins with a single, deep free-energy minimum, the design of conformational switches remains challenging. We present a general strategy to design pH-responsive protein conformational changes by precisely preorganizing histidine residues in buried hydrogen-bond networks. We design homotrimers and heterodimers that are stable above pH 6.5 but undergo cooperative, large-scale conformational changes when the pH is lowered and electrostatic and steric repulsion builds up as the network histidine residues become protonated. The transition pH and cooperativity can be controlled through the number of histidine-containing networks and the strength of the surrounding hydrophobic interactions. Upon disassembly, the designed proteins disrupt lipid membranes both in vitro and after being endocytosed in mammalian cells. Our results demonstrate that environmentally triggered conformational changes can now be programmed by de novo protein design.
Dang, Luke T., Miao, Yi, Ha, Andrew, Yuki, Kanako, Park, Keunwan, Janda, Claudia Y., Jude, Kevin M., Mohan, Kritika, Ha, Nhi, Vallon, Mario, Yuan, Jenny, Vilches-Moure, José G., Kuo, Calvin J., Garcia, K. Christopher, Baker, David
Receptor subtype discrimination using extensive shape complementary designed interfaces Journal Article
In: Nature Structural & Molecular Biology, 2019, ISSN: 1545-9985.
@article{Dang2019,
title = {Receptor subtype discrimination using extensive shape complementary designed interfaces},
author = {Dang, Luke T. and Miao, Yi and Ha, Andrew and Yuki, Kanako and Park, Keunwan and Janda, Claudia Y. and Jude, Kevin M. and Mohan, Kritika and Ha, Nhi and Vallon, Mario and Yuan, Jenny and Vilches-Moure, José G. and Kuo, Calvin J. and Garcia, K. Christopher and Baker, David},
url = {https://doi.org/10.1038/s41594-019-0224-z
https://www.bakerlab.org/wp-content/uploads/2019/05/Dang2019_NSMB_ReceptorSubtypeDiscrimination.pdf},
doi = {10.1038/s41594-019-0224-z},
issn = {1545-9985},
year = {2019},
date = {2019-05-13},
journal = {Nature Structural & Molecular Biology},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
David Baker
What has de novo protein design taught us about protein folding and biophysics? Journal Article
In: Protein Science, vol. 28, no. 4, pp. 678-683, 2019.
@article{Baker2019,
title = {What has de novo protein design taught us about protein folding and biophysics?},
author = {David Baker},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/pro.3588
https://www.bakerlab.org/wp-content/uploads/2019/04/Baker-2019-Protein_Science.pdf},
doi = {10.1002/pro.3588},
year = {2019},
date = {2019-02-12},
journal = {Protein Science},
volume = {28},
number = {4},
pages = {678-683},
abstract = {Recent progress in de novo protein design has led to an explosion of new protein structures, functions and assemblies. In this essay, I consider how the successes and failures in this new area inform our understanding of the proteins in nature and, more generally, the predictive computational modeling of biological systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent progress in de novo protein design has led to an explosion of new protein structures, functions and assemblies. In this essay, I consider how the successes and failures in this new area inform our understanding of the proteins in nature and, more generally, the predictive computational modeling of biological systems.
Silva, Daniel-Adriano and Yu, Shawn and Ulge, Umut Y. and Spangler, Jamie B. and Jude, Kevin M. and Labão-Almeida, Carlos and Ali, Lestat R. and Quijano-Rubio, Alfredo and Ruterbusch, Mikel and Leung, Isabel and Biary, Tamara and Crowley, Stephanie J. and Marcos, Enrique and Walkey, Carl D. and Weitzner, Brian D. and Pardo-Avila, Fátima and Castellanos, Javier and Carter, Lauren and Stewart, Lance and Riddell, Stanley R. and Pepper, Marion and Bernardes, Gonçalo J. L. and Dougan, Michael and Garcia, K. Christopher and Baker, David
De novo design of potent and selective mimics of IL-2 and IL-15 Journal Article
In: Nature, 2019, ISSN: 1476-4687.
@article{Silva2019,
title = {De novo design of potent and selective mimics of IL-2 and IL-15},
author = {Silva, Daniel-Adriano and
Yu, Shawn and
Ulge, Umut Y. and
Spangler, Jamie B. and
Jude, Kevin M. and
Labão-Almeida, Carlos and
Ali, Lestat R. and
Quijano-Rubio, Alfredo and
Ruterbusch, Mikel and
Leung, Isabel and
Biary, Tamara and
Crowley, Stephanie J. and
Marcos, Enrique and
Walkey, Carl D. and
Weitzner, Brian D. and
Pardo-Avila, Fátima and
Castellanos, Javier and
Carter, Lauren and
Stewart, Lance and
Riddell, Stanley R. and
Pepper, Marion and
Bernardes, Gonçalo J. L. and
Dougan, Michael and
Garcia, K. Christopher and
Baker, David
},
url = {https://www.nature.com/articles/s41586-018-0830-7
https://www.bakerlab.org/wp-content/uploads/2019/01/Silva2018_IL2-15.pdf},
doi = {10.1038/s41586-018-0830-7},
issn = {1476-4687},
year = {2019},
date = {2019-01-09},
journal = {Nature},
abstract = {We describe a de novo computational approach for designing proteins that recapitulate the binding sites of natural cytokines, but are otherwise unrelated in topology or amino acid sequence. We use this strategy to design mimics of the central immune cytokine interleukin-2 (IL-2) that bind to the IL-2 receptor βγc heterodimer (IL-2Rβγc) but have no binding site for IL-2Rα (also called CD25) or IL-15Rα (also known as CD215). The designs are hyper-stable, bind human and mouse IL-2Rβγc with higher affinity than the natural cytokines, and elicit downstream cell signalling independently of IL-2Rα and IL-15Rα. Crystal structures of the optimized design neoleukin-2/15 (Neo-2/15), both alone and in complex with IL-2Rβγc, are very similar to the designed model. Neo-2/15 has superior therapeutic activity to IL-2 in mouse models of melanoma and colon cancer, with reduced toxicity and undetectable immunogenicity. Our strategy for building hyper-stable de novo mimetics could be applied generally to signalling proteins, enabling the creation of superior therapeutic candidates.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a de novo computational approach for designing proteins that recapitulate the binding sites of natural cytokines, but are otherwise unrelated in topology or amino acid sequence. We use this strategy to design mimics of the central immune cytokine interleukin-2 (IL-2) that bind to the IL-2 receptor βγc heterodimer (IL-2Rβγc) but have no binding site for IL-2Rα (also called CD25) or IL-15Rα (also known as CD215). The designs are hyper-stable, bind human and mouse IL-2Rβγc with higher affinity than the natural cytokines, and elicit downstream cell signalling independently of IL-2Rα and IL-15Rα. Crystal structures of the optimized design neoleukin-2/15 (Neo-2/15), both alone and in complex with IL-2Rβγc, are very similar to the designed model. Neo-2/15 has superior therapeutic activity to IL-2 in mouse models of melanoma and colon cancer, with reduced toxicity and undetectable immunogenicity. Our strategy for building hyper-stable de novo mimetics could be applied generally to signalling proteins, enabling the creation of superior therapeutic candidates.
COLLABORATOR LED
Foight, Glenna Wink, Wang, Zhizhi, Wei, Cindy T., Jr Greisen, Per, Warner, Katrina M., Cunningham-Bryant, Daniel, Park, Keunwan, Brunette, T. J., Sheffler, William, Baker, David, Maly, Dustin J.
Multi-input chemical control of protein dimerization for programming graded cellular responses Journal Article
In: Nature Biotechnology, vol. 37, no. 10, pp. 1209-1216, 2019, ISBN: 1546-1696.
@article{Foight2019,
title = {Multi-input chemical control of protein dimerization for programming graded cellular responses},
author = {Foight, Glenna Wink and Wang, Zhizhi and Wei, Cindy T. and Jr Greisen, Per and Warner, Katrina M. and Cunningham-Bryant, Daniel and Park, Keunwan and Brunette, T. J. and Sheffler, William and Baker, David and Maly, Dustin J.},
url = {https://www.nature.com/articles/s41587-019-0242-8
https://www.bakerlab.org/wp-content/uploads/2020/06/Foight_et_al_2019_NatBiotech.pdf},
doi = {10.1038/s41587-019-0242-8},
isbn = {1546-1696},
year = {2019},
date = {2019-09-09},
journal = {Nature Biotechnology},
volume = {37},
number = {10},
pages = {1209-1216},
abstract = {Chemical and optogenetic methods for post-translationally controlling protein function have enabled modulation and engineering of cellular functions. However, most of these methods only confer single-input, single-output control. To increase the diversity of post-translational behaviors that can be programmed, we built a system based on a single protein receiver that can integrate multiple drug inputs, including approved therapeutics. Our system translates drug inputs into diverse outputs using a suite of engineered reader proteins to provide variable dimerization states of the receiver protein. We show that our single receiver protein architecture can be used to program a variety of cellular responses, including graded and proportional dual-output control of transcription and mammalian cell signaling. We apply our tools to titrate the competing activities of the Rac and Rho GTPases to control cell morphology. Our versatile tool set will enable researchers to post-translationally program mammalian cellular processes and to engineer cell therapies.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Chemical and optogenetic methods for post-translationally controlling protein function have enabled modulation and engineering of cellular functions. However, most of these methods only confer single-input, single-output control. To increase the diversity of post-translational behaviors that can be programmed, we built a system based on a single protein receiver that can integrate multiple drug inputs, including approved therapeutics. Our system translates drug inputs into diverse outputs using a suite of engineered reader proteins to provide variable dimerization states of the receiver protein. We show that our single receiver protein architecture can be used to program a variety of cellular responses, including graded and proportional dual-output control of transcription and mammalian cell signaling. We apply our tools to titrate the competing activities of the Rac and Rho GTPases to control cell morphology. Our versatile tool set will enable researchers to post-translationally program mammalian cellular processes and to engineer cell therapies.
Qi Wu, Zhenling Peng, Ivan Anishchenko, Qian Cong, David Baker, Jianyi Yang
Protein contact prediction using metagenome sequence data and residual neural networks Journal Article
In: Bioinformatics, vol. 36, no. 1, 2019.
@article{Wu2019,
title = {Protein contact prediction using metagenome sequence data and residual neural networks},
author = {Qi Wu and Zhenling Peng and Ivan Anishchenko and Qian Cong and David Baker and Jianyi Yang},
url = {https://academic.oup.com/bioinformatics/article/36/1/41/5512356},
doi = {10.1093/bioinformatics/btz477},
year = {2019},
date = {2019-06-07},
journal = {Bioinformatics},
volume = {36},
number = {1},
abstract = {Motivation: Almost all protein residue contact prediction methods rely on the availability of deep multiple sequence alignments (MSAs). However, many proteins from the poorly populated families do not have sufficient number of homologs in the conventional UniProt database. Here we aim to solve this issue by exploring the rich sequence data from the metagenome sequencing projects. Results: Based on the improved MSA constructed from the metagenome sequence data, we developed MapPred, a new deep learning-based contact prediction method. MapPred consists of two component methods, DeepMSA and DeepMeta, both trained with the residual neural networks. DeepMSA was inspired by the recent method DeepCov, which was trained on 441 matrices of covariance features. By considering the symmetry of contact map, we reduced the number of matrices to 231, which makes the training more efficient in DeepMSA. Experiments show that DeepMSA outperforms DeepCov by 10–13% in precision. DeepMeta works by combining predicted contacts and other sequence profile features. Experiments on three benchmark datasets suggest that the contribution from the metagenome sequence data is significant with P-values less than 4.04E-17. MapPred is shown to be complementary and comparable the state-of-the-art methods. The success of MapPred is attributed to three factors: the deeper MSA from the metagenome sequence data, improved feature design in DeepMSA and optimized training by the residual neural networks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Motivation: Almost all protein residue contact prediction methods rely on the availability of deep multiple sequence alignments (MSAs). However, many proteins from the poorly populated families do not have sufficient number of homologs in the conventional UniProt database. Here we aim to solve this issue by exploring the rich sequence data from the metagenome sequencing projects. Results: Based on the improved MSA constructed from the metagenome sequence data, we developed MapPred, a new deep learning-based contact prediction method. MapPred consists of two component methods, DeepMSA and DeepMeta, both trained with the residual neural networks. DeepMSA was inspired by the recent method DeepCov, which was trained on 441 matrices of covariance features. By considering the symmetry of contact map, we reduced the number of matrices to 231, which makes the training more efficient in DeepMSA. Experiments show that DeepMSA outperforms DeepCov by 10–13% in precision. DeepMeta works by combining predicted contacts and other sequence profile features. Experiments on three benchmark datasets suggest that the contribution from the metagenome sequence data is significant with P-values less than 4.04E-17. MapPred is shown to be complementary and comparable the state-of-the-art methods. The success of MapPred is attributed to three factors: the deeper MSA from the metagenome sequence data, improved feature design in DeepMSA and optimized training by the residual neural networks.
Mohan, Kritika, Ueda, George, Kim, Ah Ram, Jude, Kevin M., Fallas, Jorge A., Guo, Yu, Hafer, Maximillian, Miao, Yi, Saxton, Robert A., Piehler, Jacob, Sankaran, Vijay G., Baker, David, Garcia, K. Christopher
Topological control of cytokine receptor signaling induces differential effects in hematopoiesis Journal Article
In: Science, vol. 364, no. 6442, 2019.
@article{Mohan2019,
title = {Topological control of cytokine receptor signaling induces differential effects in hematopoiesis},
author = {Mohan, Kritika and Ueda, George and Kim, Ah Ram and Jude, Kevin M. and Fallas, Jorge A. and Guo, Yu and Hafer, Maximillian and Miao, Yi and Saxton, Robert A. and Piehler, Jacob and Sankaran, Vijay G. and Baker, David and Garcia, K. Christopher
},
url = {https://science.sciencemag.org/content/364/6442/eaav7532
https://www.bakerlab.org/wp-content/uploads/2019/05/Mohan2019_Science_cytokinebinders.pdf},
doi = {10.1126/science.aav7532},
year = {2019},
date = {2019-05-24},
journal = {Science},
volume = {364},
number = {6442},
abstract = {Although tunable signaling by G protein–coupled receptors can be exploited through medicinal chemistry, a comparable pharmacological approach has been lacking for the modulation of signaling through dimeric receptors, such as those for cytokines. We present a strategy to modulate cytokine receptor signaling output by use of a series of designed C2-symmetric cytokine mimetics, based on the designed ankyrin repeat protein (DARPin) scaffold, that can systematically control erythropoietin receptor (EpoR) dimerization orientation and distance between monomers. We sampled a range of EpoR geometries by varying intermonomer angle and distance, corroborated by several ligand-EpoR complex crystal structures. Across the range, we observed full, partial, and biased agonism as well as stage-selective effects on hematopoiesis. This surrogate ligand strategy opens access to pharmacological modulation of therapeutically important cytokine and growth factor receptor systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Although tunable signaling by G protein–coupled receptors can be exploited through medicinal chemistry, a comparable pharmacological approach has been lacking for the modulation of signaling through dimeric receptors, such as those for cytokines. We present a strategy to modulate cytokine receptor signaling output by use of a series of designed C2-symmetric cytokine mimetics, based on the designed ankyrin repeat protein (DARPin) scaffold, that can systematically control erythropoietin receptor (EpoR) dimerization orientation and distance between monomers. We sampled a range of EpoR geometries by varying intermonomer angle and distance, corroborated by several ligand-EpoR complex crystal structures. Across the range, we observed full, partial, and biased agonism as well as stage-selective effects on hematopoiesis. This surrogate ligand strategy opens access to pharmacological modulation of therapeutically important cytokine and growth factor receptor systems.
Chen, Zibo, Johnson, Matthew C., Chen, Jiajun, Bick, Matthew J., Boyken, Scott E., Lin, Baihan, De Yoreo, James J., Kollman, Justin M., Baker, David, DiMaio, Frank
Self-Assembling 2D Arrays with de Novo Protein Building Blocks Journal Article
In: Journal of the American Chemical Society, 2019.
@article{Chen2019,
title = {Self-Assembling 2D Arrays with de Novo Protein Building Blocks},
author = {Chen, Zibo and Johnson, Matthew C. and Chen, Jiajun and Bick, Matthew J. and Boyken, Scott E. and Lin, Baihan and De Yoreo, James J. and Kollman, Justin M. and Baker, David and DiMaio, Frank},
url = {https://www.bakerlab.org/wp-content/uploads/2020/02/Chen2019_JACS_2Darrays.pdf
https://pubs.acs.org/doi/abs/10.1021/jacs.9b01978#},
doi = {10.1021/jacs.9b01978},
year = {2019},
date = {2019-05-03},
journal = {Journal of the American Chemical Society},
abstract = {Modular self-assembly of biomolecules in two dimensions (2D) is straightforward with DNA but has been difficult to realize with proteins, due to the lack of modular specificity similar to Watson−Crick base pairing. Here we describe a general approach to design 2D arrays using de novo designed pseudosymmetric protein building blocks. A homodimeric helical bundle was reconnected into a monomeric building block, and the surface was redesigned in Rosetta to enable self-assembly into a 2D array in the C12 layer symmetry group. Two out of ten designed arrays assembled to micrometer scale under negative stain electron microscopy, and displayed the designed lattice geometry with assembly size up to 100 nm under atomic force microscopy. The design of 2D arrays with pseudosymmetric building blocks is an important step toward the design of programmable protein self-assembly via pseudosymmetric patterning of orthogonal binding interfaces.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Modular self-assembly of biomolecules in two dimensions (2D) is straightforward with DNA but has been difficult to realize with proteins, due to the lack of modular specificity similar to Watson−Crick base pairing. Here we describe a general approach to design 2D arrays using de novo designed pseudosymmetric protein building blocks. A homodimeric helical bundle was reconnected into a monomeric building block, and the surface was redesigned in Rosetta to enable self-assembly into a 2D array in the C12 layer symmetry group. Two out of ten designed arrays assembled to micrometer scale under negative stain electron microscopy, and displayed the designed lattice geometry with assembly size up to 100 nm under atomic force microscopy. The design of 2D arrays with pseudosymmetric building blocks is an important step toward the design of programmable protein self-assembly via pseudosymmetric patterning of orthogonal binding interfaces.
Jessica Marcandalli, Brooke Fiala, Sebastian Ols, Michela Perotti, Willem de van der Schueren, Joost Snijder, Edgar Hodge, Mark Benhaim, Rashmi Ravichandran, Lauren Carter, Will Sheffler, Livia Brunner, Maria Lawrenz, Patrice Dubois, Antonio Lanzavecchia, Federica Sallusto, Kelly K. Lee, David Veesler, Colin E. Correnti, Lance J. Stewart, David Baker, Karin Loré, Laurent Perez, Neil P. King,
Induction of Potent Neutralizing Antibody Responses by a Designed Protein Nanoparticle Vaccine for Respiratory Syncytial Virus Journal Article
In: Cell, vol. 176, no. 6, pp. 1420-1431, 2019.
@article{Marcandalli2019,
title = {Induction of Potent Neutralizing Antibody Responses by a Designed Protein Nanoparticle Vaccine for Respiratory Syncytial Virus},
author = {Jessica Marcandalli, Brooke Fiala, Sebastian Ols, Michela Perotti, Willem de van der Schueren, Joost Snijder, Edgar Hodge, Mark Benhaim, Rashmi Ravichandran, Lauren Carter, Will Sheffler, Livia Brunner, Maria Lawrenz, Patrice Dubois, Antonio Lanzavecchia, Federica Sallusto, Kelly K. Lee, David Veesler, Colin E. Correnti, Lance J. Stewart, David Baker, Karin Loré, Laurent Perez, Neil P. King,},
url = {https://www.cell.com/cell/pdf/S0092-8674(19)30109-6.pdf},
doi = {10.1016/j.cell.2019.01.046},
year = {2019},
date = {2019-03-07},
journal = {Cell},
volume = {176},
number = {6},
pages = {1420-1431},
abstract = {Respiratory syncytial virus (RSV) is a worldwide public health concern for which no vaccine is available. Elucidation of the prefusion structure of the RSV F glycoprotein and its identification as the main target of neutralizing antibodies have provided new opportunities for development of an effective vaccine. Here, we describe the structure-based design of a self-assembling protein nanoparticle presenting a prefusion-stabilized variant of the F glycoprotein trimer (DS-Cav1) in a repetitive array on the nanoparticle exterior. The two-component nature of the nanoparticle scaffold enabled the production of highly ordered, monodisperse immunogens that display DS-Cav1 at controllable density. In mice and nonhuman primates, the full-valency nanoparticle immunogen displaying 20 DS-Cav1 trimers induced neutralizing antibody responses ∼10-fold higher than trimeric DS-Cav1. These results motivate continued development of this promising nanoparticle RSV vaccine candidate and establish computationally designed two-component nanoparticles as a robust and customizable platform for structure-based vaccine design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Respiratory syncytial virus (RSV) is a worldwide public health concern for which no vaccine is available. Elucidation of the prefusion structure of the RSV F glycoprotein and its identification as the main target of neutralizing antibodies have provided new opportunities for development of an effective vaccine. Here, we describe the structure-based design of a self-assembling protein nanoparticle presenting a prefusion-stabilized variant of the F glycoprotein trimer (DS-Cav1) in a repetitive array on the nanoparticle exterior. The two-component nature of the nanoparticle scaffold enabled the production of highly ordered, monodisperse immunogens that display DS-Cav1 at controllable density. In mice and nonhuman primates, the full-valency nanoparticle immunogen displaying 20 DS-Cav1 trimers induced neutralizing antibody responses ∼10-fold higher than trimeric DS-Cav1. These results motivate continued development of this promising nanoparticle RSV vaccine candidate and establish computationally designed two-component nanoparticles as a robust and customizable platform for structure-based vaccine design.
2018
FROM THE LAB
Chen, Zibo and Boyken, Scott E. and Jia, Mengxuan and Busch, Florian and Flores-Solis, David and Bick, Matthew J. and Lu, Peilong and VanAernum, Zachary L. and Sahasrabuddhe, Aniruddha and Langan, Robert A. and Bermeo, Sherry and Brunette, T. J. and Mulligan, Vikram Khipple and Carter, Lauren P. and DiMaio, Frank and Sgourakis, Nikolaos G. and Wysocki, Vicki H. and Baker, David
Programmable design of orthogonal protein heterodimers Journal Article
In: Nature, 2018, ISSN: 1476-4687.
@article{Chen2018,
title = {Programmable design of orthogonal protein heterodimers},
author = {Chen, Zibo and
Boyken, Scott E. and
Jia, Mengxuan and
Busch, Florian and
Flores-Solis, David and
Bick, Matthew J. and
Lu, Peilong and
VanAernum, Zachary L. and
Sahasrabuddhe, Aniruddha and
Langan, Robert A. and
Bermeo, Sherry and
Brunette, T. J. and
Mulligan, Vikram Khipple and
Carter, Lauren P. and
DiMaio, Frank and
Sgourakis, Nikolaos G. and
Wysocki, Vicki H. and
Baker, David},
url = {https://doi.org/10.1038/s41586-018-0802-y
https://www.bakerlab.org/wp-content/uploads/2018/12/Chen2018_heterodimers.pdf},
doi = {10.1038/s41586-018-0802-y},
issn = {1476-4687},
year = {2018},
date = {2018-12-19},
journal = {Nature},
abstract = {Specificity of interactions between two DNA strands, or between protein and DNA, is often achieved by varying bases or side chains coming off the DNA or protein backbone—for example, the bases participating in Watson–Crick pairing in the double helix, or the side chains contacting DNA in TALEN–DNA complexes. By contrast, specificity of protein–protein interactions usually involves backbone shape complementarity1, which is less modular and hence harder to generalize. Coiled-coil heterodimers are an exception, but the restricted geometry of interactions across the heterodimer interface (primarily at the heptad a and d positions2) limits the number of orthogonal pairs that can be created simply by varying side-chain interactions3,4. Here we show that protein–protein interaction specificity can be achieved using extensive and modular side-chain hydrogen-bond networks. We used the Crick generating equations5 to produce millions of four-helix backbones with varying degrees of supercoiling around a central axis, identified those accommodating extensive hydrogen-bond networks, and used Rosetta to connect pairs of helices with short loops and to optimize the remainder of the sequence. Of 97 such designs expressed in Escherichia coli, 65 formed constitutive heterodimers, and the crystal structures of four designs were in close agreement with the computational models and confirmed the designed hydrogen-bond networks. In cells, six heterodimers were fully orthogonal, and in vitro—following mixing of 32 chains from 16 heterodimer designs, denaturation in 5 M guanidine hydrochloride and reannealing—almost all of the interactions observed by native mass spectrometry were between the designed cognate pairs. The ability to design orthogonal protein heterodimers should enable sophisticated protein-based control logic for synthetic biology, and illustrates that nature has not fully explored the possibilities for programmable biomolecular interaction modalities.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Specificity of interactions between two DNA strands, or between protein and DNA, is often achieved by varying bases or side chains coming off the DNA or protein backbone—for example, the bases participating in Watson–Crick pairing in the double helix, or the side chains contacting DNA in TALEN–DNA complexes. By contrast, specificity of protein–protein interactions usually involves backbone shape complementarity1, which is less modular and hence harder to generalize. Coiled-coil heterodimers are an exception, but the restricted geometry of interactions across the heterodimer interface (primarily at the heptad a and d positions2) limits the number of orthogonal pairs that can be created simply by varying side-chain interactions3,4. Here we show that protein–protein interaction specificity can be achieved using extensive and modular side-chain hydrogen-bond networks. We used the Crick generating equations5 to produce millions of four-helix backbones with varying degrees of supercoiling around a central axis, identified those accommodating extensive hydrogen-bond networks, and used Rosetta to connect pairs of helices with short loops and to optimize the remainder of the sequence. Of 97 such designs expressed in Escherichia coli, 65 formed constitutive heterodimers, and the crystal structures of four designs were in close agreement with the computational models and confirmed the designed hydrogen-bond networks. In cells, six heterodimers were fully orthogonal, and in vitro—following mixing of 32 chains from 16 heterodimer designs, denaturation in 5 M guanidine hydrochloride and reannealing—almost all of the interactions observed by native mass spectrometry were between the designed cognate pairs. The ability to design orthogonal protein heterodimers should enable sophisticated protein-based control logic for synthetic biology, and illustrates that nature has not fully explored the possibilities for programmable biomolecular interaction modalities.
Shen, Hao, Fallas, Jorge A., Lynch, Eric, Sheffler, William, Parry, Bradley, Jannetty, Nicholas, Decarreau, Justin, Wagenbach, Michael, Vicente, Juan Jesus, Chen, Jiajun, Wang, Lei, Dowling, Quinton, Oberdorfer, Gustav, Stewart, Lance, Wordeman, Linda, De Yoreo, James, Jacobs-Wagner, Christine, Kollman, Justin, Baker, David
De novo design of self-assembling helical protein filaments Journal Article
In: Science, vol. 362, no. 6415, pp. 705–709, 2018, ISSN: 0036-8075.
@article{Shen2018,
title = {De novo design of self-assembling helical protein filaments},
author = {Shen, Hao and Fallas, Jorge A. and Lynch, Eric and Sheffler, William and Parry, Bradley and Jannetty, Nicholas and Decarreau, Justin and Wagenbach, Michael and Vicente, Juan Jesus and Chen, Jiajun and Wang, Lei and Dowling, Quinton and Oberdorfer, Gustav and Stewart, Lance and Wordeman, Linda and De Yoreo, James and Jacobs-Wagner, Christine and Kollman, Justin and Baker, David},
url = {http://science.sciencemag.org/content/362/6415/705
https://www.bakerlab.org/wp-content/uploads/2018/12/Shen2018_filaments.pdf},
doi = {10.1126/science.aau3775},
issn = {0036-8075},
year = {2018},
date = {2018-11-09},
journal = {Science},
volume = {362},
number = {6415},
pages = {705–709},
abstract = {There has been some success in designing stable peptide filaments; however, mimicking the reversible assembly of many natural protein filaments is challenging. Dynamic filaments usually comprise independently folded and asymmetric proteins and using such building blocks requires the design of multiple intermonomer interfaces. Shen et al. report the design of self-assembling helical filaments based on previously designed stable repeat proteins. The filaments are micron scale, and their diameter can be tuned by varying the number of repeats in the monomer. Anchor and capping units, built from monomers that lack an interaction interface, can be used to control assembly and disassembly.Science, this issue p. 705We describe a general computational approach to designing self-assembling helical filaments from monomeric proteins and use this approach to design proteins that assemble into micrometer-scale filaments with a wide range of geometries in vivo and in vitro. Cryo{textendash}electron microscopy structures of six designs are close to the computational design models. The filament building blocks are idealized repeat proteins, and thus the diameter of the filaments can be systematically tuned by varying the number of repeat units. The assembly and disassembly of the filaments can be controlled by engineered anchor and capping units built from monomers lacking one of the interaction surfaces. The ability to generate dynamic, highly ordered structures that span micrometers from protein monomers opens up possibilities for the fabrication of new multiscale metamaterials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
There has been some success in designing stable peptide filaments; however, mimicking the reversible assembly of many natural protein filaments is challenging. Dynamic filaments usually comprise independently folded and asymmetric proteins and using such building blocks requires the design of multiple intermonomer interfaces. Shen et al. report the design of self-assembling helical filaments based on previously designed stable repeat proteins. The filaments are micron scale, and their diameter can be tuned by varying the number of repeats in the monomer. Anchor and capping units, built from monomers that lack an interaction interface, can be used to control assembly and disassembly.Science, this issue p. 705We describe a general computational approach to designing self-assembling helical filaments from monomeric proteins and use this approach to design proteins that assemble into micrometer-scale filaments with a wide range of geometries in vivo and in vitro. Cryo{textendash}electron microscopy structures of six designs are close to the computational design models. The filament building blocks are idealized repeat proteins, and thus the diameter of the filaments can be systematically tuned by varying the number of repeat units. The assembly and disassembly of the filaments can be controlled by engineered anchor and capping units built from monomers lacking one of the interaction surfaces. The ability to generate dynamic, highly ordered structures that span micrometers from protein monomers opens up possibilities for the fabrication of new multiscale metamaterials.
Marcos, Enrique and Chidyausiku, Tamuka M. and McShan, Andrew C. and Evangelidis, Thomas and Nerli, Santrupti and Carter, Lauren and Nivón, Lucas G. and Davis, Audrey and Oberdorfer, Gustav and Tripsianes, Konstantinos and Sgourakis, Nikolaos G. and Baker, David
De novo design of a non-local β-sheet protein with high stability and accuracy Journal Article
In: Nature Structural & Molecular Biology, 2018, ISSN: 1545-9985.
@article{Marcos2018,
title = {De novo design of a non-local β-sheet protein with high stability and accuracy},
author = {Marcos, Enrique and
Chidyausiku, Tamuka M. and
McShan, Andrew C. and
Evangelidis, Thomas and
Nerli, Santrupti and
Carter, Lauren and
Nivón, Lucas G. and
Davis, Audrey and
Oberdorfer, Gustav and
Tripsianes, Konstantinos and
Sgourakis, Nikolaos G. and
Baker, David},
url = {https://doi.org/10.1038/s41594-018-0141-6
https://www.bakerlab.org/wp-content/uploads/2018/11/Marcos_etal_2018.pdf},
doi = {10.1038/s41594-018-0141-6},
issn = {1545-9985},
year = {2018},
date = {2018-10-29},
journal = {Nature Structural & Molecular Biology},
abstract = {β-sheet proteins carry out critical functions in biology, and hence are attractive scaffolds for computational protein design. Despite this potential, de novo design of all-β-sheet proteins from first principles lags far behind the design of all-α or mixed-αβ domains owing to their non-local nature and the tendency of exposed β-strand edges to aggregate. Through study of loops connecting unpaired β-strands (β-arches), we have identified a series of structural relationships between loop geometry, side chain directionality and β-strand length that arise from hydrogen bonding and packing constraints on regular β-sheet structures. We use these rules to de novo design jellyroll structures with double-stranded β-helices formed by eight antiparallel β-strands. The nuclear magnetic resonance structure of a hyperthermostable design closely matched the computational model, demonstrating accurate control over the β-sheet structure and loop geometry. Our results open the door to the design of a broad range of non-local β-sheet protein structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
β-sheet proteins carry out critical functions in biology, and hence are attractive scaffolds for computational protein design. Despite this potential, de novo design of all-β-sheet proteins from first principles lags far behind the design of all-α or mixed-αβ domains owing to their non-local nature and the tendency of exposed β-strand edges to aggregate. Through study of loops connecting unpaired β-strands (β-arches), we have identified a series of structural relationships between loop geometry, side chain directionality and β-strand length that arise from hydrogen bonding and packing constraints on regular β-sheet structures. We use these rules to de novo design jellyroll structures with double-stranded β-helices formed by eight antiparallel β-strands. The nuclear magnetic resonance structure of a hyperthermostable design closely matched the computational model, demonstrating accurate control over the β-sheet structure and loop geometry. Our results open the door to the design of a broad range of non-local β-sheet protein structures.
Jiayi Dou*, Anastassia A. Vorobieva*, William Sheffler, Lindsey A. Doyle, Hahnbeom Park, Matthew J. Bick, Binchen Mao, Glenna W. Foight, Min Yen Lee, Lauren A. Gagnon, Lauren Carter, Banumathi Sankaran, Sergey Ovchinnikov, Enrique Marcos, Po-Ssu Huang, Joshua C. Vaughan, Barry L. Stoddard, David Baker
De novo design of a fluorescence-activating β-barrel Journal Article
In: Nature, 2018, ISSN: 1476-4687.
@article{1011,
title = {De novo design of a fluorescence-activating β-barrel},
author = {Jiayi Dou* and Anastassia A. Vorobieva* and William Sheffler and Lindsey A. Doyle and Hahnbeom Park and Matthew J. Bick and Binchen Mao and Glenna W. Foight and Min Yen Lee and Lauren A. Gagnon and Lauren Carter and Banumathi Sankaran and Sergey Ovchinnikov and Enrique Marcos and Po-Ssu Huang and Joshua C. Vaughan and Barry L. Stoddard and David Baker },
url = {https://www.nature.com/articles/s41586-018-0509-0
https://www.bakerlab.org/wp-content/uploads/2018/09/s41586-018-0509-0.pdf},
doi = {10.1038/s41586-018-0509-0},
issn = {1476-4687},
year = {2018},
date = {2018-09-12},
journal = {Nature},
abstract = {The regular arrangements of β-strands around a central axis in β-barrels and of α-helices in coiled coils contrast with the irregular tertiary structures of most globular proteins, and have fascinated structural biologists since they were first discovered. Simple parametric models have been used to design a wide range of α-helical coiled-coil structures, but to date there has been no success with β-barrels. Here we show that accurate de novo design of β-barrels requires considerable symmetry-breaking to achieve continuous hydrogen-bond connectivity and eliminate backbone strain. We then build ensembles of β-barrel backbone models with cavity shapes that match the fluorogenic compound DFHBI, and use a hierarchical grid-based search method to simultaneously optimize the rigid-body placement of DFHBI in these cavities and the identities of the surrounding amino acids to achieve high shape and chemical complementarity. The designs have high structural accuracy and bind and fluorescently activate DFHBI in vitro and in Escherichia coli, yeast and mammalian cells. This de novo design of small-molecule binding activity, using backbones custom-built to bind the ligand, should enable the design of increasingly sophisticated ligand-binding proteins, sensors and catalysts that are not limited by the backbone geometries available in known protein structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The regular arrangements of β-strands around a central axis in β-barrels and of α-helices in coiled coils contrast with the irregular tertiary structures of most globular proteins, and have fascinated structural biologists since they were first discovered. Simple parametric models have been used to design a wide range of α-helical coiled-coil structures, but to date there has been no success with β-barrels. Here we show that accurate de novo design of β-barrels requires considerable symmetry-breaking to achieve continuous hydrogen-bond connectivity and eliminate backbone strain. We then build ensembles of β-barrel backbone models with cavity shapes that match the fluorogenic compound DFHBI, and use a hierarchical grid-based search method to simultaneously optimize the rigid-body placement of DFHBI in these cavities and the identities of the surrounding amino acids to achieve high shape and chemical complementarity. The designs have high structural accuracy and bind and fluorescently activate DFHBI in vitro and in Escherichia coli, yeast and mammalian cells. This de novo design of small-molecule binding activity, using backbones custom-built to bind the ligand, should enable the design of increasingly sophisticated ligand-binding proteins, sensors and catalysts that are not limited by the backbone geometries available in known protein structures.
Park, Hahnbeom, Ovchinnikov, Sergey, Kim, David E., DiMaio, Frank, Baker, David
Protein homology model refinement by large-scale energy optimization Journal Article
In: Proceedings of the National Academy of Sciences, vol. 115, no. 12, pp. 3054–3059, 2018, ISSN: 0027-8424.
@article{Park2018,
title = {Protein homology model refinement by large-scale energy optimization},
author = {Park, Hahnbeom and Ovchinnikov, Sergey and Kim, David E. and DiMaio, Frank and Baker, David},
url = {https://www.pnas.org/content/115/12/3054
https://www.bakerlab.org/wp-content/uploads/2019/01/Park2018_refinement.pdf},
doi = {10.1073/pnas.1719115115},
issn = {0027-8424},
year = {2018},
date = {2018-03-20},
journal = {Proceedings of the National Academy of Sciences},
volume = {115},
number = {12},
pages = {3054–3059},
abstract = {Protein structure refinement by direct global energy optimization has been a longstanding challenge in computational structural biology due to limitations in both energy function accuracy and conformational sampling. This manuscript demonstrates that with recent advances in both areas, refinement can significantly improve protein comparative models based on structures of distant homologues.Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein structure refinement by direct global energy optimization has been a longstanding challenge in computational structural biology due to limitations in both energy function accuracy and conformational sampling. This manuscript demonstrates that with recent advances in both areas, refinement can significantly improve protein comparative models based on structures of distant homologues.Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.
Lu, Peilong, Min, Duyoung, DiMaio, Frank, Wei, Kathy Y., Vahey, Michael D., Boyken, Scott E., Chen, Zibo, Fallas, Jorge A., Ueda, George, Sheffler, William, Mulligan, Vikram Khipple, Xu, Wenqing, Bowie, James U., Baker, David
Accurate computational design of multipass transmembrane proteins Journal Article
In: Science, vol. 359, no. 6379, pp. 1042–1046, 2018, ISSN: 0036-8075.
@article{Lu1042,
title = {Accurate computational design of multipass transmembrane proteins},
author = {Lu, Peilong and Min, Duyoung and DiMaio, Frank and Wei, Kathy Y. and Vahey, Michael D. and Boyken, Scott E. and Chen, Zibo and Fallas, Jorge A. and Ueda, George and Sheffler, William and Mulligan, Vikram Khipple and Xu, Wenqing and Bowie, James U. and Baker, David},
url = {http://science.sciencemag.org/content/359/6379/1042
https://www.bakerlab.org/wp-content/uploads/2018/03/Lu_Science_2018.pdf},
doi = {10.1126/science.aaq1739},
issn = {0036-8075},
year = {2018},
date = {2018-03-02},
journal = {Science},
volume = {359},
number = {6379},
pages = {1042--1046},
abstract = {In recent years, soluble protein design has achieved successes such as artificial enzymes and large protein cages. Membrane proteins present a considerable design challenge, but here too there have been advances, including the design of a zinc-transporting tetramer. Lu et al. report the design of stable transmembrane monomers, homodimers, trimers, and tetramers with up to eight membrane-spanning regions in an oligomer. The designed proteins adopted the target oligomerization state and localized to the predicted cellular membranes, and crystal structures of the designed dimer and tetramer reflected the design models.Science, this issue p. 1042The computational design of transmembrane proteins with more than one membrane-spanning region remains a major challenge. We report the design of transmembrane monomers, homodimers, trimers, and tetramers with 76 to 215 residue subunits containing two to four membrane-spanning regions and up to 860 total residues that adopt the target oligomerization state in detergent solution. The designed proteins localize to the plasma membrane in bacteria and in mammalian cells, and magnetic tweezer unfolding experiments in the membrane indicate that they are very stable. Crystal structures of the designed dimer and tetramer{textemdash}a rocket-shaped structure with a wide cytoplasmic base that funnels into eight transmembrane helices{textemdash}are very close to the design models. Our results pave the way for the design of multispan membrane proteins with new functions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In recent years, soluble protein design has achieved successes such as artificial enzymes and large protein cages. Membrane proteins present a considerable design challenge, but here too there have been advances, including the design of a zinc-transporting tetramer. Lu et al. report the design of stable transmembrane monomers, homodimers, trimers, and tetramers with up to eight membrane-spanning regions in an oligomer. The designed proteins adopted the target oligomerization state and localized to the predicted cellular membranes, and crystal structures of the designed dimer and tetramer reflected the design models.Science, this issue p. 1042The computational design of transmembrane proteins with more than one membrane-spanning region remains a major challenge. We report the design of transmembrane monomers, homodimers, trimers, and tetramers with 76 to 215 residue subunits containing two to four membrane-spanning regions and up to 860 total residues that adopt the target oligomerization state in detergent solution. The designed proteins localize to the plasma membrane in bacteria and in mammalian cells, and magnetic tweezer unfolding experiments in the membrane indicate that they are very stable. Crystal structures of the designed dimer and tetramer{textemdash}a rocket-shaped structure with a wide cytoplasmic base that funnels into eight transmembrane helices{textemdash}are very close to the design models. Our results pave the way for the design of multispan membrane proteins with new functions.
Silva, Daniel-Adriano, Stewart, Lance, Lam, Kwok-Ho, Jin, Rongsheng, Baker, David
Structures and disulfide cross‐linking of de novo designed therapeutic mini‐proteins Journal Article
In: FEBS Journal, vol. 285, no. 10, pp. 1783-1785, 2018.
@article{Silva2018,
title = {Structures and disulfide cross‐linking of de novo designed therapeutic mini‐proteins},
author = {Silva, Daniel-Adriano and Stewart, Lance and Lam, Kwok-Ho and Jin, Rongsheng and Baker, David},
url = {https://febs.onlinelibrary.wiley.com/doi/abs/10.1111/febs.14394
},
doi = {10.1111/febs.14394},
year = {2018},
date = {2018-02-01},
journal = {FEBS Journal},
volume = {285},
number = {10},
pages = {1783-1785},
abstract = {Recent advances in computational protein design now enable the massively parallel de novo design and experimental characterization of small hyperstable binding proteins with potential therapeutic activity. By providing experimental feedback on tens of thousands of designed proteins, the design-build-test-learn pipeline provides a unique opportunity to systematically improve our understanding of protein folding and binding. Here, we review the structures of mini-protein binders in complex with Influenza hemagglutinin and Bot toxin, and illustrate in the case of disulfide bond placement how analysis of the large datasets of computational models and experimental data can be used to identify determinants of folding and binding.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent advances in computational protein design now enable the massively parallel de novo design and experimental characterization of small hyperstable binding proteins with potential therapeutic activity. By providing experimental feedback on tens of thousands of designed proteins, the design-build-test-learn pipeline provides a unique opportunity to systematically improve our understanding of protein folding and binding. Here, we review the structures of mini-protein binders in complex with Influenza hemagglutinin and Bot toxin, and illustrate in the case of disulfide bond placement how analysis of the large datasets of computational models and experimental data can be used to identify determinants of folding and binding.
COLLABORATOR LED
Day, Austin L, Greisen, Per, Doyle, Lindsey, Schena, Alberto, Stella, Nephi, Johnsson, Kai, Baker, David, Stoddard, Barry
Unintended specificity of an engineered ligand-binding protein facilitated by unpredicted plasticity of the protein fold Journal Article
In: Protein Engineering, Design and Selection, 2018.
@article{Day2018,
title = {Unintended specificity of an engineered ligand-binding protein facilitated by unpredicted plasticity of the protein fold},
author = {Day, Austin L and Greisen, Per and Doyle, Lindsey and Schena, Alberto and Stella, Nephi and Johnsson, Kai and Baker, David and Stoddard, Barry
},
url = {https://dx.doi.org/10.1093/protein/gzy031
https://www.bakerlab.org/wp-content/uploads/2019/02/Day2018.pdf},
doi = {10.1093/protein/gzy031},
year = {2018},
date = {2018-12-19},
journal = {Protein Engineering, Design and Selection},
abstract = {Attempts to create novel ligand-binding proteins often focus on formation of a binding pocket with shape complementarity against the desired ligand (particularly for compounds that lack distinct polar moieties). Although designed proteins often exhibit binding of the desired ligand, in some cases they display unintended recognition behavior. One such designed protein, that was originally intended to bind tetrahydrocannabinol (THC), was found instead to display binding of 25-hydroxy-cholecalciferol (25-D3) and was subjected to biochemical characterization, further selections for enhanced 25-D3 binding affinity and crystallographic analyses. The deviation in specificity is due in part to unexpected altertion of its conformation, corresponding to a significant change of the orientation of an α-helix and an equally large movement of a loop, both of which flank the designed ligand-binding pocket. Those changes led to engineered protein constructs that exhibit significantly more contacts and complementarity towards the 25-D3 ligand than the initial designed protein had been predicted to form towards its intended THC ligand. Molecular dynamics simulations imply that the initial computationally designed mutations may contribute to the movement of the helix. These analyses collectively indicate that accurate prediction and control of backbone dynamics conformation, through a combination of improved conformational sampling and/or de novo structure design, represents a key area of further development for the design and optimization of engineered ligand-binding proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Attempts to create novel ligand-binding proteins often focus on formation of a binding pocket with shape complementarity against the desired ligand (particularly for compounds that lack distinct polar moieties). Although designed proteins often exhibit binding of the desired ligand, in some cases they display unintended recognition behavior. One such designed protein, that was originally intended to bind tetrahydrocannabinol (THC), was found instead to display binding of 25-hydroxy-cholecalciferol (25-D3) and was subjected to biochemical characterization, further selections for enhanced 25-D3 binding affinity and crystallographic analyses. The deviation in specificity is due in part to unexpected altertion of its conformation, corresponding to a significant change of the orientation of an α-helix and an equally large movement of a loop, both of which flank the designed ligand-binding pocket. Those changes led to engineered protein constructs that exhibit significantly more contacts and complementarity towards the 25-D3 ligand than the initial designed protein had been predicted to form towards its intended THC ligand. Molecular dynamics simulations imply that the initial computationally designed mutations may contribute to the movement of the helix. These analyses collectively indicate that accurate prediction and control of backbone dynamics conformation, through a combination of improved conformational sampling and/or de novo structure design, represents a key area of further development for the design and optimization of engineered ligand-binding proteins.
Romero Romero, Maria Luisa, Yang, Fan, Lin, Yu-Ru, Toth-Petroczy, Agnes, Berezovsky, Igor N., Goncearenco, Alexander, Yang, Wen, Wellner, Alon, Kumar-Deshmukh, Fanindra, Sharon, Michal, Baker, David, Varani, Gabriele, Tawfik, Dan S.
Simple yet functional phosphate-loop proteins Journal Article
In: PNAS, vol. 115, no. 51, pp. E11943–E11950, 2018, ISSN: 0027-8424.
@article{Romero2018,
title = {Simple yet functional phosphate-loop proteins},
author = {Romero Romero, Maria Luisa and Yang, Fan and Lin, Yu-Ru and Toth-Petroczy, Agnes and Berezovsky, Igor N. and Goncearenco, Alexander and Yang, Wen and Wellner, Alon and Kumar-Deshmukh, Fanindra and Sharon, Michal and Baker, David and Varani, Gabriele and Tawfik, Dan S.},
url = {https://www.bakerlab.org/wp-content/uploads/2019/02/Romero2018.pdfhttps://www.pnas.org/content/115/51/E11943
},
doi = {10.1073/pnas.1812400115},
issn = {0027-8424},
year = {2018},
date = {2018-11-18},
journal = {PNAS},
volume = {115},
number = {51},
pages = {E11943--E11950},
abstract = {The complexity of modern proteins makes the understanding of how proteins evolved from simple beginnings a daunting challenge. The Walker-A motif is a phosphate-binding loop (P-loop) found in possibly the most ancient and abundant protein class, so-called P-loop NTPases. By combining phylogenetic analysis and computational protein design, we have generated simple proteins, of only 55 residues, that contain the P-loop and thereby confer binding of a range of phosphate-containing ligands{textemdash}and even more avidly, RNA and single-strand DNA. Our results show that biochemical function can be implemented in small and simple proteins; they intriguingly suggest that the P-loop emerged as a polynucleotide binder and catalysis of phosphoryl transfer evolved later upon acquisition of higher sequence and structural complexity.Abundant and essential motifs, such as phosphate-binding loops (P-loops), are presumed to be the seeds of modern enzymes. The Walker-A P-loop is absolutely essential in modern NTPase enzymes, in mediating binding, and transfer of the terminal phosphate groups of NTPs. However, NTPase function depends on many additional active-site residues placed throughout the protein{textquoteright}s scaffold. Can motifs such as P-loops confer function in a simpler context? We applied a phylogenetic analysis that yielded a sequence logo of the putative ancestral Walker-A P-loop element: a β-strand connected to an α-helix via the P-loop. Computational design incorporated this element into de novo designed β-α repeat proteins with relatively few sequence modifications. We obtained soluble, stable proteins that unlike modern P-loop NTPases bound ATP in a magnesium-independent manner. Foremost, these simple P-loop proteins avidly bound polynucleotides, RNA, and single-strand DNA, and mutations in the P-loop{textquoteright}s key residues abolished binding. Binding appears to be facilitated by the structural plasticity of these proteins, including quaternary structure polymorphism that promotes a combined action of multiple P-loops. Accordingly, oligomerization enabled a 55-aa protein carrying a single P-loop to confer avid polynucleotide binding. Overall, our results show that the P-loop Walker-A motif can be implemented in small and simple β-α repeat proteins, primarily as a polynucleotide binding motif.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The complexity of modern proteins makes the understanding of how proteins evolved from simple beginnings a daunting challenge. The Walker-A motif is a phosphate-binding loop (P-loop) found in possibly the most ancient and abundant protein class, so-called P-loop NTPases. By combining phylogenetic analysis and computational protein design, we have generated simple proteins, of only 55 residues, that contain the P-loop and thereby confer binding of a range of phosphate-containing ligands{textemdash}and even more avidly, RNA and single-strand DNA. Our results show that biochemical function can be implemented in small and simple proteins; they intriguingly suggest that the P-loop emerged as a polynucleotide binder and catalysis of phosphoryl transfer evolved later upon acquisition of higher sequence and structural complexity.Abundant and essential motifs, such as phosphate-binding loops (P-loops), are presumed to be the seeds of modern enzymes. The Walker-A P-loop is absolutely essential in modern NTPase enzymes, in mediating binding, and transfer of the terminal phosphate groups of NTPs. However, NTPase function depends on many additional active-site residues placed throughout the protein{textquoteright}s scaffold. Can motifs such as P-loops confer function in a simpler context? We applied a phylogenetic analysis that yielded a sequence logo of the putative ancestral Walker-A P-loop element: a β-strand connected to an α-helix via the P-loop. Computational design incorporated this element into de novo designed β-α repeat proteins with relatively few sequence modifications. We obtained soluble, stable proteins that unlike modern P-loop NTPases bound ATP in a magnesium-independent manner. Foremost, these simple P-loop proteins avidly bound polynucleotides, RNA, and single-strand DNA, and mutations in the P-loop{textquoteright}s key residues abolished binding. Binding appears to be facilitated by the structural plasticity of these proteins, including quaternary structure polymorphism that promotes a combined action of multiple P-loops. Accordingly, oligomerization enabled a 55-aa protein carrying a single P-loop to confer avid polynucleotide binding. Overall, our results show that the P-loop Walker-A motif can be implemented in small and simple β-α repeat proteins, primarily as a polynucleotide binding motif.
Geiger-Schuller, Kathryn, Sforza, Kevin, Yuhas, Max, Parmeggiani, Fabio, Baker, David, Barrick, Doug
Extreme stability in de novo-designed repeat arrays is determined by unusually stable short-range interactions Journal Article
In: PNAS, vol. 115, no. 29, pp. 7539-7544, 2018, ISSN: 0027-8424.
@article{Geiger-Schuller2018,
title = {Extreme stability in de novo-designed repeat arrays is determined by unusually stable short-range interactions},
author = {Geiger-Schuller, Kathryn and Sforza, Kevin and Yuhas, Max and Parmeggiani, Fabio and Baker, David and Barrick, Doug},
url = {https://www.pnas.org/content/115/29/7539
https://www.bakerlab.org/wp-content/uploads/2019/02/Geiger-Schuller2018.pdf},
doi = {10.1073/pnas.1800283115},
issn = {0027-8424},
year = {2018},
date = {2018-07-17},
journal = {PNAS},
volume = {115},
number = {29},
pages = {7539-7544},
abstract = {We apply a statistical thermodynamic formalism to quantify the cooperativity of folding of de novo-designed helical repeat proteins (DHRs). This analysis provides a fundamental thermodynamic description of folding for de novo-designed proteins and permits comparison with naturally occurring repeat protein thermodynamics. We find that individual DHR units are intrinsically stable, unlike those of naturally occurring proteins. This observation reveals local (intrarepeat) interactions as a source of high stability in Rosetta-designed proteins and suggests that different types of DHR repeats may be combined in a single polypeptide chain, expanding the repertoire of folded DHRs for applications such as molecular recognition. Favorable intrinsic stability imparts a downhill shape to the energy landscape, suggesting that DHRs fold fast and through parallel pathways.Designed helical repeats (DHRs) are modular helix{textendash}loop{textendash}helix{textendash}loop protein structures that are tandemly repeated to form a superhelical array. Structures combining tandem DHRs demonstrate a wide range of molecular geometries, many of which are not observed in nature. Understanding cooperativity of DHR proteins provides insight into the molecular origins of Rosetta-based protein design hyperstability and facilitates comparison of energy distributions in artificial and naturally occurring protein folds. Here, we use a nearest-neighbor Ising model to quantify the intrinsic and interfacial free energies of four different DHRs. We measure the folding free energies of constructs with varying numbers of internal and terminal capping repeats for four different DHR folds, using guanidine-HCl and glycerol as destabilizing and solubilizing cosolvents. One-dimensional Ising analysis of these series reveals that, although interrepeat coupling energies are within the range seen for naturally occurring repeat proteins, the individual repeats of DHR proteins are intrinsically stable. This favorable intrinsic stability, which has not been observed for naturally occurring repeat proteins, adds to stabilizing interfaces, resulting in extraordinarily high stability. Stable repeats also impart a downhill shape to the energy landscape for DHR folding. These intrinsic stability differences suggest that part of the success of Rosetta-based design results from capturing favorable local interactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We apply a statistical thermodynamic formalism to quantify the cooperativity of folding of de novo-designed helical repeat proteins (DHRs). This analysis provides a fundamental thermodynamic description of folding for de novo-designed proteins and permits comparison with naturally occurring repeat protein thermodynamics. We find that individual DHR units are intrinsically stable, unlike those of naturally occurring proteins. This observation reveals local (intrarepeat) interactions as a source of high stability in Rosetta-designed proteins and suggests that different types of DHR repeats may be combined in a single polypeptide chain, expanding the repertoire of folded DHRs for applications such as molecular recognition. Favorable intrinsic stability imparts a downhill shape to the energy landscape, suggesting that DHRs fold fast and through parallel pathways.Designed helical repeats (DHRs) are modular helix{textendash}loop{textendash}helix{textendash}loop protein structures that are tandemly repeated to form a superhelical array. Structures combining tandem DHRs demonstrate a wide range of molecular geometries, many of which are not observed in nature. Understanding cooperativity of DHR proteins provides insight into the molecular origins of Rosetta-based protein design hyperstability and facilitates comparison of energy distributions in artificial and naturally occurring protein folds. Here, we use a nearest-neighbor Ising model to quantify the intrinsic and interfacial free energies of four different DHRs. We measure the folding free energies of constructs with varying numbers of internal and terminal capping repeats for four different DHR folds, using guanidine-HCl and glycerol as destabilizing and solubilizing cosolvents. One-dimensional Ising analysis of these series reveals that, although interrepeat coupling energies are within the range seen for naturally occurring repeat proteins, the individual repeats of DHR proteins are intrinsically stable. This favorable intrinsic stability, which has not been observed for naturally occurring repeat proteins, adds to stabilizing interfaces, resulting in extraordinarily high stability. Stable repeats also impart a downhill shape to the energy landscape for DHR folding. These intrinsic stability differences suggest that part of the success of Rosetta-based design results from capturing favorable local interactions.
Yue-Ting K. Lau,, Vladimir Baytshtok,, Tessa A. Howard,, Brooke M. Fiala,, JayLee M. Johnson,, Lauren P. Carter,, David Baker,, Christopher D. Lima,, Christopher D. Bahl
Discovery and engineering of enhanced SUMO protease enzymes Journal Article
In: The Journal of Biological Chemistry, vol. 293, pp. 13224-13233, 2018.
@article{Lau2018,
title = {Discovery and engineering of enhanced SUMO protease enzymes},
author = {Yue-Ting K. Lau, and Vladimir Baytshtok, and Tessa A. Howard, and Brooke M. Fiala, and JayLee M. Johnson, and Lauren P. Carter, and David Baker, and Christopher D. Lima, and Christopher D. Bahl},
url = {http://www.jbc.org/content/293/34/13224.short
https://www.bakerlab.org/wp-content/uploads/2019/02/Lau2018.pdf},
doi = {10.1074/jbc.RA118.004146},
year = {2018},
date = {2018-07-05},
journal = {The Journal of Biological Chemistry},
volume = {293},
pages = {13224-13233},
abstract = {Small ubiquitin-like modifier (SUMO) is commonly used as a protein fusion domain to facilitate expression and purification of recombinant proteins, and a SUMO-specific protease is then used to remove SUMO from these proteins. Although this protease is highly specific, its limited solubility and stability hamper its utility as an in vitro reagent. Here, we report improved SUMO protease enzymes obtained via two approaches. First, we developed a computational method and used it to re-engineer WT Ulp1 from Saccharomyces cerevisiae to improve protein solubility. Second, we discovered an improved SUMO protease via genomic mining of the thermophilic fungus Chaetomium thermophilum, as proteins from thermophilic organisms are commonly employed as reagent enzymes. Following expression in Escherichia coli, we found that these re-engineered enzymes can be more thermostable and up to 12 times more soluble, all while retaining WT-or-better levels of SUMO protease activity. The computational method we developed to design solubility-enhancing substitutions is based on the RosettaScripts application for the macromolecular modeling suite Rosetta, and it is broadly applicable for the improvement of solution properties of other proteins. Moreover, we determined the X-ray crystal structure of a SUMO protease from C. thermophilum to 1.44 Å resolution. This structure revealed that this enzyme exhibits structural and functional conservation with the S. cerevisiae SUMO protease, despite exhibiting only 28% sequence identity. In summary, by re-engineering the Ulp1 protease and discovering a SUMO protease from C. thermophilum, we have obtained proteases that are more soluble, more thermostable, and more efficient than the current commercially available Ulp1 enzyme.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Small ubiquitin-like modifier (SUMO) is commonly used as a protein fusion domain to facilitate expression and purification of recombinant proteins, and a SUMO-specific protease is then used to remove SUMO from these proteins. Although this protease is highly specific, its limited solubility and stability hamper its utility as an in vitro reagent. Here, we report improved SUMO protease enzymes obtained via two approaches. First, we developed a computational method and used it to re-engineer WT Ulp1 from Saccharomyces cerevisiae to improve protein solubility. Second, we discovered an improved SUMO protease via genomic mining of the thermophilic fungus Chaetomium thermophilum, as proteins from thermophilic organisms are commonly employed as reagent enzymes. Following expression in Escherichia coli, we found that these re-engineered enzymes can be more thermostable and up to 12 times more soluble, all while retaining WT-or-better levels of SUMO protease activity. The computational method we developed to design solubility-enhancing substitutions is based on the RosettaScripts application for the macromolecular modeling suite Rosetta, and it is broadly applicable for the improvement of solution properties of other proteins. Moreover, we determined the X-ray crystal structure of a SUMO protease from C. thermophilum to 1.44 Å resolution. This structure revealed that this enzyme exhibits structural and functional conservation with the S. cerevisiae SUMO protease, despite exhibiting only 28% sequence identity. In summary, by re-engineering the Ulp1 protease and discovering a SUMO protease from C. thermophilum, we have obtained proteases that are more soluble, more thermostable, and more efficient than the current commercially available Ulp1 enzyme.
2017-1988
ALL PAPERS
2017
Hosseinzadeh, Parisa*, Bhardwaj, Gaurav*, Mulligan, Vikram Khipple*, Shortridge, Matthew D., Craven, Timothy W., Pardo-Avila, F’atima, Rettie, Stephen A., Kim, David E., Silva, Daniel-Adriano, Ibrahim, Yehia M., Webb, Ian K., Cort, John R., Adkins, Joshua N., Varani, Gabriele, Baker, David
Comprehensive computational design of ordered peptide macrocycles Journal Article
In: Science, vol. 358, no. 6369, pp. 1461-1466, 2017, ISSN: 0036-8075.
@article{Hosseinzadeh2017,
title = {Comprehensive computational design of ordered peptide macrocycles},
author = {Hosseinzadeh, Parisa* and Bhardwaj, Gaurav* and Mulligan, Vikram Khipple* and Shortridge, Matthew D. and Craven, Timothy W. and Pardo-Avila, F{'a}tima and Rettie, Stephen A. and Kim, David E. and Silva, Daniel-Adriano and Ibrahim, Yehia M. and Webb, Ian K. and Cort, John R. and Adkins, Joshua N. and Varani, Gabriele and Baker, David},
url = {http://science.sciencemag.org/content/358/6369/1461
https://www.bakerlab.org/wp-content/uploads/2017/12/Science_Hosseinzadeh_et_al_2017.pdf},
doi = {10.1126/science.aap7577},
issn = {0036-8075},
year = {2017},
date = {2017-12-15},
journal = {Science},
volume = {358},
number = {6369},
pages = {1461-1466},
abstract = {Mixed-chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to date, but there is currently no way to systematically search the structural space spanned by such compounds. Natural proteins do not provide a useful guide: Peptide macrocycles lack regular secondary structures and hydrophobic cores, and can contain local structures not accessible with L-amino acids. Here, we enumerate the stable structures that can be adopted by macrocyclic peptides composed of L- and D-amino acids by near-exhaustive backbone sampling followed by sequence design and energy landscape calculations. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. Nuclear magnetic resonance structures of 9 of 12 designed 7- to 10-residue macrocycles, and three 11- to 14-residue bicyclic designs, are close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide macrocycles and vastly increase the available starting scaffolds for both rational drug design and library selection methods.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mixed-chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to date, but there is currently no way to systematically search the structural space spanned by such compounds. Natural proteins do not provide a useful guide: Peptide macrocycles lack regular secondary structures and hydrophobic cores, and can contain local structures not accessible with L-amino acids. Here, we enumerate the stable structures that can be adopted by macrocyclic peptides composed of L- and D-amino acids by near-exhaustive backbone sampling followed by sequence design and energy landscape calculations. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. Nuclear magnetic resonance structures of 9 of 12 designed 7- to 10-residue macrocycles, and three 11- to 14-residue bicyclic designs, are close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide macrocycles and vastly increase the available starting scaffolds for both rational drug design and library selection methods.
Butterfield, Gabriel L.* and Lajoie, Marc J.* and Gustafson, Heather H. and Sellers, Drew L. and Nattermann, Una and Ellis, Daniel and Bale, Jacob B. and Ke, Sharon and Lenz, Garreck H. and Yehdego, Angelica and Ravichandran, Rashmi and Pun, Suzie H. and King, Neil P. and Baker, David
Evolution of a designed protein assembly encapsulating its own RNA genome Journal Article
In: Nature, 2017, ISSN: 1476-4687.
@article{Butterfield2017,
title = {Evolution of a designed protein assembly encapsulating its own RNA genome},
author = {Butterfield, Gabriel L.*
and Lajoie, Marc J.*
and Gustafson, Heather H.
and Sellers, Drew L.
and Nattermann, Una
and Ellis, Daniel
and Bale, Jacob B.
and Ke, Sharon
and Lenz, Garreck H.
and Yehdego, Angelica
and Ravichandran, Rashmi
and Pun, Suzie H.
and King, Neil P.
and Baker, David},
url = {http://dx.doi.org/10.1038/nature25157
https://www.bakerlab.org/wp-content/uploads/2017/12/Nature_Butterfield_et_al_2017.pdf},
doi = {10.1038/nature25157},
issn = {1476-4687},
year = {2017},
date = {2017-12-13},
journal = {Nature},
abstract = {The challenges of evolution in a complex biochemical environment, coupling genotype to phenotype and protecting the genetic material, are solved elegantly in biological systems by the encapsulation of nucleic acids. In the simplest examples, viruses use capsids to surround their genomes. Although these naturally occurring systems have been modified to change their tropism and to display proteins or peptides, billions of years of evolution have favoured efficiency at the expense of modularity, making viral capsids difficult to engineer. Synthetic systems composed of non-viral proteins could provide a ‘blank slate’ to evolve desired properties for drug delivery and other biomedical applications, while avoiding the safety risks and engineering challenges associated with viruses. Here we create synthetic nucleocapsids, which are computationally designed icosahedral protein assemblies with positively charged inner surfaces that can package their own full-length mRNA genomes. We explore the ability of these nucleocapsids to evolve virus-like properties by generating diversified populations using Escherichia coli as an expression host. Several generations of evolution resulted in markedly improved genome packaging (more than 133-fold), stability in blood (from less than 3.7% to 71% of packaged RNA protected after 6hours of treatment), and in vivo circulation time (from less than 5minutes to approximately 4.5hours). The resulting synthetic nucleocapsids package one full length RNA genome for every 11 icosahedral assemblies, similar to the best recombinant adeno-associated virus vectors. Our results show that there are simple evolutionary paths through which protein assemblies can acquire virus-like genome packaging and protection. Considerable effort has been directed at ‘top-down’ modification of viruses to be safe and effective for drug delivery and vaccine applications; the ability to design synthetic nanomaterials computationally and to optimize them through evolution now enables a complementary ‘bottom-up’ approach with considerable advantages in programmability and control.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The challenges of evolution in a complex biochemical environment, coupling genotype to phenotype and protecting the genetic material, are solved elegantly in biological systems by the encapsulation of nucleic acids. In the simplest examples, viruses use capsids to surround their genomes. Although these naturally occurring systems have been modified to change their tropism and to display proteins or peptides, billions of years of evolution have favoured efficiency at the expense of modularity, making viral capsids difficult to engineer. Synthetic systems composed of non-viral proteins could provide a ‘blank slate’ to evolve desired properties for drug delivery and other biomedical applications, while avoiding the safety risks and engineering challenges associated with viruses. Here we create synthetic nucleocapsids, which are computationally designed icosahedral protein assemblies with positively charged inner surfaces that can package their own full-length mRNA genomes. We explore the ability of these nucleocapsids to evolve virus-like properties by generating diversified populations using Escherichia coli as an expression host. Several generations of evolution resulted in markedly improved genome packaging (more than 133-fold), stability in blood (from less than 3.7% to 71% of packaged RNA protected after 6hours of treatment), and in vivo circulation time (from less than 5minutes to approximately 4.5hours). The resulting synthetic nucleocapsids package one full length RNA genome for every 11 icosahedral assemblies, similar to the best recombinant adeno-associated virus vectors. Our results show that there are simple evolutionary paths through which protein assemblies can acquire virus-like genome packaging and protection. Considerable effort has been directed at ‘top-down’ modification of viruses to be safe and effective for drug delivery and vaccine applications; the ability to design synthetic nanomaterials computationally and to optimize them through evolution now enables a complementary ‘bottom-up’ approach with considerable advantages in programmability and control.
Jiayi Dou, Lindsey Doyle, Per Greisen, Alberto Schena, Hahnbeom Park, Kai Johnsson, Barry Stoddard, David Baker
Sampling and energy evaluation challenges in ligand binding protein design Journal Article
In: Protein Science, vol. 26, pp. 2426-2437, 2017, ISSN: 1469-896.
@article{1000b,
title = {Sampling and energy evaluation challenges in ligand binding protein design},
author = {Jiayi Dou and Lindsey Doyle and Per Greisen and Alberto Schena and Hahnbeom Park and Kai Johnsson and Barry Stoddard and David Baker},
url = {http://onlinelibrary.wiley.com/doi/10.1002/pro.3317/abstract
https://www.bakerlab.org/wp-content/uploads/2017/12/Dou_et_al-2017-Protein_Science.pdf},
doi = {10.1002/pro.3317},
issn = {1469-896},
year = {2017},
date = {2017-10-30},
journal = {Protein Science},
volume = {26},
pages = {2426-2437},
abstract = {The steroid hormone 17α-hydroxylprogesterone (17-OHP) is a biomarker for congenital adrenal hyperplasia and hence there is considerable interest in development of sensors for this compound. We used computational protein design to generate protein models with binding sites for 17-OHP containing an extended, nonpolar, shape-complementary binding pocket for the four-ring core of the compound, and hydrogen bonding residues at the base of the pocket to interact with carbonyl and hydroxyl groups at the more polar end of the ligand. Eight of 16 designed proteins experimentally tested bind 17-OHP with micromolar affinity. A co-crystal structure of one of the designs revealed that 17-OHP is rotated 180° around a pseudo-two-fold axis in the compound and displays multiple binding modes within the pocket, while still interacting with all of the designed residues in the engineered site. Subsequent rounds of mutagenesis and binding selection improved the ligand affinity to nanomolar range, while appearing to constrain the ligand to a single bound conformation that maintains the same “flipped” orientation relative to the original design. We trace the discrepancy in the design calculations to two sources: first, a failure to model subtle backbone changes which alter the distribution of sidechain rotameric states and second, an underestimation of the energetic cost of desolvating the carbonyl and hydroxyl groups of the ligand. The difference between design model and crystal structure thus arises from both sampling limitations and energy function inaccuracies that are exacerbated by the near two-fold symmetry of the molecule.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The steroid hormone 17α-hydroxylprogesterone (17-OHP) is a biomarker for congenital adrenal hyperplasia and hence there is considerable interest in development of sensors for this compound. We used computational protein design to generate protein models with binding sites for 17-OHP containing an extended, nonpolar, shape-complementary binding pocket for the four-ring core of the compound, and hydrogen bonding residues at the base of the pocket to interact with carbonyl and hydroxyl groups at the more polar end of the ligand. Eight of 16 designed proteins experimentally tested bind 17-OHP with micromolar affinity. A co-crystal structure of one of the designs revealed that 17-OHP is rotated 180° around a pseudo-two-fold axis in the compound and displays multiple binding modes within the pocket, while still interacting with all of the designed residues in the engineered site. Subsequent rounds of mutagenesis and binding selection improved the ligand affinity to nanomolar range, while appearing to constrain the ligand to a single bound conformation that maintains the same “flipped” orientation relative to the original design. We trace the discrepancy in the design calculations to two sources: first, a failure to model subtle backbone changes which alter the distribution of sidechain rotameric states and second, an underestimation of the energetic cost of desolvating the carbonyl and hydroxyl groups of the ligand. The difference between design model and crystal structure thus arises from both sampling limitations and energy function inaccuracies that are exacerbated by the near two-fold symmetry of the molecule.
Aaron Chevalier*, Daniel-Adriano Silva*, Gabriel J. Rocklin*, Derrick R. Hicks, Renan Vergara, Patience Murapa, Steffen M. Bernard, Lu Zhang, Kwok-Ho Lam, Guorui Yao, Christopher D. Bahl, Shin-Ichiro Miyashita, Inna Goreshnik, James T. Fuller and Merika T. Koday, Cody M. Jenkins, Tom Colvin, Lauren Carter, Alan Bohn, Cassie M. Bryan, D. Alejandro Fernández-Velasco, Lance Stewart, Min Dong, Xuhui Huang, Rongsheng Jin, Ian A. Wilson, Deborah H. Fuller, David Baker
Massively parallel de novo protein design for targeted therapeutics Journal Article
In: Nature, vol. 550, no. 7674, pp. 74-79, 2017, ISSN: 0028-0836.
@article{Chevalier2017,
title = {Massively parallel de novo protein design for targeted therapeutics},
author = {Aaron Chevalier* and Daniel-Adriano Silva* and Gabriel J. Rocklin* and Derrick R. Hicks and Renan Vergara and Patience Murapa and Steffen M. Bernard and Lu Zhang and Kwok-Ho Lam and Guorui Yao and Christopher D. Bahl and Shin-Ichiro Miyashita and Inna Goreshnik and James T. Fuller and Merika T. Koday and Cody M. Jenkins and Tom Colvin and Lauren Carter and Alan Bohn and Cassie M. Bryan and D. Alejandro Fernández-Velasco and Lance Stewart and Min Dong and Xuhui Huang and Rongsheng Jin and Ian A. Wilson and Deborah H. Fuller and David Baker },
url = {https://www.nature.com/nature/journal/v550/n7674/full/nature23912.html
https://www.bakerlab.org/wp-content/uploads/2017/12/Nature_Chevalier_etal_2017.pdf},
doi = {10.1038/nature23912},
issn = {0028-0836},
year = {2017},
date = {2017-10-05},
journal = {Nature},
volume = {550},
number = {7674},
pages = {74-79},
abstract = {De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37–43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37–43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.
Sergey Ovchinnikov, Hahnbeom Park, David E. Kim, Frank DiMaio, David Baker
Protein structure prediction using Rosetta in CASP12 Journal Article
In: Proteins, 2017.
@article{Ovchinnikov2017,
title = {Protein structure prediction using Rosetta in CASP12},
author = {Sergey Ovchinnikov, Hahnbeom Park, David E. Kim, Frank DiMaio, David Baker},
url = {https://onlinelibrary.wiley.com/doi/epdf/10.1002/prot.25390
https://www.bakerlab.org/wp-content/uploads/2019/10/Ovchinnikov_et_al-2018-Proteins__Structure_Function_and_Bioinformatics.pdf},
doi = {10.1002/prot.25390},
year = {2017},
date = {2017-09-22},
journal = {Proteins},
abstract = {We describe several notable aspects of our structure predictions using Rosetta in CASP12 in the free modeling (FM) and refinement (TR) categories. First, we had previously generated (and published) models for most large protein families lacking experimentally determined structures usingRosetta guided by co-evolution based contact predictions, and for several targets these models proved better starting points for comparative modeling than any known crystal structure—our model database thus starts to fulfill one of the goals of the original protein structure initiative. Second, while our“human”group simply submitted ROBETTA models for most targets, for six targets expert intervention improved predictions considerably; the largest improvement was for T0886where we correctly parsed two discontinuous domains guided by predicted contact maps to accurately identify a structural homolog of the same fold. Third, Rosetta all atom refinement followed by MD simulations led to consistent but small improvements when starting models were close to the native structure, and larger but less consistent improvements when starting models were further away.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe several notable aspects of our structure predictions using Rosetta in CASP12 in the free modeling (FM) and refinement (TR) categories. First, we had previously generated (and published) models for most large protein families lacking experimentally determined structures usingRosetta guided by co-evolution based contact predictions, and for several targets these models proved better starting points for comparative modeling than any known crystal structure—our model database thus starts to fulfill one of the goals of the original protein structure initiative. Second, while our“human”group simply submitted ROBETTA models for most targets, for six targets expert intervention improved predictions considerably; the largest improvement was for T0886where we correctly parsed two discontinuous domains guided by predicted contact maps to accurately identify a structural homolog of the same fold. Third, Rosetta all atom refinement followed by MD simulations led to consistent but small improvements when starting models were close to the native structure, and larger but less consistent improvements when starting models were further away.
Bick, Matthew J*, Greisen, Per J*, Morey, Kevin J, Antunes, Mauricio S, La, David, Sankaran, Banumathi, Reymond, Luc, Johnsson, Kai, Medford, June I, Baker, David
Computational design of environmental sensors for the potent opioid fentanyl Journal Article
In: eLife Sciences Publications, vol. 6, pp. e28909, 2017, ISBN: 2050-084X.
@article{Bick2017,
title = {Computational design of environmental sensors for the potent opioid fentanyl},
author = {Bick, Matthew J* and Greisen, Per J* and Morey, Kevin J and Antunes, Mauricio S and La, David and Sankaran, Banumathi and Reymond, Luc and Johnsson, Kai and Medford, June I and Baker, David},
editor = {Cravatt, Benjamin F},
url = {https://elifesciences.org/articles/28909
https://www.bakerlab.org/wp-content/uploads/2018/06/elife-28909-v2-1.pdf},
doi = {10.7554/eLife.28909},
isbn = {2050-084X},
year = {2017},
date = {2017-09-19},
journal = {eLife Sciences Publications},
volume = {6},
pages = {e28909},
abstract = {We describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model. We use the designs to generate plant sensors for fentanyl by coupling ligand binding to design stability. The method should be generally useful for detecting toxic hydrophobic compounds in the environment.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model. We use the designs to generate plant sensors for fentanyl by coupling ligand binding to design stability. The method should be generally useful for detecting toxic hydrophobic compounds in the environment.
I Anishchenko, S Ovchinnikov, H Kamisetty, D Baker
Origins of coevolution between residues distant in protein 3D structures Journal Article
In: Proceedings of the National Academy of Sciences, vol. 114, no. 34, pp. 9122-9127, 2017.
@article{1000,
title = {Origins of coevolution between residues distant in protein 3D structures},
author = {I Anishchenko and S Ovchinnikov and H Kamisetty and D Baker},
editor = {August 22, 2017},
url = {http://www.pnas.org/content/114/34/9122
https://www.bakerlab.org/wp-content/uploads/2018/08/9122.full1_.pdf},
doi = {10.1073/pnas.1702664114},
year = {2017},
date = {2017-08-22},
journal = {Proceedings of the National Academy of Sciences},
volume = {114},
number = {34},
pages = {9122-9127},
abstract = {Residue pairs that directly coevolve in protein families are generally close in protein 3D structures. Here we study the exceptions to this general trend—directly coevolving residue pairs that are distant in protein structures—to determine the origins of evolutionary pressure on spatially distant residues and to understand the sources of error in contact-based structure prediction. Over a set of 4,000 protein families, we find that 25% of directly coevolving residue pairs are separated by more than 5 Å in protein structures and 3% by more than 15 Å. The majority (91%) of directly coevolving residue pairs in the 5–15 Å range are found to be in contact in at least one homologous structure—these exceptions arise from structural variation in the family in the region containing the residues. Thirty-five percent of the exceptions greater than 15 Å are at homo-oligomeric interfaces, 19% arise from family structural variation, and 27% are in repeat proteins likely reflecting alignment errors. Of the remaining long-range exceptions (<1% of the total number of coupled pairs), many can be attributed to close interactions in an oligomeric state. Overall, the results suggest that directly coevolving residue pairs not in repeat proteins are spatially proximal in at least one biologically relevant protein conformation within the family; we find little evidence for direct coupling between residues at spatially separated allosteric and functional sites or for increased direct coupling between residue pairs on putative allosteric pathways connecting them.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Residue pairs that directly coevolve in protein families are generally close in protein 3D structures. Here we study the exceptions to this general trend—directly coevolving residue pairs that are distant in protein structures—to determine the origins of evolutionary pressure on spatially distant residues and to understand the sources of error in contact-based structure prediction. Over a set of 4,000 protein families, we find that 25% of directly coevolving residue pairs are separated by more than 5 Å in protein structures and 3% by more than 15 Å. The majority (91%) of directly coevolving residue pairs in the 5–15 Å range are found to be in contact in at least one homologous structure—these exceptions arise from structural variation in the family in the region containing the residues. Thirty-five percent of the exceptions greater than 15 Å are at homo-oligomeric interfaces, 19% arise from family structural variation, and 27% are in repeat proteins likely reflecting alignment errors. Of the remaining long-range exceptions (<1% of the total number of coupled pairs), many can be attributed to close interactions in an oligomeric state. Overall, the results suggest that directly coevolving residue pairs not in repeat proteins are spatially proximal in at least one biologically relevant protein conformation within the family; we find little evidence for direct coupling between residues at spatially separated allosteric and functional sites or for increased direct coupling between residue pairs on putative allosteric pathways connecting them.
Yu-Ru Lin, Nobuyasu Koga, Sergey M. Vorobiev, David Baker
Cyclic oligomer design with de novo αβ-proteins Journal Article
In: Protein Science, 2017.
@article{Lin2017,
title = {Cyclic oligomer design with de novo αβ-proteins},
author = {Yu-Ru Lin and Nobuyasu Koga and Sergey M. Vorobiev and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/Lin_et_al-2017-Protein_Science.pdf
http://onlinelibrary.wiley.com/doi/10.1002/pro.3270/full},
doi = {10.1002/pro.3270},
year = {2017},
date = {2017-08-12},
journal = {Protein Science},
abstract = {We have previously shown that monomeric globular αβ- proteins can be designed de novo with considerable control over topology, size and shape. In this paper, we investigate the design of cyclic homo-oligomers from these starting points. We experimented with both keeping the original monomer backbones fixed during the cyclic docking and design process, and allowing the backbone of the monomer to conform to that of adjacent subunits in the homo-oligomer. The latter flexible backbone protocol generated designs with shape complementarity approaching that of native homo-oligomers, but experimental characterization showed that the fixed backbone designs were more stable and less aggregation prone. C2 homo-oligomers with β- strand backbone interactions were designed using both fixed and flexible backbone protocols. Designed C2 oligomers were structurally confirmed through x-ray crystallography and small-angle X-ray scattering (SAXS). In contrast, C3-C5 designed homo-oligomers with primarily nonpolar residues at interfaces all formed a range of oligomeric states. Taken together, our results suggest that for homo-oligomers formed from globular building blocks, improved structural specificity will be better achieved using monomers with increased shape complementarity and with more polar interfaces. This article is protected by copyright. All rights reserved.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have previously shown that monomeric globular αβ- proteins can be designed de novo with considerable control over topology, size and shape. In this paper, we investigate the design of cyclic homo-oligomers from these starting points. We experimented with both keeping the original monomer backbones fixed during the cyclic docking and design process, and allowing the backbone of the monomer to conform to that of adjacent subunits in the homo-oligomer. The latter flexible backbone protocol generated designs with shape complementarity approaching that of native homo-oligomers, but experimental characterization showed that the fixed backbone designs were more stable and less aggregation prone. C2 homo-oligomers with β- strand backbone interactions were designed using both fixed and flexible backbone protocols. Designed C2 oligomers were structurally confirmed through x-ray crystallography and small-angle X-ray scattering (SAXS). In contrast, C3-C5 designed homo-oligomers with primarily nonpolar residues at interfaces all formed a range of oligomeric states. Taken together, our results suggest that for homo-oligomers formed from globular building blocks, improved structural specificity will be better achieved using monomers with increased shape complementarity and with more polar interfaces. This article is protected by copyright. All rights reserved.
GJ Rocklin, TM Chidyausiku, I Goreshnik, A Ford, S Houliston, A Lemak, L Carter, R Ravichandran, VK Mulligan, A Chevalier, CH Arrowsmith, D Baker
Global analysis of protein folding using massively parallel design, synthesis, and testing Journal Article
In: Science, vol. 357, pp. 168-175, 2017.
@article{433b,
title = {Global analysis of protein folding using massively parallel design, synthesis, and testing},
author = {GJ Rocklin and TM Chidyausiku and I Goreshnik and A Ford and S Houliston and A Lemak and L Carter and R Ravichandran and VK Mulligan and A Chevalier and CH Arrowsmith and D Baker},
url = {http://science.sciencemag.org/content/357/6347/168.full?ijkey=/u00BDqfiTTGY&keytype=ref&siteid=sci
https://www.bakerlab.org/wp-content/uploads/2017/12/Science_Rocklin_etal_2017.pdf},
doi = {10.1126/science.aan0693},
year = {2017},
date = {2017-07-14},
journal = {Science},
volume = {357},
pages = {168-175},
abstract = {Proteins fold into unique native structures stabilized by thousands of weak interactions that collectively overcome the entropic cost of folding. Although these forces are “encoded” in the thousands of known protein structures, “decoding” them is challenging because of the complexity of natural proteins that have evolved for function, not stability. We combined computational protein design, next-generation gene synthesis, and a high-throughput protease susceptibility assay to measure folding and stability for more than 15,000 de novo designed miniproteins, 1000 natural proteins, 10,000 point mutants, and 30,000 negative control sequences. This analysis identified more than 2500 stable designed proteins in four basic folds—a number sufficient to enable us to systematically examine how sequence determines folding and stability in uncharted protein space. Iteration between design and experiment increased the design success rate from 6% to 47%, produced stable proteins unlike those found in nature for topologies where design was initially unsuccessful, and revealed subtle contributions to stability as designs became increasingly optimized. Our approach achieves the long-standing goal of a tight feedback cycle between computation and experiment and has the potential to transform computational protein design into a data-driven science.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Proteins fold into unique native structures stabilized by thousands of weak interactions that collectively overcome the entropic cost of folding. Although these forces are “encoded” in the thousands of known protein structures, “decoding” them is challenging because of the complexity of natural proteins that have evolved for function, not stability. We combined computational protein design, next-generation gene synthesis, and a high-throughput protease susceptibility assay to measure folding and stability for more than 15,000 de novo designed miniproteins, 1000 natural proteins, 10,000 point mutants, and 30,000 negative control sequences. This analysis identified more than 2500 stable designed proteins in four basic folds—a number sufficient to enable us to systematically examine how sequence determines folding and stability in uncharted protein space. Iteration between design and experiment increased the design success rate from 6% to 47%, produced stable proteins unlike those found in nature for topologies where design was initially unsuccessful, and revealed subtle contributions to stability as designs became increasingly optimized. Our approach achieves the long-standing goal of a tight feedback cycle between computation and experiment and has the potential to transform computational protein design into a data-driven science.
Strauch, Eva-Maria, Bernard, Steffen M, La, David, Bohn, Alan J, Lee, Peter S, Anderson, Caitlin E, Nieusma, Travis, Holstein, Carly A, Garcia, Natalie K, Hooper, Kathryn A, Ravichandran, Rashmi, Nelson, Jorgen W, Sheffler, William, Bloom, Jesse D, Lee, Kelly K, Ward, Andrew B, Yager, Paul, Fuller, Deborah H, Wilson, Ian A, Baker, David
Computational design of trimeric influenza-neutralizing proteins targeting the hemagglutinin receptor binding site Journal Article
In: Nature Biotechnology, vol. [Epub ahead of print], 2017, ISSN: 1546-1696.
@article{Strauch2017,
title = {Computational design of trimeric influenza-neutralizing proteins targeting the hemagglutinin receptor binding site},
author = {Strauch, Eva-Maria and Bernard, Steffen M and La, David and Bohn, Alan J and Lee, Peter S and Anderson, Caitlin E and Nieusma, Travis and Holstein, Carly A and Garcia, Natalie K and Hooper, Kathryn A and Ravichandran, Rashmi and Nelson, Jorgen W and Sheffler, William and Bloom, Jesse D and Lee, Kelly K and Ward, Andrew B and Yager, Paul and Fuller, Deborah H and Wilson, Ian A and Baker, David},
url = {https://www.bakerlab.org/wp-content/uploads/2017/06/Strauch_NatureBiotech_2017.pdf
https://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3907.html},
doi = {10.1038/nbt.3907},
issn = {1546-1696},
year = {2017},
date = {2017-06-12},
journal = {Nature Biotechnology},
volume = {[Epub ahead of print]},
abstract = {Many viral surface glycoproteins and cell surface receptors are homo-oligomers, and thus can potentially be targeted by geometrically matched homo-oligomers that engage all subunits simultaneously to attain high avidity and/or lock subunits together. The adaptive immune system cannot generally employ this strategy since the individual antibody binding sites are not arranged with appropriate geometry to simultaneously engage multiple sites in a single target homo-oligomer. We describe a general strategy for the computational design of homo-oligomeric protein assemblies with binding functionality precisely matched to homo-oligomeric target sites. In the first step, a small protein is designed that binds a single site on the target. In the second step, the designed protein is assembled into a homo-oligomer such that the designed binding sites are aligned with the target sites. We use this approach to design high-avidity trimeric proteins that bind influenza A hemagglutinin (HA) at its conserved receptor binding site. The designed trimers can both capture and detect HA in a paper-based diagnostic format, neutralizes influenza in cell culture, and completely protects mice when given as a single dose 24 h before or after challenge with influenza.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many viral surface glycoproteins and cell surface receptors are homo-oligomers, and thus can potentially be targeted by geometrically matched homo-oligomers that engage all subunits simultaneously to attain high avidity and/or lock subunits together. The adaptive immune system cannot generally employ this strategy since the individual antibody binding sites are not arranged with appropriate geometry to simultaneously engage multiple sites in a single target homo-oligomer. We describe a general strategy for the computational design of homo-oligomeric protein assemblies with binding functionality precisely matched to homo-oligomeric target sites. In the first step, a small protein is designed that binds a single site on the target. In the second step, the designed protein is assembled into a homo-oligomer such that the designed binding sites are aligned with the target sites. We use this approach to design high-avidity trimeric proteins that bind influenza A hemagglutinin (HA) at its conserved receptor binding site. The designed trimers can both capture and detect HA in a paper-based diagnostic format, neutralizes influenza in cell culture, and completely protects mice when given as a single dose 24 h before or after challenge with influenza.
Janda CY, Dang LT, You C, Chang J, de Lau W, Zhong ZA, Yan KS, Marecic O, Siepe D, Li X, Moody JD, Williams BO, Clevers H, Piehler J, Baker D, Kuo CJ, Garcia KC
Surrogate Wnt agonists that phenocopy canonical Wnt and β-catenin signalling. Journal Article
In: Nature, vol. 545, no. 7653, pp. 234-237, 2017.
@article{1001,
title = {Surrogate Wnt agonists that phenocopy canonical Wnt and β-catenin signalling.},
author = {Janda CY and Dang LT and You C and Chang J and de Lau W and Zhong ZA and Yan KS and Marecic O and Siepe D and Li X and Moody JD and Williams BO and Clevers H and Piehler J and Baker D and Kuo CJ and Garcia KC},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/nature22306.pdf
http://www.nature.com/nature/journal/v545/n7653/abs/nature22306.html?foxtrotcallback=true},
doi = {10.1038/nature22306},
year = {2017},
date = {2017-05-11},
journal = {Nature},
volume = {545},
number = {7653},
pages = {234-237},
abstract = {Wnt proteins modulate cell proliferation and differentiation and the self-renewal of stem cells by inducing β-catenin-dependent signalling through the Wnt receptor frizzled (FZD) and the co-receptors LRP5 and LRP6 to regulate cell fate decisions and the growth and repair of several tissues1. The 19 mammalian Wnt proteins are cross-reactive with the 10 FZD receptors, and this has complicated the attribution of distinct biological functions to specific FZD and Wnt subtype interactions. Furthermore, Wnt proteins are modified post-translationally by palmitoylation, which is essential for their secretion, function and interaction with FZD receptors2, 3, 4. As a result of their acylation, Wnt proteins are very hydrophobic and require detergents for purification, which presents major obstacles to the preparation and application of recombinant Wnt proteins. This hydrophobicity has hindered the determination of the molecular mechanisms of Wnt signalling activation and the functional importance of FZD subtypes, and the use of Wnt proteins as therapeutic agents. Here we develop surrogate Wnt agonists, water-soluble FZD–LRP5/LRP6 heterodimerizers, with FZD5/FZD8-specific and broadly FZD-reactive binding domains. Similar to WNT3A, these Wnt agonists elicit a characteristic β-catenin signalling response in a FZD-selective fashion, enhance the osteogenic lineage commitment of primary mouse and human mesenchymal stem cells, and support the growth of a broad range of primary human organoid cultures. In addition, the surrogates can be systemically expressed and exhibit Wnt activity in vivo in the mouse liver, regulating metabolic liver zonation and promoting hepatocyte proliferation, resulting in hepatomegaly. These surrogates demonstrate that canonical Wnt signalling can be activated by bi-specific ligands that induce receptor heterodimerization. Furthermore, these easily produced, non-lipidated Wnt surrogate agonists facilitate functional studies of Wnt signalling and the exploration of Wnt agonists for translational applications in regenerative medicine.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Wnt proteins modulate cell proliferation and differentiation and the self-renewal of stem cells by inducing β-catenin-dependent signalling through the Wnt receptor frizzled (FZD) and the co-receptors LRP5 and LRP6 to regulate cell fate decisions and the growth and repair of several tissues1. The 19 mammalian Wnt proteins are cross-reactive with the 10 FZD receptors, and this has complicated the attribution of distinct biological functions to specific FZD and Wnt subtype interactions. Furthermore, Wnt proteins are modified post-translationally by palmitoylation, which is essential for their secretion, function and interaction with FZD receptors2, 3, 4. As a result of their acylation, Wnt proteins are very hydrophobic and require detergents for purification, which presents major obstacles to the preparation and application of recombinant Wnt proteins. This hydrophobicity has hindered the determination of the molecular mechanisms of Wnt signalling activation and the functional importance of FZD subtypes, and the use of Wnt proteins as therapeutic agents. Here we develop surrogate Wnt agonists, water-soluble FZD–LRP5/LRP6 heterodimerizers, with FZD5/FZD8-specific and broadly FZD-reactive binding domains. Similar to WNT3A, these Wnt agonists elicit a characteristic β-catenin signalling response in a FZD-selective fashion, enhance the osteogenic lineage commitment of primary mouse and human mesenchymal stem cells, and support the growth of a broad range of primary human organoid cultures. In addition, the surrogates can be systemically expressed and exhibit Wnt activity in vivo in the mouse liver, regulating metabolic liver zonation and promoting hepatocyte proliferation, resulting in hepatomegaly. These surrogates demonstrate that canonical Wnt signalling can be activated by bi-specific ligands that induce receptor heterodimerization. Furthermore, these easily produced, non-lipidated Wnt surrogate agonists facilitate functional studies of Wnt signalling and the exploration of Wnt agonists for translational applications in regenerative medicine.
Marcos, Enrique*, Basanta, Benjamin*, Chidyausiku, Tamuka M., Tang, Yuefeng, Oberdorfer, Gustav, Liu, Gaohua, Swapna, G. V. T., Guan, Rongjin, Silva, Daniel-Adriano, Dou, Jiayi, Pereira, Jose Henrique, Xiao, Rong, Sankaran, Banumathi, Zwart, Peter H., Montelione, Gaetano T., Baker, David
Principles for designing proteins with cavities formed by curved β sheets Journal Article
In: Science, vol. 355, no. 6321, pp. 201–206, 2017, ISSN: 0036-8075.
@article{Marcos2017,
title = {Principles for designing proteins with cavities formed by curved β sheets},
author = {Marcos, Enrique* and Basanta, Benjamin* and Chidyausiku, Tamuka M. and Tang, Yuefeng and Oberdorfer, Gustav and Liu, Gaohua and Swapna, G. V. T. and Guan, Rongjin and Silva, Daniel-Adriano and Dou, Jiayi and Pereira, Jose Henrique and Xiao, Rong and Sankaran, Banumathi and Zwart, Peter H. and Montelione, Gaetano T. and Baker, David},
url = {https://www.bakerlab.org/wp-content/uploads/2017/01/Marcos_Science_2017.pdf
http://science.sciencemag.org/content/355/6321/201},
doi = {10.1126/science.aah7389},
issn = {0036-8075},
year = {2017},
date = {2017-01-01},
journal = {Science},
volume = {355},
number = {6321},
pages = {201--206},
publisher = {American Association for the Advancement of Science},
abstract = {In de novo protein design, creating custom-tailored binding sites is a particular challenge because these sites often involve nonideal backbone structures. For example, curved b sheets are a common ligand binding motif. Marcos et al. investigated the principles that drive β-sheet curvature by studying the geometry of β sheets in natural proteins and folding simulations. In a step toward custom design of enzyme catalysts, they used these principles to control β-sheet geometry and design proteins with differently shaped cavities.Science, this issue p. 201Active sites and ligand-binding cavities in native proteins are often formed by curved β sheets, and the ability to control β-sheet curvature would allow design of binding proteins with cavities customized to specific ligands. Toward this end, we investigated the mechanisms controlling β-sheet curvature by studying the geometry of β sheets in naturally occurring protein structures and folding simulations. The principles emerging from this analysis were used to design, de novo, a series of proteins with curved β sheets topped with α helices. Nuclear magnetic resonance and crystal structures of the designs closely match the computational models, showing that β-sheet curvature can be controlled with atomic-level accuracy. Our approach enables the design of proteins with cavities and provides a route to custom design ligand-binding and catalytic sites.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In de novo protein design, creating custom-tailored binding sites is a particular challenge because these sites often involve nonideal backbone structures. For example, curved b sheets are a common ligand binding motif. Marcos et al. investigated the principles that drive β-sheet curvature by studying the geometry of β sheets in natural proteins and folding simulations. In a step toward custom design of enzyme catalysts, they used these principles to control β-sheet geometry and design proteins with differently shaped cavities.Science, this issue p. 201Active sites and ligand-binding cavities in native proteins are often formed by curved β sheets, and the ability to control β-sheet curvature would allow design of binding proteins with cavities customized to specific ligands. Toward this end, we investigated the mechanisms controlling β-sheet curvature by studying the geometry of β sheets in naturally occurring protein structures and folding simulations. The principles emerging from this analysis were used to design, de novo, a series of proteins with curved β sheets topped with α helices. Nuclear magnetic resonance and crystal structures of the designs closely match the computational models, showing that β-sheet curvature can be controlled with atomic-level accuracy. Our approach enables the design of proteins with cavities and provides a route to custom design ligand-binding and catalytic sites.
Sergey Ovchinnikov, Hahnbeom Park, Neha Varghese, Po-Ssu Huang, Georgios A. Pavlopoulos, David E. Kim, Hetunandan Kamisetty, Nikos C. Kyrpides, David Baker
Protein structure determination using metagenome sequence data Journal Article
In: Science, vol. 355, no. 6322, pp. 294–298, 2017, ISSN: 0036-8075.
@article{Ovchinnikov294,
title = {Protein structure determination using metagenome sequence data},
author = { Sergey Ovchinnikov and Hahnbeom Park and Neha Varghese and Po-Ssu Huang and Georgios A. Pavlopoulos and David E. Kim and Hetunandan Kamisetty and Nikos C. Kyrpides and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2017/01/ovchinnikov_science_2017.pdf
http://science.sciencemag.org/content/355/6322/294},
doi = {10.1126/science.aah4043},
issn = {0036-8075},
year = {2017},
date = {2017-01-01},
journal = {Science},
volume = {355},
number = {6322},
pages = {294--298},
publisher = {American Association for the Advancement of Science},
abstract = {Fewer than a third of the 14,849 known protein families have at least one member with an experimentally determined structure. This leaves more than 5000 protein families with no structural information. Protein modeling using residue-residue contacts inferred from evolutionary data has been successful in modeling unknown structures, but it requires large numbers of aligned sequences. Ovchinnikov et al. augmented such sequence alignments with metagenome sequence data (see the Perspective by S"oding). They determined the number of sequences required to allow modeling, developed criteria for model quality, and, where possible, improved modeling by matching predicted contacts to known structures. Their method predicted quality structural models for 614 protein families, of which about 140 represent newly discovered protein folds.Science, this issue p. 294; see also p. 248Despite decades of work by structural biologists, there are still ~5200 protein families with unknown structure outside the range of comparative modeling. We show that Rosetta structure prediction guided by residue-residue contacts inferred from evolutionary information can accurately model proteins that belong to large families and that metagenome sequence data more than triple the number of protein families with sufficient sequences for accurate modeling. We then integrate metagenome data, contact-based structure matching, and Rosetta structure calculations to generate models for 614 protein families with currently unknown structures; 206 are membrane proteins and 137 have folds not represented in the Protein Data Bank. This approach provides the representative models for large protein families originally envisioned as the goal of the Protein Structure Initiative at a fraction of the cost.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Fewer than a third of the 14,849 known protein families have at least one member with an experimentally determined structure. This leaves more than 5000 protein families with no structural information. Protein modeling using residue-residue contacts inferred from evolutionary data has been successful in modeling unknown structures, but it requires large numbers of aligned sequences. Ovchinnikov et al. augmented such sequence alignments with metagenome sequence data (see the Perspective by S"oding). They determined the number of sequences required to allow modeling, developed criteria for model quality, and, where possible, improved modeling by matching predicted contacts to known structures. Their method predicted quality structural models for 614 protein families, of which about 140 represent newly discovered protein folds.Science, this issue p. 294; see also p. 248Despite decades of work by structural biologists, there are still ~5200 protein families with unknown structure outside the range of comparative modeling. We show that Rosetta structure prediction guided by residue-residue contacts inferred from evolutionary information can accurately model proteins that belong to large families and that metagenome sequence data more than triple the number of protein families with sufficient sequences for accurate modeling. We then integrate metagenome data, contact-based structure matching, and Rosetta structure calculations to generate models for 614 protein families with currently unknown structures; 206 are membrane proteins and 137 have folds not represented in the Protein Data Bank. This approach provides the representative models for large protein families originally envisioned as the goal of the Protein Structure Initiative at a fraction of the cost.
2016
Jeremy H. Mills, William Sheffler, Maraia E. Ener, Patrick J. Almhjell, Gustav Oberdorfer, José Henrique Pereira, Fabio Parmeggiani, Banumathi Sankaran, Peter H. Zwart, David Baker
Computational design of a homotrimeric metalloprotein with a trisbipyridyl core Journal Article
In: PNAS, vol. 113, no. 52, pp. 15012-15017, 2016.
@article{1300,
title = {Computational design of a homotrimeric metalloprotein with a trisbipyridyl core},
author = {Jeremy H. Mills and William Sheffler and Maraia E. Ener and Patrick J. Almhjell and Gustav Oberdorfer and José Henrique Pereira and Fabio Parmeggiani and Banumathi Sankaran and Peter H. Zwart and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/15012.full_.pdf
http://www.pnas.org/content/113/52/15012.abstract
},
doi = {10.1073/pnas.1600188113},
year = {2016},
date = {2016-12-08},
journal = {PNAS},
volume = {113},
number = {52},
pages = {15012-15017},
abstract = {Metal-chelating heteroaryl small molecules have found widespread use as building blocks for coordination-driven, self-assembling nanostructures. The metal-chelating noncanonical amino acid (2,2′-bipyridin-5yl)alanine (Bpy-ala) could, in principle, be used to nucleate specific metalloprotein assemblies if introduced into proteins such that one assembly had much lower free energy than all alternatives. Here we describe the use of the Rosetta computational methodology to design a self-assembling homotrimeric protein with [Fe(Bpy-ala)3]2+ complexes at the interface between monomers. X-ray crystallographic analysis of the homotrimer showed that the design process had near-atomic-level accuracy: The all-atom rmsd between the design model and crystal structure for the residues at the protein interface is ∼1.4 Å. These results demonstrate that computational protein design together with genetically encoded noncanonical amino acids can be used to drive formation of precisely specified metal-mediated protein assemblies that could find use in a wide range of photophysical applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Metal-chelating heteroaryl small molecules have found widespread use as building blocks for coordination-driven, self-assembling nanostructures. The metal-chelating noncanonical amino acid (2,2′-bipyridin-5yl)alanine (Bpy-ala) could, in principle, be used to nucleate specific metalloprotein assemblies if introduced into proteins such that one assembly had much lower free energy than all alternatives. Here we describe the use of the Rosetta computational methodology to design a self-assembling homotrimeric protein with [Fe(Bpy-ala)3]2+ complexes at the interface between monomers. X-ray crystallographic analysis of the homotrimer showed that the design process had near-atomic-level accuracy: The all-atom rmsd between the design model and crystal structure for the residues at the protein interface is ∼1.4 Å. These results demonstrate that computational protein design together with genetically encoded noncanonical amino acids can be used to drive formation of precisely specified metal-mediated protein assemblies that could find use in a wide range of photophysical applications.
Fallas JA, Ueda G, Sheffler W, Nguyen V, McNamara DE, Sankaran B, Pereira JH, Parmeggiani F, Brunette TJ, Cascio D, Yeates TR, Zwart P, Baker D
Computational design of self-assembling cyclic protein homo-oligomers Journal Article
In: Nature Chemistry, vol. 9, pp. 353–360, 2016.
@article{Fallas2016,
title = {Computational design of self-assembling cyclic protein homo-oligomers},
author = {Fallas JA and Ueda G and Sheffler W and Nguyen V and McNamara DE and Sankaran B and Pereira JH and Parmeggiani F and Brunette TJ and Cascio D and Yeates TR and Zwart P and Baker D},
url = {https://www.nature.com/articles/nchem.2673
https://www.bakerlab.org/wp-content/uploads/2020/10/Fassas-et-al-2016-Homooligomers.pdf},
doi = {10.1038/nchem.2673},
year = {2016},
date = {2016-12-05},
journal = {Nature Chemistry},
volume = {9},
pages = {353–360},
abstract = {Self-assembling cyclic protein homo-oligomers play important roles in biology, and the ability to generate custom homo-oligomeric structures could enable new approaches to probe biological function. Here we report a general approach to design cyclic homo-oligomers that employs a new residue-pair-transform method to assess the designability of a protein–protein interface. This method is sufficiently rapid to enable the systematic enumeration of cyclically docked arrangements of a monomer followed by sequence design of the newly formed interfaces. We use this method to design interfaces onto idealized repeat proteins that direct their assembly into complexes that possess cyclic symmetry. Of 96 designs that were characterized experimentally, 21 were found to form stable monodisperse homo-oligomers in solution, and 15 (four homodimers, six homotrimers, six homotetramers and one homopentamer) had solution small-angle X-ray scattering data consistent with the design models. X-ray crystal structures were obtained for five of the designs and each is very close to their corresponding computational model.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Self-assembling cyclic protein homo-oligomers play important roles in biology, and the ability to generate custom homo-oligomeric structures could enable new approaches to probe biological function. Here we report a general approach to design cyclic homo-oligomers that employs a new residue-pair-transform method to assess the designability of a protein–protein interface. This method is sufficiently rapid to enable the systematic enumeration of cyclically docked arrangements of a monomer followed by sequence design of the newly formed interfaces. We use this method to design interfaces onto idealized repeat proteins that direct their assembly into complexes that possess cyclic symmetry. Of 96 designs that were characterized experimentally, 21 were found to form stable monodisperse homo-oligomers in solution, and 15 (four homodimers, six homotrimers, six homotetramers and one homopentamer) had solution small-angle X-ray scattering data consistent with the design models. X-ray crystal structures were obtained for five of the designs and each is very close to their corresponding computational model.
Stephanie Berger, Erik Procko, Daciana Margineantu, Erinna F Lee, Betty W Shen, Alex Zelter, Daniel-Adriano Silva, and Kusum Chawla, Marco J Herold, Jean-Marc Garnier, Richard Johnson, Michael J MacCoss, Guillaume Lessene, Trisha N Davis, Patrick S Stayton, Barry L Stoddard, W Douglas Fairlie, David M Hockenbery, David Baker
Computationally designed high specificity inhibitors delineate the roles of BCL2 family proteins in cancer Journal Article
In: Elife, 2016.
@article{S2016,
title = {Computationally designed high specificity inhibitors delineate the roles of BCL2 family proteins in cancer},
author = {Stephanie Berger and Erik Procko and Daciana Margineantu and Erinna F Lee and Betty W Shen and Alex Zelter and Daniel-Adriano Silva and and Kusum Chawla and Marco J Herold and Jean-Marc Garnier and Richard Johnson and Michael J MacCoss and Guillaume Lessene and Trisha N Davis and Patrick S Stayton and Barry L Stoddard and W Douglas Fairlie and David M Hockenbery and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2017/01/Berger_elife_2016.pdf
https://elifesciences.org/articles/20352},
doi = {10.7554/eLife.20352},
year = {2016},
date = {2016-11-02},
journal = {Elife},
abstract = {Many cancers overexpress one or more of the six human pro-survival BCL2 family proteins to evade apoptosis. To determine which BCL2 protein or proteins block apoptosis in different cancers, we computationally designed three-helix bundle protein inhibitors specific for each BCL2 pro-survival protein. Following in vitro optimization, each inhibitor binds its target with high picomolar to low nanomolar affinity and at least 300-fold specificity. Expression of the designed inhibitors in human cancer cell lines revealed unique dependencies on BCL2 proteins for survival which could not be inferred from other BCL2 profiling methods. Our results show that designed inhibitors can be generated for each member of a closely-knit protein family to probe the importance of specific protein-protein interactions in complex biological processes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many cancers overexpress one or more of the six human pro-survival BCL2 family proteins to evade apoptosis. To determine which BCL2 protein or proteins block apoptosis in different cancers, we computationally designed three-helix bundle protein inhibitors specific for each BCL2 pro-survival protein. Following in vitro optimization, each inhibitor binds its target with high picomolar to low nanomolar affinity and at least 300-fold specificity. Expression of the designed inhibitors in human cancer cell lines revealed unique dependencies on BCL2 proteins for survival which could not be inferred from other BCL2 profiling methods. Our results show that designed inhibitors can be generated for each member of a closely-knit protein family to probe the importance of specific protein-protein interactions in complex biological processes.
Po-Ssu Huang, Scott E. Boyken, David Baker
The coming of age of de novo protein design Journal Article
In: Nature, vol. 537, pp. 320-327, 2016.
@article{Huang2016,
title = {The coming of age of de novo protein design},
author = {Po-Ssu Huang and Scott E. Boyken and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/09/HuangBoyken_DeNovoDesign_Nature2016.pdf},
doi = {10.1038/nature19946},
year = {2016},
date = {2016-09-15},
journal = {Nature},
volume = {537},
pages = {320-327},
abstract = {There are 20200 possible amino-acid sequences for a 200-residue protein, of which the natural evolutionary process has sampled only an infinitesimal subset. De novo protein design explores the full sequence space, guided by the physical principles that underlie protein folding. Computational methodology has advanced to the point that a wide range of structures can be designed from scratch with atomic-level accuracy. Almost all protein engineering so far has involved the modification of naturally occurring proteins; it should now be possible to design new functional proteins from the ground up to tackle current challenges in biomedicine and nanotechnology.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
There are 20200 possible amino-acid sequences for a 200-residue protein, of which the natural evolutionary process has sampled only an infinitesimal subset. De novo protein design explores the full sequence space, guided by the physical principles that underlie protein folding. Computational methodology has advanced to the point that a wide range of structures can be designed from scratch with atomic-level accuracy. Almost all protein engineering so far has involved the modification of naturally occurring proteins; it should now be possible to design new functional proteins from the ground up to tackle current challenges in biomedicine and nanotechnology.
Gaurav Bhardwaj*, Vikram Khipple Mulligan*, Christopher D. Bahl*, Jason M. Gilmore, Peta J. Harvey, Olivier Cheneval, Garry W. Buchko, Surya V. S. R. K. Pulavarti, Quentin Kaas, Alexander Eletsky, Po-Ssu Huang, William A. Johnsen, Per Jr Greisen, Gabriel J. Rocklin, Yifan Song, Thomas W. Linsky, Andrew Watkins, Stephen A. Rettie, Xianzhong Xu, Lauren P. Carter, Richard Bonneau, James M. Olson, Evangelos Coutsias, Colin E. Correnti, Thomas Szyperski, David J. Craik, David Baker
Accurate de novo design of hyperstable constrained peptides Journal Article
In: Nature, 2016.
@article{Bhardwaj2016,
title = {Accurate de novo design of hyperstable constrained peptides},
author = { Gaurav Bhardwaj* and Vikram Khipple Mulligan* and Christopher D. Bahl* and Jason M. Gilmore and Peta J. Harvey and Olivier Cheneval and Garry W. Buchko and Surya V. S. R. K. Pulavarti and Quentin Kaas and Alexander Eletsky and Po-Ssu Huang and William A. Johnsen and Per Jr Greisen and Gabriel J. Rocklin and Yifan Song and Thomas W. Linsky and Andrew Watkins and Stephen A. Rettie and Xianzhong Xu, Lauren P. Carter and Richard Bonneau and James M. Olson and Evangelos Coutsias and Colin E. Correnti and Thomas Szyperski and David J. Craik and David Baker },
url = {https://www.bakerlab.org/wp-content/uploads/2016/09/Bhardwaj_Nature_2016.pdf},
doi = {10.1038/nature19791},
year = {2016},
date = {2016-09-14},
journal = {Nature},
abstract = {Naturally occurring, pharmacologically active peptides constrained with covalent crosslinks generally have shapes that have evolved to fit precisely into binding pockets on their targets. Such peptides can have excellent pharmaceutical properties, combining the stability and tissue penetration of small-molecule drugs with the specificity of much larger protein therapeutics. The ability to design constrained peptides with precisely specified tertiary structures would enable the design of shape-complementary inhibitors of arbitrary targets. Here we describe the development of computational methods for accurate de novo design of conformationally restricted peptides, and the use of these methods to design 18–47 residue, disulfide-crosslinked peptides, a subset of which are heterochiral and/or N–C backbone-cyclized. Both genetically encodable and non-canonical peptides are exceptionally stable to thermal and chemical denaturation, and 12 experimentally determined X-ray and NMR structures are nearly identical to the computational design models. The computational design methods and stable scaffolds presented here provide the basis for development of a new generation of peptide-based drugs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Naturally occurring, pharmacologically active peptides constrained with covalent crosslinks generally have shapes that have evolved to fit precisely into binding pockets on their targets. Such peptides can have excellent pharmaceutical properties, combining the stability and tissue penetration of small-molecule drugs with the specificity of much larger protein therapeutics. The ability to design constrained peptides with precisely specified tertiary structures would enable the design of shape-complementary inhibitors of arbitrary targets. Here we describe the development of computational methods for accurate de novo design of conformationally restricted peptides, and the use of these methods to design 18–47 residue, disulfide-crosslinked peptides, a subset of which are heterochiral and/or N–C backbone-cyclized. Both genetically encodable and non-canonical peptides are exceptionally stable to thermal and chemical denaturation, and 12 experimentally determined X-ray and NMR structures are nearly identical to the computational design models. The computational design methods and stable scaffolds presented here provide the basis for development of a new generation of peptide-based drugs.
Jacob B. Bale, Shane Gonen, Yuxi Liu, William Sheffler, Daniel Ellis, Chantz Thomas, Duilio Cascio, Todd O. Yeates, Tamir Gonen, Neil P. King, David Baker
Accurate design of megadalton-scale two-component icosahedral protein complexes Journal Article
In: Science, vol. 353, no. 6297, pp. 389-394, 2016.
@article{Bale2016,
title = {Accurate design of megadalton-scale two-component icosahedral protein complexes},
author = {Jacob B. Bale and Shane Gonen and Yuxi Liu and William Sheffler and Daniel Ellis and Chantz Thomas and Duilio Cascio and Todd O. Yeates and Tamir Gonen and Neil P. King and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/Bale_Science_2016.pdf},
doi = {10.1126/science.aaf8818},
year = {2016},
date = {2016-07-22},
journal = {Science},
volume = {353},
number = {6297},
pages = {389-394},
abstract = {Nature provides many examples of self- and co-assembling protein-based molecular machines, including icosahedral protein cages that serve as scaffolds, enzymes, and compartments for essential biochemical reactions and icosahedral virus capsids, which encapsidate and protect viral genomes and mediate entry into host cells. Inspired by these natural materials, we report the computational design and experimental characterization of co-assembling, two-component, 120-subunit icosahedral protein nanostructures with molecular weights (1.8 to 2.8 megadaltons) and dimensions (24 to 40 nanometers in diameter) comparable to those of small viral capsids. Electron microscopy, small-angle x-ray scattering, and x-ray crystallography show that 10 designs spanning three distinct icosahedral architectures form materials closely matching the design models. In vitro assembly of icosahedral complexes from independently purified components occurs rapidly, at rates comparable to those of viral capsids, and enables controlled packaging of molecular cargo through charge complementarity. The ability to design megadalton-scale materials with atomic-level accuracy and controllable assembly opens the door to a new generation of genetically programmable protein-based molecular machines.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Nature provides many examples of self- and co-assembling protein-based molecular machines, including icosahedral protein cages that serve as scaffolds, enzymes, and compartments for essential biochemical reactions and icosahedral virus capsids, which encapsidate and protect viral genomes and mediate entry into host cells. Inspired by these natural materials, we report the computational design and experimental characterization of co-assembling, two-component, 120-subunit icosahedral protein nanostructures with molecular weights (1.8 to 2.8 megadaltons) and dimensions (24 to 40 nanometers in diameter) comparable to those of small viral capsids. Electron microscopy, small-angle x-ray scattering, and x-ray crystallography show that 10 designs spanning three distinct icosahedral architectures form materials closely matching the design models. In vitro assembly of icosahedral complexes from independently purified components occurs rapidly, at rates comparable to those of viral capsids, and enables controlled packaging of molecular cargo through charge complementarity. The ability to design megadalton-scale materials with atomic-level accuracy and controllable assembly opens the door to a new generation of genetically programmable protein-based molecular machines.
Yang Hsia*, Jacob B. Bale*, Shane Gonen, Dan Shi, William Sheffler, Kimberly K. Fong, Nattermann, Chunfu Xu, Po-Ssu Huang, Rashmi Ravichandran, Sue Yi, Trisha N. Davis, Tamir Gonen, Neil P. King, David Baker
Design of a hyperstable 60-subunit protein icosahedron Journal Article
In: Nature, 2016.
@article{Hsia2016,
title = {Design of a hyperstable 60-subunit protein icosahedron},
author = { Yang Hsia* and Jacob B. Bale* and Shane Gonen and Dan Shi and William Sheffler and Kimberly K. Fong and Nattermann and Chunfu Xu and Po-Ssu Huang and Rashmi Ravichandran and Sue Yi and Trisha N. Davis and Tamir Gonen and Neil P. King and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/Hsia_Nature_2016.pdf},
doi = {10.1038/nature18010},
year = {2016},
date = {2016-06-15},
journal = {Nature},
abstract = {The icosahedron is the largest of the Platonic solids, and icosahedral protein structures are widely used in biological systems for packaging and transport. There has been considerable interest in repurposing such structures for applications ranging from targeted delivery to multivalent immunogen presentation. The ability to design proteins that self-assemble into precisely specified, highly ordered icosahedral structures would open the door to a new generation of protein containers with properties custom-tailored to specific applications. Here we describe the computational design of a 25-nanometre icosahedral nanocage that self-assembles from trimeric protein building blocks. The designed protein was produced in Escherichia coli, and found by electron microscopy to assemble into a homogenous population of icosahedral particles nearly identical to the design model. The particles are stable in 6.7 molar guanidine hydrochloride at up to 80 degrees Celsius, and undergo extremely abrupt, but reversible, disassembly between 2 molar and 2.25 molar guanidinium thiocyanate. The icosahedron is robust to genetic fusions: one or two copies of green fluorescent protein (GFP) can be fused to each of the 60 subunits to create highly fluorescent ‘standard candles’ for use in light microscopy, and a designed protein pentamer can be placed in the centre of each of the 20 pentameric faces to modulate the size of the entrance/ exit channels of the cage. Such robust and customizable nanocages should have considerable utility in targeted drug delivery, vaccine design and synthetic biology.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The icosahedron is the largest of the Platonic solids, and icosahedral protein structures are widely used in biological systems for packaging and transport. There has been considerable interest in repurposing such structures for applications ranging from targeted delivery to multivalent immunogen presentation. The ability to design proteins that self-assemble into precisely specified, highly ordered icosahedral structures would open the door to a new generation of protein containers with properties custom-tailored to specific applications. Here we describe the computational design of a 25-nanometre icosahedral nanocage that self-assembles from trimeric protein building blocks. The designed protein was produced in Escherichia coli, and found by electron microscopy to assemble into a homogenous population of icosahedral particles nearly identical to the design model. The particles are stable in 6.7 molar guanidine hydrochloride at up to 80 degrees Celsius, and undergo extremely abrupt, but reversible, disassembly between 2 molar and 2.25 molar guanidinium thiocyanate. The icosahedron is robust to genetic fusions: one or two copies of green fluorescent protein (GFP) can be fused to each of the 60 subunits to create highly fluorescent ‘standard candles’ for use in light microscopy, and a designed protein pentamer can be placed in the centre of each of the 20 pentameric faces to modulate the size of the entrance/ exit channels of the cage. Such robust and customizable nanocages should have considerable utility in targeted drug delivery, vaccine design and synthetic biology.
Klein, J. C., Lajoie, M. J., Schwartz, J. J., Strauch, E.-M., Nelson, J., Baker, D., & Shendure, J
Multiplex pairwise assembly of array-derived DNA oligonucleotides Journal Article
In: Nucleic Acids Research, vol. 44, no. 5, pp. e43, 2016.
@article{Klein2016,
title = {Multiplex pairwise assembly of array-derived DNA oligonucleotides},
author = {Klein, J. C., Lajoie, M. J., Schwartz, J. J., Strauch, E.-M., Nelson, J., Baker, D., & Shendure, J},
url = {https://www.bakerlab.org/wp-content/uploads/2016/05/gkv1177.pdf},
doi = {10.1093/nar/gkv1177},
year = {2016},
date = {2016-03-18},
journal = {Nucleic Acids Research},
volume = {44},
number = {5},
pages = {e43},
abstract = {While the cost of DNA sequencing has dropped by five orders of magnitude in the past decade, DNA synthesis remains expensive for many applications. Although DNA microarrays have decreased the cost of oligonucleotide synthesis, the use of array-synthesized oligos in practice is limited by short synthesis lengths, high synthesis error rates, low yield and the challenges of assembling long constructs from complex pools. Toward addressing these issues, we developed a protocol for multiplex pairwise assembly of oligos from array-synthesized oligonucleotide pools. To evaluate the method, we attempted to assemble up to 2271 targets ranging in length from 192–252 bases using pairs of array-synthesized oligos. Within sets of complexity ranging from 131–250 targets, we observed error-free assemblies for 90.5% of all targets. When all 2271 targets were assembled in one reaction, we observed error-free constructs for 70.6%. While the assembly method intrinsically increased accuracy to a small degree, we further increased accuracy by using a high throughput ‘Dial-Out PCR’ protocol, which combines Illumina sequencing with an in-house set of unique PCR tags to selectively amplify perfect assemblies from complex synthetic pools. This approach has broad applicability to DNA assembly and high-throughput functional screens.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
While the cost of DNA sequencing has dropped by five orders of magnitude in the past decade, DNA synthesis remains expensive for many applications. Although DNA microarrays have decreased the cost of oligonucleotide synthesis, the use of array-synthesized oligos in practice is limited by short synthesis lengths, high synthesis error rates, low yield and the challenges of assembling long constructs from complex pools. Toward addressing these issues, we developed a protocol for multiplex pairwise assembly of oligos from array-synthesized oligonucleotide pools. To evaluate the method, we attempted to assemble up to 2271 targets ranging in length from 192–252 bases using pairs of array-synthesized oligos. Within sets of complexity ranging from 131–250 targets, we observed error-free assemblies for 90.5% of all targets. When all 2271 targets were assembled in one reaction, we observed error-free constructs for 70.6%. While the assembly method intrinsically increased accuracy to a small degree, we further increased accuracy by using a high throughput ‘Dial-Out PCR’ protocol, which combines Illumina sequencing with an in-house set of unique PCR tags to selectively amplify perfect assemblies from complex synthetic pools. This approach has broad applicability to DNA assembly and high-throughput functional screens.
Taylor ND, Garruss AS, Moretti R, Chan S, Arbing MA, Cascio D, Rogers JK, Isaacs FJ, Kosuri S, Baker D, Fields S, Church GM, Raman S
Engineering an allosteric transcription factor to respond to new ligands Journal Article
In: Nature Methods, vol. 13, no. 2, pp. 177-83, 2016.
@article{ND2016,
title = {Engineering an allosteric transcription factor to respond to new ligands},
author = {Taylor ND, Garruss AS, Moretti R, Chan S, Arbing MA, Cascio D, Rogers JK,
Isaacs FJ, Kosuri S, Baker D, Fields S, Church GM, Raman S},
url = {https://www.bakerlab.org/wp-content/uploads/2016/05/nmeth.36961.pdf},
doi = {10.1038/nmeth.3696},
year = {2016},
date = {2016-02-01},
journal = {Nature Methods},
volume = {13},
number = {2},
pages = {177-83},
abstract = {Genetic regulatory proteins inducible by small molecules are useful synthetic biology tools as sensors and switches. Bacterial allosteric transcription factors (aTFs) are a major class of regulatory proteins, but few aTFs have been redesigned to respond to new effectors beyond natural aTF-inducer pairs. Altering inducer specificity in these proteins is difficult because substitutions that affect inducer binding may also disrupt allostery. We engineered an aTF, the Escherichia coli lac repressor, LacI, to respond to one of four new inducer molecules: fucose, gentiobiose, lactitol and sucralose. Using computational protein design, single-residue saturation mutagenesis or random mutagenesis, along with multiplex assembly, we identified new variants comparable in specificity and induction to wild-type LacI with its inducer, isopropyl β-D-1-thiogalactopyranoside (IPTG). The ability to create designer aTFs will enable applications including dynamic control of cell metabolism, cell biology and synthetic gene circuits},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Genetic regulatory proteins inducible by small molecules are useful synthetic biology tools as sensors and switches. Bacterial allosteric transcription factors (aTFs) are a major class of regulatory proteins, but few aTFs have been redesigned to respond to new effectors beyond natural aTF-inducer pairs. Altering inducer specificity in these proteins is difficult because substitutions that affect inducer binding may also disrupt allostery. We engineered an aTF, the Escherichia coli lac repressor, LacI, to respond to one of four new inducer molecules: fucose, gentiobiose, lactitol and sucralose. Using computational protein design, single-residue saturation mutagenesis or random mutagenesis, along with multiplex assembly, we identified new variants comparable in specificity and induction to wild-type LacI with its inducer, isopropyl β-D-1-thiogalactopyranoside (IPTG). The ability to create designer aTFs will enable applications including dynamic control of cell metabolism, cell biology and synthetic gene circuits
Scott E. Boyken, Zibo Chen, Benjamin Groves, Robert A. Langan, Gustav Oberdorfer, Alex Ford, Jason M. Gilmore, Chunfu Xu, Frank DiMaio, Jose Henrique Pereira, Banumathi Sankaran, Georg Seelig, Peter H. Zwart, David Baker
De novo design of protein homo-oligomers with modular hydrogen-bond network–mediated specificity Journal Article
In: Science, vol. 352, no. 6286, pp. 680–687, 2016, ISSN: 0036-8075.
@article{Boyken680,
title = {De novo design of protein homo-oligomers with modular hydrogen-bond network–mediated specificity},
author = { Scott E. Boyken and Zibo Chen and Benjamin Groves and Robert A. Langan and Gustav Oberdorfer and Alex Ford and Jason M. Gilmore and Chunfu Xu and Frank DiMaio and Jose Henrique Pereira and Banumathi Sankaran and Georg Seelig and Peter H. Zwart and David Baker},
url = {http://science.sciencemag.org/content/352/6286/680
https://www.bakerlab.org/wp-content/uploads/2016/05/680.full_.pdf},
doi = {10.1126/science.aad8865},
issn = {0036-8075},
year = {2016},
date = {2016-01-01},
journal = {Science},
volume = {352},
number = {6286},
pages = {680--687},
publisher = {American Association for the Advancement of Science},
abstract = {General design principles for protein interaction specificity are challenging to extract. DNA nanotechnology, on the other hand, has harnessed the limited set of hydrogen-bonding interactions from Watson-Crick base-pairing to design and build a wide range of shapes. Protein-based materials have the potential for even greater geometric and chemical diversity, including additional functionality. Boyken et al. designed a class of protein oligomers that have interaction specificity determined by modular arrays of extensive hydrogen bond networks (see the Perspective by Netzer and Fleishman). They use the approach, which could one day become programmable, to build novel topologies with two concentric rings of helices.Science, this issue p. 680; see also p. 657In nature, structural specificity in DNA and proteins is encoded differently: In DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here, we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen-bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen-bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen-bond networks with atomic accuracy enables the programming of protein interaction specificity for a broad range of synthetic biology applications; more generally, our results demonstrate that, even with the tremendous diversity observed in nature, there are fundamentally new modes of interaction to be discovered in proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
General design principles for protein interaction specificity are challenging to extract. DNA nanotechnology, on the other hand, has harnessed the limited set of hydrogen-bonding interactions from Watson-Crick base-pairing to design and build a wide range of shapes. Protein-based materials have the potential for even greater geometric and chemical diversity, including additional functionality. Boyken et al. designed a class of protein oligomers that have interaction specificity determined by modular arrays of extensive hydrogen bond networks (see the Perspective by Netzer and Fleishman). They use the approach, which could one day become programmable, to build novel topologies with two concentric rings of helices.Science, this issue p. 680; see also p. 657In nature, structural specificity in DNA and proteins is encoded differently: In DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here, we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen-bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen-bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen-bond networks with atomic accuracy enables the programming of protein interaction specificity for a broad range of synthetic biology applications; more generally, our results demonstrate that, even with the tremendous diversity observed in nature, there are fundamentally new modes of interaction to be discovered in proteins.
Ovchinnikov, Sergey, Park, Hahnbeom, Kim, David E., Liu, Yuan, Wang, Ray Yu-Ruei, Baker, David
Structure prediction using sparse simulated NOE restraints with Rosetta in CASP11 Journal Article
In: Proteins: Structure, Function, and Bioinformatics, pp. n/a–n/a, 2016, ISSN: 1097-0134.
@article{PROT:PROT25006,
title = {Structure prediction using sparse simulated NOE restraints with Rosetta in CASP11},
author = {Ovchinnikov, Sergey and Park, Hahnbeom and Kim, David E. and Liu, Yuan and Wang, Ray Yu-Ruei and Baker, David},
url = {http://dx.doi.org/10.1002/prot.25006
https://www.bakerlab.org/wp-content/uploads/2016/05/Ovchinnikov_et_al-2016-Proteins__Structure_Function_and_Bioinformatics.pdf},
doi = {10.1002/prot.25006},
issn = {1097-0134},
year = {2016},
date = {2016-01-01},
journal = {Proteins: Structure, Function, and Bioinformatics},
pages = {n/a--n/a},
abstract = {In CASP11 we generated protein structure models using simulated ambiguous and unambiguous nuclear Overhauser effect (NOE) restraints with a two stage protocol. Low resolution models were generated guided by the unambiguous restraints using continuous chain folding for alpha and alpha-beta proteins, and iterative annealing for all beta proteins to take advantage of the strand pairing information implicit in the restraints. The Rosetta fragment/model hybridization protocol was then used to recombine and regularize these models, and refine them in the Rosetta full atom energy function guided by both the unambiguous and the ambiguous restraints. Fifteen out of 19 targets were modeled with GDT-TS quality scores greater than 60 for Model 1, significantly improving upon the non-assisted predictions. Our results suggest that atomic level accuracy is achievable using sparse NOE data when there is at least one correctly assigned NOE for every residue. Proteins 2016. © 2016 Wiley Periodicals, Inc.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In CASP11 we generated protein structure models using simulated ambiguous and unambiguous nuclear Overhauser effect (NOE) restraints with a two stage protocol. Low resolution models were generated guided by the unambiguous restraints using continuous chain folding for alpha and alpha-beta proteins, and iterative annealing for all beta proteins to take advantage of the strand pairing information implicit in the restraints. The Rosetta fragment/model hybridization protocol was then used to recombine and regularize these models, and refine them in the Rosetta full atom energy function guided by both the unambiguous and the ambiguous restraints. Fifteen out of 19 targets were modeled with GDT-TS quality scores greater than 60 for Model 1, significantly improving upon the non-assisted predictions. Our results suggest that atomic level accuracy is achievable using sparse NOE data when there is at least one correctly assigned NOE for every residue. Proteins 2016. © 2016 Wiley Periodicals, Inc.
Benjamin Basanta, Kui K. Chan, Patrick Barth, Tiffany King, Tobin R. Sosnick, James R. Hinshaw, Gaohua Liu, John K. Everett, Rong Xiao, Gaetano T. Montelione, David Baker
Introduction of a polar core into the de novo designed protein Top7 Journal Article
In: Protein Science, pp. n/a–n/a, 2016, ISSN: 1469-896X.
@article{PRO:PRO2899,
title = {Introduction of a polar core into the de novo designed protein Top7},
author = { Benjamin Basanta and Kui K. Chan and Patrick Barth and Tiffany King and Tobin R. Sosnick and James R. Hinshaw and Gaohua Liu and John K. Everett and Rong Xiao and Gaetano T. Montelione and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/05/Basanta_et_al-2016-Protein_Science.pdf
http://dx.doi.org/10.1002/pro.2899},
doi = {10.1002/pro.2899},
issn = {1469-896X},
year = {2016},
date = {2016-01-01},
journal = {Protein Science},
pages = {n/a--n/a},
abstract = {Design of polar interactions is a current challenge for protein design. The de novo designed protein Top7, like almost all designed proteins, has an entirely nonpolar core. Here we describe the replacing of a sizable fraction (5 residues) of this core with a designed polar hydrogen bond network. The polar core design is expressed at high levels in E. coli, has a folding free energy of 10 kcal/mol, and retains the multiphasic folding kinetics of the original Top7. The NMR structure of the design shows that conformations of three of the five residues, and the designed hydrogen bonds between them, are very close to those in the design model. The remaining two residues, which are more solvent exposed, sample a wide range of conformations in the NMR ensemble. These results show that hydrogen bond networks can be designed in protein cores, but also highlight challenges that need to be overcome when there is competition with solvent.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Design of polar interactions is a current challenge for protein design. The de novo designed protein Top7, like almost all designed proteins, has an entirely nonpolar core. Here we describe the replacing of a sizable fraction (5 residues) of this core with a designed polar hydrogen bond network. The polar core design is expressed at high levels in E. coli, has a folding free energy of 10 kcal/mol, and retains the multiphasic folding kinetics of the original Top7. The NMR structure of the design shows that conformations of three of the five residues, and the designed hydrogen bonds between them, are very close to those in the design model. The remaining two residues, which are more solvent exposed, sample a wide range of conformations in the NMR ensemble. These results show that hydrogen bond networks can be designed in protein cores, but also highlight challenges that need to be overcome when there is competition with solvent.
Merika Treants AND Nelson Jorgen AND Chevalier Aaron AND Koday Michael AND Kalinoski Hannah AND Stewart Lance AND Carter Lauren AND Nieusma Travis AND Lee Peter S. AND Ward Andrew B. AND Wilson Ian A. AND Dagley Ashley AND Smee Donald F. AND Baker David AND Fuller Deborah Heydenburg Koday
A Computationally Designed Hemagglutinin Stem-Binding Protein Provides In Vivo Protection from Influenza Independent of a Host Immune Response Journal Article
In: PLoS Pathog, vol. 12, no. 2, pp. 1-23, 2016.
@article{10.1371/journal.ppat.1005409,
title = {A Computationally Designed Hemagglutinin Stem-Binding Protein Provides In Vivo Protection from Influenza Independent of a Host Immune Response},
author = { Merika Treants AND Nelson Jorgen AND Chevalier Aaron AND Koday Michael AND Kalinoski Hannah AND Stewart Lance AND Carter Lauren AND Nieusma Travis AND Lee Peter S. AND Ward Andrew B. AND Wilson Ian A. AND Dagley Ashley AND Smee Donald F. AND Baker David AND Fuller Deborah Heydenburg Koday},
url = {http://dx.doi.org/10.1371%2Fjournal.ppat.1005409
https://www.bakerlab.org/wp-content/uploads/2016/05/journal.ppat_.1005409.pdf},
doi = {10.1371/journal.ppat.1005409},
year = {2016},
date = {2016-01-01},
journal = {PLoS Pathog},
volume = {12},
number = {2},
pages = {1-23},
publisher = {Public Library of Science},
abstract = {<title>Author Summary</title> <p>Influenza is a major public health threat, and pandemics, such as the 2009 H1N1 outbreak, are inevitable. Due to low efficacy of seasonal flu vaccines and the increase in drug-resistant strains of influenza viruses, there is a crucial need to develop new antivirals to protect from seasonal and pandemic influenza. Recently, several broadly neutralizing antibodies have been characterized that bind to a highly conserved site on the viral hemagglutinin (HA) stem region. These antibodies are protective against a wide range of diverse influenza viruses, but their efficacy depends on a host immune effector response through the antibody Fc region (ADCC). Here we show that a small engineered protein computationally designed to bind to the same region of the HA stem as broadly neutralizing antibodies mediated protection against diverse strains of influenza in mice by a distinct mechanism that is independent of a host immune response. Protection was superior to that afforded by oseltamivir, a lead marketed antiviral. Furthermore, combination therapy with low doses of the engineered protein and oseltamivir resulted in enhanced and synergistic protection from lethal challenge. Thus, through computational protein engineering, we have designed a new antiviral with strong biopotency <italic>in vivo</italic> that targets a neutralizing epitope on the hemagglutinin of influenza virus and inhibits its fusion activity. These results have significant implications for the use of computational modeling to design new antivirals against influenza and other viral diseases.</p>},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
<title>Author Summary</title> <p>Influenza is a major public health threat, and pandemics, such as the 2009 H1N1 outbreak, are inevitable. Due to low efficacy of seasonal flu vaccines and the increase in drug-resistant strains of influenza viruses, there is a crucial need to develop new antivirals to protect from seasonal and pandemic influenza. Recently, several broadly neutralizing antibodies have been characterized that bind to a highly conserved site on the viral hemagglutinin (HA) stem region. These antibodies are protective against a wide range of diverse influenza viruses, but their efficacy depends on a host immune effector response through the antibody Fc region (ADCC). Here we show that a small engineered protein computationally designed to bind to the same region of the HA stem as broadly neutralizing antibodies mediated protection against diverse strains of influenza in mice by a distinct mechanism that is independent of a host immune response. Protection was superior to that afforded by oseltamivir, a lead marketed antiviral. Furthermore, combination therapy with low doses of the engineered protein and oseltamivir resulted in enhanced and synergistic protection from lethal challenge. Thus, through computational protein engineering, we have designed a new antiviral with strong biopotency <italic>in vivo</italic> that targets a neutralizing epitope on the hemagglutinin of influenza virus and inhibits its fusion activity. These results have significant implications for the use of computational modeling to design new antivirals against influenza and other viral diseases.</p>
Kristen E Garcia, Sofia Babanova, William Scheffler, Mansij Hans, David Baker, Plamen Atanassov, Scott Banta
Designed protein aggregates entrapping carbon nanotubes for bioelectrochemical oxygen reduction Journal Article
In: Biotechnology and Bioengineering, pp. n/a–n/a, 2016, ISSN: 1097-0290.
@article{BIT:BIT25996,
title = {Designed protein aggregates entrapping carbon nanotubes for bioelectrochemical oxygen reduction},
author = { Kristen E Garcia and Sofia Babanova and William Scheffler and Mansij Hans and David Baker and Plamen Atanassov and Scott Banta},
url = {http://dx.doi.org/10.1002/bit.25996
https://www.bakerlab.org/wp-content/uploads/2016/05/Garcia_et_al-2016-Biotechnology_and_Bioengineering.pdf},
doi = {10.1002/bit.25996},
issn = {1097-0290},
year = {2016},
date = {2016-01-01},
journal = {Biotechnology and Bioengineering},
pages = {n/a--n/a},
abstract = {The engineering of robust protein/nanomaterial interfaces is critical in the development of bioelectrocatalytic systems. We have used computational protein design to identify two amino acid mutations in the small laccase protein (SLAC) from Streptomyces coelicolor to introduce new inter-protein disulfide bonds. The new dimeric interface introduced by these disulfide bonds in combination with the natural trimeric structure drive the self-assembly of SLAC into functional aggregates. The mutations had a minimal effect on kinetic parameters, and the enzymatic assemblies exhibited an increased resistance to irreversible thermal denaturation. The SLAC assemblies were combined with single-walled carbon nanotubes (SWNTs), and explored for use in oxygen reduction electrodes. The incorporation of SWNTs into the SLAC aggregates enabled operation an elevated temperature and reduced the reaction overpotential. A current density of 1.1 mA/cm2 at 0 V vs. Ag/AgCl was achieved in an air-breathing cathode system. This article is protected by copyright. All rights reserved},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The engineering of robust protein/nanomaterial interfaces is critical in the development of bioelectrocatalytic systems. We have used computational protein design to identify two amino acid mutations in the small laccase protein (SLAC) from Streptomyces coelicolor to introduce new inter-protein disulfide bonds. The new dimeric interface introduced by these disulfide bonds in combination with the natural trimeric structure drive the self-assembly of SLAC into functional aggregates. The mutations had a minimal effect on kinetic parameters, and the enzymatic assemblies exhibited an increased resistance to irreversible thermal denaturation. The SLAC assemblies were combined with single-walled carbon nanotubes (SWNTs), and explored for use in oxygen reduction electrodes. The incorporation of SWNTs into the SLAC aggregates enabled operation an elevated temperature and reduced the reaction overpotential. A current density of 1.1 mA/cm2 at 0 V vs. Ag/AgCl was achieved in an air-breathing cathode system. This article is protected by copyright. All rights reserved
2015
J Feng, BW Jester, CE Tinberg, DJ Mandell, MS Antunes, R Chari, KJ Morey, X Rios, JI Medford, GM Church, S Fields, D Baker
A general strategy to construct small molecule biosensors in eukaryotes Journal Article
In: Elife, 2015.
@article{J2015,
title = {A general strategy to construct small molecule biosensors in eukaryotes},
author = {J Feng and BW Jester and CE Tinberg and DJ Mandell and MS Antunes and R Chari and KJ Morey and X Rios and JI Medford and GM Church and S Fields and D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/04/elife-10606-v3-download.pdf},
doi = {10.7554/eLife.10606},
year = {2015},
date = {2015-12-29},
journal = {Elife},
abstract = {Biosensors for small molecules can be used in applications that range from
metabolic engineering to orthogonal control of transcription. Here, we produce
biosensors based on a ligand-binding domain (LBD) by using a method that, in
principle, can be applied to any target molecule. The LBD is fused to either a
fluorescent protein or a transcriptional activator and is destabilized by
mutation such that the fusion accumulates only in cells containing the target
ligand. We illustrate the power of this method by developing biosensors for
digoxin and progesterone. Addition of ligand to yeast, mammalian or plant cells
expressing a biosensor activates transcription with a dynamic range of up to
~100-fold. We use the biosensors to improve the biotransformation of pregnenolone
to progesterone in yeast and to regulate CRISPR activity in mammalian cells. This
work provides a general methodology to develop biosensors for a broad range of
molecules in eukaryotes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Biosensors for small molecules can be used in applications that range from
metabolic engineering to orthogonal control of transcription. Here, we produce
biosensors based on a ligand-binding domain (LBD) by using a method that, in
principle, can be applied to any target molecule. The LBD is fused to either a
fluorescent protein or a transcriptional activator and is destabilized by
mutation such that the fusion accumulates only in cells containing the target
ligand. We illustrate the power of this method by developing biosensors for
digoxin and progesterone. Addition of ligand to yeast, mammalian or plant cells
expressing a biosensor activates transcription with a dynamic range of up to
~100-fold. We use the biosensors to improve the biotransformation of pregnenolone
to progesterone in yeast and to regulate CRISPR activity in mammalian cells. This
work provides a general methodology to develop biosensors for a broad range of
molecules in eukaryotes.
metabolic engineering to orthogonal control of transcription. Here, we produce
biosensors based on a ligand-binding domain (LBD) by using a method that, in
principle, can be applied to any target molecule. The LBD is fused to either a
fluorescent protein or a transcriptional activator and is destabilized by
mutation such that the fusion accumulates only in cells containing the target
ligand. We illustrate the power of this method by developing biosensors for
digoxin and progesterone. Addition of ligand to yeast, mammalian or plant cells
expressing a biosensor activates transcription with a dynamic range of up to
~100-fold. We use the biosensors to improve the biotransformation of pregnenolone
to progesterone in yeast and to regulate CRISPR activity in mammalian cells. This
work provides a general methodology to develop biosensors for a broad range of
molecules in eukaryotes.
L Doyle, J Hallinan, J Bolduc, F Parmeggiani, D Baker, BL Stoddard, P Bradley
Rational design of α-helical tandem repeat proteins with closed architectures Journal Article
In: Nature, vol. 528(7583), pp. 585-8, 2015.
@article{L2015,
title = {Rational design of α-helical tandem repeat proteins with closed architectures},
author = {L Doyle and J Hallinan and J Bolduc and F Parmeggiani and D Baker and BL Stoddard and P Bradley},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Doyle_Nature_2015.pdf},
doi = {10.1038/nature16191},
year = {2015},
date = {2015-12-24},
journal = {Nature},
volume = {528(7583)},
pages = {585-8},
abstract = {Tandem repeat proteins, which are formed by repetition of modular units of protein sequence and structure, play important biological roles as macromolecular binding and scaffolding domains, enzymes, and building blocks for the assembly of fibrous materials. The modular nature of repeat proteins enables the rapid construction and diversification of extended binding surfaces by duplication and recombination of simple building blocks. The overall architecture of tandem repeat protein structures--which is dictated by the internal geometry and local packing of the repeat building blocks--is highly diverse, ranging from extended, super-helical folds that bind peptide, DNA, and RNA partners, to closed and compact conformations with internal cavities suitable for small molecule binding and catalysis. Here we report the development and validation of computational methods for de novo design of tandem repeat protein architectures driven purely by geometric criteria defining the inter-repeat geometry, without reference to the sequences and structures of existing repeat protein families. We have applied these methods to design a series of closed α-solenoid repeat structures (α-toroids) in which the inter-repeat packing geometry is constrained so as to juxtapose the amino (N) and carboxy (C) termini; several of these designed structures have been validated by X-ray crystallography. Unlike previous approaches to tandem repeat protein engineering, our design procedure does not rely on template sequence or structural information taken from natural repeat proteins and hence can produce structures unlike those seen in nature. As an example, we have successfully designed and validated closed α-solenoid repeats with a left-handed helical architecture that--to our knowledge--is not yet present in the protein structure database.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Tandem repeat proteins, which are formed by repetition of modular units of protein sequence and structure, play important biological roles as macromolecular binding and scaffolding domains, enzymes, and building blocks for the assembly of fibrous materials. The modular nature of repeat proteins enables the rapid construction and diversification of extended binding surfaces by duplication and recombination of simple building blocks. The overall architecture of tandem repeat protein structures–which is dictated by the internal geometry and local packing of the repeat building blocks–is highly diverse, ranging from extended, super-helical folds that bind peptide, DNA, and RNA partners, to closed and compact conformations with internal cavities suitable for small molecule binding and catalysis. Here we report the development and validation of computational methods for de novo design of tandem repeat protein architectures driven purely by geometric criteria defining the inter-repeat geometry, without reference to the sequences and structures of existing repeat protein families. We have applied these methods to design a series of closed α-solenoid repeat structures (α-toroids) in which the inter-repeat packing geometry is constrained so as to juxtapose the amino (N) and carboxy (C) termini; several of these designed structures have been validated by X-ray crystallography. Unlike previous approaches to tandem repeat protein engineering, our design procedure does not rely on template sequence or structural information taken from natural repeat proteins and hence can produce structures unlike those seen in nature. As an example, we have successfully designed and validated closed α-solenoid repeats with a left-handed helical architecture that–to our knowledge–is not yet present in the protein structure database.
TJ Brunette, F Parmeggiani, PS Huang, G Bhabha, DC Ekiert, SE Tsutakawa, GL Hura, JA Tainer, D Baker
Exploring the repeat protein universe through computational protein design Journal Article
In: Nature, vol. 528(7583), pp. 580-4, 2015.
@article{TJ2015,
title = {Exploring the repeat protein universe through computational protein design},
author = {TJ Brunette and F Parmeggiani and PS Huang and G Bhabha and DC Ekiert and SE Tsutakawa and GL Hura and JA Tainer and D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Brunette_Nature_2015.pdf},
doi = {10.1038/nature16162},
year = {2015},
date = {2015-12-24},
journal = {Nature},
volume = {528(7583)},
pages = {580-4},
abstract = {A central question in protein evolution is the extent to which naturally occurring proteins sample the space of folded structures accessible to the polypeptide chain. Repeat proteins composed of multiple tandem copies of a modular structure unit are widespread in nature and have critical roles in molecular recognition, signalling, and other essential biological processes. Naturally occurring repeat proteins have been re-engineered for molecular recognition and modular scaffolding applications. Here we use computational protein design to investigate the space of folded structures that can be generated by tandem repeating a simple helix-loop-helix-loop structural motif. Eighty-three designs with sequences unrelated to known repeat proteins were experimentally characterized. Of these, 53 are monomeric and stable at 95 °C, and 43 have solution X-ray scattering spectra consistent with the design models. Crystal structures of 15 designs spanning a broad range of curvatures are in close agreement with the design models with root mean square deviations ranging from 0.7 to 2.5 Å. Our results show that existing repeat proteins occupy only a small fraction of the possible repeat protein sequence and structure space and that it is possible to design novel repeat proteins with precisely specified geometries, opening up a wide array of new possibilities for biomolecular engineering. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A central question in protein evolution is the extent to which naturally occurring proteins sample the space of folded structures accessible to the polypeptide chain. Repeat proteins composed of multiple tandem copies of a modular structure unit are widespread in nature and have critical roles in molecular recognition, signalling, and other essential biological processes. Naturally occurring repeat proteins have been re-engineered for molecular recognition and modular scaffolding applications. Here we use computational protein design to investigate the space of folded structures that can be generated by tandem repeating a simple helix-loop-helix-loop structural motif. Eighty-three designs with sequences unrelated to known repeat proteins were experimentally characterized. Of these, 53 are monomeric and stable at 95 °C, and 43 have solution X-ray scattering spectra consistent with the design models. Crystal structures of 15 designs spanning a broad range of curvatures are in close agreement with the design models with root mean square deviations ranging from 0.7 to 2.5 Å. Our results show that existing repeat proteins occupy only a small fraction of the possible repeat protein sequence and structure space and that it is possible to design novel repeat proteins with precisely specified geometries, opening up a wide array of new possibilities for biomolecular engineering.
ND Taylor, AS Garruss, R Moretti, S Chan, MA Arbing, D Cascio, JK Rogers, FJ Isaacs, S Kosuri, D Baker, S Fields, GM Church, S Raman
Engineering an allosteric transcription factor to respond to new ligands Journal Article
In: Nature Methods, 2015.
@article{ND2015,
title = {Engineering an allosteric transcription factor to respond to new ligands},
author = {ND Taylor and AS Garruss and R Moretti and S Chan and MA Arbing and D Cascio and JK Rogers and FJ Isaacs and S Kosuri and D Baker and S Fields and GM Church and S Raman},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Taylor_NatMeth_2015.pdf},
doi = {10.1038/nmeth.3696},
year = {2015},
date = {2015-12-21},
journal = {Nature Methods},
abstract = {Genetic regulatory proteins inducible by small molecules are useful synthetic biology tools as sensors and switches. Bacterial allosteric transcription factors (aTFs) are a major class of regulatory proteins, but few aTFs have been redesigned to respond to new effectors beyond natural aTF-inducer pairs. Altering inducer specificity in these proteins is difficult because substitutions that affect inducer binding may also disrupt allostery. We engineered an aTF, the Escherichia coli lac repressor, LacI, to respond to one of four new inducer molecules: fucose, gentiobiose, lactitol and sucralose. Using computational protein design, single-residue saturation mutagenesis or random mutagenesis, along with multiplex assembly, we identified new variants comparable in specificity and induction to wild-type LacI with its inducer, isopropyl β-D-1-thiogalactopyranoside (IPTG). The ability to create designer aTFs will enable applications including dynamic control of cell metabolism, cell biology and synthetic gene circuits.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Genetic regulatory proteins inducible by small molecules are useful synthetic biology tools as sensors and switches. Bacterial allosteric transcription factors (aTFs) are a major class of regulatory proteins, but few aTFs have been redesigned to respond to new effectors beyond natural aTF-inducer pairs. Altering inducer specificity in these proteins is difficult because substitutions that affect inducer binding may also disrupt allostery. We engineered an aTF, the Escherichia coli lac repressor, LacI, to respond to one of four new inducer molecules: fucose, gentiobiose, lactitol and sucralose. Using computational protein design, single-residue saturation mutagenesis or random mutagenesis, along with multiplex assembly, we identified new variants comparable in specificity and induction to wild-type LacI with its inducer, isopropyl β-D-1-thiogalactopyranoside (IPTG). The ability to create designer aTFs will enable applications including dynamic control of cell metabolism, cell biology and synthetic gene circuits.
S Ovchinnikov, DE Kim, RY Wang, Y Liu, F DiMaio, D Baker
Improved de novo structure prediction in CASP11 by incorporating Co-evolution information into rosetta Journal Article
In: Proteins, 2015.
@article{S2015,
title = {Improved de novo structure prediction in CASP11 by incorporating Co-evolution information into rosetta},
author = {S Ovchinnikov and DE Kim and RY Wang and Y Liu and F DiMaio and D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Ovchinnikov_Proteins_2015.pdf},
doi = {10.1002/prot.24974},
year = {2015},
date = {2015-12-17},
journal = {Proteins},
abstract = {We describe CASP11 de novo blind structure predictions made using the Rosetta structure prediction methodology with both automatic and human assisted protocols. Model accuracy was generally improved using co-evolution derived residue-residue contact information as restraints during Rosetta conformational sampling and refinement, particularly when the number of sequences in the family was more than three times the length of the protein. The highlight was the human assisted prediction of T0806, a large and topologically complex target with no homologs of known structure, which had unprecedented accuracy - <3.0 Å root-mean-square deviation (RMSD) from the crystal structure over 223 residues. For this target, we increased the amount of conformational sampling over our fully automated method by employing an iterative hybridization protocol. Our results clearly demonstrate, in a blind prediction scenario, that co-evolution derived contacts can considerably increase the accuracy of template-free structure modeling. This article is protected by copyright. All rights reserved.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe CASP11 de novo blind structure predictions made using the Rosetta structure prediction methodology with both automatic and human assisted protocols. Model accuracy was generally improved using co-evolution derived residue-residue contact information as restraints during Rosetta conformational sampling and refinement, particularly when the number of sequences in the family was more than three times the length of the protein. The highlight was the human assisted prediction of T0806, a large and topologically complex target with no homologs of known structure, which had unprecedented accuracy – <3.0 Å root-mean-square deviation (RMSD) from the crystal structure over 223 residues. For this target, we increased the amount of conformational sampling over our fully automated method by employing an iterative hybridization protocol. Our results clearly demonstrate, in a blind prediction scenario, that co-evolution derived contacts can considerably increase the accuracy of template-free structure modeling. This article is protected by copyright. All rights reserved.
IC King, J Gleixner, L Doyle, A Kuzin, JF Hunt, R Xiao, GT Montelione, BL Stoddard, F DiMaio, D Baker
Precise assembly of complex beta sheet topologies from de novo designed building blocks Journal Article
In: Elife, 2015.
@article{IC2015,
title = {Precise assembly of complex beta sheet topologies from de novo designed building blocks},
author = {IC King and J Gleixner and L Doyle and A Kuzin and JF Hunt and R Xiao and GT Montelione and BL Stoddard and F DiMaio and D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/King_elife_2015.pdf},
doi = {10.7554/eLife.11012},
year = {2015},
date = {2015-12-09},
journal = {Elife},
abstract = {Design of complex alpha-beta protein topologies poses a challenge because of the large number of alternative packing arrangements. A similar challenge presumably limited the emergence of large and complex protein topologies in evolution. Here we demonstrate that protein topologies with six and seven-stranded beta sheets can be designed by insertion of one de novo designed beta sheet containing protein into another such that the two beta sheets are merged to form a single extended sheet, followed by amino acid sequence optimization at the newly formed strand-strand, strand-helix, and helix-helix interfaces. Crystal structures of two such designs closely match the computational design models. Searches for similar structures in the SCOP protein domain database yield only weak matches with different beta sheet connectivities. A similar beta sheet fusion mechanism may have contributed to the emergence of complex beta sheets during natural protein evolution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Design of complex alpha-beta protein topologies poses a challenge because of the large number of alternative packing arrangements. A similar challenge presumably limited the emergence of large and complex protein topologies in evolution. Here we demonstrate that protein topologies with six and seven-stranded beta sheets can be designed by insertion of one de novo designed beta sheet containing protein into another such that the two beta sheets are merged to form a single extended sheet, followed by amino acid sequence optimization at the newly formed strand-strand, strand-helix, and helix-helix interfaces. Crystal structures of two such designs closely match the computational design models. Searches for similar structures in the SCOP protein domain database yield only weak matches with different beta sheet connectivities. A similar beta sheet fusion mechanism may have contributed to the emergence of complex beta sheets during natural protein evolution.
M Goldsmith, S Eckstein, Y Ashani, P Jr Greisen, H Leader, JL Sussman, N Aggarwal, S Ovchinnikov, DS Tawfik, D Baker, H Thiermann, F Worek
Catalytic efficiencies of directly evolved phosphotriesterase variants with structurally different organophosphorus compounds in vitro Journal Article
In: Archives of Toxicology, 2015.
@article{M2015,
title = {Catalytic efficiencies of directly evolved phosphotriesterase variants with structurally different organophosphorus compounds in vitro},
author = {M Goldsmith and S Eckstein and Y Ashani and P Jr Greisen and H Leader and JL Sussman and N Aggarwal and S Ovchinnikov and DS Tawfik and D Baker and H Thiermann and F Worek},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Goldsmith_ArchToxicol_2015.pdf},
doi = {10.1007/s00204-015-1626-2},
year = {2015},
date = {2015-11-26},
journal = {Archives of Toxicology},
abstract = {The nearly 200,000 fatalities following exposure to organophosphorus (OP) pesticides each year and the omnipresent danger of a terroristic attack with OP nerve agents emphasize the demand for the development of effective OP antidotes. Standard treatments for intoxicated patients with a combination of atropine and an oxime are limited in their efficacy. Thus, research focuses on developing catalytic bioscavengers as an alternative approach using OP-hydrolyzing enzymes such as Brevundimonas diminuta phosphotriesterase (PTE). Recently, a PTE mutant dubbed C23 was engineered, exhibiting reversed stereoselectivity and high catalytic efficiency (k cat/K M) for the hydrolysis of the toxic enantiomers of VX, CVX, and VR. Additionally, C23's ability to prevent systemic toxicity of VX using a low protein dose has been shown in vivo. In this study, the catalytic efficiencies of V-agent hydrolysis by two newly selected PTE variants were determined. Moreover, in order to establish trends in sequence-activity relationships along the pathway of PTE's laboratory evolution, we examined k cat/K M values of several variants with a number of V-type and G-type nerve agents as well as with different OP pesticides. Although none of the new PTE variants exhibited k cat/K M values >107 M-1 min-1 with V-type nerve agents, which is required for effective prophylaxis, they were improved with VR relative to previously evolved variants. The new variants detoxify a broad spectrum of OPs and provide insight into OP hydrolysis and sequence-activity relationships.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The nearly 200,000 fatalities following exposure to organophosphorus (OP) pesticides each year and the omnipresent danger of a terroristic attack with OP nerve agents emphasize the demand for the development of effective OP antidotes. Standard treatments for intoxicated patients with a combination of atropine and an oxime are limited in their efficacy. Thus, research focuses on developing catalytic bioscavengers as an alternative approach using OP-hydrolyzing enzymes such as Brevundimonas diminuta phosphotriesterase (PTE). Recently, a PTE mutant dubbed C23 was engineered, exhibiting reversed stereoselectivity and high catalytic efficiency (k cat/K M) for the hydrolysis of the toxic enantiomers of VX, CVX, and VR. Additionally, C23’s ability to prevent systemic toxicity of VX using a low protein dose has been shown in vivo. In this study, the catalytic efficiencies of V-agent hydrolysis by two newly selected PTE variants were determined. Moreover, in order to establish trends in sequence-activity relationships along the pathway of PTE’s laboratory evolution, we examined k cat/K M values of several variants with a number of V-type and G-type nerve agents as well as with different OP pesticides. Although none of the new PTE variants exhibited k cat/K M values >107 M-1 min-1 with V-type nerve agents, which is required for effective prophylaxis, they were improved with VR relative to previously evolved variants. The new variants detoxify a broad spectrum of OPs and provide insight into OP hydrolysis and sequence-activity relationships.
PS Huang, K Feldmeier, F Parmeggiani, DA Fernandez Velasco, B Höcker, D Baker
De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy Journal Article
In: Nature Chemical Biology, vol. 12(1), pp. 29-34, 2015.
@article{PS2015,
title = {De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy},
author = {PS Huang and K Feldmeier and F Parmeggiani and DA Fernandez Velasco and B Höcker and D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Huang_NatChemBio_2015.pdf},
doi = {10.1038/nchembio.1966},
year = {2015},
date = {2015-11-23},
journal = {Nature Chemical Biology},
volume = {12(1)},
pages = {29-34},
abstract = {Despite efforts for over 25 years, de novo protein design has not succeeded in achieving the TIM-barrel fold. Here we describe the computational design of four-fold symmetrical (β/α)8 barrels guided by geometrical and chemical principles. Experimental characterization of 33 designs revealed the importance of side chain-backbone hydrogen bonds for defining the strand register between repeat units. The X-ray crystal structure of a designed thermostable 184-residue protein is nearly identical to that of the designed TIM-barrel model. PSI-BLAST searches do not identify sequence similarities to known TIM-barrel proteins, and sensitive profile-profile searches indicate that the design sequence is distant from other naturally occurring TIM-barrel superfamilies, suggesting that Nature has sampled only a subset of the sequence space available to the TIM-barrel fold. The ability to design TIM barrels de novo opens new possibilities for custom-made enzymes. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Despite efforts for over 25 years, de novo protein design has not succeeded in achieving the TIM-barrel fold. Here we describe the computational design of four-fold symmetrical (β/α)8 barrels guided by geometrical and chemical principles. Experimental characterization of 33 designs revealed the importance of side chain-backbone hydrogen bonds for defining the strand register between repeat units. The X-ray crystal structure of a designed thermostable 184-residue protein is nearly identical to that of the designed TIM-barrel model. PSI-BLAST searches do not identify sequence similarities to known TIM-barrel proteins, and sensitive profile-profile searches indicate that the design sequence is distant from other naturally occurring TIM-barrel superfamilies, suggesting that Nature has sampled only a subset of the sequence space available to the TIM-barrel fold. The ability to design TIM barrels de novo opens new possibilities for custom-made enzymes.
Lin YR, Koga N, Tatsumi-Koga R, Liu G, Clouser AF, Montelione GT, Baker D
Control over overall shape and size in de novo designed proteins Journal Article
In: Proc Natl Acad Sci U S A., pp. E5478-85, 2015.
@article{YR2015,
title = {Control over overall shape and size in de novo designed proteins},
author = {Lin YR, Koga N, Tatsumi-Koga R, Liu G, Clouser AF, Montelione GT, Baker D},
url = {https://www.bakerlab.org/wp-content/uploads/2016/04/PNAS-2015-Lin-E5478-85.pdf},
doi = {10.1073/pnas.1509508112},
year = {2015},
date = {2015-10-06},
journal = {Proc Natl Acad Sci U S A.},
pages = {E5478-85},
abstract = {We recently described general principles for designing ideal protein structures stabilized by completely consistent local and nonlocal interactions. The principles relate secondary structure patterns to tertiary packing motifs and enable design of different protein topologies. To achieve fine control over protein shape and size within a particular topology, we have extended the design rules by systematically analyzing the codependencies between the lengths and packing geometry of successive secondary structure elements and the backbone torsion angles of the loop linking them. We demonstrate the control afforded by the resulting extended rule set by designing a series of proteins with the same fold but considerable variation in secondary structure length, loop geometry, β-strand registry, and overall shape. Solution NMR structures of four designed proteins for two different folds show that protein shape and size can be precisely controlled within a given protein fold. These extended design principles provide the foundation for custom design of protein structures performing desired functions. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We recently described general principles for designing ideal protein structures stabilized by completely consistent local and nonlocal interactions. The principles relate secondary structure patterns to tertiary packing motifs and enable design of different protein topologies. To achieve fine control over protein shape and size within a particular topology, we have extended the design rules by systematically analyzing the codependencies between the lengths and packing geometry of successive secondary structure elements and the backbone torsion angles of the loop linking them. We demonstrate the control afforded by the resulting extended rule set by designing a series of proteins with the same fold but considerable variation in secondary structure length, loop geometry, β-strand registry, and overall shape. Solution NMR structures of four designed proteins for two different folds show that protein shape and size can be precisely controlled within a given protein fold. These extended design principles provide the foundation for custom design of protein structures performing desired functions.
Carly A Holstein, Aaron Chevalier, Steven Bennett, Caitlin E Anderson, Karen Keniston, Cathryn Olsen, Bing Li, Brian Bales, David R Moore, Elain Fu, David Baker, Paul Yager
Immobilizing affinity proteins to nitrocellulose: a toolbox for paper-based assay developers. Journal Article
In: Analytical and bioanalytical chemistry, 2015, ISSN: 1618-2650.
@article{626,
title = {Immobilizing affinity proteins to nitrocellulose: a toolbox for paper-based assay developers.},
author = { Carly A Holstein and Aaron Chevalier and Steven Bennett and Caitlin E Anderson and Karen Keniston and Cathryn Olsen and Bing Li and Brian Bales and David R Moore and Elain Fu and David Baker and Paul Yager},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Holstien_Anal_Bioanal_Chem_2015.pdf},
doi = {10.1007/s00216-015-9052-0},
issn = {1618-2650},
year = {2015},
date = {2015-10-01},
journal = {Analytical and bioanalytical chemistry},
abstract = {To enable enhanced paper-based diagnostics with improved detection capabilities, new methods are needed to immobilize affinity reagents to porous substrates, especially for capture molecules other than IgG. To this end, we have developed and characterized three novel methods for immobilizing protein-based affinity reagents to nitrocellulose membranes. We have demonstrated these methods using recombinant affinity proteins for the influenza surface protein hemagglutinin, leveraging the customizability of these recombinant "flu binders" for the design of features for immobilization. The three approaches shown are: (1) covalent attachment of thiolated affinity protein to an epoxide-functionalized nitrocellulose membrane, (2) attachment of biotinylated affinity protein through a nitrocellulose-binding streptavidin anchor protein, and (3) fusion of affinity protein to a novel nitrocellulose-binding anchor protein for direct coupling and immobilization. We also characterized the use of direct adsorption for the flu binders, as a point of comparison and motivation for these novel methods. Finally, we demonstrated that these novel methods can provide improved performance to an influenza hemagglutinin assay, compared to a traditional antibody-based capture system. Taken together, this work advances the toolkit available for the development of next-generation paper-based diagnostics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To enable enhanced paper-based diagnostics with improved detection capabilities, new methods are needed to immobilize affinity reagents to porous substrates, especially for capture molecules other than IgG. To this end, we have developed and characterized three novel methods for immobilizing protein-based affinity reagents to nitrocellulose membranes. We have demonstrated these methods using recombinant affinity proteins for the influenza surface protein hemagglutinin, leveraging the customizability of these recombinant "flu binders" for the design of features for immobilization. The three approaches shown are: (1) covalent attachment of thiolated affinity protein to an epoxide-functionalized nitrocellulose membrane, (2) attachment of biotinylated affinity protein through a nitrocellulose-binding streptavidin anchor protein, and (3) fusion of affinity protein to a novel nitrocellulose-binding anchor protein for direct coupling and immobilization. We also characterized the use of direct adsorption for the flu binders, as a point of comparison and motivation for these novel methods. Finally, we demonstrated that these novel methods can provide improved performance to an influenza hemagglutinin assay, compared to a traditional antibody-based capture system. Taken together, this work advances the toolkit available for the development of next-generation paper-based diagnostics.
S Ovchinnikov, L Kinch, H Park, Y Liao, J Pei, DE Kim, H Kamisetty, NV Grishin, D Baker
Large-scale determination of previously unsolved protein structures using evolutionary information Journal Article
In: eLife, 2015.
@article{S2015b,
title = {Large-scale determination of previously unsolved protein structures using evolutionary information},
author = {S Ovchinnikov, L Kinch, H Park, Y Liao, J Pei, DE Kim, H Kamisetty, NV Grishin, D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/01/Ovchinnikov_eLife_2015.pdf},
doi = {10.7554/eLife.09248},
year = {2015},
date = {2015-09-03},
journal = {eLife},
abstract = {The prediction of the structures of proteins without detectable sequence similarity to any protein of known structure remains an outstanding scientific challenge. Here we report significant progress in this area. We first describe de novo blind structure predictions of unprecendented accuracy we made for two proteins in large families in the recent CASP11 blind test of protein structure prediction methods by incorporating residue-residue co-evolution information in the Rosetta structure prediction program. We then describe the use of this method to generate structure models for 58 of the 121 large protein families in prokaryotes for which three-dimensional structures are not available. These models, which are posted online for public access, provide structural information for the over 400,000 proteins belonging to the 58 families and suggest hypotheses about mechanism for the subset for which the function is known, and hypotheses about function for the remainder. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The prediction of the structures of proteins without detectable sequence similarity to any protein of known structure remains an outstanding scientific challenge. Here we report significant progress in this area. We first describe de novo blind structure predictions of unprecendented accuracy we made for two proteins in large families in the recent CASP11 blind test of protein structure prediction methods by incorporating residue-residue co-evolution information in the Rosetta structure prediction program. We then describe the use of this method to generate structure models for 58 of the 121 large protein families in prokaryotes for which three-dimensional structures are not available. These models, which are posted online for public access, provide structural information for the over 400,000 proteins belonging to the 58 families and suggest hypotheses about mechanism for the subset for which the function is known, and hypotheses about function for the remainder.
Clancey Wolf, Justin B Siegel, Christine Tinberg, Alessandra Camarca, Carmen Gianfrani, Shirley Paski, Rongjin Guan, Gaetano T Montelione, David Baker, Ingrid S Pultz
Engineering of Kuma030: a gliadin peptidase that rapidly degrades immunogenic gliadin peptides in gastric conditions. Journal Article
In: Journal of the American Chemical Society, 2015, ISSN: 1520-5126.
@article{617,
title = {Engineering of Kuma030: a gliadin peptidase that rapidly degrades immunogenic gliadin peptides in gastric conditions.},
author = { Clancey Wolf and Justin B Siegel and Christine Tinberg and Alessandra Camarca and Carmen Gianfrani and Shirley Paski and Rongjin Guan and Gaetano T Montelione and David Baker and Ingrid S Pultz},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Wolf_JACS_2015.pdf},
doi = {10.1021/jacs.5b08325},
issn = {1520-5126},
year = {2015},
date = {2015-09-01},
journal = {Journal of the American Chemical Society},
abstract = {Celiac disease is characterized by intestinal inflammation triggered by gliadin, a component of dietary gluten. Oral administration of proteases that can rapidly degrade gliadin in the gastric compartment has been proposed as a treatment for celiac disease; however, no protease has been shown to specifically reduce the immunogenic gliadin content, in gastric conditions, to below the threshold shown to be toxic for celiac patients. Here, we used the Rosetta Molecular Modeling Suite to redesign the active site of the acid-active gliadin endopeptidase KumaMax. The resulting protease, Kuma030, specifically recognizes tripeptide sequences that are found throughout the immunogenic regions of gliadin, as well as in homologous proteins in barley and rye. Indeed, treatment of gliadin with Kuma030 eliminates the ability of gliadin to stimulate a T cell response. Kuma030 is capable of degrading >99% of the immunogenic gliadin fraction in laboratory-simulated gastric digestions with minutes, to a level below the toxic threshold for celiac patients, suggesting great potential for this enzyme as an oral therapeutic for celiac disease.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Celiac disease is characterized by intestinal inflammation triggered by gliadin, a component of dietary gluten. Oral administration of proteases that can rapidly degrade gliadin in the gastric compartment has been proposed as a treatment for celiac disease; however, no protease has been shown to specifically reduce the immunogenic gliadin content, in gastric conditions, to below the threshold shown to be toxic for celiac patients. Here, we used the Rosetta Molecular Modeling Suite to redesign the active site of the acid-active gliadin endopeptidase KumaMax. The resulting protease, Kuma030, specifically recognizes tripeptide sequences that are found throughout the immunogenic regions of gliadin, as well as in homologous proteins in barley and rye. Indeed, treatment of gliadin with Kuma030 eliminates the ability of gliadin to stimulate a T cell response. Kuma030 is capable of degrading >99% of the immunogenic gliadin fraction in laboratory-simulated gastric digestions with minutes, to a level below the toxic threshold for celiac patients, suggesting great potential for this enzyme as an oral therapeutic for celiac disease.
Jacob B Bale, Rachel U Park, Yuxi Liu, Shane Gonen, Tamir Gonen, Duilio Cascio, Neil P. King, Todd O. Yeates, David Baker
Structure of a designed tetrahedral protein assembly variant engineered to have improved soluble expression Journal Article
In: Protein science : a publication of the Protein Society, 2015, ISSN: 1469-896X.
@article{616,
title = {Structure of a designed tetrahedral protein assembly variant engineered to have improved soluble expression},
author = { Jacob B Bale and Rachel U Park and Yuxi Liu and Shane Gonen and Tamir Gonen and Duilio Cascio and Neil P. King and Todd O. Yeates and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Bale_designed_tetrahedral_ProteinSci2015.pdf},
doi = {10.1002/pro.2748},
issn = {1469-896X},
year = {2015},
date = {2015-07-01},
journal = {Protein science : a publication of the Protein Society},
abstract = {We recently reported the development of a computational method for the design of coassembling multicomponent protein nanomaterials. While four such materials were validated at high-resolution by X-ray crystallography, low yield of soluble protein prevented X-ray structure determination of a fifth designed material, T33-09. Here we report the design and crystal structure of T33-31, a variant of T33-09 with improved soluble yield resulting from redesign efforts focused on mutating solvent-exposed side chains to charged amino acids. The structure is found to match the computational design model with atomic-level accuracy, providing further validation of the design approach and demonstrating a simple and potentially general means of improving the yield of designed protein nanomaterials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We recently reported the development of a computational method for the design of coassembling multicomponent protein nanomaterials. While four such materials were validated at high-resolution by X-ray crystallography, low yield of soluble protein prevented X-ray structure determination of a fifth designed material, T33-09. Here we report the design and crystal structure of T33-31, a variant of T33-09 with improved soluble yield resulting from redesign efforts focused on mutating solvent-exposed side chains to charged amino acids. The structure is found to match the computational design model with atomic-level accuracy, providing further validation of the design approach and demonstrating a simple and potentially general means of improving the yield of designed protein nanomaterials.
Shane Gonen, Frank DiMaio, Tamir Gonen, David Baker
Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces Journal Article
In: Science (New York, N.Y.), vol. 348, pp. 1365-8, 2015, ISSN: 1095-9203.
@article{613,
title = {Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces},
author = { Shane Gonen and Frank DiMaio and Tamir Gonen and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Gonen_2DArrays_Baker2015.pdf},
doi = {10.1126/science.aaa9897},
issn = {1095-9203},
year = {2015},
date = {2015-06-01},
journal = {Science (New York, N.Y.)},
volume = {348},
pages = {1365-8},
abstract = {We describe a general approach to designing two-dimensional (2D) protein arrays mediated by noncovalent protein-protein interfaces. Protein homo-oligomers are placed into one of the seventeen 2D layer groups, the degrees of freedom of the lattice are sampled to identify configurations with shape-complementary interacting surfaces, and the interaction energy is minimized using sequence design calculations. We used the method to design proteins that self-assemble into layer groups P 3 2 1, P 4 2(1) 2, and P 6. Projection maps of micrometer-scale arrays, assembled both in vitro and in vivo, are consistent with the design models and display the target layer group symmetry. Such programmable 2D protein lattices should enable new approaches to structure determination, sensing, and nanomaterial engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a general approach to designing two-dimensional (2D) protein arrays mediated by noncovalent protein-protein interfaces. Protein homo-oligomers are placed into one of the seventeen 2D layer groups, the degrees of freedom of the lattice are sampled to identify configurations with shape-complementary interacting surfaces, and the interaction energy is minimized using sequence design calculations. We used the method to design proteins that self-assemble into layer groups P 3 2 1, P 4 2(1) 2, and P 6. Projection maps of micrometer-scale arrays, assembled both in vitro and in vivo, are consistent with the design models and display the target layer group symmetry. Such programmable 2D protein lattices should enable new approaches to structure determination, sensing, and nanomaterial engineering.
Hahnbeom Park, Frank DiMaio, David Baker
The origin of consistent protein structure refinement from structural averaging. Journal Article
In: Structure (London, England : 1993), vol. 23, pp. 1123-8, 2015, ISSN: 1878-4186.
@article{615,
title = {The origin of consistent protein structure refinement from structural averaging.},
author = { Hahnbeom Park and Frank DiMaio and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Park_Structure_2015.pdf
http://www.ncbi.nlm.nih.gov/pubmed/?term=The+Origin+of+Consistent+Protein+Structure+Refinement+from+Structural+Averaging},
doi = {10.1016/j.str.2015.03.022},
issn = {1878-4186},
year = {2015},
date = {2015-06-01},
journal = {Structure (London, England : 1993)},
volume = {23},
pages = {1123-8},
abstract = {Recent studies have shown that explicit solvent molecular dynamics (MD) simulation followed by structural averaging can consistently improve protein structure models. We find that improvement upon averaging is not limited to explicit water MD simulation, as consistent improvements are also observed for more efficient implicit solvent MD or Monte Carlo minimization simulations. To determine the origin of these improvements, we examine the changes in model accuracy brought about by averaging at the individual residue level. We find that the improvement in model quality from averaging results from the superposition of two effects: a dampening of deviations from the correct structure in the least well modeled regions, and a reinforcement of consistent movements towards the correct structure in better modeled regions. These observations are consistent with an energy landscape model in which the magnitude of the energy gradient toward the native structure decreases with increasing distance from the native state.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent studies have shown that explicit solvent molecular dynamics (MD) simulation followed by structural averaging can consistently improve protein structure models. We find that improvement upon averaging is not limited to explicit water MD simulation, as consistent improvements are also observed for more efficient implicit solvent MD or Monte Carlo minimization simulations. To determine the origin of these improvements, we examine the changes in model accuracy brought about by averaging at the individual residue level. We find that the improvement in model quality from averaging results from the superposition of two effects: a dampening of deviations from the correct structure in the least well modeled regions, and a reinforcement of consistent movements towards the correct structure in better modeled regions. These observations are consistent with an energy landscape model in which the magnitude of the energy gradient toward the native structure decreases with increasing distance from the native state.
Justin B Siegel, Amanda Lee Smith, Sean Poust, Adam J Wargacki, Arren Bar-Even, Catherine Louw, Betty W Shen, Christopher B Eiben, Huu M Tran, Elad Noor, Jasmine L Gallaher, Jacob Bale, Yasuo Yoshikuni, Michael H Gelb, Jay D Keasling, Barry L Stoddard, Mary E Lidstrom, David Baker
Computational protein design enables a novel one-carbon assimilation pathway Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, 2015, ISSN: 1091-6490.
@article{565,
title = {Computational protein design enables a novel one-carbon assimilation pathway},
author = { Justin B Siegel and Amanda Lee Smith and Sean Poust and Adam J Wargacki and Arren Bar-Even and Catherine Louw and Betty W Shen and Christopher B Eiben and Huu M Tran and Elad Noor and Jasmine L Gallaher and Jacob Bale and Yasuo Yoshikuni and Michael H Gelb and Jay D Keasling and Barry L Stoddard and Mary E Lidstrom and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/siegel15A.pdf},
doi = {10.1073/pnas.1500545112},
issn = {1091-6490},
year = {2015},
date = {2015-03-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
abstract = {We describe a computationally designed enzyme, formolase (FLS), which catalyzes the carboligation of three one-carbon formaldehyde molecules into one three-carbon dihydroxyacetone molecule. The existence of FLS enables the design of a new carbon fixation pathway, the formolase pathway, consisting of a small number of thermodynamically favorable chemical transformations that convert formate into a three-carbon sugar in central metabolism. The formolase pathway is predicted to use carbon more efficiently and with less backward flux than any naturally occurring one-carbon assimilation pathway. When supplemented with enzymes carrying out the other steps in the pathway, FLS converts formate into dihydroxyacetone phosphate and other central metabolites in vitro. These results demonstrate how modern protein engineering and design tools can facilitate the construction of a completely new biosynthetic pathway.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a computationally designed enzyme, formolase (FLS), which catalyzes the carboligation of three one-carbon formaldehyde molecules into one three-carbon dihydroxyacetone molecule. The existence of FLS enables the design of a new carbon fixation pathway, the formolase pathway, consisting of a small number of thermodynamically favorable chemical transformations that convert formate into a three-carbon sugar in central metabolism. The formolase pathway is predicted to use carbon more efficiently and with less backward flux than any naturally occurring one-carbon assimilation pathway. When supplemented with enzymes carrying out the other steps in the pathway, FLS converts formate into dihydroxyacetone phosphate and other central metabolites in vitro. These results demonstrate how modern protein engineering and design tools can facilitate the construction of a completely new biosynthetic pathway.
Frank DiMaio, Yifan Song, Xueming Li, Matthias J Brunner, Chunfu Xu, Vincent Conticello, Edward Egelman, Thomas C Marlovits, Yifan Cheng, David Baker
Atomic-accuracy models from 4.5-r A cryo-electron microscopy data with density-guided iterative local refinement. Journal Article
In: Nature methods, 2015, ISSN: 1548-7105.
@article{560,
title = {Atomic-accuracy models from 4.5-r A cryo-electron microscopy data with density-guided iterative local refinement.},
author = { Frank DiMaio and Yifan Song and Xueming Li and Matthias J Brunner and Chunfu Xu and Vincent Conticello and Edward Egelman and Thomas C Marlovits and Yifan Cheng and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/DiMaio_NatMethods_2015.pdf},
doi = {10.1038/nmeth.3286},
issn = {1548-7105},
year = {2015},
date = {2015-02-01},
journal = {Nature methods},
abstract = {We describe a general approach for refining protein structure models on the basis of cryo-electron microscopy maps with near-atomic resolution. The method integrates Monte Carlo sampling with local density-guided optimization, Rosetta all-atom refinement and real-space B-factor fitting. In tests on experimental maps of three different systems with 4.5-r A resolution or better, the method consistently produced models with atomic-level accuracy largely independently of starting-model quality, and it outperformed the molecular dynamics-based MDFF method. Cross-validated model quality statistics correlated with model accuracy over the three test systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a general approach for refining protein structure models on the basis of cryo-electron microscopy maps with near-atomic resolution. The method integrates Monte Carlo sampling with local density-guided optimization, Rosetta all-atom refinement and real-space B-factor fitting. In tests on experimental maps of three different systems with 4.5-r A resolution or better, the method consistently produced models with atomic-level accuracy largely independently of starting-model quality, and it outperformed the molecular dynamics-based MDFF method. Cross-validated model quality statistics correlated with model accuracy over the three test systems.
Ray Yu-Ruei Wang, Mikhail Kudryashev, Xueming Li, Edward H Egelman, Marek Basler, Yifan Cheng, David Baker, Frank DiMaio
De novo protein structure determination from near-atomic-resolution cryo-EM maps. Journal Article
In: Nature methods, 2015, ISSN: 1548-7105.
@article{559,
title = {De novo protein structure determination from near-atomic-resolution cryo-EM maps.},
author = { Ray Yu-Ruei Wang and Mikhail Kudryashev and Xueming Li and Edward H Egelman and Marek Basler and Yifan Cheng and David Baker and Frank DiMaio},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Wang_NatMethods_2015.pdf},
doi = {10.1038/nmeth.3287},
issn = {1548-7105},
year = {2015},
date = {2015-02-01},
journal = {Nature methods},
abstract = {We present a de novo model-building approach that combines predicted backbone conformations with side-chain fit to density to accurately assign sequence into density maps. This method yielded accurate models for six of nine experimental maps at 3.3- to 4.8-r A resolution and produced a nearly complete model for an unsolved map containing a 660-residue heterodimeric protein. This method should enable rapid and reliable protein structure determination from near-atomic-resolution cryo-electron microscopy (cryo-EM) maps.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present a de novo model-building approach that combines predicted backbone conformations with side-chain fit to density to accurately assign sequence into density maps. This method yielded accurate models for six of nine experimental maps at 3.3- to 4.8-r A resolution and produced a nearly complete model for an unsolved map containing a 660-residue heterodimeric protein. This method should enable rapid and reliable protein structure determination from near-atomic-resolution cryo-electron microscopy (cryo-EM) maps.
Paolo Rossi, Lei Shi, Gaohua Liu, Christopher M Barbieri, Hsiau-Wei Lee, Thomas D Grant, Joseph R Luft, Rong Xiao, Thomas B Acton, Edward H Snell, Gaetano T Montelione, David Baker, Oliver F Lange, Nikolaos G Sgourakis
A hybrid NMR/SAXS-based approach for discriminating oligomeric protein interfaces using Rosetta Journal Article
In: Proteins, vol. 83, pp. 309-17, 2015, ISSN: 1097-0134.
@article{611,
title = {A hybrid NMR/SAXS-based approach for discriminating oligomeric protein interfaces using Rosetta},
author = { Paolo Rossi and Lei Shi and Gaohua Liu and Christopher M Barbieri and Hsiau-Wei Lee and Thomas D Grant and Joseph R Luft and Rong Xiao and Thomas B Acton and Edward H Snell and Gaetano T Montelione and David Baker and Oliver F Lange and Nikolaos G Sgourakis},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/ahybridnmrsaxsbased_Baker2015.pdf},
doi = {10.1002/prot.24719},
issn = {1097-0134},
year = {2015},
date = {2015-02-01},
journal = {Proteins},
volume = {83},
pages = {309-17},
abstract = {Oligomeric proteins are important targets for structure determination in solution. While in most cases the fold of individual subunits can be determined experimentally, or predicted by homology-based methods, protein-protein interfaces are challenging to determine de novo using conventional NMR structure determination protocols. Here we focus on a member of the bet-V1 superfamily, Aha1 from Colwellia psychrerythraea. This family displays a broad range of crystallographic interfaces none of which can be reconciled with the NMR and SAXS data collected for Aha1. Unlike conventional methods relying on a dense network of experimental restraints, the sparse data are used to limit conformational search during optimization of a physically realistic energy function. This work highlights a new approach for studying minor conformational changes due to structural plasticity within a single dimeric interface in solution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Oligomeric proteins are important targets for structure determination in solution. While in most cases the fold of individual subunits can be determined experimentally, or predicted by homology-based methods, protein-protein interfaces are challenging to determine de novo using conventional NMR structure determination protocols. Here we focus on a member of the bet-V1 superfamily, Aha1 from Colwellia psychrerythraea. This family displays a broad range of crystallographic interfaces none of which can be reconciled with the NMR and SAXS data collected for Aha1. Unlike conventional methods relying on a dense network of experimental restraints, the sparse data are used to limit conformational search during optimization of a physically realistic energy function. This work highlights a new approach for studying minor conformational changes due to structural plasticity within a single dimeric interface in solution.
Aaron D Pearson, Jeremy H Mills, Yifan Song, Fariborz Nasertorabi, Gye Won Han, David Baker, Raymond C Stevens, Peter G Schultz
Transition states. Trapping a transition state in a computationally designed protein bottle. Journal Article
In: Science (New York, N.Y.), vol. 347, pp. 863-7, 2015, ISSN: 1095-9203.
@article{561,
title = {Transition states. Trapping a transition state in a computationally designed protein bottle.},
author = { Aaron D Pearson and Jeremy H Mills and Yifan Song and Fariborz Nasertorabi and Gye Won Han and David Baker and Raymond C Stevens and Peter G Schultz},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Mills_Science_2015A.pdf},
doi = {10.1126/science.aaa2424},
issn = {1095-9203},
year = {2015},
date = {2015-02-01},
journal = {Science (New York, N.Y.)},
volume = {347},
pages = {863-7},
abstract = {The fleeting lifetimes of the transition states (TSs) of chemical reactions make determination of their three-dimensional structures by diffraction methods a challenge. Here, we used packing interactions within the core of a protein to stabilize the planar TS conformation for rotation around the central carbon-carbon bond of biphenyl so that it could be directly observed by x-ray crystallography. The computational protein design software Rosetta was used to design a pocket within threonyl-transfer RNA synthetase from the thermophile Pyrococcus abyssi that forms complementary van der Waals interactions with a planar biphenyl. This latter moiety was introduced biosynthetically as the side chain of the noncanonical amino acid p-biphenylalanine. Through iterative rounds of computational design and structural analysis, we identified a protein in which the side chain of p-biphenylalanine is trapped in the energetically disfavored, coplanar conformation of the TS of the bond rotation reaction.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The fleeting lifetimes of the transition states (TSs) of chemical reactions make determination of their three-dimensional structures by diffraction methods a challenge. Here, we used packing interactions within the core of a protein to stabilize the planar TS conformation for rotation around the central carbon-carbon bond of biphenyl so that it could be directly observed by x-ray crystallography. The computational protein design software Rosetta was used to design a pocket within threonyl-transfer RNA synthetase from the thermophile Pyrococcus abyssi that forms complementary van der Waals interactions with a planar biphenyl. This latter moiety was introduced biosynthetically as the side chain of the noncanonical amino acid p-biphenylalanine. Through iterative rounds of computational design and structural analysis, we identified a protein in which the side chain of p-biphenylalanine is trapped in the energetically disfavored, coplanar conformation of the TS of the bond rotation reaction.
E H Egelman, C. Xu, F. DiMaio, E Magnotti, C Modlin, X Yu, E Wright, D Baker, V P Conticello
Structural plasticity of helical nanotubes based on coiled-coil assemblies. Journal Article
In: Structure (London, England : 1993), vol. 23, pp. 280-9, 2015, ISSN: 1878-4186.
@article{609,
title = {Structural plasticity of helical nanotubes based on coiled-coil assemblies.},
author = { E H Egelman and C. Xu and F. DiMaio and E Magnotti and C Modlin and X Yu and E Wright and D Baker and V P Conticello},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/structuralplasticity_Baker2015.pdf},
doi = {10.1016/j.str.2014.12.008},
issn = {1878-4186},
year = {2015},
date = {2015-02-01},
journal = {Structure (London, England : 1993)},
volume = {23},
pages = {280-9},
abstract = {Numerous instances can be seen in evolution in which protein quaternary structures have diverged while the sequences of the building blocks have remained fairly conserved. However, the path through which such divergence has taken place is usually not known. We have designed two synthetic 29-residue α-helical peptides, based on the coiled-coil structural motif, that spontaneously self-assemble into helical nanotubes in vitro. Using electron cryomicroscopy with a newly available direct electron detection capability, we can achieve near-atomic resolution of these thin structures. We show how conservative changes of only one or two amino acids result in dramatic changes in quaternary structure, in which the assemblies can be switched between two very different forms. This system provides a framework for understanding how small sequence changes in evolution can translate into very large changes in supramolecular structure, a phenomenon that may have significant implications for the de novo design of synthetic peptide assemblies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Numerous instances can be seen in evolution in which protein quaternary structures have diverged while the sequences of the building blocks have remained fairly conserved. However, the path through which such divergence has taken place is usually not known. We have designed two synthetic 29-residue α-helical peptides, based on the coiled-coil structural motif, that spontaneously self-assemble into helical nanotubes in vitro. Using electron cryomicroscopy with a newly available direct electron detection capability, we can achieve near-atomic resolution of these thin structures. We show how conservative changes of only one or two amino acids result in dramatic changes in quaternary structure, in which the assemblies can be switched between two very different forms. This system provides a framework for understanding how small sequence changes in evolution can translate into very large changes in supramolecular structure, a phenomenon that may have significant implications for the de novo design of synthetic peptide assemblies.
Omry Morag, Nikolaos G Sgourakis, David Baker, Amir Goldbourt
The NMR-Rosetta capsid model of M13 bacteriophage reveals a quadrupled hydrophobic packing epitope Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 112, pp. 971-6, 2015, ISSN: 1091-6490.
@article{607,
title = {The NMR-Rosetta capsid model of M13 bacteriophage reveals a quadrupled hydrophobic packing epitope},
author = { Omry Morag and Nikolaos G Sgourakis and David Baker and Amir Goldbourt},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/thenmrrosettacapsid_Baker2015.pdf},
doi = {10.1073/pnas.1415393112},
issn = {1091-6490},
year = {2015},
date = {2015-01-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {112},
pages = {971-6},
abstract = {Filamentous phage are elongated semiflexible ssDNA viruses that infect bacteria. The M13 phage, belonging to the family inoviridae, has a length of ~1 μm and a diameter of ~7 nm. Here we present a structural model for the capsid of intact M13 bacteriophage using Rosetta model building guided by structure restraints obtained from magic-angle spinning solid-state NMR experimental data. The C5 subunit symmetry observed in fiber diffraction studies was enforced during model building. The structure consists of stacked pentamers with largely alpha helical subunits containing an N-terminal type II β-turn; there is a rise of 16.6-16.7 r A and a tilt of 36.1-36.6textdegree between consecutive pentamers. The packing of the subunits is stabilized by a repeating hydrophobic stacking pocket; each subunit participates in four pockets by contributing different hydrophobic residues, which are spread along the subunit sequence. Our study provides, to our knowledge, the first magic-angle spinning NMR structure of an intact filamentous virus capsid and further demonstrates the strength of this technique as a method of choice to study noncrystalline, high-molecular-weight molecular assemblies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Filamentous phage are elongated semiflexible ssDNA viruses that infect bacteria. The M13 phage, belonging to the family inoviridae, has a length of ~1 μm and a diameter of ~7 nm. Here we present a structural model for the capsid of intact M13 bacteriophage using Rosetta model building guided by structure restraints obtained from magic-angle spinning solid-state NMR experimental data. The C5 subunit symmetry observed in fiber diffraction studies was enforced during model building. The structure consists of stacked pentamers with largely alpha helical subunits containing an N-terminal type II β-turn; there is a rise of 16.6-16.7 r A and a tilt of 36.1-36.6textdegree between consecutive pentamers. The packing of the subunits is stabilized by a repeating hydrophobic stacking pocket; each subunit participates in four pockets by contributing different hydrophobic residues, which are spread along the subunit sequence. Our study provides, to our knowledge, the first magic-angle spinning NMR structure of an intact filamentous virus capsid and further demonstrates the strength of this technique as a method of choice to study noncrystalline, high-molecular-weight molecular assemblies.
Vinayak Vittal, Lei Shi, Dawn M Wenzel, K Matthew Scaglione, Emily D Duncan, Venkatesha Basrur, Kojo S J Elenitoba-Johnson, David Baker, Henry L Paulson, Peter S Brzovic, Rachel E Klevit
Intrinsic disorder drives N-terminal ubiquitination by Ube2w Journal Article
In: Nature Chemical Biology, vol. 11, pp. 83-9, 2015, ISSN: 1552-4469.
@article{610,
title = {Intrinsic disorder drives N-terminal ubiquitination by Ube2w},
author = { Vinayak Vittal and Lei Shi and Dawn M Wenzel and K Matthew Scaglione and Emily D Duncan and Venkatesha Basrur and Kojo S J Elenitoba-Johnson and David Baker and Henry L Paulson and Peter S Brzovic and Rachel E Klevit},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/intrinsicdisorderdrives_Baker2015.pdf},
doi = {10.1038/nchembio.1700},
issn = {1552-4469},
year = {2015},
date = {2015-01-01},
journal = {Nature Chemical Biology},
volume = {11},
pages = {83-9},
abstract = {Ubiquitination of the αN-terminus of protein substrates has been reported sporadically since the early 1980s. However, the identity of an enzyme responsible for this unique ubiquitin (Ub) modification has only recently been elucidated. We show the Ub-conjugating enzyme (E2) Ube2w uses a unique mechanism to facilitate the specific ubiquitination of the α-amino group of its substrates that involves recognition of backbone atoms of intrinsically disordered N termini. We present the NMR-based solution ensemble of full-length Ube2w that reveals a structural architecture unlike that of any other E2 in which its C terminus is partly disordered and flexible to accommodate variable substrate N termini. Flexibility of the substrate is critical for recognition by Ube2w, and either point mutations in or the removal of the flexible C terminus of Ube2w inhibits substrate binding and modification. Mechanistic insights reported here provide guiding principles for future efforts to define the N-terminal ubiquitome in cells.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ubiquitination of the αN-terminus of protein substrates has been reported sporadically since the early 1980s. However, the identity of an enzyme responsible for this unique ubiquitin (Ub) modification has only recently been elucidated. We show the Ub-conjugating enzyme (E2) Ube2w uses a unique mechanism to facilitate the specific ubiquitination of the α-amino group of its substrates that involves recognition of backbone atoms of intrinsically disordered N termini. We present the NMR-based solution ensemble of full-length Ube2w that reveals a structural architecture unlike that of any other E2 in which its C terminus is partly disordered and flexible to accommodate variable substrate N termini. Flexibility of the substrate is critical for recognition by Ube2w, and either point mutations in or the removal of the flexible C terminus of Ube2w inhibits substrate binding and modification. Mechanistic insights reported here provide guiding principles for future efforts to define the N-terminal ubiquitome in cells.
Keunwan Park, Betty W Shen, Fabio Parmeggiani, Po-Ssu Huang, Barry L Stoddard, David Baker
Control of repeat-protein curvature by computational protein design. Journal Article
In: Nature structural & molecular biology, 2015, ISSN: 1545-9985.
@article{557,
title = {Control of repeat-protein curvature by computational protein design.},
author = { Keunwan Park and Betty W Shen and Fabio Parmeggiani and Po-Ssu Huang and Barry L Stoddard and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Park_2015.pdf},
doi = {10.1038/nsmb.2938},
issn = {1545-9985},
year = {2015},
date = {2015-01-01},
journal = {Nature structural & molecular biology},
abstract = {Shape complementarity is an important component of molecular recognition, and the ability to precisely adjust the shape of a binding scaffold to match a target of interest would greatly facilitate the creation of high-affinity protein reagents and therapeutics. Here we describe a general approach to control the shape of the binding surface on repeat-protein scaffolds and apply it to leucine-rich-repeat proteins. First, self-compatible building-block modules are designed that, when polymerized, generate surfaces with unique but constant curvatures. Second, a set of junction modules that connect the different building blocks are designed. Finally, new proteins with custom-designed shapes are generated by appropriately combining building-block and junction modules. Crystal structures of the designs illustrate the power of the approach in controlling repeat-protein curvature.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Shape complementarity is an important component of molecular recognition, and the ability to precisely adjust the shape of a binding scaffold to match a target of interest would greatly facilitate the creation of high-affinity protein reagents and therapeutics. Here we describe a general approach to control the shape of the binding surface on repeat-protein scaffolds and apply it to leucine-rich-repeat proteins. First, self-compatible building-block modules are designed that, when polymerized, generate surfaces with unique but constant curvatures. Second, a set of junction modules that connect the different building blocks are designed. Finally, new proteins with custom-designed shapes are generated by appropriately combining building-block and junction modules. Crystal structures of the designs illustrate the power of the approach in controlling repeat-protein curvature.
Julien R C Bergeron, Liam J Worrall, Soumya De, Nikolaos G Sgourakis, Adrienne H Cheung, Emilie Lameignere, Mark Okon, Gregory A Wasney, David Baker, Lawrence P McIntosh, Natalie C J Strynadka
The modular structure of the inner-membrane ring component PrgK facilitates assembly of the type III secretion system basal body Journal Article
In: Structure (London, England : 1993), vol. 23, pp. 161-72, 2015, ISSN: 1878-4186.
@article{608,
title = {The modular structure of the inner-membrane ring component PrgK facilitates assembly of the type III secretion system basal body},
author = { Julien R C Bergeron and Liam J Worrall and Soumya De and Nikolaos G Sgourakis and Adrienne H Cheung and Emilie Lameignere and Mark Okon and Gregory A Wasney and David Baker and Lawrence P McIntosh and Natalie C J Strynadka},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/themodularstructure_Baker2015.pdf},
doi = {10.1016/j.str.2014.10.021},
issn = {1878-4186},
year = {2015},
date = {2015-01-01},
journal = {Structure (London, England : 1993)},
volume = {23},
pages = {161-72},
abstract = {The type III secretion system (T3SS) is a large macromolecular assembly found at the surface of many pathogenic Gram-negative bacteria. Its role is to inject toxic "effector" proteins into the cells of infected organisms. The molecular details of the assembly of this large, multimembrane-spanning complex remain poorly understood. Here, we report structural, biochemical, and functional analyses of PrgK, an inner-membrane component of the prototypical Salmonella typhimurium T3SS. We have obtained the atomic structures of the two ring building globular domains and show that the C-terminal transmembrane helix is not essential for assembly and secretion. We also demonstrate that structural rearrangement of the two PrgK globular domains, driven by an interconnecting linker region, may promote oligomerization into ring structures. Finally, we used electron microscopy-guided symmetry modeling to propose a structural model for the intimately associated PrgH-PrgK ring interaction within the assembled basal body.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The type III secretion system (T3SS) is a large macromolecular assembly found at the surface of many pathogenic Gram-negative bacteria. Its role is to inject toxic "effector" proteins into the cells of infected organisms. The molecular details of the assembly of this large, multimembrane-spanning complex remain poorly understood. Here, we report structural, biochemical, and functional analyses of PrgK, an inner-membrane component of the prototypical Salmonella typhimurium T3SS. We have obtained the atomic structures of the two ring building globular domains and show that the C-terminal transmembrane helix is not essential for assembly and secretion. We also demonstrate that structural rearrangement of the two PrgK globular domains, driven by an interconnecting linker region, may promote oligomerization into ring structures. Finally, we used electron microscopy-guided symmetry modeling to propose a structural model for the intimately associated PrgH-PrgK ring interaction within the assembled basal body.
2014
Summer B Thyme, Yifan Song, Tj Brunette, Mindy D Szeto, Lara Kusak, Philip Bradley, David Baker
Massively parallel determination and modeling of endonuclease substrate specificity Journal Article
In: Nucleic Acids Research, vol. 42, pp. 13839-52, 2014, ISSN: 1362-4962.
@article{606,
title = {Massively parallel determination and modeling of endonuclease substrate specificity},
author = { Summer B Thyme and Yifan Song and Tj Brunette and Mindy D Szeto and Lara Kusak and Philip Bradley and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/massivelyparallel_Baker2013.pdf},
doi = {10.1093/nar/gku1096},
issn = {1362-4962},
year = {2014},
date = {2014-12-01},
journal = {Nucleic Acids Research},
volume = {42},
pages = {13839-52},
abstract = {We describe the identification and characterization of novel homing endonucleases using genome database mining to identify putative target sites, followed by high throughput activity screening in a bacterial selection system. We characterized the substrate specificity and kinetics of these endonucleases by monitoring DNA cleavage events with deep sequencing. The endonuclease specificities revealed by these experiments can be partially recapitulated using 3D structure-based computational models. Analysis of these models together with genome sequence data provide insights into how alternative endonuclease specificities were generated during natural evolution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe the identification and characterization of novel homing endonucleases using genome database mining to identify putative target sites, followed by high throughput activity screening in a bacterial selection system. We characterized the substrate specificity and kinetics of these endonucleases by monitoring DNA cleavage events with deep sequencing. The endonuclease specificities revealed by these experiments can be partially recapitulated using 3D structure-based computational models. Analysis of these models together with genome sequence data provide insights into how alternative endonuclease specificities were generated during natural evolution.
Fabio Parmeggiani, Po-Ssu Huang, Sergey Vorobiev, Rong Xiao, Keunwan Park, Silvia Caprari, Min Su, Jayaraman Seetharaman, Lei Mao, Haleema Janjua, Gaetano T Montelione, John Hunt, David Baker
A General Computational Approach for Repeat Protein Design. Journal Article
In: Journal of molecular biology, 2014, ISSN: 1089-8638.
@article{555,
title = {A General Computational Approach for Repeat Protein Design.},
author = { Fabio Parmeggiani and Po-Ssu Huang and Sergey Vorobiev and Rong Xiao and Keunwan Park and Silvia Caprari and Min Su and Jayaraman Seetharaman and Lei Mao and Haleema Janjua and Gaetano T Montelione and John Hunt and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Parmeggiani-2014.pdf},
doi = {10.1016/j.jmb.2014.11.005},
issn = {1089-8638},
year = {2014},
date = {2014-11-01},
journal = {Journal of molecular biology},
abstract = {Repeat proteins have considerable potential for use as modular binding reagents or biomaterials in biomedical and nanotechnology applications. Here we describe a general computational method for building idealized repeats that integrates available family sequences and structural information with Rosetta de novo protein design calculations. Idealized designs from six different repeat families were generated and experimentally characterized; 80% of the proteins were expressed and soluble and more than 40% were folded and monomeric with high thermal stability. Crystal structures determined for members of three families are within 1r A root-mean-square deviation to the design models. The method provides a general approach for fast and reliable generation of stable modular repeat protein scaffolds.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Repeat proteins have considerable potential for use as modular binding reagents or biomaterials in biomedical and nanotechnology applications. Here we describe a general computational method for building idealized repeats that integrates available family sequences and structural information with Rosetta de novo protein design calculations. Idealized designs from six different repeat families were generated and experimentally characterized; 80% of the proteins were expressed and soluble and more than 40% were folded and monomeric with high thermal stability. Crystal structures determined for members of three families are within 1r A root-mean-square deviation to the design models. The method provides a general approach for fast and reliable generation of stable modular repeat protein scaffolds.
Daniel S Liu, Lucas G Niv’on, Florian Richter, Peter J Goldman, Thomas J Deerinck, Jennifer Z Yao, Douglas Richardson, William S Phipps, Anne Z Ye, Mark H Ellisman, Catherine L Drennan, David Baker, Alice Y Ting
Computational design of a red fluorophore ligase for site-specific protein labeling in living cells. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 111, pp. E4551-9, 2014, ISSN: 1091-6490.
@article{619,
title = {Computational design of a red fluorophore ligase for site-specific protein labeling in living cells.},
author = { Daniel S Liu and Lucas G Niv'on and Florian Richter and Peter J Goldman and Thomas J Deerinck and Jennifer Z Yao and Douglas Richardson and William S Phipps and Anne Z Ye and Mark H Ellisman and Catherine L Drennan and David Baker and Alice Y Ting},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Liu_computational_PNAS_2014.pdf},
doi = {10.1073/pnas.1404736111},
issn = {1091-6490},
year = {2014},
date = {2014-10-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {111},
pages = {E4551-9},
abstract = {Chemical fluorophores offer tremendous size and photophysical advantages over fluorescent proteins but are much more challenging to target to specific cellular proteins. Here, we used Rosetta-based computation to design a fluorophore ligase that accepts the red dye resorufin, starting from Escherichia coli lipoic acid ligase. X-ray crystallography showed that the design closely matched the experimental structure. Resorufin ligase catalyzed the site-specific and covalent attachment of resorufin to various cellular proteins genetically fused to a 13-aa recognition peptide in multiple mammalian cell lines and in primary cultured neurons. We used resorufin ligase to perform superresolution imaging of the intermediate filament protein vimentin by stimulated emission depletion and electron microscopies. This work illustrates the power of Rosetta for major redesign of enzyme specificity and introduces a tool for minimally invasive, highly specific imaging of cellular proteins by both conventional and superresolution microscopies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Chemical fluorophores offer tremendous size and photophysical advantages over fluorescent proteins but are much more challenging to target to specific cellular proteins. Here, we used Rosetta-based computation to design a fluorophore ligase that accepts the red dye resorufin, starting from Escherichia coli lipoic acid ligase. X-ray crystallography showed that the design closely matched the experimental structure. Resorufin ligase catalyzed the site-specific and covalent attachment of resorufin to various cellular proteins genetically fused to a 13-aa recognition peptide in multiple mammalian cell lines and in primary cultured neurons. We used resorufin ligase to perform superresolution imaging of the intermediate filament protein vimentin by stimulated emission depletion and electron microscopies. This work illustrates the power of Rosetta for major redesign of enzyme specificity and introduces a tool for minimally invasive, highly specific imaging of cellular proteins by both conventional and superresolution microscopies.
P. Huang, G. Oberdorfer, C. Xu, X.Y. Pei, B.L. Nannenga, J.M. Rogers, F. DiMaio, T. Gonen, B. Luisi, D Baker
High thermodynamic stability of parametrically designed helical bundles Journal Article
In: Science, vol. 346, pp. 481-85, 2014.
@article{552,
title = {High thermodynamic stability of parametrically designed helical bundles},
author = { P. Huang and G. Oberdorfer and C. Xu and X.Y. Pei and B.L. Nannenga and J.M. Rogers and F. DiMaio and T. Gonen and B. Luisi and D Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Huang_2014.pdf},
doi = {10.1126/science.1257481},
year = {2014},
date = {2014-10-01},
journal = {Science},
volume = {346},
pages = {481-85},
chapter = {481},
abstract = {We describe a procedure for designing proteins with backbones produced by varying the parameters in the Crick coiled coil–generating equations. Combinatorial design calculations identify low-energy sequences for alternative helix supercoil arrangements, and the helices in the lowest-energy arrangements are connected by loop building. We design an antiparallel monomeric untwisted three-helix bundle with 80-residue helices, an antiparallel monomeric right-handed four-helix bundle, and a pentameric parallel left-handed five-helix bundle. The designed proteins are extremely stable (extrapolated ΔGfold > 60 kilocalories per mole), and their crystal structures are close to those of the design models with nearly identical core packing between the helices. The approach enables the custom design of hyperstable proteins with fine-tuned geometries for a wide range of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a procedure for designing proteins with backbones produced by varying the parameters in the Crick coiled coil–generating equations. Combinatorial design calculations identify low-energy sequences for alternative helix supercoil arrangements, and the helices in the lowest-energy arrangements are connected by loop building. We design an antiparallel monomeric untwisted three-helix bundle with 80-residue helices, an antiparallel monomeric right-handed four-helix bundle, and a pentameric parallel left-handed five-helix bundle. The designed proteins are extremely stable (extrapolated ΔGfold > 60 kilocalories per mole), and their crystal structures are close to those of the design models with nearly identical core packing between the helices. The approach enables the custom design of hyperstable proteins with fine-tuned geometries for a wide range of applications.
Yu Liu, Xin Zhang, Yun Lei Tan, Gira Bhabha, Damian C Ekiert, Yakov Kipnis, Sinisa Bjelic, David Baker, Jeffery W Kelly
De novo-designed enzymes as small-molecule-regulated fluorescence imaging tags and fluorescent reporters. Journal Article
In: Journal of the American Chemical Society, vol. 136, pp. 13102-5, 2014, ISSN: 1520-5126.
@article{621,
title = {De novo-designed enzymes as small-molecule-regulated fluorescence imaging tags and fluorescent reporters.},
author = { Yu Liu and Xin Zhang and Yun Lei Tan and Gira Bhabha and Damian C Ekiert and Yakov Kipnis and Sinisa Bjelic and David Baker and Jeffery W Kelly},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Liu_JACS_2014.pdf},
doi = {10.1021/ja5056356},
issn = {1520-5126},
year = {2014},
date = {2014-09-01},
journal = {Journal of the American Chemical Society},
volume = {136},
pages = {13102-5},
abstract = {Enzyme-based tags attached to a protein-of-interest (POI) that react with a small molecule, rendering the conjugate fluorescent, are very useful for studying the POI in living cells. These tags are typically based on endogenous enzymes, so protein engineering is required to ensure that the small-molecule probe does not react with the endogenous enzyme in the cell of interest. Here we demonstrate that de novo-designed enzymes can be used as tags to attach to POIs. The inherent bioorthogonality of the de novo-designed enzyme-small-molecule probe reaction circumvents the need for protein engineering, since these enzyme activities are not present in living organisms. Herein, we transform a family of de novo-designed retroaldolases into variable-molecular-weight tags exhibiting fluorescence imaging, reporter, and electrophoresis applications that are regulated by tailored, reactive small-molecule fluorophores.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Enzyme-based tags attached to a protein-of-interest (POI) that react with a small molecule, rendering the conjugate fluorescent, are very useful for studying the POI in living cells. These tags are typically based on endogenous enzymes, so protein engineering is required to ensure that the small-molecule probe does not react with the endogenous enzyme in the cell of interest. Here we demonstrate that de novo-designed enzymes can be used as tags to attach to POIs. The inherent bioorthogonality of the de novo-designed enzyme-small-molecule probe reaction circumvents the need for protein engineering, since these enzyme activities are not present in living organisms. Herein, we transform a family of de novo-designed retroaldolases into variable-molecular-weight tags exhibiting fluorescence imaging, reporter, and electrophoresis applications that are regulated by tailored, reactive small-molecule fluorophores.
George A Khoury, Adam Liwo, Firas Khatib, Hongyi Zhou, Gaurav Chopra, Jaume Bacardit, Leandro O Bortot, Rodrigo A Faccioli, Xin Deng, Yi He, Pawel Krupa, Jilong Li, Magdalena A Mozolewska, Adam K Sieradzan, James Smadbeck, Tomasz Wirecki, Seth Cooper, Jeff Flatten, Kefan Xu, David Baker, Jianlin Cheng, Alexandre C B Delbem, Christodoulos A Floudas, Chen Keasar, Michael Levitt, Zoran Popovi’c, Harold A Scheraga, Jeffrey Skolnick, Silvia N Crivelli
WeFold: a coopetition for protein structure prediction. Journal Article
In: Proteins, vol. 82, pp. 1850-68, 2014, ISSN: 1097-0134.
@article{625,
title = {WeFold: a coopetition for protein structure prediction.},
author = { George A Khoury and Adam Liwo and Firas Khatib and Hongyi Zhou and Gaurav Chopra and Jaume Bacardit and Leandro O Bortot and Rodrigo A Faccioli and Xin Deng and Yi He and Pawel Krupa and Jilong Li and Magdalena A Mozolewska and Adam K Sieradzan and James Smadbeck and Tomasz Wirecki and Seth Cooper and Jeff Flatten and Kefan Xu and David Baker and Jianlin Cheng and Alexandre C B Delbem and Christodoulos A Floudas and Chen Keasar and Michael Levitt and Zoran Popovi'c and Harold A Scheraga and Jeffrey Skolnick and Silvia N Crivelli},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Khoury_Proteins_2014.pdf},
doi = {10.1002/prot.24538},
issn = {1097-0134},
year = {2014},
date = {2014-09-01},
journal = {Proteins},
volume = {82},
pages = {1850-68},
abstract = {The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During the collaboration, the laboratories were simultaneously competing with each other. Here, we present the first attempt at "coopetition" in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During the collaboration, the laboratories were simultaneously competing with each other. Here, we present the first attempt at "coopetition" in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org.
Rudolf Griss, Alberto Schena, Luc Reymond, Luc Patiny, Dominique Werner, Christine E Tinberg, David Baker, Kai Johnsson
Bioluminescent sensor proteins for point-of-care therapeutic drug monitoring Journal Article
In: Nature chemical biology, vol. 10, pp. 598-603, 2014, ISSN: 1552-4469.
@article{539,
title = {Bioluminescent sensor proteins for point-of-care therapeutic drug monitoring},
author = { Rudolf Griss and Alberto Schena and Luc Reymond and Luc Patiny and Dominique Werner and Christine E Tinberg and David Baker and Kai Johnsson},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Griss_2014A.pdf},
doi = {10.1038/nchembio.1554},
issn = {1552-4469},
year = {2014},
date = {2014-07-01},
journal = {Nature chemical biology},
volume = {10},
pages = {598-603},
abstract = {For many drugs, finding the balance between efficacy and toxicity requires monitoring their concentrations in the patienttextquoterights blood. Quantifying drug levels at the bedside or at home would have advantages in terms of therapeutic outcome and convenience, but current techniques require the setting of a diagnostic laboratory. We have developed semisynthetic bioluminescent sensors that permit precise measurements of drug concentrations in patient samples by spotting minimal volumes on paper and recording the signal using a simple point-and-shoot camera. Our sensors have a modular design consisting of a protein-based and a synthetic part and can be engineered to selectively recognize a wide range of drugs, including immunosuppressants, antiepileptics, anticancer agents and antiarrhythmics. This low-cost point-of-care method could make therapies safer, increase the convenience of doctors and patients and make therapeutic drug monitoring available in regions with poor infrastructure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
For many drugs, finding the balance between efficacy and toxicity requires monitoring their concentrations in the patienttextquoterights blood. Quantifying drug levels at the bedside or at home would have advantages in terms of therapeutic outcome and convenience, but current techniques require the setting of a diagnostic laboratory. We have developed semisynthetic bioluminescent sensors that permit precise measurements of drug concentrations in patient samples by spotting minimal volumes on paper and recording the signal using a simple point-and-shoot camera. Our sensors have a modular design consisting of a protein-based and a synthetic part and can be engineered to selectively recognize a wide range of drugs, including immunosuppressants, antiepileptics, anticancer agents and antiarrhythmics. This low-cost point-of-care method could make therapies safer, increase the convenience of doctors and patients and make therapeutic drug monitoring available in regions with poor infrastructure.
Nathalie Preiswerk, Tobias Beck, Jessica D Schulz, Peter Milovn’ik, Clemens Mayer, Justin B Siegel, David Baker, Donald Hilvert
Impact of scaffold rigidity on the design and evolution of an artificial Diels-Alderase. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 111, pp. 8013-8, 2014, ISSN: 1091-6490.
@article{623,
title = {Impact of scaffold rigidity on the design and evolution of an artificial Diels-Alderase.},
author = { Nathalie Preiswerk and Tobias Beck and Jessica D Schulz and Peter Milovn'ik and Clemens Mayer and Justin B Siegel and David Baker and Donald Hilvert},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Preiswerk_PNAS_2014.pdf},
doi = {10.1073/pnas.1401073111},
issn = {1091-6490},
year = {2014},
date = {2014-06-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {111},
pages = {8013-8},
abstract = {By combining targeted mutagenesis, computational refinement, and directed evolution, a modestly active, computationally designed Diels-Alderase was converted into the most proficient biocatalyst for [4+2] cycloadditions known. The high stereoselectivity and minimal product inhibition of the evolved enzyme enabled preparative scale synthesis of a single product diastereomer. X-ray crystallography of the enzyme-product complex shows that the molecular changes introduced over the course of optimization, including addition of a lid structure, gradually reshaped the pocket for more effective substrate preorganization and transition state stabilization. The good overall agreement between the experimental structure and the original design model with respect to the orientations of both the bound product and the catalytic side chains contrasts with other computationally designed enzymes. Because design accuracy appears to correlate with scaffold rigidity, improved control over backbone conformation will likely be the key to future efforts to design more efficient enzymes for diverse chemical reactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
By combining targeted mutagenesis, computational refinement, and directed evolution, a modestly active, computationally designed Diels-Alderase was converted into the most proficient biocatalyst for [4+2] cycloadditions known. The high stereoselectivity and minimal product inhibition of the evolved enzyme enabled preparative scale synthesis of a single product diastereomer. X-ray crystallography of the enzyme-product complex shows that the molecular changes introduced over the course of optimization, including addition of a lid structure, gradually reshaped the pocket for more effective substrate preorganization and transition state stabilization. The good overall agreement between the experimental structure and the original design model with respect to the orientations of both the bound product and the catalytic side chains contrasts with other computationally designed enzymes. Because design accuracy appears to correlate with scaffold rigidity, improved control over backbone conformation will likely be the key to future efforts to design more efficient enzymes for diverse chemical reactions.
Ronit Mazor, Jaime A Eberle, Xiaobo Hu, Aaron N Vassall, Masanori Onda, Richard Beers, Elizabeth C Lee, Robert J Kreitman, Byungkook Lee, David Baker, Chris King, Raffit Hassan, Itai Benhar, Ira Pastan
Recombinant immunotoxin for cancer treatment with low immunogenicity by identification and silencing of human T-cell epitopes. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 111, pp. 8571-6, 2014, ISSN: 1091-6490.
@article{624,
title = {Recombinant immunotoxin for cancer treatment with low immunogenicity by identification and silencing of human T-cell epitopes.},
author = { Ronit Mazor and Jaime A Eberle and Xiaobo Hu and Aaron N Vassall and Masanori Onda and Richard Beers and Elizabeth C Lee and Robert J Kreitman and Byungkook Lee and David Baker and Chris King and Raffit Hassan and Itai Benhar and Ira Pastan},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Mazor_PNAS_2014.pdf},
doi = {10.1073/pnas.1405153111},
issn = {1091-6490},
year = {2014},
date = {2014-06-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {111},
pages = {8571-6},
abstract = {Nonhuman proteins have valuable therapeutic properties, but their efficacy is limited by neutralizing antibodies. Recombinant immunotoxins (RITs) are potent anticancer agents that have produced many complete remissions in leukemia, but immunogenicity limits the number of doses that can be given to patients with normal immune systems. Using human cells, we identified eight helper T-cell epitopes in PE38, a portion of the bacterial protein Pseudomonas exotoxin A which consists of the toxin moiety of the RIT, and used this information to make LMB-T18 in which three epitopes were deleted and five others diminished by point mutations in key residues. LMB-T18 has high cytotoxic and antitumor activity and is very resistant to thermal denaturation. The new immunotoxin has a 93% decrease in T-cell epitopes and should have improved efficacy in patients because more treatment cycles can be given. Furthermore, the deimmunized toxin can be used to make RITs targeting other antigens, and the approach we describe can be used to deimmunize other therapeutically useful nonhuman proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Nonhuman proteins have valuable therapeutic properties, but their efficacy is limited by neutralizing antibodies. Recombinant immunotoxins (RITs) are potent anticancer agents that have produced many complete remissions in leukemia, but immunogenicity limits the number of doses that can be given to patients with normal immune systems. Using human cells, we identified eight helper T-cell epitopes in PE38, a portion of the bacterial protein Pseudomonas exotoxin A which consists of the toxin moiety of the RIT, and used this information to make LMB-T18 in which three epitopes were deleted and five others diminished by point mutations in key residues. LMB-T18 has high cytotoxic and antitumor activity and is very resistant to thermal denaturation. The new immunotoxin has a 93% decrease in T-cell epitopes and should have improved efficacy in patients because more treatment cycles can be given. Furthermore, the deimmunized toxin can be used to make RITs targeting other antigens, and the approach we describe can be used to deimmunize other therapeutically useful nonhuman proteins.
Javier G Magad’an, Meghan O Altman, William L Ince, Heather D Hickman, James Stevens, Aaron Chevalier, David Baker, Patrick C Wilson, Rafi Ahmed, Jack R Bennink, Jonathan W Yewdell
Biogenesis of Influenza A Virus Hemagglutinin Cross-Protective Stem Epitopes. Journal Article
In: PLoS pathogens, vol. 10, pp. e1004204, 2014, ISSN: 1553-7374.
@article{537,
title = {Biogenesis of Influenza A Virus Hemagglutinin Cross-Protective Stem Epitopes.},
author = { Javier G Magad'an and Meghan O Altman and William L Ince and Heather D Hickman and James Stevens and Aaron Chevalier and David Baker and Patrick C Wilson and Rafi Ahmed and Jack R Bennink and Jonathan W Yewdell},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Magadan_2014A.pdf},
doi = {10.1371/journal.ppat.1004204},
issn = {1553-7374},
year = {2014},
date = {2014-06-01},
journal = {PLoS pathogens},
volume = {10},
pages = {e1004204},
abstract = {Antigenic variation in the globular domain of influenza A virus (IAV) hemagglutinin (HA) precludes effective immunity to this major human pathogen. Although the HA stem is highly conserved between influenza virus strains, HA stem-reactive antibodies (StRAbs) were long considered biologically inert. It is now clear, however, that StRAbs reduce viral replication in animal models and protect against pathogenicity and death, supporting the potential of HA stem-based immunogens as drift-resistant vaccines. Optimally designing StRAb-inducing immunogens and understanding StRAb effector functions require thorough comprehension of HA stem structure and antigenicity. Here, we study the biogenesis of HA stem epitopes recognized in cells infected with various drifted IAV H1N1 strains using mouse and human StRAbs. Using a novel immunofluorescence (IF)-based assay, we find that human StRAbs bind monomeric HA in the endoplasmic reticulum (ER) and trimerized HA in the Golgi complex (GC) with similar high avidity, potentially good news for producing effective monomeric HA stem immunogens. Though HA stem epitopes are nestled among several N-linked oligosaccharides, glycosylation is not required for full antigenicity. Rather, as N-linked glycans increase in size during intracellular transport of HA through the GC, StRAb binding becomes temperature-sensitive, binding poorly to HA at 4textdegreeC and well at 37textdegreeC. A de novo designed, 65-residue protein binds the mature HA stem independently of temperature, consistent with a lack of N-linked oligosaccharide steric hindrance due to its small size. Likewise, StRAbs bind recombinant HA carrying simple N-linked glycans in a temperature-independent manner. Chemical cross-linking experiments show that N-linked oligosaccharides likely influence StRAb binding by direct local effects rather than by globally modifying the conformational flexibility of HA. Our findings indicate that StRAb binding to HA is precarious, raising the possibility that sufficient immune pressure on the HA stem region could select for viral escape mutants with increased steric hindrance from N-linked glycans.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Antigenic variation in the globular domain of influenza A virus (IAV) hemagglutinin (HA) precludes effective immunity to this major human pathogen. Although the HA stem is highly conserved between influenza virus strains, HA stem-reactive antibodies (StRAbs) were long considered biologically inert. It is now clear, however, that StRAbs reduce viral replication in animal models and protect against pathogenicity and death, supporting the potential of HA stem-based immunogens as drift-resistant vaccines. Optimally designing StRAb-inducing immunogens and understanding StRAb effector functions require thorough comprehension of HA stem structure and antigenicity. Here, we study the biogenesis of HA stem epitopes recognized in cells infected with various drifted IAV H1N1 strains using mouse and human StRAbs. Using a novel immunofluorescence (IF)-based assay, we find that human StRAbs bind monomeric HA in the endoplasmic reticulum (ER) and trimerized HA in the Golgi complex (GC) with similar high avidity, potentially good news for producing effective monomeric HA stem immunogens. Though HA stem epitopes are nestled among several N-linked oligosaccharides, glycosylation is not required for full antigenicity. Rather, as N-linked glycans increase in size during intracellular transport of HA through the GC, StRAb binding becomes temperature-sensitive, binding poorly to HA at 4textdegreeC and well at 37textdegreeC. A de novo designed, 65-residue protein binds the mature HA stem independently of temperature, consistent with a lack of N-linked oligosaccharide steric hindrance due to its small size. Likewise, StRAbs bind recombinant HA carrying simple N-linked glycans in a temperature-independent manner. Chemical cross-linking experiments show that N-linked oligosaccharides likely influence StRAb binding by direct local effects rather than by globally modifying the conformational flexibility of HA. Our findings indicate that StRAb binding to HA is precarious, raising the possibility that sufficient immune pressure on the HA stem region could select for viral escape mutants with increased steric hindrance from N-linked glycans.
Erik Procko, Geoffrey Y Berguig, Betty W Shen, Yifan Song, Shani Frayo, Anthony J Convertine, Daciana Margineantu, Garrett Booth, Bruno E Correia, Yuanhua Cheng, William R Schief, David M Hockenbery, Oliver W Press, Barry L Stoddard, Patrick S Stayton, David Baker
A computationally designed inhibitor of an epstein-barr viral bcl-2 protein induces apoptosis in infected cells. Journal Article
In: Cell, vol. 157, pp. 1644-56, 2014, ISSN: 1097-4172.
@article{538,
title = {A computationally designed inhibitor of an epstein-barr viral bcl-2 protein induces apoptosis in infected cells.},
author = { Erik Procko and Geoffrey Y Berguig and Betty W Shen and Yifan Song and Shani Frayo and Anthony J Convertine and Daciana Margineantu and Garrett Booth and Bruno E Correia and Yuanhua Cheng and William R Schief and David M Hockenbery and Oliver W Press and Barry L Stoddard and Patrick S Stayton and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Procko2014A.pdf},
doi = {10.1016/j.cell.2014.04.034},
issn = {1097-4172},
year = {2014},
date = {2014-06-01},
journal = {Cell},
volume = {157},
pages = {1644-56},
abstract = {Because apoptosis of infected cells can limit virus production and spread, some viruses have co-opted prosurvival genes from the host. This includes the Epstein-Barr virus (EBV) gene BHRF1, a homolog of human Bcl-2 proteins that block apoptosis and are associated with cancer. Computational design and experimental optimization were used to generate a novel protein called BINDI that binds BHRF1 with picomolar affinity. BINDI recognizes the hydrophobic cleft of BHRF1 in a manner similar to other Bcl-2 protein interactions but makes many additional contacts to achieve exceptional affinity and specificity. BINDI induces apoptosis in EBV-infected cancer lines, and when delivered with an antibody-targeted intracellular delivery carrier, BINDI suppressed tumor growth and extended survival in a xenograft disease model of EBV-positive human lymphoma. High-specificity-designed proteins that selectively kill target cells may provide an advantage over the toxic compounds used in current generation antibody-drug conjugates.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Because apoptosis of infected cells can limit virus production and spread, some viruses have co-opted prosurvival genes from the host. This includes the Epstein-Barr virus (EBV) gene BHRF1, a homolog of human Bcl-2 proteins that block apoptosis and are associated with cancer. Computational design and experimental optimization were used to generate a novel protein called BINDI that binds BHRF1 with picomolar affinity. BINDI recognizes the hydrophobic cleft of BHRF1 in a manner similar to other Bcl-2 protein interactions but makes many additional contacts to achieve exceptional affinity and specificity. BINDI induces apoptosis in EBV-infected cancer lines, and when delivered with an antibody-targeted intracellular delivery carrier, BINDI suppressed tumor growth and extended survival in a xenograft disease model of EBV-positive human lymphoma. High-specificity-designed proteins that selectively kill target cells may provide an advantage over the toxic compounds used in current generation antibody-drug conjugates.
Kuang-Yui M Chen, Jiaming Sun, Jason S Salvo, David Baker, Patrick Barth
High-resolution modeling of transmembrane helical protein structures from distant homologues. Journal Article
In: PLoS computational biology, vol. 10, pp. e1003636, 2014, ISSN: 1553-7358.
@article{622,
title = {High-resolution modeling of transmembrane helical protein structures from distant homologues.},
author = { Kuang-Yui M Chen and Jiaming Sun and Jason S Salvo and David Baker and Patrick Barth},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Chen_PLOS_2014.pdf},
doi = {10.1371/journal.pcbi.1003636},
issn = {1553-7358},
year = {2014},
date = {2014-05-01},
journal = {PLoS computational biology},
volume = {10},
pages = {e1003636},
abstract = {Eukaryotic transmembrane helical (TMH) proteins perform a wide diversity of critical cellular functions, but remain structurally largely uncharacterized and their high-resolution structure prediction is currently hindered by the lack of close structural homologues. To address this problem, we present a novel and generic method for accurately modeling large TMH protein structures from distant homologues exhibiting distinct loop and TMH conformations. Models of the adenosine A2AR and chemokine CXCR4 receptors were first ranked in GPCR-DOCK blind prediction contests in the receptor structure accuracy category. In a benchmark of 50 TMH protein homolog pairs of diverse topology (from 5 to 12 TMHs), size (from 183 to 420 residues) and sequence identity (from 15% to 70%), the method improves most starting templates, and achieves near-atomic accuracy prediction of membrane-embedded regions. Unlike starting templates, the models are of suitable quality for computer-based protein engineering: redesigned models and redesigned X-ray structures exhibit very similar native interactions. The method should prove useful for the atom-level modeling and design of a large fraction of structurally uncharacterized TMH proteins from a wide range of structural homologues.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Eukaryotic transmembrane helical (TMH) proteins perform a wide diversity of critical cellular functions, but remain structurally largely uncharacterized and their high-resolution structure prediction is currently hindered by the lack of close structural homologues. To address this problem, we present a novel and generic method for accurately modeling large TMH protein structures from distant homologues exhibiting distinct loop and TMH conformations. Models of the adenosine A2AR and chemokine CXCR4 receptors were first ranked in GPCR-DOCK blind prediction contests in the receptor structure accuracy category. In a benchmark of 50 TMH protein homolog pairs of diverse topology (from 5 to 12 TMHs), size (from 183 to 420 residues) and sequence identity (from 15% to 70%), the method improves most starting templates, and achieves near-atomic accuracy prediction of membrane-embedded regions. Unlike starting templates, the models are of suitable quality for computer-based protein engineering: redesigned models and redesigned X-ray structures exhibit very similar native interactions. The method should prove useful for the atom-level modeling and design of a large fraction of structurally uncharacterized TMH proteins from a wide range of structural homologues.
Neil P. King, Jacob B Bale, William Sheffler, Dan E McNamara, Shane Gonen, Tamir Gonen, Todd O. Yeates, David Baker
Accurate design of co-assembling multi-component protein nanomaterials. Journal Article
In: Nature, 2014, ISSN: 1476-4687.
@article{534,
title = {Accurate design of co-assembling multi-component protein nanomaterials.},
author = { Neil P. King and Jacob B Bale and William Sheffler and Dan E McNamara and Shane Gonen and Tamir Gonen and Todd O. Yeates and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/King_Nature2014A.pdf},
doi = {10.1038/nature13404},
issn = {1476-4687},
year = {2014},
date = {2014-05-01},
journal = {Nature},
abstract = {The self-assembly of proteins into highly ordered nanoscale architectures is a hallmark of biological systems. The sophisticated functions of these molecular machines have inspired the development of methods to engineer self-assembling protein nanostructures; however, the design of multi-component protein nanomaterials with high accuracy remains an outstanding challenge. Here we report a computational method for designing protein nanomaterials in which multiple copies of two distinct subunits co-assemble into a specific architecture. We use the method to design five 24-subunit cage-like protein nanomaterials in two distinct symmetric architectures and experimentally demonstrate that their structures are in close agreement with the computational design models. The accuracy of the method and the number and variety of two-component materials that it makes accessible suggest a route to the construction of functional protein nanomaterials tailored to specific applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The self-assembly of proteins into highly ordered nanoscale architectures is a hallmark of biological systems. The sophisticated functions of these molecular machines have inspired the development of methods to engineer self-assembling protein nanostructures; however, the design of multi-component protein nanomaterials with high accuracy remains an outstanding challenge. Here we report a computational method for designing protein nanomaterials in which multiple copies of two distinct subunits co-assemble into a specific architecture. We use the method to design five 24-subunit cage-like protein nanomaterials in two distinct symmetric architectures and experimentally demonstrate that their structures are in close agreement with the computational design models. The accuracy of the method and the number and variety of two-component materials that it makes accessible suggest a route to the construction of functional protein nanomaterials tailored to specific applications.
Gregory M Alushin, Gabriel C Lander, Elizabeth H Kellogg, Rui Zhang, David Baker, Eva Nogales
High-resolution microtubule structures reveal the structural transitions in αβ-tubulin upon GTP hydrolysis. Journal Article
In: Cell, vol. 157, pp. 1117-29, 2014, ISSN: 1097-4172.
@article{541,
title = {High-resolution microtubule structures reveal the structural transitions in αβ-tubulin upon GTP hydrolysis.},
author = { Gregory M Alushin and Gabriel C Lander and Elizabeth H Kellogg and Rui Zhang and David Baker and Eva Nogales},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Alushin_2014A.pdf},
doi = {10.1016/j.cell.2014.03.053},
issn = {1097-4172},
year = {2014},
date = {2014-05-01},
journal = {Cell},
volume = {157},
pages = {1117-29},
abstract = {Dynamic instability, the stochastic switching between growth and shrinkage, is essential for microtubule function. This behavior is driven by GTP hydrolysis in the microtubule lattice and is inhibited by anticancer agents like Taxol. We provide insight into the mechanism of dynamic instability, based on high-resolution cryo-EM structures (4.7-5.6 r A) of dynamic microtubules and microtubules stabilized by GMPCPP or Taxol. We infer that hydrolysis leads to a compaction around the E-site nucleotide at longitudinal interfaces, as well as movement of the α-tubulin intermediate domain and H7 helix. Displacement of the C-terminal helices in both α- and β-tubulin subunits suggests an effect on interactions with binding partners that contact this region. Taxol inhibits most of these conformational changes, allosterically inducing a GMPCPP-like state. Lateral interactions are similar in all conditions we examined, suggesting that microtubule lattice stability is primarily modulated at longitudinal interfaces.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dynamic instability, the stochastic switching between growth and shrinkage, is essential for microtubule function. This behavior is driven by GTP hydrolysis in the microtubule lattice and is inhibited by anticancer agents like Taxol. We provide insight into the mechanism of dynamic instability, based on high-resolution cryo-EM structures (4.7-5.6 r A) of dynamic microtubules and microtubules stabilized by GMPCPP or Taxol. We infer that hydrolysis leads to a compaction around the E-site nucleotide at longitudinal interfaces, as well as movement of the α-tubulin intermediate domain and H7 helix. Displacement of the C-terminal helices in both α- and β-tubulin subunits suggests an effect on interactions with binding partners that contact this region. Taxol inhibits most of these conformational changes, allosterically inducing a GMPCPP-like state. Lateral interactions are similar in all conditions we examined, suggesting that microtubule lattice stability is primarily modulated at longitudinal interfaces.
Chris King, Esteban N Garza, Ronit Mazor, Jonathan L Linehan, Ira Pastan, Marion Pepper, David Baker
Removing T-cell epitopes with computational protein design. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, 2014, ISSN: 1091-6490.
@article{533,
title = {Removing T-cell epitopes with computational protein design.},
author = { Chris King and Esteban N Garza and Ronit Mazor and Jonathan L Linehan and Ira Pastan and Marion Pepper and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/King_PNAS_2014A.pdf},
doi = {10.1073/pnas.1321126111},
issn = {1091-6490},
year = {2014},
date = {2014-05-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
abstract = {Immune responses can make protein therapeutics ineffective or even dangerous. We describe a general computational protein design method for reducing immunogenicity by eliminating known and predicted T-cell epitopes and maximizing the content of human peptide sequences without disrupting protein structure and function. We show that the method recapitulates previous experimental results on immunogenicity reduction, and we use it to disrupt T-cell epitopes in GFP and Pseudomonas exotoxin A without disrupting function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Immune responses can make protein therapeutics ineffective or even dangerous. We describe a general computational protein design method for reducing immunogenicity by eliminating known and predicted T-cell epitopes and maximizing the content of human peptide sequences without disrupting protein structure and function. We show that the method recapitulates previous experimental results on immunogenicity reduction, and we use it to disrupt T-cell epitopes in GFP and Pseudomonas exotoxin A without disrupting function.
Sergey Ovchinnikov, Hetunandan Kamisetty, David Baker
Robust and accurate prediction of residue-residue interactions across protein interfaces using evolutionary information. Journal Article
In: eLife, vol. 3, pp. e02030, 2014, ISSN: 2050-084X.
@article{540,
title = {Robust and accurate prediction of residue-residue interactions across protein interfaces using evolutionary information.},
author = { Sergey Ovchinnikov and Hetunandan Kamisetty and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Ovchinnikov_2014A.pdf},
doi = {10.7554/eLife.02030},
issn = {2050-084X},
year = {2014},
date = {2014-05-01},
journal = {eLife},
volume = {3},
pages = {e02030},
abstract = {Do the amino acid sequence identities of residues that make contact across protein interfaces covary during evolution? If so, such covariance could be used to predict contacts across interfaces and assemble models of biological complexes. We find that residue pairs identified using a pseudo-likelihood-based method to covary across protein-protein interfaces in the 50S ribosomal unit and 28 additional bacterial protein complexes with known structure are almost always in contact in the complex, provided that the number of aligned sequences is greater than the average length of the two proteins. We use this method to make subunit contact predictions for an additional 36 protein complexes with unknown structures, and present models based on these predictions for the tripartite ATP-independent periplasmic (TRAP) transporter, the tripartite efflux system, the pyruvate formate lyase-activating enzyme complex, and the methionine ABC transporter.DOI: http://dx.doi.org/10.7554/eLife.02030.001.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Do the amino acid sequence identities of residues that make contact across protein interfaces covary during evolution? If so, such covariance could be used to predict contacts across interfaces and assemble models of biological complexes. We find that residue pairs identified using a pseudo-likelihood-based method to covary across protein-protein interfaces in the 50S ribosomal unit and 28 additional bacterial protein complexes with known structure are almost always in contact in the complex, provided that the number of aligned sequences is greater than the average length of the two proteins. We use this method to make subunit contact predictions for an additional 36 protein complexes with unknown structures, and present models based on these predictions for the tripartite ATP-independent periplasmic (TRAP) transporter, the tripartite efflux system, the pyruvate formate lyase-activating enzyme complex, and the methionine ABC transporter.DOI: http://dx.doi.org/10.7554/eLife.02030.001.
Sridharan Rajagopalan, Chu Wang, Kai Yu, Alexandre P Kuzin, Florian Richter, Scott Lew, Aleksandr E Miklos, Megan L Matthews, Jayaraman Seetharaman, Min Su, John F Hunt, Benjamin F Cravatt, David Baker
Design of activated serine-containing catalytic triads with atomic-level accuracy Journal Article
In: Nature chemical biology, vol. 10, pp. 386-391, 2014, ISSN: 1552-4469.
@article{528,
title = {Design of activated serine-containing catalytic triads with atomic-level accuracy},
author = { Sridharan Rajagopalan and Chu Wang and Kai Yu and Alexandre P Kuzin and Florian Richter and Scott Lew and Aleksandr E Miklos and Megan L Matthews and Jayaraman Seetharaman and Min Su and John F Hunt and Benjamin F Cravatt and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Rajagopalan_nchembio_2014A.pdf},
doi = {10.1038/nchembio.1498},
issn = {1552-4469},
year = {2014},
date = {2014-04-01},
journal = {Nature chemical biology},
volume = {10},
pages = {386-391},
abstract = {A challenge in the computational design of enzymes is that multiple properties, including substrate binding, transition state stabilization and product release, must be simultaneously optimized, and this has limited the absolute activity of successful designs. Here, we focus on a single critical property of many enzymes: the nucleophilicity of an active site residue that initiates catalysis. We design proteins with idealized serine-containing catalytic triads and assess their nucleophilicity directly in native biological systems using activity-based organophosphate probes. Crystal structures of the most successful designs show unprecedented agreement with computational models, including extensive hydrogen bonding networks between the catalytic triad (or quartet) residues, and mutagenesis experiments demonstrate that these networks are critical for serine activation and organophosphate reactivity. Following optimization by yeast display, the designs react with organophosphate probes at rates comparable to natural serine hydrolases. Co-crystal structures with diisopropyl fluorophosphate bound to the serine nucleophile suggest that the designs could provide the basis for a new class of organophosphate capture agents.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A challenge in the computational design of enzymes is that multiple properties, including substrate binding, transition state stabilization and product release, must be simultaneously optimized, and this has limited the absolute activity of successful designs. Here, we focus on a single critical property of many enzymes: the nucleophilicity of an active site residue that initiates catalysis. We design proteins with idealized serine-containing catalytic triads and assess their nucleophilicity directly in native biological systems using activity-based organophosphate probes. Crystal structures of the most successful designs show unprecedented agreement with computational models, including extensive hydrogen bonding networks between the catalytic triad (or quartet) residues, and mutagenesis experiments demonstrate that these networks are critical for serine activation and organophosphate reactivity. Following optimization by yeast display, the designs react with organophosphate probes at rates comparable to natural serine hydrolases. Co-crystal structures with diisopropyl fluorophosphate bound to the serine nucleophile suggest that the designs could provide the basis for a new class of organophosphate capture agents.
David Baker
Protein folding, structure prediction and design. Journal Article
In: Biochemical Society transactions, vol. 42, pp. 225-9, 2014, ISSN: 1470-8752.
@article{529,
title = {Protein folding, structure prediction and design.},
author = { David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Baker_BiochemSocTrans_2014.pdf},
doi = {10.1042/BST20130055},
issn = {1470-8752},
year = {2014},
date = {2014-04-01},
journal = {Biochemical Society transactions},
volume = {42},
pages = {225-9},
abstract = {I describe how experimental studies of protein folding have led to advances in protein structure prediction and protein design. I describe the finding that protein sequences are not optimized for rapid folding, the contact order-protein folding rate correlation, the incorporation of experimental insights into protein folding into the Rosetta protein structure production methodology and the use of this methodology to determine structures from sparse experimental data. I then describe the inverse problem (protein design) and give an overview of recent work on designing proteins with new structures and functions. I also describe the contributions of the general public to these efforts through the Rosetta@home distributed computing project and the FoldIt interactive protein folding and design game.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
I describe how experimental studies of protein folding have led to advances in protein structure prediction and protein design. I describe the finding that protein sequences are not optimized for rapid folding, the contact order-protein folding rate correlation, the incorporation of experimental insights into protein folding into the Rosetta protein structure production methodology and the use of this methodology to determine structures from sparse experimental data. I then describe the inverse problem (protein design) and give an overview of recent work on designing proteins with new structures and functions. I also describe the contributions of the general public to these efforts through the Rosetta@home distributed computing project and the FoldIt interactive protein folding and design game.
Yupeng Wang, Iram F Khan, Sandrine Boissel, Jordan Jarjour, Joseph Pangallo, Summer Thyme, David Baker, Andrew M Scharenberg, David J Rawlings
Progressive engineering of a homing endonuclease genome editing reagent for the murine X-linked immunodeficiency locus. Journal Article
In: Nucleic acids research, 2014, ISSN: 1362-4962.
@article{527,
title = {Progressive engineering of a homing endonuclease genome editing reagent for the murine X-linked immunodeficiency locus.},
author = { Yupeng Wang and Iram F Khan and Sandrine Boissel and Jordan Jarjour and Joseph Pangallo and Summer Thyme and David Baker and Andrew M Scharenberg and David J Rawlings},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Boissel_NucleicAcids_2014.pdf},
issn = {1362-4962},
year = {2014},
date = {2014-03-01},
journal = {Nucleic acids research},
abstract = {LAGLIDADG homing endonucleases (LHEs) are compact endonucleases with 20-22 bp recognition sites, and thus are ideal scaffolds for engineering site-specific DNA cleavage enzymes for genome editing applications. Here, we describe a general approach to LHE engineering that combines rational design with directed evolution, using a yeast surface display high-throughput cleavage selection. This approach was employed to alter the binding and cleavage specificity of the I-Anil LHE to recognize a mutation in the mouse Bruton tyrosine kinase (Btk) gene causative for mouse X-linked immunodeficiency (XID)-a model of human X-linked agammaglobulinemia (XLA). The required re-targeting of I-AniI involved progressive resculpting of the DNA contact interface to accommodate nine base differences from the native cleavage sequence. The enzyme emerging from the progressive engineering process was specific for the XID mutant allele versus the wild-type (WT) allele, and exhibited activity equivalent to WT I-AniI in vitro and in cellulo reporter assays. Fusion of the enzyme to a site-specific DNA binding domain of transcription activator-like effector (TALE) resulted in a further enhancement of gene editing efficiency. These results illustrate the potential of LHE enzymes as specific and efficient tools for therapeutic genome engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
LAGLIDADG homing endonucleases (LHEs) are compact endonucleases with 20-22 bp recognition sites, and thus are ideal scaffolds for engineering site-specific DNA cleavage enzymes for genome editing applications. Here, we describe a general approach to LHE engineering that combines rational design with directed evolution, using a yeast surface display high-throughput cleavage selection. This approach was employed to alter the binding and cleavage specificity of the I-Anil LHE to recognize a mutation in the mouse Bruton tyrosine kinase (Btk) gene causative for mouse X-linked immunodeficiency (XID)-a model of human X-linked agammaglobulinemia (XLA). The required re-targeting of I-AniI involved progressive resculpting of the DNA contact interface to accommodate nine base differences from the native cleavage sequence. The enzyme emerging from the progressive engineering process was specific for the XID mutant allele versus the wild-type (WT) allele, and exhibited activity equivalent to WT I-AniI in vitro and in cellulo reporter assays. Fusion of the enzyme to a site-specific DNA binding domain of transcription activator-like effector (TALE) resulted in a further enhancement of gene editing efficiency. These results illustrate the potential of LHE enzymes as specific and efficient tools for therapeutic genome engineering.
Yu Liu, Yun Lei Tan, Xin Zhang, Gira Bhabha, Damian C Ekiert, Joseph C Genereux, Younhee Cho, Yakov Kipnis, Sinisa Bjelic, David Baker, Jeffery W Kelly
Small molecule probes to quantify the functional fraction of a specific protein in a cell with minimal folding equilibrium shifts. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, 2014, ISSN: 1091-6490.
@article{526,
title = {Small molecule probes to quantify the functional fraction of a specific protein in a cell with minimal folding equilibrium shifts.},
author = { Yu Liu and Yun Lei Tan and Xin Zhang and Gira Bhabha and Damian C Ekiert and Joseph C Genereux and Younhee Cho and Yakov Kipnis and Sinisa Bjelic and David Baker and Jeffery W Kelly},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Liu_PNAS_2014.pdf},
issn = {1091-6490},
year = {2014},
date = {2014-03-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
abstract = {Although much is known about protein folding in buffers, it remains unclear how the cellular protein homeostasis network functions as a system to partition client proteins between folded and functional, soluble and misfolded, and aggregated conformations. Herein, we develop small molecule folding probes that specifically react with the folded and functional fraction of the protein of interest, enabling fluorescence-based quantification of this fraction in cell lysate at a time point of interest. Importantly, these probes minimally perturb a proteintextquoterights folding equilibria within cells during and after cell lysis, because sufficient cellular chaperone/chaperonin holdase activity is created by rapid ATP depletion during cell lysis. The folding probe strategy and the faithful quantification of a particular proteintextquoterights functional fraction are exemplified with retroaldolase, a de novo designed enzyme, and transthyretin, a nonenzyme protein. Our findings challenge the often invoked assumption that the soluble fraction of a client protein is fully folded in the cell. Moreover, our results reveal that the partitioning of destabilized retroaldolase and transthyretin mutants between the aforementioned conformational states is strongly influenced by cytosolic proteostasis network perturbations. Overall, our results suggest that applying a chemical folding probe strategy to other client proteins offers opportunities to reveal how the proteostasis network functions as a system to regulate the folding and function of individual client proteins in vivo.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Although much is known about protein folding in buffers, it remains unclear how the cellular protein homeostasis network functions as a system to partition client proteins between folded and functional, soluble and misfolded, and aggregated conformations. Herein, we develop small molecule folding probes that specifically react with the folded and functional fraction of the protein of interest, enabling fluorescence-based quantification of this fraction in cell lysate at a time point of interest. Importantly, these probes minimally perturb a proteintextquoterights folding equilibria within cells during and after cell lysis, because sufficient cellular chaperone/chaperonin holdase activity is created by rapid ATP depletion during cell lysis. The folding probe strategy and the faithful quantification of a particular proteintextquoterights functional fraction are exemplified with retroaldolase, a de novo designed enzyme, and transthyretin, a nonenzyme protein. Our findings challenge the often invoked assumption that the soluble fraction of a client protein is fully folded in the cell. Moreover, our results reveal that the partitioning of destabilized retroaldolase and transthyretin mutants between the aforementioned conformational states is strongly influenced by cytosolic proteostasis network perturbations. Overall, our results suggest that applying a chemical folding probe strategy to other client proteins offers opportunities to reveal how the proteostasis network functions as a system to regulate the folding and function of individual client proteins in vivo.
Hein J Wijma, Robert J Floor, Peter A Jekel, David Baker, Siewert J Marrink, Dick B Janssen
Computationally designed libraries for rapid enzyme stabilization. Journal Article
In: Protein engineering, design & selection : PEDS, vol. 27, pp. 49-58, 2014, ISSN: 1741-0134.
@article{520,
title = {Computationally designed libraries for rapid enzyme stabilization.},
author = { Hein J Wijma and Robert J Floor and Peter A Jekel and David Baker and Siewert J Marrink and Dick B Janssen},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Wijma_PEDS_2014.pdf},
doi = {10.1093/protein/gzt061},
issn = {1741-0134},
year = {2014},
date = {2014-02-01},
journal = {Protein engineering, design & selection : PEDS},
volume = {27},
pages = {49-58},
abstract = {The ability to engineer enzymes and other proteins to any desired stability would have wide-ranging applications. Here, we demonstrate that computational design of a library with chemically diverse stabilizing mutations allows the engineering of drastically stabilized and fully functional variants of the mesostable enzyme limonene epoxide hydrolase. First, point mutations were selected if they significantly improved the predicted free energy of protein folding. Disulfide bonds were designed using sampling of backbone conformational space, which tripled the number of experimentally stabilizing disulfide bridges. Next, orthogonal in silico screening steps were used to remove chemically unreasonable mutations and mutations that are predicted to increase protein flexibility. The resulting library of 64 variants was experimentally screened, which revealed 21 (pairs of) stabilizing mutations located both in relatively rigid and in flexible areas of the enzyme. Finally, combining 10-12 of these confirmed mutations resulted in multi-site mutants with an increase in apparent melting temperature from 50 to 85textdegreeC, enhanced catalytic activity, preserved regioselectivity and a >250-fold longer half-life. The developed Framework for Rapid Enzyme Stabilization by Computational libraries (FRESCO) requires far less screening than conventional directed evolution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ability to engineer enzymes and other proteins to any desired stability would have wide-ranging applications. Here, we demonstrate that computational design of a library with chemically diverse stabilizing mutations allows the engineering of drastically stabilized and fully functional variants of the mesostable enzyme limonene epoxide hydrolase. First, point mutations were selected if they significantly improved the predicted free energy of protein folding. Disulfide bonds were designed using sampling of backbone conformational space, which tripled the number of experimentally stabilizing disulfide bridges. Next, orthogonal in silico screening steps were used to remove chemically unreasonable mutations and mutations that are predicted to increase protein flexibility. The resulting library of 64 variants was experimentally screened, which revealed 21 (pairs of) stabilizing mutations located both in relatively rigid and in flexible areas of the enzyme. Finally, combining 10-12 of these confirmed mutations resulted in multi-site mutants with an increase in apparent melting temperature from 50 to 85textdegreeC, enhanced catalytic activity, preserved regioselectivity and a >250-fold longer half-life. The developed Framework for Rapid Enzyme Stabilization by Computational libraries (FRESCO) requires far less screening than conventional directed evolution.
Bruno E Correia, John T Bates, Rebecca J Loomis, Gretchen Baneyx, Chris Carrico, Joseph G Jardine, Peter Rupert, Colin Correnti, Oleksandr Kalyuzhniy, Vinayak Vittal, Mary J Connell, Eric Stevens, Alexandria Schroeter, Man Chen, Skye MacPherson, Andreia M Serra, Yumiko Adachi, Margaret A Holmes, Yuxing Li, Rachel E Klevit, Barney S Graham, Richard T Wyatt, David Baker, Roland K Strong, James E Crowe, Philip R Johnson, William R Schief
Proof of principle for epitope-focused vaccine design Journal Article
In: Nature, 2014, ISSN: 1476-4687.
@article{522,
title = {Proof of principle for epitope-focused vaccine design},
author = { Bruno E Correia and John T Bates and Rebecca J Loomis and Gretchen Baneyx and Chris Carrico and Joseph G Jardine and Peter Rupert and Colin Correnti and Oleksandr Kalyuzhniy and Vinayak Vittal and Mary J Connell and Eric Stevens and Alexandria Schroeter and Man Chen and Skye MacPherson and Andreia M Serra and Yumiko Adachi and Margaret A Holmes and Yuxing Li and Rachel E Klevit and Barney S Graham and Richard T Wyatt and David Baker and Roland K Strong and James E Crowe and Philip R Johnson and William R Schief},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Correia14.pdf},
doi = {10.1038/nature12966},
issn = {1476-4687},
year = {2014},
date = {2014-02-01},
journal = {Nature},
abstract = {Vaccines prevent infectious disease largely by inducing protective neutralizing antibodies against vulnerable epitopes. Several major pathogens have resisted traditional vaccine development, although vulnerable epitopes targeted by neutralizing antibodies have been identified for several such cases. Hence, new vaccine design methods to induce epitope-specific neutralizing antibodies are needed. Here we show, with a neutralization epitope from respiratory syncytial virus, that computational protein design can generate small, thermally and conformationally stable protein scaffolds that accurately mimic the viral epitope structure and induce potent neutralizing antibodies. These scaffolds represent promising leads for the research and development of a human respiratory syncytial virus vaccine needed to protect infants, young children and the elderly. More generally, the results provide proof of principle for epitope-focused and scaffold-based vaccine design, and encourage the evaluation and further development of these strategies for a variety of other vaccine targets, including antigenically highly variable pathogens such as human immunodeficiency virus and influenza.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Vaccines prevent infectious disease largely by inducing protective neutralizing antibodies against vulnerable epitopes. Several major pathogens have resisted traditional vaccine development, although vulnerable epitopes targeted by neutralizing antibodies have been identified for several such cases. Hence, new vaccine design methods to induce epitope-specific neutralizing antibodies are needed. Here we show, with a neutralization epitope from respiratory syncytial virus, that computational protein design can generate small, thermally and conformationally stable protein scaffolds that accurately mimic the viral epitope structure and induce potent neutralizing antibodies. These scaffolds represent promising leads for the research and development of a human respiratory syncytial virus vaccine needed to protect infants, young children and the elderly. More generally, the results provide proof of principle for epitope-focused and scaffold-based vaccine design, and encourage the evaluation and further development of these strategies for a variety of other vaccine targets, including antigenically highly variable pathogens such as human immunodeficiency virus and influenza.
Tyler D Shropshire, Jack Reifert, Sridharan Rajagopalan, David Baker, Stuart C Feinstein, Patrick S Daugherty
Amyloid β peptide cleavage by kallikrein 7 attenuates fibril growth and rescues neurons from Aβ-mediated toxicity in vitro. Journal Article
In: Biological chemistry, vol. 395, pp. 109-18, 2014, ISSN: 1437-4315.
@article{510,
title = {Amyloid β peptide cleavage by kallikrein 7 attenuates fibril growth and rescues neurons from Aβ-mediated toxicity in vitro.},
author = { Tyler D Shropshire and Jack Reifert and Sridharan Rajagopalan and David Baker and Stuart C Feinstein and Patrick S Daugherty},
doi = {10.1515/hsz-2013-0230},
issn = {1437-4315},
year = {2014},
date = {2014-01-01},
journal = {Biological chemistry},
volume = {395},
pages = {109-18},
abstract = {Abstract The gradual accumulation and assembly of β-amyloid (Aβ) peptide into neuritic plaques is a major pathological hallmark of Alzheimer disease (AD). Proteolytic degradation of Aβ is an important clearance mechanism under normal circumstances, and it has been found to be compromised in those with AD. Here, the extended substrate specificity and Aβ-degrading capacity of kallikrein 7 (KLK7), a serine protease with a unique chymotrypsin-like specificity, was characterized. Preferred peptide substrates of KLK7 identified using a bacterial display substrate library were found to exhibit a consensus motif of RXΦ(Y/F)textdownarrow(Y/F)textdownarrow(S/A/G/T) or RXΦ(Y/F)textdownarrow(S/T/A) (Φ=hydrophobic), which is remarkably similar to the hydrophobic core motif of Aβ (K16L17V18F19F20 A21) that is largely responsible for aggregation propensity. KLK7 was found to cleave after both Phe residues within the core of Aβ42 in vitro, thereby inhibiting Aβ fibril formation and promoting the degradation of preformed fibrils. Finally, the treatment of Aβ oligomer preparations with KLK7, but not inactive pro-KLK7, significantly reduced Aβ42-mediated toxicity to rat hippocampal neurons to the same extent as the known Aβ-degrading protease insulin-degrading enzyme (IDE). Taken together, these results indicate that KLK7 possesses an Aβ-degrading capacity that can ameliorate the toxic effects of the aggregated peptide in vitro.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract The gradual accumulation and assembly of β-amyloid (Aβ) peptide into neuritic plaques is a major pathological hallmark of Alzheimer disease (AD). Proteolytic degradation of Aβ is an important clearance mechanism under normal circumstances, and it has been found to be compromised in those with AD. Here, the extended substrate specificity and Aβ-degrading capacity of kallikrein 7 (KLK7), a serine protease with a unique chymotrypsin-like specificity, was characterized. Preferred peptide substrates of KLK7 identified using a bacterial display substrate library were found to exhibit a consensus motif of RXΦ(Y/F)textdownarrow(Y/F)textdownarrow(S/A/G/T) or RXΦ(Y/F)textdownarrow(S/T/A) (Φ=hydrophobic), which is remarkably similar to the hydrophobic core motif of Aβ (K16L17V18F19F20 A21) that is largely responsible for aggregation propensity. KLK7 was found to cleave after both Phe residues within the core of Aβ42 in vitro, thereby inhibiting Aβ fibril formation and promoting the degradation of preformed fibrils. Finally, the treatment of Aβ oligomer preparations with KLK7, but not inactive pro-KLK7, significantly reduced Aβ42-mediated toxicity to rat hippocampal neurons to the same extent as the known Aβ-degrading protease insulin-degrading enzyme (IDE). Taken together, these results indicate that KLK7 possesses an Aβ-degrading capacity that can ameliorate the toxic effects of the aggregated peptide in vitro.
Summer Thyme, David Baker
Redesigning the Specificity of Protein-DNA Interactions with Rosetta. Journal Article
In: Methods in molecular biology (Clifton, N.J.), vol. 1123, pp. 265-82, 2014, ISSN: 1940-6029.
@article{525,
title = {Redesigning the Specificity of Protein-DNA Interactions with Rosetta.},
author = { Summer Thyme and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Thyme_2014.pdf},
doi = {10.1007/978-1-62703-968-0_17},
issn = {1940-6029},
year = {2014},
date = {2014-01-01},
journal = {Methods in molecular biology (Clifton, N.J.)},
volume = {1123},
pages = {265-82},
abstract = {Building protein tools that can selectively bind or cleave specific DNA sequences requires efficient technologies for modifying protein-DNA interactions. Computational design is one method for accomplishing this goal. In this chapter, we present the current state of protein-DNA interface design with the Rosetta macromolecular modeling program. The LAGLIDADG endonuclease family of DNA-cleaving enzymes, under study as potential gene therapy reagents, has been the main testing ground for these in silico protocols. At this time, the computational methods are most useful for designing endonuclease variants that can accommodate small numbers of target site substitutions. Attempts to engineer for more extensive interface changes will likely benefit from an approach that uses the computational design results in conjunction with a high-throughput directed evolution or screening procedure. The family of enzymes presents an engineering challenge because their interfaces are highly integrated and there is significant coordination between the binding and catalysis events. Future developments in the computational algorithms depend on experimental feedback to improve understanding and modeling of these complex enzymatic features. This chapter presents both the basic method of design that has been successfully used to modulate specificity and more advanced procedures that incorporate DNA flexibility and other properties that are likely necessary for reliable modeling of more extensive target site changes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Building protein tools that can selectively bind or cleave specific DNA sequences requires efficient technologies for modifying protein-DNA interactions. Computational design is one method for accomplishing this goal. In this chapter, we present the current state of protein-DNA interface design with the Rosetta macromolecular modeling program. The LAGLIDADG endonuclease family of DNA-cleaving enzymes, under study as potential gene therapy reagents, has been the main testing ground for these in silico protocols. At this time, the computational methods are most useful for designing endonuclease variants that can accommodate small numbers of target site substitutions. Attempts to engineer for more extensive interface changes will likely benefit from an approach that uses the computational design results in conjunction with a high-throughput directed evolution or screening procedure. The family of enzymes presents an engineering challenge because their interfaces are highly integrated and there is significant coordination between the binding and catalysis events. Future developments in the computational algorithms depend on experimental feedback to improve understanding and modeling of these complex enzymatic features. This chapter presents both the basic method of design that has been successfully used to modulate specificity and more advanced procedures that incorporate DNA flexibility and other properties that are likely necessary for reliable modeling of more extensive target site changes.
Binchen Mao, Roberto Tejero, David Baker, Gaetano Thomas Montelione
Protein NMR Structures Refined with Rosetta Have Higher Accuracy Relative to Corresponding X-ray Crystal Structures. Journal Article
In: Journal of the American Chemical Society, 2014, ISSN: 1520-5126.
@article{519,
title = {Protein NMR Structures Refined with Rosetta Have Higher Accuracy Relative to Corresponding X-ray Crystal Structures.},
author = { Binchen Mao and Roberto Tejero and David Baker and Gaetano Thomas Montelione},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Mao_JACS_2014.pdf},
issn = {1520-5126},
year = {2014},
date = {2014-01-01},
journal = {Journal of the American Chemical Society},
abstract = {We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5 - 22 kDa, restrained-Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 38 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained-Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10 - 25 kDa the less cpu intensive restrained-Rosetta refinement protocols provided more accurate structures. The restrained-Rosetta protocols described here can improve the accuracy of protein NMR structures, and should find broad and general for studies of protein structure and function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5 – 22 kDa, restrained-Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 38 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained-Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10 – 25 kDa the less cpu intensive restrained-Rosetta refinement protocols provided more accurate structures. The restrained-Rosetta protocols described here can improve the accuracy of protein NMR structures, and should find broad and general for studies of protein structure and function.
Jean-Philippe Demers, Birgit Habenstein, Antoine Loquet, Suresh Kumar Vasa, Karin Giller, Stefan Becker, David Baker, Adam Lange, Nikolaos G Sgourakis
High-resolution structure of the Shigella type-III secretion needle by solid-state NMR and cryo-electron microscopy. Journal Article
In: Nature communications, vol. 5, pp. 4976, 2014, ISSN: 2041-1723.
@article{620,
title = {High-resolution structure of the Shigella type-III secretion needle by solid-state NMR and cryo-electron microscopy.},
author = { Jean-Philippe Demers and Birgit Habenstein and Antoine Loquet and Suresh Kumar Vasa and Karin Giller and Stefan Becker and David Baker and Adam Lange and Nikolaos G Sgourakis},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Demers_Nature_2014.pdf},
doi = {10.1038/ncomms5976},
issn = {2041-1723},
year = {2014},
date = {2014-00-01},
journal = {Nature communications},
volume = {5},
pages = {4976},
abstract = {We introduce a general hybrid approach for determining the structures of supramolecular assemblies. Cryo-electron microscopy (cryo-EM) data define the overall envelope of the assembly and rigid-body orientation of the subunits while solid-state nuclear magnetic resonance (ssNMR) chemical shifts and distance constraints define the local secondary structure, protein fold and inter-subunit interactions. Finally, Rosetta structure calculations provide a general framework to integrate the different sources of structural information. Combining a 7.7-r A cryo-EM density map and 996 ssNMR distance constraints, the structure of the type-III secretion system needle of Shigella flexneri is determined to a precision of 0.4 r A. The calculated structures are cross-validated using an independent data set of 691 ssNMR constraints and scanning transmission electron microscopy measurements. The hybrid model resolves the conformation of the non-conserved N terminus, which occupies a protrusion in the cryo-EM density, and reveals conserved pore residues forming a continuous pattern of electrostatic interactions, thereby suggesting a mechanism for effector protein translocation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We introduce a general hybrid approach for determining the structures of supramolecular assemblies. Cryo-electron microscopy (cryo-EM) data define the overall envelope of the assembly and rigid-body orientation of the subunits while solid-state nuclear magnetic resonance (ssNMR) chemical shifts and distance constraints define the local secondary structure, protein fold and inter-subunit interactions. Finally, Rosetta structure calculations provide a general framework to integrate the different sources of structural information. Combining a 7.7-r A cryo-EM density map and 996 ssNMR distance constraints, the structure of the type-III secretion system needle of Shigella flexneri is determined to a precision of 0.4 r A. The calculated structures are cross-validated using an independent data set of 691 ssNMR constraints and scanning transmission electron microscopy measurements. The hybrid model resolves the conformation of the non-conserved N terminus, which occupies a protrusion in the cryo-EM density, and reveals conserved pore residues forming a continuous pattern of electrostatic interactions, thereby suggesting a mechanism for effector protein translocation.
Pierre Leblanc, Leonard Moise, Cybelle Luza, Kanawat Chantaralawan, Lynchy Lezeau, Jianping Yuan, Mary Field, Daniel Richer, Christine Boyle, William D Martin, Jordan B Fishman, Eric A Berg, David Baker, Brandon Zeigler, Dale E Mais, William Taylor, Russell Coleman, H Shaw Warren, Jeffrey A Gelfand, Anne S De Groot, Timothy Brauns, Mark C Poznansky
VaxCelerate II: rapid development of a self-assembling vaccine for Lassa fever. Journal Article
In: Human vaccines & immunotherapeutics, vol. 10, pp. 3022-38, 2014, ISSN: 2164-554X.
@article{618,
title = {VaxCelerate II: rapid development of a self-assembling vaccine for Lassa fever.},
author = { Pierre Leblanc and Leonard Moise and Cybelle Luza and Kanawat Chantaralawan and Lynchy Lezeau and Jianping Yuan and Mary Field and Daniel Richer and Christine Boyle and William D Martin and Jordan B Fishman and Eric A Berg and David Baker and Brandon Zeigler and Dale E Mais and William Taylor and Russell Coleman and H Shaw Warren and Jeffrey A Gelfand and Anne S De Groot and Timothy Brauns and Mark C Poznansky},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Leblanc_HumanVI_2014.pdf},
doi = {10.4161/hv.34413},
issn = {2164-554X},
year = {2014},
date = {2014-00-01},
journal = {Human vaccines & immunotherapeutics},
volume = {10},
pages = {3022-38},
abstract = {Development of effective vaccines against emerging infectious diseases (EID) can take as much or more than a decade to progress from pathogen isolation/identification to clinical approval. As a result, conventional approaches fail to produce field-ready vaccines before the EID has spread extensively. Lassa is a prototypical emerging infectious disease endemic to West Africa for which no successful vaccine is available. We established the VaxCelerate Consortium to address the need for more rapid vaccine development by creating a platform capable of generating and pre-clinically testing a new vaccine against specific pathogen targets in less than 120 d A self-assembling vaccine is at the core of the approach. It consists of a fusion protein composed of the immunostimulatory Mycobacterium tuberculosis heat shock protein 70 (MtbHSP70) and the biotin binding protein, avidin. Mixing the resulting protein (MAV) with biotinylated pathogen-specific immunogenic peptides yields a self-assembled vaccine (SAV). To meet the time constraint imposed on this project, we used a distributed R&D model involving experts in the fields of protein engineering and production, bioinformatics, peptide synthesis/design and GMP/GLP manufacturing and testing standards. SAV immunogenicity was first tested using H1N1 influenza specific peptides and the entire VaxCelerate process was then tested in a mock live-fire exercise targeting Lassa fever virus. We demonstrated that the Lassa fever vaccine induced significantly increased class II peptide specific interferon-γ CD4(+) T cell responses in HLA-DR3 transgenic mice compared to peptide or MAV alone controls. We thereby demonstrated that our SAV in combination with a distributed development model may facilitate accelerated regulatory review by using an identical design for each vaccine and by applying safety and efficacy assessment tools that are more relevant to human vaccine responses than current animal models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Development of effective vaccines against emerging infectious diseases (EID) can take as much or more than a decade to progress from pathogen isolation/identification to clinical approval. As a result, conventional approaches fail to produce field-ready vaccines before the EID has spread extensively. Lassa is a prototypical emerging infectious disease endemic to West Africa for which no successful vaccine is available. We established the VaxCelerate Consortium to address the need for more rapid vaccine development by creating a platform capable of generating and pre-clinically testing a new vaccine against specific pathogen targets in less than 120 d A self-assembling vaccine is at the core of the approach. It consists of a fusion protein composed of the immunostimulatory Mycobacterium tuberculosis heat shock protein 70 (MtbHSP70) and the biotin binding protein, avidin. Mixing the resulting protein (MAV) with biotinylated pathogen-specific immunogenic peptides yields a self-assembled vaccine (SAV). To meet the time constraint imposed on this project, we used a distributed R&D model involving experts in the fields of protein engineering and production, bioinformatics, peptide synthesis/design and GMP/GLP manufacturing and testing standards. SAV immunogenicity was first tested using H1N1 influenza specific peptides and the entire VaxCelerate process was then tested in a mock live-fire exercise targeting Lassa fever virus. We demonstrated that the Lassa fever vaccine induced significantly increased class II peptide specific interferon-γ CD4(+) T cell responses in HLA-DR3 transgenic mice compared to peptide or MAV alone controls. We thereby demonstrated that our SAV in combination with a distributed development model may facilitate accelerated regulatory review by using an identical design for each vaccine and by applying safety and efficacy assessment tools that are more relevant to human vaccine responses than current animal models.
2013
Eva-Maria Strauch, Sarel J Fleishman, David Baker
Computational design of a pH-sensitive IgG binding protein Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, 2013, ISSN: 1091-6490.
@article{499,
title = {Computational design of a pH-sensitive IgG binding protein},
author = { Eva-Maria Strauch and Sarel J Fleishman and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Strauch-1313605111_PNAS_13W.pdf},
issn = {1091-6490},
year = {2013},
date = {2013-12-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
abstract = {Computational design provides the opportunity to program protein-protein interactions for desired applications. We used de novo protein interface design to generate a pH-dependent Fc domain binding protein that buries immunoglobulin G (IgG) His-433. Using next-generation sequencing of na"ive and selected pools of a library of design variants, we generated a molecular footprint of the designed binding surface, confirming the binding mode and guiding further optimization of the balance between affinity and pH sensitivity. In biolayer interferometry experiments, the optimized design binds IgG with a Kd of ~4 nM at pH 8.2, and approximately 500-fold more weakly at pH 5.5. The protein is extremely stable, heat-resistant and highly expressed in bacteria, and allows pH-based control of binding for IgG affinity purification and diagnostic devices.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational design provides the opportunity to program protein-protein interactions for desired applications. We used de novo protein interface design to generate a pH-dependent Fc domain binding protein that buries immunoglobulin G (IgG) His-433. Using next-generation sequencing of na"ive and selected pools of a library of design variants, we generated a molecular footprint of the designed binding surface, confirming the binding mode and guiding further optimization of the balance between affinity and pH sensitivity. In biolayer interferometry experiments, the optimized design binds IgG with a Kd of ~4 nM at pH 8.2, and approximately 500-fold more weakly at pH 5.5. The protein is extremely stable, heat-resistant and highly expressed in bacteria, and allows pH-based control of binding for IgG affinity purification and diagnostic devices.
Jie Fang, Alexander Mehlich, Nobuyasu Koga, Jiqing Huang, Rie Koga, Xiaoye Gao, Chunguang Hu, Chi Jin, Matthias Rief, Juergen Kast, David Baker, Hongbin Li
Forced protein unfolding leads to highly elastic and tough protein hydrogels. Journal Article
In: Nature communications, vol. 4, pp. 2974, 2013, ISSN: 2041-1723.
@article{517,
title = {Forced protein unfolding leads to highly elastic and tough protein hydrogels.},
author = { Jie Fang and Alexander Mehlich and Nobuyasu Koga and Jiqing Huang and Rie Koga and Xiaoye Gao and Chunguang Hu and Chi Jin and Matthias Rief and Juergen Kast and David Baker and Hongbin Li},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Fang_NatCommun_2013.pdf},
doi = {10.1038/ncomms3974},
issn = {2041-1723},
year = {2013},
date = {2013-12-01},
journal = {Nature communications},
volume = {4},
pages = {2974},
abstract = {Protein-based hydrogels usually do not exhibit high stretchability or toughness, significantly limiting the scope of their potential biomedical applications. Here we report the engineering of a chemically cross-linked, highly elastic and tough protein hydrogel using a mechanically extremely labile, de novo-designed protein that assumes the classical ferredoxin-like fold structure. Due to the low mechanical stability of the ferredoxin-like fold structure, swelling of hydrogels causes a significant fraction of the folded domains to unfold. Subsequent collapse and aggregation of unfolded ferredoxin-like domains leads to intertwining of physically and chemically cross-linked networks, entailing hydrogels with unusual physical and mechanical properties: a negative swelling ratio, high stretchability and toughness. These hydrogels can withstand an average strain of 450% before breaking and show massive energy dissipation. Upon relaxation, refolding of the ferredoxin-like domains enables the hydrogel to recover its massive hysteresis. This novel biomaterial may expand the scope of hydrogel applications in tissue engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-based hydrogels usually do not exhibit high stretchability or toughness, significantly limiting the scope of their potential biomedical applications. Here we report the engineering of a chemically cross-linked, highly elastic and tough protein hydrogel using a mechanically extremely labile, de novo-designed protein that assumes the classical ferredoxin-like fold structure. Due to the low mechanical stability of the ferredoxin-like fold structure, swelling of hydrogels causes a significant fraction of the folded domains to unfold. Subsequent collapse and aggregation of unfolded ferredoxin-like domains leads to intertwining of physically and chemically cross-linked networks, entailing hydrogels with unusual physical and mechanical properties: a negative swelling ratio, high stretchability and toughness. These hydrogels can withstand an average strain of 450% before breaking and show massive energy dissipation. Upon relaxation, refolding of the ferredoxin-like domains enables the hydrogel to recover its massive hysteresis. This novel biomaterial may expand the scope of hydrogel applications in tissue engineering.
Sandrine Boissel, Jordan Jarjour, Alexander Astrakhan, Andrew Adey, Agn`es Gouble, Philippe Duchateau, Jay Shendure, Barry L Stoddard, Michael T Certo, David Baker, Andrew M Scharenberg
megaTALs: a rare-cleaving nuclease architecture for therapeutic genome engineering. Journal Article
In: Nucleic acids research, 2013, ISSN: 1362-4962.
@article{516,
title = {megaTALs: a rare-cleaving nuclease architecture for therapeutic genome engineering.},
author = { Sandrine Boissel and Jordan Jarjour and Alexander Astrakhan and Andrew Adey and Agn`es Gouble and Philippe Duchateau and Jay Shendure and Barry L Stoddard and Michael T Certo and David Baker and Andrew M Scharenberg},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Boissel_NAR_2013.pdf},
issn = {1362-4962},
year = {2013},
date = {2013-11-01},
journal = {Nucleic acids research},
abstract = {Rare-cleaving endonucleases have emerged as important tools for making targeted genome modifications. While multiple platforms are now available to generate reagents for research applications, each existing platform has significant limitations in one or more of three key properties necessary for therapeutic application: efficiency of cleavage at the desired target site, specificity of cleavage (i.e. rate of cleavage at textquoterightoff-targettextquoteright sites), and efficient/facile means for delivery to desired target cells. Here, we describe the development of a single-chain rare-cleaving nuclease architecture, which we designate textquoterightmegaTALtextquoteright, in which the DNA binding region of a transcription activator-like (TAL) effector is used to textquoterightaddresstextquoteright a site-specific meganuclease adjacent to a single desired genomic target site. This architecture allows the generation of extremely active and hyper-specific compact nucleases that are compatible with all current viral and nonviral cell delivery methods.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rare-cleaving endonucleases have emerged as important tools for making targeted genome modifications. While multiple platforms are now available to generate reagents for research applications, each existing platform has significant limitations in one or more of three key properties necessary for therapeutic application: efficiency of cleavage at the desired target site, specificity of cleavage (i.e. rate of cleavage at textquoterightoff-targettextquoteright sites), and efficient/facile means for delivery to desired target cells. Here, we describe the development of a single-chain rare-cleaving nuclease architecture, which we designate textquoterightmegaTALtextquoteright, in which the DNA binding region of a transcription activator-like (TAL) effector is used to textquoterightaddresstextquoteright a site-specific meganuclease adjacent to a single desired genomic target site. This architecture allows the generation of extremely active and hyper-specific compact nucleases that are compatible with all current viral and nonviral cell delivery methods.
Summer B Thyme, Sandrine J S Boissel, S Arshiya Quadri, Tony Nolan, Dean A Baker, Rachel U Park, Lara Kusak, Justin Ashworth, David Baker
Reprogramming homing endonuclease specificity through computational design and directed evolution. Journal Article
In: Nucleic acids research, 2013, ISSN: 1362-4962.
@article{515,
title = {Reprogramming homing endonuclease specificity through computational design and directed evolution.},
author = { Summer B Thyme and Sandrine J S Boissel and S Arshiya Quadri and Tony Nolan and Dean A Baker and Rachel U Park and Lara Kusak and Justin Ashworth and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Thyme_NAR_2013.pdf},
issn = {1362-4962},
year = {2013},
date = {2013-11-01},
journal = {Nucleic acids research},
abstract = {Homing endonucleases (HEs) can be used to induce targeted genome modification to reduce the fitness of pathogen vectors such as the malaria-transmitting Anopheles gambiae and to correct deleterious mutations in genetic diseases. We describe the creation of an extensive set of HE variants with novel DNA cleavage specificities using an integrated experimental and computational approach. Using computational modeling and an improved selection strategy, which optimizes specificity in addition to activity, we engineered an endonuclease to cleave in a gene associated with Anopheles sterility and another to cleave near a mutation that causes pyruvate kinase deficiency. In the course of this work we observed unanticipated context-dependence between bases which will need to be mechanistically understood for reprogramming of specificity to succeed more generally.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Homing endonucleases (HEs) can be used to induce targeted genome modification to reduce the fitness of pathogen vectors such as the malaria-transmitting Anopheles gambiae and to correct deleterious mutations in genetic diseases. We describe the creation of an extensive set of HE variants with novel DNA cleavage specificities using an integrated experimental and computational approach. Using computational modeling and an improved selection strategy, which optimizes specificity in addition to activity, we engineered an endonuclease to cleave in a gene associated with Anopheles sterility and another to cleave near a mutation that causes pyruvate kinase deficiency. In the course of this work we observed unanticipated context-dependence between bases which will need to be mechanistically understood for reprogramming of specificity to succeed more generally.
Izhack Cherny, Per Greisen, Yacov Ashani, Sagar D Khare, Gustav Oberdorfer, Haim Leader, David Baker, Dan S Tawfik
Engineering V-type nerve agents detoxifying enzymes using computationally focused libraries Journal Article
In: ACS chemical biology, vol. 8, pp. 2394-403, 2013, ISSN: 1554-8937.
@article{497,
title = {Engineering V-type nerve agents detoxifying enzymes using computationally focused libraries},
author = { Izhack Cherny and Per Greisen and Yacov Ashani and Sagar D Khare and Gustav Oberdorfer and Haim Leader and David Baker and Dan S Tawfik},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Cherny_cb4004892_13W.pdf},
doi = {10.1021/cb4004892},
issn = {1554-8937},
year = {2013},
date = {2013-11-01},
journal = {ACS chemical biology},
volume = {8},
pages = {2394-403},
abstract = {VX and its Russian (RVX) and Chinese (CVX) analogues rapidly inactivate acetylcholinesterase and are the most toxic stockpile nerve agents. These organophosphates have a thiol leaving group with a choline-like moiety and are hydrolyzed very slowly by natural enzymes. We used an integrated computational and experimental approach to increase Brevundimonas diminuta phosphotriesterasetextquoterights (PTE) detoxification rate of V-agents by 5000-fold. Computational models were built of the complex between PTE and V-agents. On the basis of these models, the active site was redesigned to be complementary in shape to VX and RVX and to include favorable electrostatic interactions with their choline-like leaving group. Small libraries based on designed sequences were constructed. The libraries were screened by a direct assay for V-agent detoxification, as our initial studies showed that colorimetric surrogates fail to report the detoxification rates of the actual agents. The experimental results were fed back to improve the computational models. Overall, five rounds of iterating between experiment and model refinement led to variants that hydrolyze the toxic SP isomers of all three V-agents with kcat/KM values of up to 5 texttimes 10(6) M(-1) min(-1) and also efficiently detoxify G-agents. These new catalysts provide the basis for broad spectrum nerve agent detoxification.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
VX and its Russian (RVX) and Chinese (CVX) analogues rapidly inactivate acetylcholinesterase and are the most toxic stockpile nerve agents. These organophosphates have a thiol leaving group with a choline-like moiety and are hydrolyzed very slowly by natural enzymes. We used an integrated computational and experimental approach to increase Brevundimonas diminuta phosphotriesterasetextquoterights (PTE) detoxification rate of V-agents by 5000-fold. Computational models were built of the complex between PTE and V-agents. On the basis of these models, the active site was redesigned to be complementary in shape to VX and RVX and to include favorable electrostatic interactions with their choline-like leaving group. Small libraries based on designed sequences were constructed. The libraries were screened by a direct assay for V-agent detoxification, as our initial studies showed that colorimetric surrogates fail to report the detoxification rates of the actual agents. The experimental results were fed back to improve the computational models. Overall, five rounds of iterating between experiment and model refinement led to variants that hydrolyze the toxic SP isomers of all three V-agents with kcat/KM values of up to 5 texttimes 10(6) M(-1) min(-1) and also efficiently detoxify G-agents. These new catalysts provide the basis for broad spectrum nerve agent detoxification.
Rocco Moretti, Sarel J Fleishman, Rudi Agius, Mieczyslaw Torchala, Paul A Bates, Panagiotis L Kastritis, Jo~ao P G L M Rodrigues, Mika"el Trellet, Alexandre M J J Bonvin, Meng Cui, Marianne Rooman, Dimitri Gillis, Yves Dehouck, Iain Moal, Miguel Romero-Durana, Laura Perez-Cano, Chiara Pallara, Brian Jimenez, Juan Fernandez-Recio, Samuel Flores, Michael Pacella, Krishna Praneeth Kilambi, Jeffrey J Gray, Petr Popov, Sergei Grudinin, Juan Esquivel-Rodr’iguez, Daisuke Kihara, Nan Zhao, Dmitry Korkin, Xiaolei Zhu, Omar N A Demerdash, Julie C Mitchell, Eiji Kanamori, Yuko Tsuchiya, Haruki Nakamura, Hasup Lee, Hahnbeom Park, Chaok Seok, Jamica Sarmiento, Shide Liang, Shusuke Teraguchi, Daron M Standley, Hiromitsu Shimoyama, Genki Terashi, Mayuko Takeda-Shitaka, Mitsuo Iwadate, Hideaki Umeyama, Dmitri Beglov, David R Hall, Dima Kozakov, Sandor Vajda, Brian G Pierce, Howook Hwang, Thom Vreven, Zhiping Weng, Yangyu Huang, Haotian Li, Xiufeng Yang, Xiaofeng Ji, Shiyong Liu, Yi Xiao, Martin Zacharias, Sanbo Qin, Huan-Xiang Zhou, Sheng-You Huang, Xiaoqin Zou, Sameer Velankar, Jo"el Janin, Shoshana J Wodak, David Baker
Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions. Journal Article
In: Proteins, vol. 81, pp. 1980-7, 2013, ISSN: 1097-0134.
@article{505,
title = {Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions.},
author = { Rocco Moretti and Sarel J Fleishman and Rudi Agius and Mieczyslaw Torchala and Paul A Bates and Panagiotis L Kastritis and Jo~ao P G L M Rodrigues and Mika"el Trellet and Alexandre M J J Bonvin and Meng Cui and Marianne Rooman and Dimitri Gillis and Yves Dehouck and Iain Moal and Miguel Romero-Durana and Laura Perez-Cano and Chiara Pallara and Brian Jimenez and Juan Fernandez-Recio and Samuel Flores and Michael Pacella and Krishna Praneeth Kilambi and Jeffrey J Gray and Petr Popov and Sergei Grudinin and Juan Esquivel-Rodr'iguez and Daisuke Kihara and Nan Zhao and Dmitry Korkin and Xiaolei Zhu and Omar N A Demerdash and Julie C Mitchell and Eiji Kanamori and Yuko Tsuchiya and Haruki Nakamura and Hasup Lee and Hahnbeom Park and Chaok Seok and Jamica Sarmiento and Shide Liang and Shusuke Teraguchi and Daron M Standley and Hiromitsu Shimoyama and Genki Terashi and Mayuko Takeda-Shitaka and Mitsuo Iwadate and Hideaki Umeyama and Dmitri Beglov and David R Hall and Dima Kozakov and Sandor Vajda and Brian G Pierce and Howook Hwang and Thom Vreven and Zhiping Weng and Yangyu Huang and Haotian Li and Xiufeng Yang and Xiaofeng Ji and Shiyong Liu and Yi Xiao and Martin Zacharias and Sanbo Qin and Huan-Xiang Zhou and Sheng-You Huang and Xiaoqin Zou and Sameer Velankar and Jo"el Janin and Shoshana J Wodak and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Moretti_Proteins_2013.pdf},
doi = {10.1002/prot.24356},
issn = {1097-0134},
year = {2013},
date = {2013-11-01},
journal = {Proteins},
volume = {81},
pages = {1980-7},
abstract = {Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies.
Frank DiMaio, Nathaniel Echols, Jeffrey J Headd, Thomas C Terwilliger, Paul D Adams, David Baker
Improved low-resolution crystallographic refinement with Phenix and Rosetta. Journal Article
In: Nature methods, vol. 10, pp. 1102-4, 2013, ISSN: 1548-7105.
@article{513,
title = {Improved low-resolution crystallographic refinement with Phenix and Rosetta.},
author = { Frank DiMaio and Nathaniel Echols and Jeffrey J Headd and Thomas C Terwilliger and Paul D Adams and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/DiMaio_NatureMethods_2013.pdf},
doi = {10.1038/nmeth.2648},
issn = {1548-7105},
year = {2013},
date = {2013-11-01},
journal = {Nature methods},
volume = {10},
pages = {1102-4},
abstract = {Refinement of macromolecular structures against low-resolution crystallographic data is limited by the ability of current methods to converge on a structure with realistic geometry. We developed a low-resolution crystallographic refinement method that combines the Rosetta sampling methodology and energy function with reciprocal-space X-ray refinement in Phenix. On a set of difficult low-resolution cases, the method yielded improved model geometry and lower free R factors than alternate refinement methods.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Refinement of macromolecular structures against low-resolution crystallographic data is limited by the ability of current methods to converge on a structure with realistic geometry. We developed a low-resolution crystallographic refinement method that combines the Rosetta sampling methodology and energy function with reciprocal-space X-ray refinement in Phenix. On a set of difficult low-resolution cases, the method yielded improved model geometry and lower free R factors than alternate refinement methods.
Yifan Song, Frank DiMaio, Ray Yu-Ruei Wang, David Kim, Chris Miles, Tj Brunette, James Thompson, David Baker
High-resolution comparative modeling with RosettaCM. Journal Article
In: Structure (London, England : 1993), vol. 21, pp. 1735-42, 2013, ISSN: 1878-4186.
@article{512,
title = {High-resolution comparative modeling with RosettaCM.},
author = { Yifan Song and Frank DiMaio and Ray Yu-Ruei Wang and David Kim and Chris Miles and Tj Brunette and James Thompson and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Song_Structure_2013.pdf},
doi = {10.1016/j.str.2013.08.005},
issn = {1878-4186},
year = {2013},
date = {2013-10-01},
journal = {Structure (London, England : 1993)},
volume = {21},
pages = {1735-42},
abstract = {We describe an improved method for comparative modeling, RosettaCM, which optimizes a physically realistic all-atom energy function over the conformational space defined by homologous structures. Given a set of sequence alignments, RosettaCM assembles topologies by recombining aligned segments in Cartesian space and building unaligned regions de novo in torsion space. The junctions between segments are regularized using a loop closure method combining fragment superposition with gradient-based minimization. The energies of the resulting models are optimized by all-atom refinement, and the most representative low-energy model is selected. The CASP10 experiment suggests that RosettaCM yields models with more accurate side-chain and backbone conformations than other methods when the sequence identity to the templates is greater than ~15%.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe an improved method for comparative modeling, RosettaCM, which optimizes a physically realistic all-atom energy function over the conformational space defined by homologous structures. Given a set of sequence alignments, RosettaCM assembles topologies by recombining aligned segments in Cartesian space and building unaligned regions de novo in torsion space. The junctions between segments are regularized using a loop closure method combining fragment superposition with gradient-based minimization. The energies of the resulting models are optimized by all-atom refinement, and the most representative low-energy model is selected. The CASP10 experiment suggests that RosettaCM yields models with more accurate side-chain and backbone conformations than other methods when the sequence identity to the templates is greater than ~15%.
Lucas G Niv’on, Sinisa Bjelic, Chris King, David Baker
Automating human intuition for protein design Journal Article
In: Proteins, 2013, ISSN: 1097-0134.
@article{495,
title = {Automating human intuition for protein design},
author = { Lucas G Niv'on and Sinisa Bjelic and Chris King and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Nivón_prot24463_13M.pdf},
doi = {10.1002/prot.24463},
issn = {1097-0134},
year = {2013},
date = {2013-10-01},
journal = {Proteins},
abstract = {In the design of new enzymes and binding proteins, human intuition is often used to modify computationally designed amino acid sequences prior to experimental characterization. The manual sequence changes involve both reversions of amino acid mutations back to the identity present in the parent scaffold and the introduction of residues making additional interactions with the binding partner or backing up first shell interactions. Automation of this manual sequence refinement process would allow more systematic evaluation and considerably reduce the amount of human designer effort involved. Here we introduce a benchmark for evaluating the ability of automated methods to recapitulate the sequence changes made to computer-generated models by human designers, and use it to assess alternative computational methods. We find the best performance for a greedy one-position-at-a-time optimization protocol that utilizes metrics (such as shape complementarity) and local refinement methods too computationally expensive for global Monte Carlo (MC) sequence optimization. This protocol should be broadly useful for improving the stability and function of designed binding proteins. Proteins 2013. textcopyright 2013 Wiley Periodicals, Inc.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In the design of new enzymes and binding proteins, human intuition is often used to modify computationally designed amino acid sequences prior to experimental characterization. The manual sequence changes involve both reversions of amino acid mutations back to the identity present in the parent scaffold and the introduction of residues making additional interactions with the binding partner or backing up first shell interactions. Automation of this manual sequence refinement process would allow more systematic evaluation and considerably reduce the amount of human designer effort involved. Here we introduce a benchmark for evaluating the ability of automated methods to recapitulate the sequence changes made to computer-generated models by human designers, and use it to assess alternative computational methods. We find the best performance for a greedy one-position-at-a-time optimization protocol that utilizes metrics (such as shape complementarity) and local refinement methods too computationally expensive for global Monte Carlo (MC) sequence optimization. This protocol should be broadly useful for improving the stability and function of designed binding proteins. Proteins 2013. textcopyright 2013 Wiley Periodicals, Inc.
Patrick Conway, Michael D Tyka, Frank DiMaio, David E Konerding, David Baker
Relaxation of backbone bond geometry improves protein energy landscape modeling. Journal Article
In: Protein science : a publication of the Protein Society, 2013, ISSN: 1469-896X.
@article{514,
title = {Relaxation of backbone bond geometry improves protein energy landscape modeling.},
author = { Patrick Conway and Michael D Tyka and Frank DiMaio and David E Konerding and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Conway_ProteinScience_2013.pdf},
doi = {10.1002/pro.2389},
issn = {1469-896X},
year = {2013},
date = {2013-10-01},
journal = {Protein science : a publication of the Protein Society},
abstract = {A key issue in macromolecular structure modeling is the granularity of the molecular representation. A fine-grained representation can approximate the actual structure more accurately, but may require many more degrees of freedom than a coarse-grained representation and hence make conformational search more challenging. We investigate this tradeoff between the accuracy and the size of protein conformational search space for two frequently used representations: one with fixed bond angles and lengths and one that has full flexibility. We performed large-scale explorations of the energy landscapes of 82 protein domains under each model, and find that the introduction of bond angle flexibility significantly increases the average energy gap between native and non-native structures. We also find that incorporating bonded geometry flexibility improves low resolution X-ray crystallographic refinement. These results suggest that backbone bond angle relaxation makes an important contribution to native structure energetics, that current energy functions are sufficiently accurate to capture the energetic gain associated with subtle deformations from chain ideality, and more speculatively, that backbone geometry distortions occur late in protein folding to optimize packing in the native state.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A key issue in macromolecular structure modeling is the granularity of the molecular representation. A fine-grained representation can approximate the actual structure more accurately, but may require many more degrees of freedom than a coarse-grained representation and hence make conformational search more challenging. We investigate this tradeoff between the accuracy and the size of protein conformational search space for two frequently used representations: one with fixed bond angles and lengths and one that has full flexibility. We performed large-scale explorations of the energy landscapes of 82 protein domains under each model, and find that the introduction of bond angle flexibility significantly increases the average energy gap between native and non-native structures. We also find that incorporating bonded geometry flexibility improves low resolution X-ray crystallographic refinement. These results suggest that backbone bond angle relaxation makes an important contribution to native structure energetics, that current energy functions are sufficiently accurate to capture the energetic gain associated with subtle deformations from chain ideality, and more speculatively, that backbone geometry distortions occur late in protein folding to optimize packing in the native state.
Sinisa Bjelic, Yakov Kipnis, Ling Wang, Zbigniew Pianowski, Sergey Vorobiev, Min Su, Jayaraman Seetharaman, Rong Xiao, Gregory Kornhaber, John F Hunt, Liang Tong, Donald Hilvert, David Baker
Exploration of Alternate Catalytic Mechanisms and Optimization Strategies for Retroaldolase Design Journal Article
In: Journal of molecular biology, vol. 426, pp. 256-271, 2013, ISSN: 1089-8638.
@article{494,
title = {Exploration of Alternate Catalytic Mechanisms and Optimization Strategies for Retroaldolase Design},
author = { Sinisa Bjelic and Yakov Kipnis and Ling Wang and Zbigniew Pianowski and Sergey Vorobiev and Min Su and Jayaraman Seetharaman and Rong Xiao and Gregory Kornhaber and John F Hunt and Liang Tong and Donald Hilvert and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Bjelic_JMB_13N.pdf},
doi = {10.1016/j.jmb.2013.10.012},
issn = {1089-8638},
year = {2013},
date = {2013-10-01},
journal = {Journal of molecular biology},
volume = {426},
pages = {256-271},
chapter = {256},
abstract = {Designed retroaldolases have utilized a nucleophilic lysine to promote carbon-carbon bond cleavage of β-hydroxy-ketones via a covalent Schiff base intermediate. Previous computational designs have incorporated a water molecule to facilitate formation and breakdown of the carbinolamine intermediate to give the Schiff base and to function as a general acid/base. Here we investigate an alternative active-site design in which the catalytic water molecule was replaced by the side chain of a glutamic acid. Five out of seven designs expressed solubly and exhibited catalytic efficiencies similar to previously designed retroaldolases for the conversion of 4-hydroxy-4-(6-methoxy-2-naphthyl)-2-butanone to 6-methoxy-2-naphthaldehyde and acetone. After one round of site-directed saturation mutagenesis, improved variants of the two best designs, RA114 and RA117, exhibited among the highest kcat (>10(-3)s(-1)) and kcat/KM (11-25M(-1)s(-1)) values observed for retroaldolase designs prior to comprehensive directed evolution. In both cases, the >10(5)-fold rate accelerations that were achieved are within 1-3 orders of magnitude of the rate enhancements reported for the best catalysts for related reactions, including catalytic antibodies (kcat/kuncat=10(6) to 10(8)) and an extensively evolved computational design (kcat/kuncat>10(7)). The catalytic sites, revealed by X-ray structures of optimized versions of the two active designs, are in close agreement with the design models except for the catalytic lysine in RA114. We further improved the variants by computational remodeling of the loops and yeast display selection for reactivity of the catalytic lysine with a diketone probe, obtaining an additional order of magnitude enhancement in activity with both approaches.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Designed retroaldolases have utilized a nucleophilic lysine to promote carbon-carbon bond cleavage of β-hydroxy-ketones via a covalent Schiff base intermediate. Previous computational designs have incorporated a water molecule to facilitate formation and breakdown of the carbinolamine intermediate to give the Schiff base and to function as a general acid/base. Here we investigate an alternative active-site design in which the catalytic water molecule was replaced by the side chain of a glutamic acid. Five out of seven designs expressed solubly and exhibited catalytic efficiencies similar to previously designed retroaldolases for the conversion of 4-hydroxy-4-(6-methoxy-2-naphthyl)-2-butanone to 6-methoxy-2-naphthaldehyde and acetone. After one round of site-directed saturation mutagenesis, improved variants of the two best designs, RA114 and RA117, exhibited among the highest kcat (>10(-3)s(-1)) and kcat/KM (11-25M(-1)s(-1)) values observed for retroaldolase designs prior to comprehensive directed evolution. In both cases, the >10(5)-fold rate accelerations that were achieved are within 1-3 orders of magnitude of the rate enhancements reported for the best catalysts for related reactions, including catalytic antibodies (kcat/kuncat=10(6) to 10(8)) and an extensively evolved computational design (kcat/kuncat>10(7)). The catalytic sites, revealed by X-ray structures of optimized versions of the two active designs, are in close agreement with the design models except for the catalytic lysine in RA114. We further improved the variants by computational remodeling of the loops and yeast display selection for reactivity of the catalytic lysine with a diketone probe, obtaining an additional order of magnitude enhancement in activity with both approaches.
Robert Vernon, Yang Shen, David Baker, Oliver F Lange
Improved chemical shift based fragment selection for CS-Rosetta using Rosetta3 fragment picker. Journal Article
In: Journal of biomolecular NMR, vol. 57, pp. 117-27, 2013, ISSN: 1573-5001.
@article{508,
title = {Improved chemical shift based fragment selection for CS-Rosetta using Rosetta3 fragment picker.},
author = { Robert Vernon and Yang Shen and David Baker and Oliver F Lange},
doi = {10.1007/s10858-013-9772-4},
issn = {1573-5001},
year = {2013},
date = {2013-10-01},
journal = {Journal of biomolecular NMR},
volume = {57},
pages = {117-27},
abstract = {A new fragment picker has been developed for CS-Rosetta that combines beneficial features of the original fragment picker, MFR, used with CS-Rosetta, and the fragment picker, NNMake, that was used for purely sequence based fragment selection in the context of ROSETTA de-novo structure prediction. Additionally, the new fragment picker has reduced sensitivity to outliers and other difficult to match data points rendering the protocol more robust and less likely to introduce bias towards wrong conformations in cases where data is bad, missing or inconclusive. The fragment picker protocol gives significant improvements on 6 of 23 CS-Rosetta targets. An independent benchmark on 39 protein targets, whose NMR data sets were published only after protocol optimization had been finished, also show significantly improved performance for the new fragment picker (van der Schot et al. in J Biomol NMR, 2013).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A new fragment picker has been developed for CS-Rosetta that combines beneficial features of the original fragment picker, MFR, used with CS-Rosetta, and the fragment picker, NNMake, that was used for purely sequence based fragment selection in the context of ROSETTA de-novo structure prediction. Additionally, the new fragment picker has reduced sensitivity to outliers and other difficult to match data points rendering the protocol more robust and less likely to introduce bias towards wrong conformations in cases where data is bad, missing or inconclusive. The fragment picker protocol gives significant improvements on 6 of 23 CS-Rosetta targets. An independent benchmark on 39 protein targets, whose NMR data sets were published only after protocol optimization had been finished, also show significantly improved performance for the new fragment picker (van der Schot et al. in J Biomol NMR, 2013).
Seth Cooper, Firas Khatib, David Baker
Increasing public involvement in structural biology Journal Article
In: Structure (London, England : 1993), vol. 21, pp. 1482-4, 2013, ISSN: 1878-4186.
@article{486,
title = {Increasing public involvement in structural biology},
author = { Seth Cooper and Firas Khatib and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Cooper13L.pdf},
doi = {10.1016/j.str.2013.08.009},
issn = {1878-4186},
year = {2013},
date = {2013-09-01},
journal = {Structure (London, England : 1993)},
volume = {21},
pages = {1482-4},
abstract = {Public participation in scientific research can be a powerful supplement to more-traditional approaches. We~discuss aspects of the public participation project Foldit that may help others interested in starting their own projects.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Public participation in scientific research can be a powerful supplement to more-traditional approaches. We~discuss aspects of the public participation project Foldit that may help others interested in starting their own projects.
Hetunandan Kamisetty, Sergey Ovchinnikov, David Baker
Assessing the utility of coevolution-based residue-residue contact predictions in a sequence- and structure-rich era. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 110, pp. 15674-9, 2013, ISSN: 1091-6490.
@article{498,
title = {Assessing the utility of coevolution-based residue-residue contact predictions in a sequence- and structure-rich era.},
author = { Hetunandan Kamisetty and Sergey Ovchinnikov and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Kamisetty_PNAS_2013.pdf},
doi = {10.1073/pnas.1314045110},
issn = {1091-6490},
year = {2013},
date = {2013-09-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {110},
pages = {15674-9},
abstract = {Recently developed methods have shown considerable promise in predicting residue-residue contacts in protein 3D structures using evolutionary covariance information. However, these methods require large numbers of evolutionarily related sequences to robustly assess the extent of residue covariation, and the larger the protein family, the more likely that contact information is unnecessary because a reasonable model can be built based on the structure of a homolog. Here we describe a method that integrates sequence coevolution and structural context information using a pseudolikelihood approach, allowing more accurate contact predictions from fewer homologous sequences. We rigorously assess the utility of predicted contacts for protein structure prediction using large and representative sequence and structure databases from recent structure prediction experiments. We find that contact predictions are likely to be accurate when the number of aligned sequences (with sequence redundancy reduced to 90%) is greater than five times the length of the protein, and that accurate predictions are likely to be useful for structure modeling if the aligned sequences are more similar to the protein of interest than to the closest homolog of known structure. These conditions are currently met by 422 of the protein families collected in the Pfam database.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recently developed methods have shown considerable promise in predicting residue-residue contacts in protein 3D structures using evolutionary covariance information. However, these methods require large numbers of evolutionarily related sequences to robustly assess the extent of residue covariation, and the larger the protein family, the more likely that contact information is unnecessary because a reasonable model can be built based on the structure of a homolog. Here we describe a method that integrates sequence coevolution and structural context information using a pseudolikelihood approach, allowing more accurate contact predictions from fewer homologous sequences. We rigorously assess the utility of predicted contacts for protein structure prediction using large and representative sequence and structure databases from recent structure prediction experiments. We find that contact predictions are likely to be accurate when the number of aligned sequences (with sequence redundancy reduced to 90%) is greater than five times the length of the protein, and that accurate predictions are likely to be useful for structure modeling if the aligned sequences are more similar to the protein of interest than to the closest homolog of known structure. These conditions are currently met by 422 of the protein families collected in the Pfam database.
Erik Procko, Rickard Hedman, Keith Hamilton, Jayaraman Seetharaman, Sarel J Fleishman, Min Su, James Aramini, Gregory Kornhaber, John F Hunt, Liang Tong, Gaetano T Montelione, David Baker
Computational design of a protein-based enzyme inhibitor. Journal Article
In: Journal of molecular biology, vol. 425, pp. 3563-75, 2013, ISSN: 1089-8638.
@article{511,
title = {Computational design of a protein-based enzyme inhibitor.},
author = { Erik Procko and Rickard Hedman and Keith Hamilton and Jayaraman Seetharaman and Sarel J Fleishman and Min Su and James Aramini and Gregory Kornhaber and John F Hunt and Liang Tong and Gaetano T Montelione and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Procko13.pdf},
doi = {10.1016/j.jmb.2013.06.035},
issn = {1089-8638},
year = {2013},
date = {2013-09-01},
journal = {Journal of molecular biology},
volume = {425},
pages = {3563-75},
abstract = {While there has been considerable progress in designing protein-protein interactions, the design of proteins that bind polar surfaces is an unmet challenge. We describe the computational design of a protein that binds the acidic active site of hen egg lysozyme and inhibits the enzyme. The design process starts with two polar amino acids that fit deep into the enzyme active site, identifies a protein scaffold that supports these residues and is complementary in shape to the lysozyme active-site region, and finally optimizes the surrounding contact surface for high-affinity binding. Following affinity maturation, a protein designed using this method bound lysozyme with low nanomolar affinity, and a combination of NMR studies, crystallography, and knockout mutagenesis confirmed the designed binding surface and orientation. Saturation mutagenesis with selection and deep sequencing demonstrated that specific designed interactions extending well beyond the centrally grafted polar residues are critical for high-affinity binding.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
While there has been considerable progress in designing protein-protein interactions, the design of proteins that bind polar surfaces is an unmet challenge. We describe the computational design of a protein that binds the acidic active site of hen egg lysozyme and inhibits the enzyme. The design process starts with two polar amino acids that fit deep into the enzyme active site, identifies a protein scaffold that supports these residues and is complementary in shape to the lysozyme active-site region, and finally optimizes the surrounding contact surface for high-affinity binding. Following affinity maturation, a protein designed using this method bound lysozyme with low nanomolar affinity, and a combination of NMR studies, crystallography, and knockout mutagenesis confirmed the designed binding surface and orientation. Saturation mutagenesis with selection and deep sequencing demonstrated that specific designed interactions extending well beyond the centrally grafted polar residues are critical for high-affinity binding.
Christine E Tinberg, Sagar D Khare, Jiayi Dou, Lindsey Doyle, Jorgen W Nelson, Alberto Schena, Wojciech Jankowski, Charalampos G Kalodimos, Kai Johnsson, Barry L Stoddard, David Baker
Computational design of ligand-binding proteins with high affinity and selectivity Journal Article
In: Nature, vol. 501, pp. 212-6, 2013, ISSN: 1476-4687.
@article{480,
title = {Computational design of ligand-binding proteins with high affinity and selectivity},
author = { Christine E Tinberg and Sagar D Khare and Jiayi Dou and Lindsey Doyle and Jorgen W Nelson and Alberto Schena and Wojciech Jankowski and Charalampos G Kalodimos and Kai Johnsson and Barry L Stoddard and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Tinberg13K.pdf},
doi = {10.1038/nature12443},
issn = {1476-4687},
year = {2013},
date = {2013-09-01},
journal = {Nature},
volume = {501},
pages = {212-6},
abstract = {The ability to design proteins with high affinity and selectivity for any given small molecule is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition. Attempts to rationally design ligand-binding proteins have met with little success, however, and the computational design of protein-small-molecule interfaces remains an unsolved problem. Current approaches for designing ligand-binding proteins for medical and biotechnological uses rely on raising antibodies against a target antigen in immunized animals and/or performing laboratory-directed evolution of proteins with an existing low affinity for the desired ligand, neither of which allows complete control over the interactions involved in binding. Here we describe a general computational method for designing pre-organized and shape complementary small-molecule-binding sites, and use it to generate protein binders to the steroid digoxigenin (DIG). Of seventeen experimentally characterized designs, two bind DIG; the model of the higher affinity binder has the most energetically favourable and pre-organized interface in the design set. A comprehensive binding-fitness landscape of this design, generated by library selections and deep sequencing, was used to optimize its binding affinity to a picomolar level, and X-ray co-crystal structures of two variants show atomic-level agreement with the corresponding computational models. The optimized binder is selective for DIG over the related steroids digitoxigenin, progesterone and β-oestradiol, and this steroid binding preference can be reprogrammed by manipulation of explicitly designed hydrogen-bonding interactions. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics and diagnostics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ability to design proteins with high affinity and selectivity for any given small molecule is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition. Attempts to rationally design ligand-binding proteins have met with little success, however, and the computational design of protein-small-molecule interfaces remains an unsolved problem. Current approaches for designing ligand-binding proteins for medical and biotechnological uses rely on raising antibodies against a target antigen in immunized animals and/or performing laboratory-directed evolution of proteins with an existing low affinity for the desired ligand, neither of which allows complete control over the interactions involved in binding. Here we describe a general computational method for designing pre-organized and shape complementary small-molecule-binding sites, and use it to generate protein binders to the steroid digoxigenin (DIG). Of seventeen experimentally characterized designs, two bind DIG; the model of the higher affinity binder has the most energetically favourable and pre-organized interface in the design set. A comprehensive binding-fitness landscape of this design, generated by library selections and deep sequencing, was used to optimize its binding affinity to a picomolar level, and X-ray co-crystal structures of two variants show atomic-level agreement with the corresponding computational models. The optimized binder is selective for DIG over the related steroids digitoxigenin, progesterone and β-oestradiol, and this steroid binding preference can be reprogrammed by manipulation of explicitly designed hydrogen-bonding interactions. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics and diagnostics.
Jeremy H Mills, Sagar D Khare, Jill M Bolduc, Farhad Forouhar, Vikram Khipple Mulligan, Scott Lew, Jayaraman Seetharaman, Liang Tong, Barry L Stoddard, David Baker
Computational design of an unnatural amino acid dependent metalloprotein with atomic level accuracy. Journal Article
In: Journal of the American Chemical Society, vol. 135, pp. 13393-9, 2013, ISSN: 1520-5126.
@article{509,
title = {Computational design of an unnatural amino acid dependent metalloprotein with atomic level accuracy.},
author = { Jeremy H Mills and Sagar D Khare and Jill M Bolduc and Farhad Forouhar and Vikram Khipple Mulligan and Scott Lew and Jayaraman Seetharaman and Liang Tong and Barry L Stoddard and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Mills13.pdf},
doi = {10.1021/ja403503m},
issn = {1520-5126},
year = {2013},
date = {2013-09-01},
journal = {Journal of the American Chemical Society},
volume = {135},
pages = {13393-9},
abstract = {Genetically encoded unnatural amino acids could facilitate the design of proteins and enzymes of novel function, but correctly specifying sites of incorporation and the identities and orientations of surrounding residues represents a formidable challenge. Computational design methods have been used to identify optimal locations for functional sites in proteins and design the surrounding residues but have not incorporated unnatural amino acids in this process. We extended the Rosetta design methodology to design metalloproteins in which the amino acid (2,2textquoteright-bipyridin-5yl)alanine (Bpy-Ala) is a primary ligand of a bound metal ion. Following initial results that indicated the importance of buttressing the Bpy-Ala amino acid, we designed a buried metal binding site with octahedral coordination geometry consisting of Bpy-Ala, two protein-based metal ligands, and two metal-bound water molecules. Experimental characterization revealed a Bpy-Ala-mediated metalloprotein with the ability to bind divalent cations including Co(2+), Zn(2+), Fe(2+), and Ni(2+), with a Kd for Zn(2+) of ~40 pM. X-ray crystal structures of the designed protein bound to Co(2+) and Ni(2+) have RMSDs to the design model of 0.9 and 1.0 r A respectively over all atoms in the binding site.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Genetically encoded unnatural amino acids could facilitate the design of proteins and enzymes of novel function, but correctly specifying sites of incorporation and the identities and orientations of surrounding residues represents a formidable challenge. Computational design methods have been used to identify optimal locations for functional sites in proteins and design the surrounding residues but have not incorporated unnatural amino acids in this process. We extended the Rosetta design methodology to design metalloproteins in which the amino acid (2,2textquoteright-bipyridin-5yl)alanine (Bpy-Ala) is a primary ligand of a bound metal ion. Following initial results that indicated the importance of buttressing the Bpy-Ala amino acid, we designed a buried metal binding site with octahedral coordination geometry consisting of Bpy-Ala, two protein-based metal ligands, and two metal-bound water molecules. Experimental characterization revealed a Bpy-Ala-mediated metalloprotein with the ability to bind divalent cations including Co(2+), Zn(2+), Fe(2+), and Ni(2+), with a Kd for Zn(2+) of ~40 pM. X-ray crystal structures of the designed protein bound to Co(2+) and Ni(2+) have RMSDs to the design model of 0.9 and 1.0 r A respectively over all atoms in the binding site.
Gijs van der Schot, Zaiyong Zhang, Robert Vernon, Yang Shen, Wim F Vranken, David Baker, Alexandre M J J Bonvin, Oliver F Lange
Improving 3D structure prediction from chemical shift data. Journal Article
In: Journal of biomolecular NMR, vol. 57, pp. 27-35, 2013, ISSN: 1573-5001.
@article{507,
title = {Improving 3D structure prediction from chemical shift data.},
author = { Gijs van der Schot and Zaiyong Zhang and Robert Vernon and Yang Shen and Wim F Vranken and David Baker and Alexandre M J J Bonvin and Oliver F Lange},
doi = {10.1007/s10858-013-9762-6},
issn = {1573-5001},
year = {2013},
date = {2013-09-01},
journal = {Journal of biomolecular NMR},
volume = {57},
pages = {27-35},
abstract = {We report advances in the calculation of protein structures from chemical shift nuclear magnetic resonance data alone. Our previously developed method, CS-Rosetta, assembles structures from a library of short protein fragments picked from a large library of protein structures using chemical shifts and sequence information. Here we demonstrate that combination of a new and improved fragment picker and the iterative sampling algorithm RASREC yield significant improvements in convergence and accuracy. Moreover, we introduce improved criteria for assessing the accuracy of the models produced by the method. The method was tested on 39 proteins in the 50-100 residue size range and yields reliable structures in 70~% of the cases. All structures that passed the reliability filter were accurate (<2~r A RMSD from the reference).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We report advances in the calculation of protein structures from chemical shift nuclear magnetic resonance data alone. Our previously developed method, CS-Rosetta, assembles structures from a library of short protein fragments picked from a large library of protein structures using chemical shifts and sequence information. Here we demonstrate that combination of a new and improved fragment picker and the iterative sampling algorithm RASREC yield significant improvements in convergence and accuracy. Moreover, we introduce improved criteria for assessing the accuracy of the models produced by the method. The method was tested on 39 proteins in the 50-100 residue size range and yields reliable structures in 70~% of the cases. All structures that passed the reliability filter were accurate (<2~r A RMSD from the reference).
Lars Giger, Sami Caner, Richard Obexer, Peter Kast, David Baker, Nenad Ban, Donald Hilvert
Evolution of a designed retro-aldolase leads to complete active site remodeling. Journal Article
In: Nature chemical biology, vol. 9, pp. 494-8, 2013, ISSN: 1552-4469.
@article{504,
title = {Evolution of a designed retro-aldolase leads to complete active site remodeling.},
author = { Lars Giger and Sami Caner and Richard Obexer and Peter Kast and David Baker and Nenad Ban and Donald Hilvert},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Giger_nchembio_2013.pdf},
doi = {10.1038/nchembio.1276},
issn = {1552-4469},
year = {2013},
date = {2013-08-01},
journal = {Nature chemical biology},
volume = {9},
pages = {494-8},
abstract = {Evolutionary advances are often fueled by unanticipated innovation. Directed evolution of a computationally designed enzyme suggests that pronounced molecular changes can also drive the optimization of primitive protein active sites. The specific activity of an artificial retro-aldolase was boosted >4,400-fold by random mutagenesis and screening, affording catalytic efficiencies approaching those of natural enzymes. However, structural and mechanistic studies reveal that the engineered catalytic apparatus, consisting of a reactive lysine and an ordered water molecule, was unexpectedly abandoned in favor of a new lysine residue in a substrate-binding pocket created during the optimization process. Structures of the initial in silico design, a mechanistically promiscuous intermediate and one of the most evolved variants highlight the importance of loop mobility and supporting functional groups in the emergence of the new catalytic center. Such internal competition between alternative reactive sites may have characterized the early evolution of many natural enzymes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Evolutionary advances are often fueled by unanticipated innovation. Directed evolution of a computationally designed enzyme suggests that pronounced molecular changes can also drive the optimization of primitive protein active sites. The specific activity of an artificial retro-aldolase was boosted >4,400-fold by random mutagenesis and screening, affording catalytic efficiencies approaching those of natural enzymes. However, structural and mechanistic studies reveal that the engineered catalytic apparatus, consisting of a reactive lysine and an ordered water molecule, was unexpectedly abandoned in favor of a new lysine residue in a substrate-binding pocket created during the optimization process. Structures of the initial in silico design, a mechanistically promiscuous intermediate and one of the most evolved variants highlight the importance of loop mobility and supporting functional groups in the emergence of the new catalytic center. Such internal competition between alternative reactive sites may have characterized the early evolution of many natural enzymes.
David E Kim, Frank DiMaio, Ray Yu-Ruei Wang, Yifan Song, David Baker
One contact for every twelve residues allows robust and accurate topology-level protein structure modeling. Journal Article
In: Proteins, 2013, ISSN: 1097-0134.
@article{506,
title = {One contact for every twelve residues allows robust and accurate topology-level protein structure modeling.},
author = { David E Kim and Frank DiMaio and Ray Yu-Ruei Wang and Yifan Song and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Kim_Proteins_2013.pdf},
doi = {10.1002/prot.24374},
issn = {1097-0134},
year = {2013},
date = {2013-07-01},
journal = {Proteins},
abstract = {A number of methods have been described for identifying pairs of contacting residues in protein three-dimensional structures, but it is unclear how many contacts are required for accurate structure modeling. The CASP10 assisted contact experiment provided a blind test of contact guided protein structure modeling. We describe the models generated for these contact guided prediction challenges using the Rosetta structure modeling methodology. For nearly all cases, the submitted models had the correct overall topology, and in some cases, they had near atomic-level accuracy; for example the model of the 384 residue homo-oligomeric tetramer (Tc680o) had only 2.9 r A root-mean-square deviation (RMSD) from the crystal structure. Our results suggest that experimental and bioinformatic methods for obtaining contact information may need to generate only one correct contact for every 12 residues in the protein to allow accurate topology level modeling. Proteins 2013;. textcopyright 2013 Wiley Periodicals, Inc.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A number of methods have been described for identifying pairs of contacting residues in protein three-dimensional structures, but it is unclear how many contacts are required for accurate structure modeling. The CASP10 assisted contact experiment provided a blind test of contact guided protein structure modeling. We describe the models generated for these contact guided prediction challenges using the Rosetta structure modeling methodology. For nearly all cases, the submitted models had the correct overall topology, and in some cases, they had near atomic-level accuracy; for example the model of the 384 residue homo-oligomeric tetramer (Tc680o) had only 2.9 r A root-mean-square deviation (RMSD) from the crystal structure. Our results suggest that experimental and bioinformatic methods for obtaining contact information may need to generate only one correct contact for every 12 residues in the protein to allow accurate topology level modeling. Proteins 2013;. textcopyright 2013 Wiley Periodicals, Inc.
Frank DiMaio, Junjie Zhang, Wah Chiu, David Baker
Cryo-EM model validation using independent map reconstructions Journal Article
In: Protein science : a publication of the Protein Society, vol. 22, pp. 865-8, 2013, ISSN: 1469-896X.
@article{476,
title = {Cryo-EM model validation using independent map reconstructions},
author = { Frank DiMaio and Junjie Zhang and Wah Chiu and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/DiMaio_pro2267_13Q.pdf},
doi = {10.1002/pro.2267},
issn = {1469-896X},
year = {2013},
date = {2013-06-01},
journal = {Protein science : a publication of the Protein Society},
volume = {22},
pages = {865-8},
abstract = {An increasing number of cryo-electron microscopy (cryo-EM) density maps are being generated with suitable resolution to trace the protein backbone and guide sidechain placement. Generating and evaluating atomic models based on such maps would be greatly facilitated by independent validation metrics for assessing the fit of the models to the data. We describe such a metric based on the fit of atomic models with independent test maps from single particle reconstructions not used in model refinement. The metric provides a means to determine the proper balance between the fit to the density and model energy and stereochemistry during refinement, and is likely to be useful in determining values of model building and refinement metaparameters quite generally.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
An increasing number of cryo-electron microscopy (cryo-EM) density maps are being generated with suitable resolution to trace the protein backbone and guide sidechain placement. Generating and evaluating atomic models based on such maps would be greatly facilitated by independent validation metrics for assessing the fit of the models to the data. We describe such a metric based on the fit of atomic models with independent test maps from single particle reconstructions not used in model refinement. The metric provides a means to determine the proper balance between the fit to the density and model energy and stereochemistry during refinement, and is likely to be useful in determining values of model building and refinement metaparameters quite generally.
Gert Kiss, Nihan Celebi-"Olc c"um, Rocco Moretti, David Baker, K N Houk
Computational enzyme design Journal Article
In: Angewandte Chemie (International ed. in English), vol. 52, pp. 5700-25, 2013, ISSN: 1521-3773.
@article{472,
title = {Computational enzyme design},
author = { Gert Kiss and Nihan Celebi-"Olc c"um and Rocco Moretti and David Baker and K N Houk},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Kiss_AngewChemIntEd_2013.pdf},
doi = {10.1002/anie.201204077},
issn = {1521-3773},
year = {2013},
date = {2013-05-01},
journal = {Angewandte Chemie (International ed. in English)},
volume = {52},
pages = {5700-25},
abstract = {Recent developments in computational chemistry and biology have come together in the "inside-out" approach to enzyme engineering. Proteins have been designed to catalyze reactions not previously accelerated in nature. Some of these proteins fold and act as catalysts, but the success rate is still low. The achievements and limitations of the current technology are highlighted and contrasted to other protein engineering techniques. On its own, computational "inside-out" design can lead to the production of catalytically active and selective proteins, but their kinetic performances fall short of natural enzymes. When combined with directed evolution, molecular dynamics simulations, and crowd-sourced structure-prediction approaches, however, computational designs can be significantly improved in terms of binding, turnover, and thermal stability.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent developments in computational chemistry and biology have come together in the "inside-out" approach to enzyme engineering. Proteins have been designed to catalyze reactions not previously accelerated in nature. Some of these proteins fold and act as catalysts, but the success rate is still low. The achievements and limitations of the current technology are highlighted and contrasted to other protein engineering techniques. On its own, computational "inside-out" design can lead to the production of catalytically active and selective proteins, but their kinetic performances fall short of natural enzymes. When combined with directed evolution, molecular dynamics simulations, and crowd-sourced structure-prediction approaches, however, computational designs can be significantly improved in terms of binding, turnover, and thermal stability.
Joseph Jardine, Jean-Philippe Julien, Sergey Menis, Takayuki Ota, Oleksandr Kalyuzhniy, Andrew McGuire, Devin Sok, Po-Ssu Huang, Skye MacPherson, Meaghan Jones, Travis Nieusma, John Mathison, David Baker, Andrew B Ward, Dennis R Burton, Leonidas Stamatatos, David Nemazee, Ian A Wilson, William R Schief
Rational HIV immunogen design to target specific germline B cell receptors Journal Article
In: Science (New York, N.Y.), vol. 340, pp. 711-6, 2013, ISSN: 1095-9203.
@article{467,
title = {Rational HIV immunogen design to target specific germline B cell receptors},
author = { Joseph Jardine and Jean-Philippe Julien and Sergey Menis and Takayuki Ota and Oleksandr Kalyuzhniy and Andrew McGuire and Devin Sok and Po-Ssu Huang and Skye MacPherson and Meaghan Jones and Travis Nieusma and John Mathison and David Baker and Andrew B Ward and Dennis R Burton and Leonidas Stamatatos and David Nemazee and Ian A Wilson and William R Schief},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Jardine_Science_13O.pdf},
doi = {10.1126/science.1234150},
issn = {1095-9203},
year = {2013},
date = {2013-05-01},
journal = {Science (New York, N.Y.)},
volume = {340},
pages = {711-6},
abstract = {Vaccine development to induce broadly neutralizing antibodies (bNAbs) against HIV-1 is a global health priority. Potent VRC01-class bNAbs against the CD4 binding site of HIV gp120 have been isolated from HIV-1-infected individuals; however, such bNAbs have not been induced by vaccination. Wild-type gp120 proteins lack detectable affinity for predicted germline precursors of VRC01-class bNAbs, making them poor immunogens to prime a VRC01-class response. We employed computation-guided, in vitro screening to engineer a germline-targeting gp120 outer domain immunogen that binds to multiple VRC01-class bNAbs and germline precursors, and elucidated germline binding crystallographically. When multimerized on nanoparticles, this immunogen (eOD-GT6) activates germline and mature VRC01-class B cells. Thus, eOD-GT6 nanoparticles have promise as a vaccine prime. In principle, germline-targeting strategies could be applied to other epitopes and pathogens.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Vaccine development to induce broadly neutralizing antibodies (bNAbs) against HIV-1 is a global health priority. Potent VRC01-class bNAbs against the CD4 binding site of HIV gp120 have been isolated from HIV-1-infected individuals; however, such bNAbs have not been induced by vaccination. Wild-type gp120 proteins lack detectable affinity for predicted germline precursors of VRC01-class bNAbs, making them poor immunogens to prime a VRC01-class response. We employed computation-guided, in vitro screening to engineer a germline-targeting gp120 outer domain immunogen that binds to multiple VRC01-class bNAbs and germline precursors, and elucidated germline binding crystallographically. When multimerized on nanoparticles, this immunogen (eOD-GT6) activates germline and mature VRC01-class B cells. Thus, eOD-GT6 nanoparticles have promise as a vaccine prime. In principle, germline-targeting strategies could be applied to other epitopes and pathogens.
Sinisa Bjelic, Lucas G Niv’on, Nihan c Celebi-"Olc c"um, Gert Kiss, Carolyn F Rosewall, Helena M Lovick, Erica L Ingalls, Jasmine Lynn Gallaher, Jayaraman Seetharaman, Scott Lew, Gaetano Thomas Montelione, John Francis Hunt, Forrest Edwin Michael, K N Houk, David Baker
Computational design of enone-binding proteins with catalytic activity for the Morita-Baylis-Hillman reaction Journal Article
In: ACS chemical biology, vol. 8, pp. 749-57, 2013, ISSN: 1554-8937.
@article{475,
title = {Computational design of enone-binding proteins with catalytic activity for the Morita-Baylis-Hillman reaction},
author = { Sinisa Bjelic and Lucas G Niv'on and Nihan c Celebi-"Olc c"um and Gert Kiss and Carolyn F Rosewall and Helena M Lovick and Erica L Ingalls and Jasmine Lynn Gallaher and Jayaraman Seetharaman and Scott Lew and Gaetano Thomas Montelione and John Francis Hunt and Forrest Edwin Michael and K N Houk and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Bjelic_cb3006227_13R.pdf},
doi = {10.1021/cb3006227},
issn = {1554-8937},
year = {2013},
date = {2013-04-01},
journal = {ACS chemical biology},
volume = {8},
pages = {749-57},
abstract = {The Morita-Baylis-Hillman reaction forms a carbon-carbon bond between the α-carbon of a conjugated carbonyl compound and a carbon electrophile. The reaction mechanism involves Michael addition of a nucleophile catalyst at the carbonyl β-carbon, followed by bond formation with the electrophile and catalyst disassociation to release the product. We used Rosetta to design 48 proteins containing active sites predicted to carry out this mechanism, of which two show catalytic activity by mass spectrometry (MS). Substrate labeling measured by MS and site-directed mutagenesis experiments show that the designed active-site residues are responsible for activity, although rate acceleration over background is modest. To characterize the designed proteins, we developed a fluorescence-based screen for intermediate formation in cell lysates, carried out microsecond molecular dynamics simulations, and solved X-ray crystal structures. These data indicate a partially formed active site and suggest several clear avenues for designing more active catalysts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Morita-Baylis-Hillman reaction forms a carbon-carbon bond between the α-carbon of a conjugated carbonyl compound and a carbon electrophile. The reaction mechanism involves Michael addition of a nucleophile catalyst at the carbonyl β-carbon, followed by bond formation with the electrophile and catalyst disassociation to release the product. We used Rosetta to design 48 proteins containing active sites predicted to carry out this mechanism, of which two show catalytic activity by mass spectrometry (MS). Substrate labeling measured by MS and site-directed mutagenesis experiments show that the designed active-site residues are responsible for activity, although rate acceleration over background is modest. To characterize the designed proteins, we developed a fluorescence-based screen for intermediate formation in cell lysates, carried out microsecond molecular dynamics simulations, and solved X-ray crystal structures. These data indicate a partially formed active site and suggest several clear avenues for designing more active catalysts.
Sebastian Geibel, Erik Procko, Scott J Hultgren, David Baker, Gabriel Waksman
Structural and energetic basis of folded-protein transport by the FimD usher Journal Article
In: Nature, vol. 496, pp. 243-6, 2013, ISSN: 1476-4687.
@article{469,
title = {Structural and energetic basis of folded-protein transport by the FimD usher},
author = { Sebastian Geibel and Erik Procko and Scott J Hultgren and David Baker and Gabriel Waksman},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Geibel_nature12007_13S.pdf},
doi = {10.1038/nature12007},
issn = {1476-4687},
year = {2013},
date = {2013-04-01},
journal = {Nature},
volume = {496},
pages = {243-6},
abstract = {Type 1 pili, produced by uropathogenic Escherichia coli, are multisubunit fibres crucial in recognition of and adhesion to host tissues. During pilus biogenesis, subunits are recruited to an outer membrane assembly platform, the FimD usher, which catalyses their polymerization and mediates pilus secretion. The recent determination of the crystal structure of an initiation complex provided insight into the initiation step of pilus biogenesis resulting in pore activation, but very little is known about the elongation steps that follow. Here, to address this question, we determine the structure of an elongation complex in which the tip complex assembly composed of FimC, FimF, FimG and FimH passes through FimD. This structure demonstrates the conformational changes required to prevent backsliding of the nascent pilus through the FimD pore and also reveals unexpected properties of the usher pore. We show that the circular binding interface between the pore lumen and the folded substrate participates in transport by defining a low-energy pathway along which the nascent pilus polymer is guided during secretion.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Type 1 pili, produced by uropathogenic Escherichia coli, are multisubunit fibres crucial in recognition of and adhesion to host tissues. During pilus biogenesis, subunits are recruited to an outer membrane assembly platform, the FimD usher, which catalyses their polymerization and mediates pilus secretion. The recent determination of the crystal structure of an initiation complex provided insight into the initiation step of pilus biogenesis resulting in pore activation, but very little is known about the elongation steps that follow. Here, to address this question, we determine the structure of an elongation complex in which the tip complex assembly composed of FimC, FimF, FimG and FimH passes through FimD. This structure demonstrates the conformational changes required to prevent backsliding of the nascent pilus through the FimD pore and also reveals unexpected properties of the usher pore. We show that the circular binding interface between the pore lumen and the folded substrate participates in transport by defining a low-energy pathway along which the nascent pilus polymer is guided during secretion.
Julien R C Bergeron, Liam J Worrall, Nikolaos G Sgourakis, Frank DiMaio, Richard A Pfuetzner, Heather B Felise, Marija Vuckovic, Angel C Yu, Samuel I Miller, David Baker, Natalie C J Strynadka
A Refined Model of the Prototypical Salmonella SPI-1 T3SS Basal Body Reveals the Molecular Basis for Its Assembly Journal Article
In: PLoS pathogens, vol. 9, pp. e1003307, 2013, ISSN: 1553-7374.
@article{468,
title = {A Refined Model of the Prototypical Salmonella SPI-1 T3SS Basal Body Reveals the Molecular Basis for Its Assembly},
author = { Julien R C Bergeron and Liam J Worrall and Nikolaos G Sgourakis and Frank DiMaio and Richard A Pfuetzner and Heather B Felise and Marija Vuckovic and Angel C Yu and Samuel I Miller and David Baker and Natalie C J Strynadka},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Bergeron_ppat1003307_13T.pdf},
doi = {10.1371/journal.ppat.1003307},
issn = {1553-7374},
year = {2013},
date = {2013-04-01},
journal = {PLoS pathogens},
volume = {9},
pages = {e1003307},
abstract = {The T3SS injectisome is a syringe-shaped macromolecular assembly found in pathogenic Gram-negative bacteria that allows for the direct delivery of virulence effectors into host cells. It is composed of a "basal body", a lock-nut structure spanning both bacterial membranes, and a "needle" that protrudes away from the bacterial surface. A hollow channel spans throughout the apparatus, permitting the translocation of effector proteins from the bacterial cytosol to the host plasma membrane. The basal body is composed largely of three membrane-embedded proteins that form oligomerized concentric rings. Here, we report the crystal structures of three domains of the prototypical Salmonella SPI-1 basal body, and use a new approach incorporating symmetric flexible backbone docking and EM data to produce a model for their oligomeric assembly. The obtained models, validated by biochemical and in vivo assays, reveal the molecular details of the interactions driving basal body assembly, and notably demonstrate a conserved oligomerization mechanism.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The T3SS injectisome is a syringe-shaped macromolecular assembly found in pathogenic Gram-negative bacteria that allows for the direct delivery of virulence effectors into host cells. It is composed of a "basal body", a lock-nut structure spanning both bacterial membranes, and a "needle" that protrudes away from the bacterial surface. A hollow channel spans throughout the apparatus, permitting the translocation of effector proteins from the bacterial cytosol to the host plasma membrane. The basal body is composed largely of three membrane-embedded proteins that form oligomerized concentric rings. Here, we report the crystal structures of three domains of the prototypical Salmonella SPI-1 basal body, and use a new approach incorporating symmetric flexible backbone docking and EM data to produce a model for their oligomeric assembly. The obtained models, validated by biochemical and in vivo assays, reveal the molecular details of the interactions driving basal body assembly, and notably demonstrate a conserved oligomerization mechanism.
Jean-Philippe Demers, Nikolaos G Sgourakis, Rashmi Gupta, Antoine Loquet, Karin Giller, Dietmar Riedel, Britta Laube, Michael Kolbe, David Baker, Stefan Becker, Adam Lange
The common structural architecture of Shigella flexneri and Salmonella typhimurium type three secretion needles Journal Article
In: PLoS pathogens, vol. 9, pp. e1003245, 2013, ISSN: 1553-7374.
@article{471,
title = {The common structural architecture of Shigella flexneri and Salmonella typhimurium type three secretion needles},
author = { Jean-Philippe Demers and Nikolaos G Sgourakis and Rashmi Gupta and Antoine Loquet and Karin Giller and Dietmar Riedel and Britta Laube and Michael Kolbe and David Baker and Stefan Becker and Adam Lange},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Demers_PLosPathogen_13P.pdf},
doi = {10.1371/journal.ppat.1003245},
issn = {1553-7374},
year = {2013},
date = {2013-03-01},
journal = {PLoS pathogens},
volume = {9},
pages = {e1003245},
abstract = {The Type Three Secretion System (T3SS), or injectisome, is a macromolecular infection machinery present in many pathogenic Gram-negative bacteria. It consists of a basal body, anchored in both bacterial membranes, and a hollow needle through which effector proteins are delivered into the target host cell. Two different architectures of the T3SS needle have been previously proposed. First, an atomic model of the Salmonella typhimurium needle was generated from solid-state NMR data. The needle subunit protein, PrgI, comprises a rigid-extended N-terminal segment and a helix-loop-helix motif with the N-terminus located on the outside face of the needle. Second, a model of the Shigella flexneri needle was generated from a high-resolution 7.7-r A cryo-electron microscopy density map. The subunit protein, MxiH, contains an N-terminal α-helix, a loop, another α-helix, a 14-residue-long β-hairpin (Q51-Q64) and a C-terminal α-helix, with the N-terminus facing inward to the lumen of the needle. In the current study, we carried out solid-state NMR measurements of wild-type Shigella flexneri needles polymerized in vitro and identified the following secondary structure elements for MxiH: a rigid-extended N-terminal segment (S2-T11), an α-helix (L12-A38), a loop (E39-P44) and a C-terminal α-helix (Q45-R83). Using immunogold labeling in vitro and in vivo on functional needles, we located the N-terminus of MxiH subunits on the exterior of the assembly, consistent with evolutionary sequence conservation patterns and mutagenesis data. We generated a homology model of Shigella flexneri needles compatible with both experimental data: the MxiH solid-state NMR chemical shifts and the state-of-the-art cryoEM density map. These results corroborate the solid-state NMR structure previously solved for Salmonella typhimurium PrgI needles and establish that Shigella flexneri and Salmonella typhimurium subunit proteins adopt a conserved structure and orientation in their assembled state. Our study reveals a common structural architecture of T3SS needles, essential to understand T3SS-mediated infection and develop treatments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Type Three Secretion System (T3SS), or injectisome, is a macromolecular infection machinery present in many pathogenic Gram-negative bacteria. It consists of a basal body, anchored in both bacterial membranes, and a hollow needle through which effector proteins are delivered into the target host cell. Two different architectures of the T3SS needle have been previously proposed. First, an atomic model of the Salmonella typhimurium needle was generated from solid-state NMR data. The needle subunit protein, PrgI, comprises a rigid-extended N-terminal segment and a helix-loop-helix motif with the N-terminus located on the outside face of the needle. Second, a model of the Shigella flexneri needle was generated from a high-resolution 7.7-r A cryo-electron microscopy density map. The subunit protein, MxiH, contains an N-terminal α-helix, a loop, another α-helix, a 14-residue-long β-hairpin (Q51-Q64) and a C-terminal α-helix, with the N-terminus facing inward to the lumen of the needle. In the current study, we carried out solid-state NMR measurements of wild-type Shigella flexneri needles polymerized in vitro and identified the following secondary structure elements for MxiH: a rigid-extended N-terminal segment (S2-T11), an α-helix (L12-A38), a loop (E39-P44) and a C-terminal α-helix (Q45-R83). Using immunogold labeling in vitro and in vivo on functional needles, we located the N-terminus of MxiH subunits on the exterior of the assembly, consistent with evolutionary sequence conservation patterns and mutagenesis data. We generated a homology model of Shigella flexneri needles compatible with both experimental data: the MxiH solid-state NMR chemical shifts and the state-of-the-art cryoEM density map. These results corroborate the solid-state NMR structure previously solved for Salmonella typhimurium PrgI needles and establish that Shigella flexneri and Salmonella typhimurium subunit proteins adopt a conserved structure and orientation in their assembled state. Our study reveals a common structural architecture of T3SS needles, essential to understand T3SS-mediated infection and develop treatments.
Matthew Harger, Lei Zheng, Austin Moon, Casey Ager, Ju Hye An, Chris Choe, Yi-Ling Lai, Benjamin Mo, David Zong, Matthew D Smith, Robert G Egbert, Jeremy H Mills, David Baker, Ingrid Swanson Pultz, Justin B Siegel
Expanding the product profile of a microbial alkane biosynthetic pathway. Journal Article
In: ACS synthetic biology, vol. 2, pp. 59-62, 2013, ISSN: 2161-5063.
@article{503,
title = {Expanding the product profile of a microbial alkane biosynthetic pathway.},
author = { Matthew Harger and Lei Zheng and Austin Moon and Casey Ager and Ju Hye An and Chris Choe and Yi-Ling Lai and Benjamin Mo and David Zong and Matthew D Smith and Robert G Egbert and Jeremy H Mills and David Baker and Ingrid Swanson Pultz and Justin B Siegel},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Harger_ACSSynthBiol_2013.pdf},
doi = {10.1021/sb300061x},
issn = {2161-5063},
year = {2013},
date = {2013-01-01},
journal = {ACS synthetic biology},
volume = {2},
pages = {59-62},
abstract = {Microbially produced alkanes are a new class of biofuels that closely match the chemical composition of petroleum-based fuels. Alkanes can be generated from the fatty acid biosynthetic pathway by the reduction of acyl-ACPs followed by decarbonylation of the resulting aldehydes. A current limitation of this pathway is the restricted product profile, which consists of n-alkanes of 13, 15, and 17 carbons in length. To expand the product profile, we incorporated a new part, FabH2 from Bacillus subtilis , an enzyme known to have a broader specificity profile for fatty acid initiation than the native FabH of Escherichia coli . When provided with the appropriate substrate, the addition of FabH2 resulted in an altered alkane product profile in which significant levels of n-alkanes of 14 and 16 carbons in length are produced. The production of even chain length alkanes represents initial steps toward the expansion of this recently discovered microbial alkane production pathway to synthesize complex fuels. This work was conceived and performed as part of the 2011 University of Washington international Genetically Engineered Machines (iGEM) project.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Microbially produced alkanes are a new class of biofuels that closely match the chemical composition of petroleum-based fuels. Alkanes can be generated from the fatty acid biosynthetic pathway by the reduction of acyl-ACPs followed by decarbonylation of the resulting aldehydes. A current limitation of this pathway is the restricted product profile, which consists of n-alkanes of 13, 15, and 17 carbons in length. To expand the product profile, we incorporated a new part, FabH2 from Bacillus subtilis , an enzyme known to have a broader specificity profile for fatty acid initiation than the native FabH of Escherichia coli . When provided with the appropriate substrate, the addition of FabH2 resulted in an altered alkane product profile in which significant levels of n-alkanes of 14 and 16 carbons in length are produced. The production of even chain length alkanes represents initial steps toward the expansion of this recently discovered microbial alkane production pathway to synthesize complex fuels. This work was conceived and performed as part of the 2011 University of Washington international Genetically Engineered Machines (iGEM) project.
Timothy A Whitehead, David Baker, Sarel J Fleishman
Computational design of novel protein binders and experimental affinity maturation Journal Article
In: Methods in enzymology, vol. 523, pp. 1-19, 2013, ISSN: 1557-7988.
@article{474,
title = {Computational design of novel protein binders and experimental affinity maturation},
author = { Timothy A Whitehead and David Baker and Sarel J Fleishman},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Whitehead_MethEnzymology_13V.pdf},
doi = {10.1016/B978-0-12-394292-0.00001-1},
issn = {1557-7988},
year = {2013},
date = {2013-00-01},
journal = {Methods in enzymology},
volume = {523},
pages = {1-19},
abstract = {Computational design of novel protein binders has recently emerged as a useful technique to study biomolecular recognition and generate molecules for use in biotechnology, research, and biomedicine. Current limitations in computational design methodology have led to the adoption of high-throughput screening and affinity maturation techniques to diagnose modeling inaccuracies and generate high activity binders. Here, we scrutinize this combination of computational and experimental aspects and propose areas for future methodological improvements.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational design of novel protein binders has recently emerged as a useful technique to study biomolecular recognition and generate molecules for use in biotechnology, research, and biomedicine. Current limitations in computational design methodology have led to the adoption of high-throughput screening and affinity maturation techniques to diagnose modeling inaccuracies and generate high activity binders. Here, we scrutinize this combination of computational and experimental aspects and propose areas for future methodological improvements.
Lucas Gregorio Niv’on, Rocco Moretti, David Baker
A Pareto-optimal refinement method for protein design scaffolds Journal Article
In: PloS one, vol. 8, pp. e59004, 2013, ISSN: 1932-6203.
@article{470,
title = {A Pareto-optimal refinement method for protein design scaffolds},
author = { Lucas Gregorio Niv'on and Rocco Moretti and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Nivon_pone0059004_13U.pdf},
doi = {10.1371/journal.pone.0059004},
issn = {1932-6203},
year = {2013},
date = {2013-00-01},
journal = {PloS one},
volume = {8},
pages = {e59004},
abstract = {Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or "scaffolds", are searched to find regions where functional sites (an enzyme active site, ligand binding pocket, protein-protein interaction region, etc.) can be placed, and the identities of the surrounding amino acids are optimized to satisfy functional constraints. Input native protein structures almost invariably have regions that score very poorly with the design force field, and any design based on these unmodified structures may result in mutations away from the native sequence solely as a result of the energetic strain. Because the input structure is already a stable protein, it is desirable to keep the total number of mutations to a minimum and to avoid mutations resulting from poorly-scoring input structures. Here we describe a protocol using cycles of minimization with combined backbone/sidechain restraints that is Pareto-optimal with respect to RMSD to the native structure and energetic strain reduction. The protocol should be broadly useful in the preparation of scaffold libraries for functional site design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or "scaffolds", are searched to find regions where functional sites (an enzyme active site, ligand binding pocket, protein-protein interaction region, etc.) can be placed, and the identities of the surrounding amino acids are optimized to satisfy functional constraints. Input native protein structures almost invariably have regions that score very poorly with the design force field, and any design based on these unmodified structures may result in mutations away from the native sequence solely as a result of the energetic strain. Because the input structure is already a stable protein, it is desirable to keep the total number of mutations to a minimum and to avoid mutations resulting from poorly-scoring input structures. Here we describe a protocol using cycles of minimization with combined backbone/sidechain restraints that is Pareto-optimal with respect to RMSD to the native structure and energetic strain reduction. The protocol should be broadly useful in the preparation of scaffold libraries for functional site design.
MA Molski, JL Goodman, FC Chou, D Baker, R Das, A Schepartz
Remodeling a beta-peptide bundle Journal Article
In: Chemical Science, vol. 4, pp. 319-324, 2013, ISSN: 2041-6520.
@article{605,
title = {Remodeling a beta-peptide bundle},
author = { MA Molski and JL Goodman and FC Chou and D Baker and R Das and A Schepartz},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/remodelingabeta_Baker2013.pdf},
doi = {10.1039/c2sc21117c},
issn = {2041-6520},
year = {2013},
date = {2013-00-01},
journal = {Chemical Science},
volume = {4},
pages = {319-324},
abstract = {Natural biopolymers fold with fidelity, burying diverse side chains into well-packed cores and protecting their backbones from solvent. Certain beta-peptide oligomers assemble into bundles of defined octameric stoichiometry that resemble natural proteins in many respects. These beta-peptide bundles are thermostable, fold cooperatively, exchange interior amide N-H protons slowly, exclude hydrophobic dyes, and can be characterized at high resolution using X-ray crystallography - just like many proteins found in nature. But unlike natural proteins, all octameric beta-peptide bundles contain a sequence-uniform hydrophobic core composed of 32 leucine side chains. Here we apply rational design principles, including the Rosetta computational design methodology, to introduce sequence diversity into the bundle core while retaining the characteristic beta-peptide bundle fold. Using circular dichroism spectroscopy and analytical ultracentrifugation, we confirmed the prediction that an octameric bundle still assembles upon a major remodelling of its core: the mutation of sixteen core beta-homo-leucine side chains into sixteen beta-homo-phenylalanine side chains. Nevertheless, the bundle containing a partially beta-homo-phenylalanine core poorly protects interior amide protons from exchange, suggesting molten-globule-like properties. We further improve stability by the incorporation of eight beta-homo-pentafluorophenyalanine side chains, giving an assembly with amide protection factors comparable to prior well-structured bundles. By demonstrating that their cores tolerate significant sequence variation, the beta-peptide bundles reported here represent a starting point for the "bottom-up" construction of beta-peptide assemblies possessing both structure and sophisticated function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Natural biopolymers fold with fidelity, burying diverse side chains into well-packed cores and protecting their backbones from solvent. Certain beta-peptide oligomers assemble into bundles of defined octameric stoichiometry that resemble natural proteins in many respects. These beta-peptide bundles are thermostable, fold cooperatively, exchange interior amide N-H protons slowly, exclude hydrophobic dyes, and can be characterized at high resolution using X-ray crystallography – just like many proteins found in nature. But unlike natural proteins, all octameric beta-peptide bundles contain a sequence-uniform hydrophobic core composed of 32 leucine side chains. Here we apply rational design principles, including the Rosetta computational design methodology, to introduce sequence diversity into the bundle core while retaining the characteristic beta-peptide bundle fold. Using circular dichroism spectroscopy and analytical ultracentrifugation, we confirmed the prediction that an octameric bundle still assembles upon a major remodelling of its core: the mutation of sixteen core beta-homo-leucine side chains into sixteen beta-homo-phenylalanine side chains. Nevertheless, the bundle containing a partially beta-homo-phenylalanine core poorly protects interior amide protons from exchange, suggesting molten-globule-like properties. We further improve stability by the incorporation of eight beta-homo-pentafluorophenyalanine side chains, giving an assembly with amide protection factors comparable to prior well-structured bundles. By demonstrating that their cores tolerate significant sequence variation, the beta-peptide bundles reported here represent a starting point for the "bottom-up" construction of beta-peptide assemblies possessing both structure and sophisticated function.
Andrew Leaver-Fay, Matthew J OtextquoterightMeara, Mike Tyka, Ron Jacak, Yifan Song, Elizabeth H Kellogg, James Thompson, Ian W Davis, Roland A Pache, Sergey Lyskov, Jeffrey J Gray, Tanja Kortemme, Jane S Richardson, James J Havranek, Jack Snoeyink, David Baker, Brian Kuhlman
Scientific benchmarks for guiding macromolecular energy function improvement. Journal Article
In: Methods in enzymology, vol. 523, pp. 109-43, 2013, ISSN: 1557-7988.
@article{473,
title = {Scientific benchmarks for guiding macromolecular energy function improvement.},
author = { Andrew Leaver-Fay and Matthew J OtextquoterightMeara and Mike Tyka and Ron Jacak and Yifan Song and Elizabeth H Kellogg and James Thompson and Ian W Davis and Roland A Pache and Sergey Lyskov and Jeffrey J Gray and Tanja Kortemme and Jane S Richardson and James J Havranek and Jack Snoeyink and David Baker and Brian Kuhlman},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/LeaverFay_MethodsEnzymol_2013.pdf},
doi = {10.1016/B978-0-12-394292-0.00006-0},
issn = {1557-7988},
year = {2013},
date = {2013-00-01},
journal = {Methods in enzymology},
volume = {523},
pages = {109-43},
abstract = {Accurate energy functions are critical to macromolecular modeling and design. We describe new tools for identifying inaccuracies in energy functions and guiding their improvement, and illustrate the application of these tools to the improvement of the Rosetta energy function. The feature analysis tool identifies discrepancies between structures deposited in the PDB and low-energy structures generated by Rosetta; these likely arise from inaccuracies in the energy function. The optE tool optimizes the weights on the different components of the energy function by maximizing the recapitulation of a wide range of experimental observations. We use the tools to examine three proposed modifications to the Rosetta energy function: improving the unfolded state energy model (reference energies), using bicubic spline interpolation to generate knowledge-based torisonal potentials, and incorporating the recently developed Dunbrack 2010 rotamer library (Shapovalov & Dunbrack, 2011).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Accurate energy functions are critical to macromolecular modeling and design. We describe new tools for identifying inaccuracies in energy functions and guiding their improvement, and illustrate the application of these tools to the improvement of the Rosetta energy function. The feature analysis tool identifies discrepancies between structures deposited in the PDB and low-energy structures generated by Rosetta; these likely arise from inaccuracies in the energy function. The optE tool optimizes the weights on the different components of the energy function by maximizing the recapitulation of a wide range of experimental observations. We use the tools to examine three proposed modifications to the Rosetta energy function: improving the unfolded state energy model (reference energies), using bicubic spline interpolation to generate knowledge-based torisonal potentials, and incorporating the recently developed Dunbrack 2010 rotamer library (Shapovalov & Dunbrack, 2011).
2012
Michael D Tyka, Kenneth Jung, David Baker
Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers. Journal Article
In: Journal of computational chemistry, vol. 33, pp. 2483-91, 2012, ISSN: 1096-987X.
@article{453,
title = {Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers.},
author = { Michael D Tyka and Kenneth Jung and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Tyka_JComputChem_2012.pdf},
doi = {10.1002/jcc.23069},
issn = {1096-987X},
year = {2012},
date = {2012-12-01},
journal = {Journal of computational chemistry},
volume = {33},
pages = {2483-91},
abstract = {All-atom sampling is a critical and compute-intensive end stage to protein structural modeling. Because of the vast size and extreme ruggedness of conformational space, even close to the native structure, the high-resolution sampling problem is almost as difficult as predicting the rough fold of a protein. Here, we present a combination of new algorithms that considerably speed up the exploration of very rugged conformational landscapes and are capable of finding heretofore hidden low-energy states. The algorithm is based on a hierarchical workflow and can be parallelized on supercomputers with up to 128,000 compute cores with near perfect efficiency. Such scaling behavior is notable, as with Mooretextquoterights law continuing only in the number of cores per chip, parallelizability is a critical property of new algorithms. Using the enhanced sampling power, we have uncovered previously invisible deficiencies in the Rosetta force field and created an extensive decoy training set for optimizing and testing force fields. textcopyright 2012 Wiley Periodicals, Inc.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
All-atom sampling is a critical and compute-intensive end stage to protein structural modeling. Because of the vast size and extreme ruggedness of conformational space, even close to the native structure, the high-resolution sampling problem is almost as difficult as predicting the rough fold of a protein. Here, we present a combination of new algorithms that considerably speed up the exploration of very rugged conformational landscapes and are capable of finding heretofore hidden low-energy states. The algorithm is based on a hierarchical workflow and can be parallelized on supercomputers with up to 128,000 compute cores with near perfect efficiency. Such scaling behavior is notable, as with Mooretextquoterights law continuing only in the number of cores per chip, parallelizability is a critical property of new algorithms. Using the enhanced sampling power, we have uncovered previously invisible deficiencies in the Rosetta force field and created an extensive decoy training set for optimizing and testing force fields. textcopyright 2012 Wiley Periodicals, Inc.
Sydney R Gordon, Elizabeth J Stanley, Sarah Wolf, Angus Toland, Sean J Wu, Daniel Hadidi, Jeremy H Mills, David Baker, Ingrid Swanson Pultz, Justin B Siegel
Computational Design of an α-gliadin Peptidase Journal Article
In: Journal of the American Chemical Society, vol. 134, pp. 20513-20, 2012, ISSN: 1520-5126.
@article{479,
title = {Computational Design of an α-gliadin Peptidase},
author = { Sydney R Gordon and Elizabeth J Stanley and Sarah Wolf and Angus Toland and Sean J Wu and Daniel Hadidi and Jeremy H Mills and David Baker and Ingrid Swanson Pultz and Justin B Siegel},
url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Gordon12E.pdf
http://www.ncbi.nlm.nih.gov/pubmed/23153249},
doi = {10.1021/ja3094795},
issn = {1520-5126},
year = {2012},
date = {2012-12-01},
journal = {Journal of the American Chemical Society},
volume = {134},
pages = {20513-20},
abstract = {The ability to rationally modify enzymes to perform novel chemical transformations is essential for the rapid production of next-generation protein therapeutics. Here we describe the use of chemical principles to identify a naturally occurring acid-active peptidase, and the subsequent use of computational protein design tools to reengineer its specificity toward immunogenic elements found in gluten that are the proposed cause of celiac disease. The engineered enzyme exhibits a k(cat)/K(M) of 568 M(-1) s(-1), representing a 116-fold greater proteolytic activity for a model gluten tetrapeptide than the native template enzyme, as well as an over 800-fold switch in substrate specificity toward immunogenic portions of gluten peptides. The computationally engineered enzyme is resistant to proteolysis by digestive proteases and degrades over 95% of an immunogenic peptide implicated in celiac disease in under an hour. Thus, through identification of a natural enzyme with the pre-existing qualities relevant to an ultimate goal and redefinition of its substrate specificity using computational modeling, we were able to generate an enzyme with potential as a therapeutic for celiac disease.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ability to rationally modify enzymes to perform novel chemical transformations is essential for the rapid production of next-generation protein therapeutics. Here we describe the use of chemical principles to identify a naturally occurring acid-active peptidase, and the subsequent use of computational protein design tools to reengineer its specificity toward immunogenic elements found in gluten that are the proposed cause of celiac disease. The engineered enzyme exhibits a k(cat)/K(M) of 568 M(-1) s(-1), representing a 116-fold greater proteolytic activity for a model gluten tetrapeptide than the native template enzyme, as well as an over 800-fold switch in substrate specificity toward immunogenic portions of gluten peptides. The computationally engineered enzyme is resistant to proteolysis by digestive proteases and degrades over 95% of an immunogenic peptide implicated in celiac disease in under an hour. Thus, through identification of a natural enzyme with the pre-existing qualities relevant to an ultimate goal and redefinition of its substrate specificity using computational modeling, we were able to generate an enzyme with potential as a therapeutic for celiac disease.
Nobuyasu Koga, Rie Tatsumi-Koga, Gaohua Liu, Rong Xiao, Thomas B Acton, Gaetano T Montelione, David Baker
Principles for designing ideal protein structures. Journal Article
In: Nature, vol. 491, pp. 222-7, 2012, ISSN: 1476-4687.
@article{465,
title = {Principles for designing ideal protein structures.},
author = { Nobuyasu Koga and Rie Tatsumi-Koga and Gaohua Liu and Rong Xiao and Thomas B Acton and Gaetano T Montelione and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/nature11600.pdf},
doi = {10.1038/nature11600},
issn = {1476-4687},
year = {2012},
date = {2012-11-01},
journal = {Nature},
volume = {491},
pages = {222-7},
abstract = {Unlike random heteropolymers, natural proteins fold into unique ordered structures. Understanding how these are encoded in amino-acid sequences is complicated by energetically unfavourable non-ideal features--for example kinked α-helices, bulged β-strands, strained loops and buried polar groups--that arise in proteins from evolutionary selection for biological function or from neutral drift. Here we describe an approach to designing ideal protein structures stabilized by completely consistent local and non-local interactions. The approach is based on a set of rules relating secondary structure patterns to protein tertiary motifs, which make possible the design of funnel-shaped protein folding energy landscapes leading into the target folded state. Guided by these rules, we designed sequences predicted to fold into ideal protein structures consisting of α-helices, β-strands and minimal loops. Designs for five different topologies were found to be monomeric and very stable and to adopt structures in solution nearly identical to the computational models. These results illuminate how the folding funnels of natural proteins arise and provide the foundation for engineering a new generation of functional proteins free from natural evolution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Unlike random heteropolymers, natural proteins fold into unique ordered structures. Understanding how these are encoded in amino-acid sequences is complicated by energetically unfavourable non-ideal features–for example kinked α-helices, bulged β-strands, strained loops and buried polar groups–that arise in proteins from evolutionary selection for biological function or from neutral drift. Here we describe an approach to designing ideal protein structures stabilized by completely consistent local and non-local interactions. The approach is based on a set of rules relating secondary structure patterns to protein tertiary motifs, which make possible the design of funnel-shaped protein folding energy landscapes leading into the target folded state. Guided by these rules, we designed sequences predicted to fold into ideal protein structures consisting of α-helices, β-strands and minimal loops. Designs for five different topologies were found to be monomeric and very stable and to adopt structures in solution nearly identical to the computational models. These results illuminate how the folding funnels of natural proteins arise and provide the foundation for engineering a new generation of functional proteins free from natural evolution.
Florian Richter, Rebecca Blomberg, Sagar D Khare, Gert Kiss, Alexandre P Kuzin, Adam J T Smith, Jasmine Gallaher, Zbigniew Pianowski, Roger C Helgeson, Alexej Grjasnow, Rong Xiao, Jayaraman Seetharaman, Min Su, Sergey Vorobiev, Scott Lew, Farhad Forouhar, Gregory J Kornhaber, John F Hunt, Gaetano T Montelione, Liang Tong, K N Houk, Donald Hilvert, David Baker
Computational design of catalytic dyads and oxyanion holes for ester hydrolysis. Journal Article
In: Journal of the American Chemical Society, vol. 134, pp. 16197-206, 2012, ISSN: 1520-5126.
@article{452,
title = {Computational design of catalytic dyads and oxyanion holes for ester hydrolysis.},
author = { Florian Richter and Rebecca Blomberg and Sagar D Khare and Gert Kiss and Alexandre P Kuzin and Adam J T Smith and Jasmine Gallaher and Zbigniew Pianowski and Roger C Helgeson and Alexej Grjasnow and Rong Xiao and Jayaraman Seetharaman and Min Su and Sergey Vorobiev and Scott Lew and Farhad Forouhar and Gregory J Kornhaber and John F Hunt and Gaetano T Montelione and Liang Tong and K N Houk and Donald Hilvert and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Richter_JACS_2012.pdf},
doi = {10.1021/ja3037367},
issn = {1520-5126},
year = {2012},
date = {2012-10-01},
journal = {Journal of the American Chemical Society},
volume = {134},
pages = {16197-206},
abstract = {Nucleophilic catalysis is a general strategy for accelerating ester and amide hydrolysis. In natural active sites, nucleophilic elements such as catalytic dyads and triads are usually paired with oxyanion holes for substrate activation, but it is difficult to parse out the independent contributions of these elements or to understand how they emerged in the course of evolution. Here we explore the minimal requirements for esterase activity by computationally designing artificial catalysts using catalytic dyads and oxyanion holes. We found much higher success rates using designed oxyanion holes formed by backbone NH groups rather than by side chains or bridging water molecules and obtained four active designs in different scaffolds by combining this motif with a Cys-His dyad. Following active site optimization, the most active of the variants exhibited a catalytic efficiency (k(cat)/K(M)) of 400 M(-1) s(-1) for the cleavage of a p-nitrophenyl ester. Kinetic experiments indicate that the active site cysteines are rapidly acylated as programmed by design, but the subsequent slow hydrolysis of the acyl-enzyme intermediate limits overall catalytic efficiency. Moreover, the Cys-His dyads are not properly formed in crystal structures of the designed enzymes. These results highlight the challenges that computational design must overcome to achieve high levels of activity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Nucleophilic catalysis is a general strategy for accelerating ester and amide hydrolysis. In natural active sites, nucleophilic elements such as catalytic dyads and triads are usually paired with oxyanion holes for substrate activation, but it is difficult to parse out the independent contributions of these elements or to understand how they emerged in the course of evolution. Here we explore the minimal requirements for esterase activity by computationally designing artificial catalysts using catalytic dyads and oxyanion holes. We found much higher success rates using designed oxyanion holes formed by backbone NH groups rather than by side chains or bridging water molecules and obtained four active designs in different scaffolds by combining this motif with a Cys-His dyad. Following active site optimization, the most active of the variants exhibited a catalytic efficiency (k(cat)/K(M)) of 400 M(-1) s(-1) for the cleavage of a p-nitrophenyl ester. Kinetic experiments indicate that the active site cysteines are rapidly acylated as programmed by design, but the subsequent slow hydrolysis of the acyl-enzyme intermediate limits overall catalytic efficiency. Moreover, the Cys-His dyads are not properly formed in crystal structures of the designed enzymes. These results highlight the challenges that computational design must overcome to achieve high levels of activity.
Elizabeth H Kellogg, Oliver F Lange, David Baker
Evaluation and optimization of discrete state models of protein folding. Journal Article
In: The journal of physical chemistry. B, vol. 116, pp. 11405-13, 2012, ISSN: 1520-5207.
@article{477,
title = {Evaluation and optimization of discrete state models of protein folding.},
author = { Elizabeth H Kellogg and Oliver F Lange and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Kellogg_PhysChemB_2012.pdf},
issn = {1520-5207},
year = {2012},
date = {2012-09-01},
journal = {The journal of physical chemistry. B},
volume = {116},
pages = {11405-13},
abstract = {The space accessed by a folding macromolecule is vast, and how to best project computer simulations of protein folding trajectories into an interpretable sequence of discrete states is an open research problem. There are numerous alternative ways of associating individual configurations into collective states, and in deciding on the number of such clustered states there is a trade-off between human interpretability (smaller number of states) and accuracy of representation (larger number of states). Here we introduce a trajectory likelihood measure for assessing alternative discrete state models of protein folding. We find that widely used rmsd-based clustering methods require large numbers of initial states and a second agglomeration step based on kinetic connectivity to produce models with high predictive power; this is the approach taken in elegant recent work with Markov State Models of protein folding. In contrast, we find that grouping of states based on secondary structure pairings or contact maps, when refined with K-means clustering, yields higher likelihood models with many fewer states. Using the most predictive contact map representation to study the folding transitions of the WW domain in very long molecular dynamics simulations, we identify new states and transitions. The methods should be generally useful for investigating the structural transitions in protein folding simulations for larger proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The space accessed by a folding macromolecule is vast, and how to best project computer simulations of protein folding trajectories into an interpretable sequence of discrete states is an open research problem. There are numerous alternative ways of associating individual configurations into collective states, and in deciding on the number of such clustered states there is a trade-off between human interpretability (smaller number of states) and accuracy of representation (larger number of states). Here we introduce a trajectory likelihood measure for assessing alternative discrete state models of protein folding. We find that widely used rmsd-based clustering methods require large numbers of initial states and a second agglomeration step based on kinetic connectivity to produce models with high predictive power; this is the approach taken in elegant recent work with Markov State Models of protein folding. In contrast, we find that grouping of states based on secondary structure pairings or contact maps, when refined with K-means clustering, yields higher likelihood models with many fewer states. Using the most predictive contact map representation to study the folding transitions of the WW domain in very long molecular dynamics simulations, we identify new states and transitions. The methods should be generally useful for investigating the structural transitions in protein folding simulations for larger proteins.
Sarah Baxter, Abigail R Lambert, Ryan Kuhar, Jordan Jarjour, Nadia Kulshina, Fabio Parmeggiani, Patrick Danaher, Jacob Gano, David Baker, Barry L Stoddard, Andrew M Scharenberg
Engineering domain fusion chimeras from I-OnuI family LAGLIDADG homing endonucleases. Journal Article
In: Nucleic acids research, vol. 40, pp. 7985-8000, 2012, ISSN: 1362-4962.
@article{455,
title = {Engineering domain fusion chimeras from I-OnuI family LAGLIDADG homing endonucleases.},
author = { Sarah Baxter and Abigail R Lambert and Ryan Kuhar and Jordan Jarjour and Nadia Kulshina and Fabio Parmeggiani and Patrick Danaher and Jacob Gano and David Baker and Barry L Stoddard and Andrew M Scharenberg},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Baxter_NuclAcRes_2012.pdf},
issn = {1362-4962},
year = {2012},
date = {2012-09-01},
journal = {Nucleic acids research},
volume = {40},
pages = {7985-8000},
abstract = {Although engineered LAGLIDADG homing endonucleases (LHEs) are finding increasing applications in biotechnology, their generation remains a challenging, industrial-scale process. As new single-chain LAGLIDADG nuclease scaffolds are identified, however, an alternative paradigm is emerging: identification of an LHE scaffold whose native cleavage site is a close match to a desired target sequence, followed by small-scale engineering to modestly refine recognition specificity. The application of this paradigm could be accelerated if methods were available for fusing N- and C-terminal domains from newly identified LHEs into chimeric enzymes with hybrid cleavage sites. Here we have analyzed the structural requirements for fusion of domains extracted from six single-chain I-OnuI family LHEs, spanning 40-70% amino acid identity. Our analyses demonstrate that both the LAGLIDADG helical interface residues and the linker peptide composition have important effects on the stability and activity of chimeric enzymes. Using a simple domain fusion method in which linker peptide residues predicted to contact their respective domains are retained, and in which limited variation is introduced into the LAGLIDADG helix and nearby interface residues, catalytically active enzymes were recoverable for ~70% of domain chimeras. This method will be useful for creating large numbers of chimeric LHEs for genome engineering applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Although engineered LAGLIDADG homing endonucleases (LHEs) are finding increasing applications in biotechnology, their generation remains a challenging, industrial-scale process. As new single-chain LAGLIDADG nuclease scaffolds are identified, however, an alternative paradigm is emerging: identification of an LHE scaffold whose native cleavage site is a close match to a desired target sequence, followed by small-scale engineering to modestly refine recognition specificity. The application of this paradigm could be accelerated if methods were available for fusing N- and C-terminal domains from newly identified LHEs into chimeric enzymes with hybrid cleavage sites. Here we have analyzed the structural requirements for fusion of domains extracted from six single-chain I-OnuI family LHEs, spanning 40-70% amino acid identity. Our analyses demonstrate that both the LAGLIDADG helical interface residues and the linker peptide composition have important effects on the stability and activity of chimeric enzymes. Using a simple domain fusion method in which linker peptide residues predicted to contact their respective domains are retained, and in which limited variation is introduced into the LAGLIDADG helix and nearby interface residues, catalytically active enzymes were recoverable for ~70% of domain chimeras. This method will be useful for creating large numbers of chimeric LHEs for genome engineering applications.
Yakov Kipnis, David Baker
Comparison of designed and randomly generated catalysts for simple chemical reactions Journal Article
In: Protein Science : A Publication of the Protein Society, vol. 21, pp. 1388-95, 2012, ISSN: 1469-896X.
@article{603,
title = {Comparison of designed and randomly generated catalysts for simple chemical reactions},
author = { Yakov Kipnis and David Baker},
url = {http://www.bakerlab.org/wp-content/uploads/2015/12/comparisonofdesigned_Baker2012.pdf},
doi = {10.1002/pro.2125},
issn = {1469-896X},
year = {2012},
date = {2012-09-01},
journal = {Protein Science : A Publication of the Protein Society},
volume = {21},
pages = {1388-95},
abstract = {There has been recent success in designing enzymes for simple chemical reactions using a two-step protocol. In the first step, a geometric matching algorithm is used to identify naturally occurring protein scaffolds at which predefined idealized active sites can be realized. In the second step, the residues surrounding the transition state model are optimized to increase transition state binding affinity and to bolster the primary catalytic side chains. To improve the design methodology, we investigated how the set of solutions identified by the design calculations relate to the overall set of solutions for two different chemical reactions. Using a TIM barrel scaffold in which catalytically active Kemp eliminase and retroaldolase designs were obtained previously, we carried out activity screens of random libraries made to be compositionally similar to active designs. A small number of active catalysts were found in screens of 10textthreesuperior variants for each of the two reactions, which differ from the computational designs in that they reuse charged residues already present in the native scaffold. The results suggest that computational design considerably increases the frequency of catalyst generation for active sites involving newly introduced catalytic residues, highlighting the importance of interaction cooperativity in enzyme active sites.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
There has been recent success in designing enzymes for simple chemical reactions using a two-step protocol. In the first step, a geometric matching algorithm is used to identify naturally occurring protein scaffolds at which predefined idealized active sites can be realized. In the second step, the residues surrounding the transition state model are optimized to increase transition state binding affinity and to bolster the primary catalytic side chains. To improve the design methodology, we investigated how the set of solutions identified by the design calculations relate to the overall set of solutions for two different chemical reactions. Using a TIM barrel scaffold in which catalytically active Kemp eliminase and retroaldolase designs were obtained previously, we carried out activity screens of random libraries made to be compositionally similar to active designs. A small number of active catalysts were found in screens of 10textthreesuperior variants for each of the two reactions, which differ from the computational designs in that they reuse charged residues already present in the native scaffold. The results suggest that computational design considerably increases the frequency of catalyst generation for active sites involving newly introduced catalytic residues, highlighting the importance of interaction cooperativity in enzyme active sites.
Assaf Alon, Iris Grossman, Yair Gat, Vamsi K Kodali, Frank DiMaio, Tevie Mehlman, Gilad Haran, David Baker, Colin Thorpe, Deborah Fass
The dynamic disulphide relay of quiescin sulphydryl oxidase Journal Article
In: Nature, vol. 488, pp. 414-8, 2012, ISSN: 1476-4687.
@article{600,
title = {The dynamic disulphide relay of quiescin sulphydryl oxidase},
author = { Assaf Alon and Iris Grossman and Yair Gat and Vamsi K Kodali and Frank DiMaio and Tevie Mehlman and Gilad Haran and David Baker and Colin Thorpe and Deborah Fass},
url = {https://www.bakerlab.org/wp-content/uploads/2016/01/thedynamicdisulphide_Baker2012.pdf},
doi = {10.1038/nature11267},
issn = {1476-4687},
year = {2012},
date = {2012-08-01},
journal = {Nature},
volume = {488},
pages = {414-8},
abstract = {Protein stability, assembly, localization and regulation often depend on the formation of disulphide crosslinks between cysteine side chains. Enzymes known as sulphydryl oxidases catalyse de novo disulphide formation and initiate intra- and intermolecular dithiol/disulphide relays to deliver the disulphides to substrate proteins. Quiescin sulphydryl oxidase (QSOX) is a unique, multi-domain disulphide catalyst that is localized primarily to the Golgi apparatus and secreted fluids and has attracted attention owing to its overproduction in tumours. In addition to its physiological importance, QSOX is a mechanistically intriguing enzyme, encompassing functions typically carried out by a series of proteins in other disulphide-formation pathways. How disulphides are relayed through the multiple redox-active sites of QSOX and whether there is a functional benefit to concatenating these sites on a single polypeptide are open questions. Here we present the first crystal structure of an intact QSOX enzyme, derived from a trypanosome parasite. Notably, sequential sites in the disulphide relay were found more than 40 r A apart in this structure, too far for direct disulphide transfer. To resolve this puzzle, we trapped and crystallized an intermediate in the disulphide hand-off, which showed a 165textdegree domain rotation relative to the original structure, bringing the two active sites within disulphide-bonding distance. The comparable structure of a mammalian QSOX enzyme, also presented here, shows further biochemical features that facilitate disulphide transfer in metazoan orthologues. Finally, we quantified the contribution of concatenation to QSOX activity, providing general lessons for the understanding of multi-domain enzymes and the design of new catalytic relays.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein stability, assembly, localization and regulation often depend on the formation of disulphide crosslinks between cysteine side chains. Enzymes known as sulphydryl oxidases catalyse de novo disulphide formation and initiate intra- and intermolecular dithiol/disulphide relays to deliver the disulphides to substrate proteins. Quiescin sulphydryl oxidase (QSOX) is a unique, multi-domain disulphide catalyst that is localized primarily to the Golgi apparatus and secreted fluids and has attracted attention owing to its overproduction in tumours. In addition to its physiological importance, QSOX is a mechanistically intriguing enzyme, encompassing functions typically carried out by a series of proteins in other disulphide-formation pathways. How disulphides are relayed through the multiple redox-active sites of QSOX and whether there is a functional benefit to concatenating these sites on a single polypeptide are open questions. Here we present the first crystal structure of an intact QSOX enzyme, derived from a trypanosome parasite. Notably, sequential sites in the disulphide relay were found more than 40 r A apart in this structure, too far for direct disulphide transfer. To resolve this puzzle, we trapped and crystallized an intermediate in the disulphide hand-off, which showed a 165textdegree domain rotation relative to the original structure, bringing the two active sites within disulphide-bonding distance. The comparable structure of a mammalian QSOX enzyme, also presented here, shows further biochemical features that facilitate disulphide transfer in metazoan orthologues. Finally, we quantified the contribution of concatenation to QSOX activity, providing general lessons for the understanding of multi-domain enzymes and the design of new catalytic relays.
Oliver F Lange, Paolo Rossi, Nikolaos G Sgourakis, Yifan Song, Hsiau-Wei Lee, James M Aramini, Asli Ertekin, Rong Xiao, Thomas B Acton, Gaetano T Montelione, David Baker
Determination of solution structures of proteins up to 40 kDa using CS-Rosetta with sparse NMR data from deuterated samples. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 109, pp. 10873-8, 2012, ISSN: 1091-6490.
@article{454,
title = {Determination of solution structures of proteins up to 40 kDa using CS-Rosetta with sparse NMR data from deuterated samples.},
author = { Oliver F Lange and Paolo Rossi and Nikolaos G Sgourakis and Yifan Song and Hsiau-Wei Lee and James M Aramini and Asli Ertekin and Rong Xiao and Thomas B Acton and Gaetano T Montelione and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/10873.full_.pdf
http://www.pnas.org/content/109/27/10873.full},
issn = {1091-6490},
year = {2012},
date = {2012-07-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {109},
pages = {10873-8},
abstract = {We have developed an approach for determining NMR structures of proteins over 20~kDa that utilizes sparse distance restraints obtained using transverse relaxation optimized spectroscopy experiments on perdeuterated samples to guide RASREC Rosetta NMR structure calculations. The method was tested on 11 proteins ranging from 15 to 40~kDa, seven of which were previously unsolved. The RASREC Rosetta models were in good agreement with models obtained using traditional NMR methods with larger restraint sets. In five cases X-ray structures were determined or were available, allowing comparison of the accuracy of the Rosetta models and conventional NMR models. In all five cases, the Rosetta models were more similar to the X-ray structures over both the backbone and side-chain conformations than the "best effort" structures determined by conventional methods. The incorporation of sparse distance restraints into RASREC Rosetta allows routine determination of high-quality solution NMR structures for proteins up to 40~kDa, and should be broadly useful in structural biology.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have developed an approach for determining NMR structures of proteins over 20~kDa that utilizes sparse distance restraints obtained using transverse relaxation optimized spectroscopy experiments on perdeuterated samples to guide RASREC Rosetta NMR structure calculations. The method was tested on 11 proteins ranging from 15 to 40~kDa, seven of which were previously unsolved. The RASREC Rosetta models were in good agreement with models obtained using traditional NMR methods with larger restraint sets. In five cases X-ray structures were determined or were available, allowing comparison of the accuracy of the Rosetta models and conventional NMR models. In all five cases, the Rosetta models were more similar to the X-ray structures over both the backbone and side-chain conformations than the "best effort" structures determined by conventional methods. The incorporation of sparse distance restraints into RASREC Rosetta allows routine determination of high-quality solution NMR structures for proteins up to 40~kDa, and should be broadly useful in structural biology.
Summer B Thyme, David Baker, Philip Bradley
Improved modeling of side-chain–base interactions and plasticity in protein–DNA interface design. Journal Article
In: Journal of molecular biology, vol. 419, pp. 255-74, 2012, ISSN: 1089-8638.
@article{459,
title = {Improved modeling of side-chain--base interactions and plasticity in protein--DNA interface design.},
author = { Summer B Thyme and David Baker and Philip Bradley},
url = {http://beta.baker/wp-content/uploads/2015/12/Thyme_JMolBiol_2012.pdf},
issn = {1089-8638},
year = {2012},
date = {2012-06-01},
journal = {Journal of molecular biology},
volume = {419},
pages = {255-74},
abstract = {Combinatorial sequence optimization for protein design requires libraries of discrete side-chain conformations. The discreteness of these libraries is problematic, particularly for long, polar side chains, since favorable interactions can be missed. Previously, an approach to loop remodeling where protein backbone movement is directed by side-chain rotamers predicted to form interactions previously observed in native complexes (termed "motifs") was described. Here, we show how such motif libraries can be incorporated into combinatorial sequence optimization protocols and improve native complex recapitulation. Guided by the motif rotamer searches, we made improvements to the underlying energy function, increasing recapitulation of native interactions. To further test the methods, we carried out a comprehensive experimental scan of amino acid preferences in the I-AniI protein-DNA interface and found that many positions tolerated multiple amino acids. This sequence plasticity is not observed in the computational results because of the fixed-backbone approximation of the model. We improved modeling of this diversity by introducing DNA flexibility and reducing the convergence of the simulated annealing algorithm that drives the design process. In addition to serving as a benchmark, this extensive experimental data set provides insight into the types of interactions essential to maintain the function of this potential gene therapy reagent.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Combinatorial sequence optimization for protein design requires libraries of discrete side-chain conformations. The discreteness of these libraries is problematic, particularly for long, polar side chains, since favorable interactions can be missed. Previously, an approach to loop remodeling where protein backbone movement is directed by side-chain rotamers predicted to form interactions previously observed in native complexes (termed "motifs") was described. Here, we show how such motif libraries can be incorporated into combinatorial sequence optimization protocols and improve native complex recapitulation. Guided by the motif rotamer searches, we made improvements to the underlying energy function, increasing recapitulation of native interactions. To further test the methods, we carried out a comprehensive experimental scan of amino acid preferences in the I-AniI protein-DNA interface and found that many positions tolerated multiple amino acids. This sequence plasticity is not observed in the computational results because of the fixed-backbone approximation of the model. We improved modeling of this diversity by introducing DNA flexibility and reducing the convergence of the simulated annealing algorithm that drives the design process. In addition to serving as a benchmark, this extensive experimental data set provides insight into the types of interactions essential to maintain the function of this potential gene therapy reagent.
Olga Khersonsky, Gert Kiss, Daniela R"othlisberger, Orly Dym, Shira Albeck, Kendall N Houk, David Baker, Dan S Tawfik
Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 109, pp. 10358-63, 2012, ISSN: 1091-6490.
@article{456,
title = {Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59.},
author = { Olga Khersonsky and Gert Kiss and Daniela R"othlisberger and Orly Dym and Shira Albeck and Kendall N Houk and David Baker and Dan S Tawfik},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/10358.full_.pdf
www.pnas.org/content/109/26/10358},
issn = {1091-6490},
year = {2012},
date = {2012-06-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {109},
pages = {10358-63},
abstract = {Computational design is a test of our understanding of enzyme catalysis and a means of engineering novel, tailor-made enzymes. While the de novo computational design of catalytically efficient enzymes remains a challenge, designed enzymes may comprise unique starting points for further optimization by directed evolution. Directed evolution of two computationally designed Kemp eliminases, KE07 and KE70, led to low to moderately efficient enzymes (k(cat)/K(m) values of <= 5 10(4) M(-1)s(-1)). Here we describe the optimization of a third design, KE59. Although KE59 was the most catalytically efficient Kemp eliminase from this design series (by k(cat)/K(m), and by catalyzing the elimination of nonactivated benzisoxazoles), its impaired stability prevented its evolutionary optimization. To boost KE59textquoterights evolvability, stabilizing consensus mutations were included in the libraries throughout the directed evolution process. The libraries were also screened with less activated substrates. Sixteen rounds of mutation and selection led to > 2,000-fold increase in catalytic efficiency, mainly via higher k(cat) values. The best KE59 variants exhibited k(cat)/K(m) values up to 0.6 10(6) M(-1)s(-1), and k(cat)/k(uncat) values of <= 10(7) almost regardless of substrate reactivity. Biochemical, structural, and molecular dynamics (MD) simulation studies provided insights regarding the optimization of KE59. Overall, the directed evolution of three different designed Kemp eliminases, KE07, KE70, and KE59, demonstrates that computational designs are highly evolvable and can be optimized to high catalytic efficiencies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational design is a test of our understanding of enzyme catalysis and a means of engineering novel, tailor-made enzymes. While the de novo computational design of catalytically efficient enzymes remains a challenge, designed enzymes may comprise unique starting points for further optimization by directed evolution. Directed evolution of two computationally designed Kemp eliminases, KE07 and KE70, led to low to moderately efficient enzymes (k(cat)/K(m) values of <= 5 10(4) M(-1)s(-1)). Here we describe the optimization of a third design, KE59. Although KE59 was the most catalytically efficient Kemp eliminase from this design series (by k(cat)/K(m), and by catalyzing the elimination of nonactivated benzisoxazoles), its impaired stability prevented its evolutionary optimization. To boost KE59textquoterights evolvability, stabilizing consensus mutations were included in the libraries throughout the directed evolution process. The libraries were also screened with less activated substrates. Sixteen rounds of mutation and selection led to > 2,000-fold increase in catalytic efficiency, mainly via higher k(cat) values. The best KE59 variants exhibited k(cat)/K(m) values up to 0.6 10(6) M(-1)s(-1), and k(cat)/k(uncat) values of <= 10(7) almost regardless of substrate reactivity. Biochemical, structural, and molecular dynamics (MD) simulation studies provided insights regarding the optimization of KE59. Overall, the directed evolution of three different designed Kemp eliminases, KE07, KE70, and KE59, demonstrates that computational designs are highly evolvable and can be optimized to high catalytic efficiencies.
James M Thompson, Nikolaos G Sgourakis, Gaohua Liu, Paolo Rossi, Yuefeng Tang, Jeffrey L Mills, Thomas Szyperski, Gaetano T Montelione, David Baker
Accurate protein structure modeling using sparse NMR data and homologous structure information. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 109, pp. 9875-80, 2012, ISSN: 1091-6490.
@article{457,
title = {Accurate protein structure modeling using sparse NMR data and homologous structure information.},
author = { James M Thompson and Nikolaos G Sgourakis and Gaohua Liu and Paolo Rossi and Yuefeng Tang and Jeffrey L Mills and Thomas Szyperski and Gaetano T Montelione and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/9875.full_.pdf
http://www.pnas.org/content/109/25/9875},
issn = {1091-6490},
year = {2012},
date = {2012-06-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {109},
pages = {9875-80},
abstract = {While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 A backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 A relative to the conventional determined NMR ensembles and of 0.9-1.6 A relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 A backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 A relative to the conventional determined NMR ensembles and of 0.9-1.6 A relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.
Thomas C Terwilliger, Frank DiMaio, Randy J Read, David Baker, G’abor Bunk’oczi, Paul D Adams, Ralf W Grosse-Kunstleve, Pavel V Afonine, Nathaniel Echols
phenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and Rosetta. Journal Article
In: Journal of structural and functional genomics, vol. 13, pp. 81-90, 2012, ISSN: 1570-0267.
@article{462,
title = {phenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and Rosetta.},
author = { Thomas C Terwilliger and Frank DiMaio and Randy J Read and David Baker and G'abor Bunk'oczi and Paul D Adams and Ralf W Grosse-Kunstleve and Pavel V Afonine and Nathaniel Echols},
doi = {10.1007/s10969-012-9129-3},
issn = {1570-0267},
year = {2012},
date = {2012-06-01},
journal = {Journal of structural and functional genomics},
volume = {13},
pages = {81-90},
abstract = {The combination of algorithms from the structure-modeling field with those of crystallographic structure determination can broaden the range of templates that are useful for structure determination by the method of molecular replacement. Automated tools in phenix.mr_rosetta simplify the application of these combined approaches by integrating Phenix crystallographic algorithms and Rosetta structure-modeling algorithms and by systematically generating and evaluating models with a combination of these methods. The phenix.mr_rosetta algorithms can be used to automatically determine challenging structures. The approaches used in phenix.mr_rosetta are described along with examples that show roles that structure-modeling can play in molecular replacement.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The combination of algorithms from the structure-modeling field with those of crystallographic structure determination can broaden the range of templates that are useful for structure determination by the method of molecular replacement. Automated tools in phenix.mr_rosetta simplify the application of these combined approaches by integrating Phenix crystallographic algorithms and Rosetta structure-modeling algorithms and by systematically generating and evaluating models with a combination of these methods. The phenix.mr_rosetta algorithms can be used to automatically determine challenging structures. The approaches used in phenix.mr_rosetta are described along with examples that show roles that structure-modeling can play in molecular replacement.
Neil P. King, Will Sheffler, Michael R Sawaya, Breanna S. Vollmar, John P. Sumida, Ingemar Andr’e, Tamir Gonen, Todd O. Yeates, David Baker
Computational design of self-assembling protein nanomaterials with atomic level accuracy Journal Article
In: Science, 2012.
@article{445,
title = {Computational design of self-assembling protein nanomaterials with atomic level accuracy},
author = { Neil P. King and Will Sheffler and Michael R Sawaya and Breanna S. Vollmar and John P. Sumida and Ingemar Andr'e and Tamir Gonen and Todd O. Yeates and David Baker},
doi = {10.1126/science.1219364},
year = {2012},
date = {2012-06-01},
journal = {Science},
abstract = {We describe a general computational method for designing proteins that self-assemble to a desired symmetric architecture. Protein building blocks are docked together symmetrically to identify complementary packing arrangements, and low-energy protein-protein interfaces are then designed between the building blocks in order to drive self-assembly. We used trimeric protein building blocks to design a 24-subunit, 13-nm diameter complex with octahedral symmetry and a 12-subunit, 11-nm diameter complex with tetrahedral symmetry. The designed proteins assembled to the desired oligomeric states in solution, and the crystal structures of the complexes revealed that the resulting materials closely match the design models. The method can be used to design a wide variety of self-assembling protein nanomaterials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a general computational method for designing proteins that self-assemble to a desired symmetric architecture. Protein building blocks are docked together symmetrically to identify complementary packing arrangements, and low-energy protein-protein interfaces are then designed between the building blocks in order to drive self-assembly. We used trimeric protein building blocks to design a 24-subunit, 13-nm diameter complex with octahedral symmetry and a 12-subunit, 11-nm diameter complex with tetrahedral symmetry. The designed proteins assembled to the desired oligomeric states in solution, and the crystal structures of the complexes revealed that the resulting materials closely match the design models. The method can be used to design a wide variety of self-assembling protein nanomaterials.
Timothy A Whitehead, Aaron Chevalier, Yifan Song, Cyrille Dreyfus, Sarel J Fleishman, Cecilia De Mattos, Chris A Myers, Hetunandan Kamisetty, Patrick Blair, Ian A Wilson, David Baker
Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing Journal Article
In: Nature biotechnology, 2012, ISSN: 1546-1696.
@article{444,
title = {Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing},
author = { Timothy A Whitehead and Aaron Chevalier and Yifan Song and Cyrille Dreyfus and Sarel J Fleishman and Cecilia De Mattos and Chris A Myers and Hetunandan Kamisetty and Patrick Blair and Ian A Wilson and David Baker},
url = {http://beta.baker/wp-content/uploads/2015/12/whitehead12A.pdf},
doi = {10.1038/nbt.2214},
issn = {1546-1696},
year = {2012},
date = {2012-05-01},
journal = {Nature biotechnology},
abstract = {We show that comprehensive sequence-function maps obtained by deep sequencing can be used to reprogram interaction specificity and to leapfrog over bottlenecks in affinity maturation by combining many individually small contributions not detectable in conventional approaches. We use this approach to optimize two computationally designed inhibitors against H1N1 influenza hemagglutinin and, in both cases, obtain variants with subnanomolar binding affinity. The most potent of these, a 51-residue protein, is broadly cross-reactive against all influenza group 1 hemagglutinins, including human H2, and neutralizes H1N1 viruses with a potency that rivals that of several human monoclonal antibodies, demonstrating that computational design followed by comprehensive energy landscape mapping can generate proteins with potential therapeutic utility.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We show that comprehensive sequence-function maps obtained by deep sequencing can be used to reprogram interaction specificity and to leapfrog over bottlenecks in affinity maturation by combining many individually small contributions not detectable in conventional approaches. We use this approach to optimize two computationally designed inhibitors against H1N1 influenza hemagglutinin and, in both cases, obtain variants with subnanomolar binding affinity. The most potent of these, a 51-residue protein, is broadly cross-reactive against all influenza group 1 hemagglutinins, including human H2, and neutralizes H1N1 viruses with a potency that rivals that of several human monoclonal antibodies, demonstrating that computational design followed by comprehensive energy landscape mapping can generate proteins with potential therapeutic utility.
Eric A Althoff, Ling Wang, Lin Jiang, Lars Giger, Jonathan K Lassila, Zhizhi Wang, Matthew Smith, Sanjay Hari, Peter Kast, Daniel Herschlag, Donald Hilvert, David Baker
Robust design and optimization of retroaldol enzymes. Journal Article
In: Protein science : a publication of the Protein Society, vol. 21, pp. 717-26, 2012, ISSN: 1469-896X.
@article{461,
title = {Robust design and optimization of retroaldol enzymes.},
author = { Eric A Althoff and Ling Wang and Lin Jiang and Lars Giger and Jonathan K Lassila and Zhizhi Wang and Matthew Smith and Sanjay Hari and Peter Kast and Daniel Herschlag and Donald Hilvert and David Baker},
url = {http://beta.baker/wp-content/uploads/2015/12/Althoff_ProteinScience_2012.pdf},
doi = {10.1002/pro.2059},
issn = {1469-896X},
year = {2012},
date = {2012-05-01},
journal = {Protein science : a publication of the Protein Society},
volume = {21},
pages = {717-26},
abstract = {Enzyme catalysts of a retroaldol reaction have been generated by computational design using a motif that combines a lysine in a nonpolar environment with water-mediated stabilization of the carbinolamine hydroxyl and β-hydroxyl groups. Here, we show that the design process is robust and repeatable, with 33 new active designs constructed on 13 different protein scaffold backbones. The initial activities are not high but are increased through site-directed mutagenesis and laboratory evolution. Mutational data highlight areas for improvement in design. Different designed catalysts give different borohydride-reduced reaction intermediates, suggesting a distribution of properties of the designed enzymes that may be further explored and exploited.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Enzyme catalysts of a retroaldol reaction have been generated by computational design using a motif that combines a lysine in a nonpolar environment with water-mediated stabilization of the carbinolamine hydroxyl and β-hydroxyl groups. Here, we show that the design process is robust and repeatable, with 33 new active designs constructed on 13 different protein scaffold backbones. The initial activities are not high but are increased through site-directed mutagenesis and laboratory evolution. Mutational data highlight areas for improvement in design. Different designed catalysts give different borohydride-reduced reaction intermediates, suggesting a distribution of properties of the designed enzymes that may be further explored and exploited.
Wei Wu, Goran Ahlsen, David Baker, Lawrence Shapiro, S Lawrence Zipursky
Complementary chimeric isoforms reveal Dscam1 binding specificity in vivo Journal Article
In: Neuron, vol. 74, pp. 261-8, 2012, ISSN: 1097-4199.
@article{602,
title = {Complementary chimeric isoforms reveal Dscam1 binding specificity in vivo},
author = { Wei Wu and Goran Ahlsen and David Baker and Lawrence Shapiro and S Lawrence Zipursky},
doi = {10.1016/j.neuron.2012.02.029},
issn = {1097-4199},
year = {2012},
date = {2012-04-01},
journal = {Neuron},
volume = {74},
pages = {261-8},
abstract = {Dscam1 potentially encodes 19,008 ectodomains of a cell recognition molecule of the immunoglobulin (Ig) superfamily through alternative splicing. Each ectodomain, comprising a unique combination of three variable (Ig) domains, exhibits isoform-specific homophilic binding in~vitro. Although we have proposed that the ability of Dscam1 isoforms to distinguish between one another is crucial for neural circuit assembly, via a process called self-avoidance, whether recognition specificity is essential in~vivo has not been addressed. Here we tackle this issue by assessing the function of Dscam1 isoforms with altered binding specificities. We generated pairs of chimeric isoforms that bind to each other (heterophilic) but not to themselves (homophilic). These isoforms failed to support self-avoidance or did so poorly. By contrast, coexpression of complementary isoforms within the same neuron restored self-avoidance. These data establish that recognition between Dscam1 isoforms on neurites of the same cell provides the molecular basis for self-avoidance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dscam1 potentially encodes 19,008 ectodomains of a cell recognition molecule of the immunoglobulin (Ig) superfamily through alternative splicing. Each ectodomain, comprising a unique combination of three variable (Ig) domains, exhibits isoform-specific homophilic binding in~vitro. Although we have proposed that the ability of Dscam1 isoforms to distinguish between one another is crucial for neural circuit assembly, via a process called self-avoidance, whether recognition specificity is essential in~vivo has not been addressed. Here we tackle this issue by assessing the function of Dscam1 isoforms with altered binding specificities. We generated pairs of chimeric isoforms that bind to each other (heterophilic) but not to themselves (homophilic). These isoforms failed to support self-avoidance or did so poorly. By contrast, coexpression of complementary isoforms within the same neuron restored self-avoidance. These data establish that recognition between Dscam1 isoforms on neurites of the same cell provides the molecular basis for self-avoidance.
Sarel J Fleishman, David Baker
Role of the biomolecular energy gap in protein design, structure, and evolution. Journal Article
In: Cell, vol. 149, pp. 262-73, 2012, ISSN: 1097-4172.
@article{458,
title = {Role of the biomolecular energy gap in protein design, structure, and evolution.},
author = { Sarel J Fleishman and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/PIIS0092867412003492.pdf
https://www.cell.com/cell/fulltext/S0092-8674(12)00349-2},
issn = {1097-4172},
year = {2012},
date = {2012-04-01},
journal = {Cell},
volume = {149},
pages = {262-73},
abstract = {The folding of natural biopolymers into unique three-dimensional structures that determine their function is remarkable considering the vast number of alternative states and requires a large gap in the energy of the functional state compared to the many alternatives. This Perspective explores the implications of this energy gap for computing the structures of naturally occurring biopolymers, designing proteins with new structures and functions, and optimally integrating experiment and computation in these endeavors. Possible parallels between the generation of functional molecules in computational design and natural evolution are highlighted.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The folding of natural biopolymers into unique three-dimensional structures that determine their function is remarkable considering the vast number of alternative states and requires a large gap in the energy of the functional state compared to the many alternatives. This Perspective explores the implications of this energy gap for computing the structures of naturally occurring biopolymers, designing proteins with new structures and functions, and optimally integrating experiment and computation in these endeavors. Possible parallels between the generation of functional molecules in computational design and natural evolution are highlighted.
Troy C Krzysiak, Jinwon Jung, James Thompson, David Baker, Angela M Gronenborn
APOBEC2 is a monomer in solution: implications for APOBEC3G models Journal Article
In: Biochemistry, vol. 51, pp. 2008-17, 2012, ISSN: 1520-4995.
@article{604,
title = {APOBEC2 is a monomer in solution: implications for APOBEC3G models},
author = { Troy C Krzysiak and Jinwon Jung and James Thompson and David Baker and Angela M Gronenborn},
url = {http://beta.baker/wp-content/uploads/2015/12/apobec2isamonomer_Baker2012.pdf},
doi = {10.1021/bi300021s},
issn = {1520-4995},
year = {2012},
date = {2012-03-01},
journal = {Biochemistry},
volume = {51},
pages = {2008-17},
abstract = {Although the physiological role of APOBEC2 is still largely unknown, a crystal structure of a truncated variant of this protein was determined several years ago [Prochnow, C. (2007) Nature445, 447-451]. This APOBEC2 structure had considerable impact in the HIV field because it was considered a good model for the structure of APOBEC3G, an important HIV restriction factor that abrogates HIV infectivity in the absence of the viral accessory protein Vif. The quaternary structure and the arrangement of the monomers of APOBEC2 in the crystal were taken as being representative for APOBEC3G and exploited in explaining its enzymatic and anti-HIV activity. Here we show, unambiguously, that in contrast to the findings for the crystal, APOBEC2 is monomeric in solution. The nuclear magnetic resonance solution structure of full-length APOBEC2 reveals that the N-terminal tail that was removed for crystallization resides close to strand β2, the dimer interface in the crystal structure, and shields this region of the protein from engaging in intermolecular contacts. In addition, the presence of the N-terminal region drastically alters the aggregation propensity of APOBEC2, rendering the full-length protein highly soluble and not prone to precipitation. In summary, our results cast doubt on all previous structure-function predictions for APOBEC3G that were based on the crystal structure of APOBEC2.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Although the physiological role of APOBEC2 is still largely unknown, a crystal structure of a truncated variant of this protein was determined several years ago [Prochnow, C. (2007) Nature445, 447-451]. This APOBEC2 structure had considerable impact in the HIV field because it was considered a good model for the structure of APOBEC3G, an important HIV restriction factor that abrogates HIV infectivity in the absence of the viral accessory protein Vif. The quaternary structure and the arrangement of the monomers of APOBEC2 in the crystal were taken as being representative for APOBEC3G and exploited in explaining its enzymatic and anti-HIV activity. Here we show, unambiguously, that in contrast to the findings for the crystal, APOBEC2 is monomeric in solution. The nuclear magnetic resonance solution structure of full-length APOBEC2 reveals that the N-terminal tail that was removed for crystallization resides close to strand β2, the dimer interface in the crystal structure, and shields this region of the protein from engaging in intermolecular contacts. In addition, the presence of the N-terminal region drastically alters the aggregation propensity of APOBEC2, rendering the full-length protein highly soluble and not prone to precipitation. In summary, our results cast doubt on all previous structure-function predictions for APOBEC3G that were based on the crystal structure of APOBEC2.
Oliver F Lange, David Baker
Resolution-adapted recombination of structural features significantly improves sampling in restraint-guided structure calculation. Journal Article
In: Proteins, vol. 80, pp. 884-95, 2012, ISSN: 1097-0134.
@article{460,
title = {Resolution-adapted recombination of structural features significantly improves sampling in restraint-guided structure calculation.},
author = { Oliver F Lange and David Baker},
url = {http://beta.baker/wp-content/uploads/2015/12/Lange_Proteins_2012.pdf},
issn = {1097-0134},
year = {2012},
date = {2012-03-01},
journal = {Proteins},
volume = {80},
pages = {884-95},
abstract = {Recent work has shown that NMR structures can be determined by integrating sparse NMR data with structure prediction methods such as Rosetta. The experimental data serve to guide the search for the lowest energy state towards the deep minimum at the native state which is frequently missed in Rosetta de novo structure calculations. However, as the protein size increases, sampling again becomes limiting; for example, the standard Rosetta protocol involving Monte Carlo fragment insertion starting from an extended chain fails to converge for proteins over 150 amino acids even with guidance from chemical shifts (CS-Rosetta) and other NMR data. The primary limitation of this protocol--that every folding trajectory is completely independent of every other--was recently overcome with the development of a new approach involving resolution-adapted structural recombination (RASREC). Here we describe the RASREC approach in detail and compare it to standard CS-Rosetta. We show that the improved sampling of RASREC is essential in obtaining accurate structures over a benchmark set of 11 proteins in the 15-25 kDa size range using chemical shifts, backbone RDCs and HN-HN NOE data; in a number of cases the improved sampling methodology makes a larger contribution than incorporation of additional experimental data. Experimental data are invaluable for guiding sampling to the vicinity of the global energy minimum, but for larger proteins, the standard Rosetta fold-from-extended-chain protocol does not converge on the native minimum even with experimental data and the more powerful RASREC approach is necessary to converge to accurate solutions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent work has shown that NMR structures can be determined by integrating sparse NMR data with structure prediction methods such as Rosetta. The experimental data serve to guide the search for the lowest energy state towards the deep minimum at the native state which is frequently missed in Rosetta de novo structure calculations. However, as the protein size increases, sampling again becomes limiting; for example, the standard Rosetta protocol involving Monte Carlo fragment insertion starting from an extended chain fails to converge for proteins over 150 amino acids even with guidance from chemical shifts (CS-Rosetta) and other NMR data. The primary limitation of this protocol–that every folding trajectory is completely independent of every other–was recently overcome with the development of a new approach involving resolution-adapted structural recombination (RASREC). Here we describe the RASREC approach in detail and compare it to standard CS-Rosetta. We show that the improved sampling of RASREC is essential in obtaining accurate structures over a benchmark set of 11 proteins in the 15-25 kDa size range using chemical shifts, backbone RDCs and HN-HN NOE data; in a number of cases the improved sampling methodology makes a larger contribution than incorporation of additional experimental data. Experimental data are invaluable for guiding sampling to the vicinity of the global energy minimum, but for larger proteins, the standard Rosetta fold-from-extended-chain protocol does not converge on the native minimum even with experimental data and the more powerful RASREC approach is necessary to converge to accurate solutions.
Antonio Rosato, James M Aramini, Cheryl Arrowsmith, Anurag Bagaria, David Baker, Andrea Cavalli, Jurgen F Doreleijers, Alexander Eletsky, Andrea Giachetti, Paul Guerry, Aleksandras Gutmanas, Peter G"untert, Yunfen He, Torsten Herrmann, Yuanpeng J Huang, Victor Jaravine, Hendrik R A Jonker, Michael A Kennedy, Oliver F Lange, Gaohua Liu, Th’er`ese E Malliavin, Rajeswari Mani, Binchen Mao, Gaetano T Montelione, Michael Nilges, Paolo Rossi, Gijs van der Schot, Harald Schwalbe, Thomas A Szyperski, Michele Vendruscolo, Robert Vernon, Wim F Vranken, Sjoerd de Vries, Geerten W Vuister, Bin Wu, Yunhuang Yang, Alexandre M J J Bonvin
Blind testing of routine, fully automated determination of protein structures from NMR data Journal Article
In: Structure, vol. 20, pp. 227-36, 2012, ISSN: 1878-4186.
@article{428,
title = {Blind testing of routine, fully automated determination of protein structures from NMR data},
author = { Antonio Rosato and James M Aramini and Cheryl Arrowsmith and Anurag Bagaria and David Baker and Andrea Cavalli and Jurgen F Doreleijers and Alexander Eletsky and Andrea Giachetti and Paul Guerry and Aleksandras Gutmanas and Peter G"untert and Yunfen He and Torsten Herrmann and Yuanpeng J Huang and Victor Jaravine and Hendrik R A Jonker and Michael A Kennedy and Oliver F Lange and Gaohua Liu and Th'er`ese E Malliavin and Rajeswari Mani and Binchen Mao and Gaetano T Montelione and Michael Nilges and Paolo Rossi and Gijs van der Schot and Harald Schwalbe and Thomas A Szyperski and Michele Vendruscolo and Robert Vernon and Wim F Vranken and Sjoerd de Vries and Geerten W Vuister and Bin Wu and Yunhuang Yang and Alexandre M J J Bonvin},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0969212612000081-main.pdf
https://www.sciencedirect.com/science/article/pii/S0969212612000081?via%3Dihub},
issn = {1878-4186},
year = {2012},
date = {2012-02-01},
journal = {Structure},
volume = {20},
pages = {227-36},
abstract = {The protocols currently used for protein structure determination by nuclear magnetic resonance (NMR) depend on the determination of a large number of upper distance limits for proton-proton pairs. Typically, this task is performed manually by an experienced researcher rather than automatically by using a specific computer program. To assess whether it is indeed possible to generate in a fully automated manner NMR structures adequate for deposition in the Protein Data Bank, we gathered 10 experimental data sets with unassigned nuclear Overhauser effect spectroscopy (NOESY) peak lists for various proteins of unknown structure, computed structures for each of them using different, fully automatic programs, and compared the results to each other and to the manually solved reference structures that were not available at the time the data were provided. This constitutes a stringent "blind" assessment similar to the CASP and CAPRI initiatives. This study demonstrates the feasibility of routine, fully automated protein structure determination by NMR.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The protocols currently used for protein structure determination by nuclear magnetic resonance (NMR) depend on the determination of a large number of upper distance limits for proton-proton pairs. Typically, this task is performed manually by an experienced researcher rather than automatically by using a specific computer program. To assess whether it is indeed possible to generate in a fully automated manner NMR structures adequate for deposition in the Protein Data Bank, we gathered 10 experimental data sets with unassigned nuclear Overhauser effect spectroscopy (NOESY) peak lists for various proteins of unknown structure, computed structures for each of them using different, fully automatic programs, and compared the results to each other and to the manually solved reference structures that were not available at the time the data were provided. This constitutes a stringent "blind" assessment similar to the CASP and CAPRI initiatives. This study demonstrates the feasibility of routine, fully automated protein structure determination by NMR.
Sagar D Khare, Yakov Kipnis, Per Jr Greisen, Ryo Takeuchi, Yacov Ashani, Moshe Goldsmith, Yifan Song, Jasmine L Gallaher, Israel Silman, Haim Leader, Joel L Sussman, Barry L Stoddard, Dan S Tawfik, David Baker
Computational redesign of a mononuclear zinc metalloenzyme for organophosphate hydrolysis Journal Article
In: Nature chemical biology, 2012, ISSN: 1552-4469.
@article{427,
title = {Computational redesign of a mononuclear zinc metalloenzyme for organophosphate hydrolysis},
author = { Sagar D Khare and Yakov Kipnis and Per Jr Greisen and Ryo Takeuchi and Yacov Ashani and Moshe Goldsmith and Yifan Song and Jasmine L Gallaher and Israel Silman and Haim Leader and Joel L Sussman and Barry L Stoddard and Dan S Tawfik and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/nchembio.777.pdf
https://www.nature.com/articles/nchembio.777},
doi = {10.1038/nchembio.777},
issn = {1552-4469},
year = {2012},
date = {2012-02-01},
journal = {Nature chemical biology},
abstract = {The ability to redesign enzymes to catalyze noncognate chemical transformations would have wide-ranging applications. We developed a computational method for repurposing the reactivity of metalloenzyme active site functional groups to catalyze new reactions. Using this method, we engineered a zinc-containing mouse adenosine deaminase to catalyze the hydrolysis of a model organophosphate with a catalytic efficiency (k(cat)/K(m)) of ~10(4) M(-1) s(-1) after directed evolution. In the high-resolution crystal structure of the enzyme, all but one of the designed residues adopt the designed conformation. The designed enzyme efficiently catalyzes the hydrolysis of the R(P) isomer of a coumarinyl analog of the nerve agent cyclosarin, and it shows marked substrate selectivity for coumarinyl leaving groups. Computational redesign of native enzyme active sites complements directed evolution methods and offers a general approach for exploring their untapped catalytic potential for new reactivities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ability to redesign enzymes to catalyze noncognate chemical transformations would have wide-ranging applications. We developed a computational method for repurposing the reactivity of metalloenzyme active site functional groups to catalyze new reactions. Using this method, we engineered a zinc-containing mouse adenosine deaminase to catalyze the hydrolysis of a model organophosphate with a catalytic efficiency (k(cat)/K(m)) of ~10(4) M(-1) s(-1) after directed evolution. In the high-resolution crystal structure of the enzyme, all but one of the designed residues adopt the designed conformation. The designed enzyme efficiently catalyzes the hydrolysis of the R(P) isomer of a coumarinyl analog of the nerve agent cyclosarin, and it shows marked substrate selectivity for coumarinyl leaving groups. Computational redesign of native enzyme active sites complements directed evolution methods and offers a general approach for exploring their untapped catalytic potential for new reactivities.
Julia Handl, Joshua Knowles, Robert Vernon, David Baker, Simon C Lovell
The dual role of fragments in fragment-assembly methods for de novo protein structure prediction Journal Article
In: Proteins, vol. 80, pp. 490-504, 2012, ISSN: 1097-0134.
@article{601,
title = {The dual role of fragments in fragment-assembly methods for de novo protein structure prediction},
author = { Julia Handl and Joshua Knowles and Robert Vernon and David Baker and Simon C Lovell},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/Handl_et_al-2012-Proteins3A_Structure2C_Function2C_and_Bioinformatics.pdf
https://onlinelibrary.wiley.com/doi/full/10.1002/prot.23215},
doi = {10.1002/prot.23215},
issn = {1097-0134},
year = {2012},
date = {2012-02-01},
journal = {Proteins},
volume = {80},
pages = {490-504},
abstract = {In fragment-assembly techniques for protein structure prediction, models of protein structure are assembled from fragments of known protein structures. This process is typically guided by a knowledge-based energy function and uses a heuristic optimization method. The fragments play two important roles in this process: they define the set of structural parameters available, and they also assume the role of the main variation operators that are used by the optimiser. Previous analysis has typically focused on the first of these roles. In particular, the relationship between local amino acid sequence and local protein structure has been studied by a range of authors. The correlation between the two has been shown to vary with the window length considered, and the results of these analyses have informed directly the choice of fragment length in state-of-the-art prediction techniques. Here, we focus on the second role of fragments and aim to determine the effect of fragment length from an optimization perspective. We use theoretical analyses to reveal how the size and structure of the search space changes as a function of insertion length. Furthermore, empirical analyses are used to explore additional ways in which the size of the fragment insertion influences the search both in a simulation model and for the fragment-assembly technique, Rosetta.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In fragment-assembly techniques for protein structure prediction, models of protein structure are assembled from fragments of known protein structures. This process is typically guided by a knowledge-based energy function and uses a heuristic optimization method. The fragments play two important roles in this process: they define the set of structural parameters available, and they also assume the role of the main variation operators that are used by the optimiser. Previous analysis has typically focused on the first of these roles. In particular, the relationship between local amino acid sequence and local protein structure has been studied by a range of authors. The correlation between the two has been shown to vary with the window length considered, and the results of these analyses have informed directly the choice of fragment length in state-of-the-art prediction techniques. Here, we focus on the second role of fragments and aim to determine the effect of fragment length from an optimization perspective. We use theoretical analyses to reveal how the size and structure of the search space changes as a function of insertion length. Furthermore, empirical analyses are used to explore additional ways in which the size of the fragment insertion influences the search both in a simulation model and for the fragment-assembly technique, Rosetta.
Mihai L Azoitei, Yih-En Andrew Ban, Jean-Philippe Julien, Steve Bryson, Alexandria Schroeter, Oleksandr Kalyuzhniy, Justin R Porter, Yumiko Adachi, David Baker, Emil F Pai, William R Schief
Computational design of high-affinity epitope scaffolds by backbone grafting of a linear epitope Journal Article
In: Journal of molecular biology, vol. 415, pp. 175-92, 2012, ISSN: 1089-8638.
@article{425,
title = {Computational design of high-affinity epitope scaffolds by backbone grafting of a linear epitope},
author = { Mihai L Azoitei and Yih-En Andrew Ban and Jean-Philippe Julien and Steve Bryson and Alexandria Schroeter and Oleksandr Kalyuzhniy and Justin R Porter and Yumiko Adachi and David Baker and Emil F Pai and William R Schief},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0022283611011272-main.pdf
https://www.sciencedirect.com/science/article/pii/S0022283611011272?via%3Dihub},
doi = {10.1016/j.jmb.2011.10.003},
issn = {1089-8638},
year = {2012},
date = {2012-01-01},
journal = {Journal of molecular biology},
volume = {415},
pages = {175-92},
abstract = {Computational grafting of functional motifs onto scaffold proteins is a promising way to engineer novel proteins with pre-specified functionalities. Typically, protein grafting involves the transplantation of protein side chains from a functional motif onto structurally homologous regions of scaffold proteins. Using this approach, we previously transplanted the human immunodeficiency virus 2F5 and 4E10 epitopes onto heterologous proteins to design novel "epitope-scaffold" antigens. However, side-chain grafting is limited by the availability of scaffolds with compatible backbone for a given epitope structure and offers no route to modify backbone structure to improve mimicry or binding affinity. To address this, we report here a new and more aggressive computational method-backbone grafting of linear motifs-that transplants the backbone and side chains of linear functional motifs onto scaffold proteins. To test this method, we first used side-chain grafting to design new 2F5 epitope scaffolds with improved biophysical characteristics. We then independently transplanted the 2F5 epitope onto three of the same parent scaffolds using the newly developed backbone grafting procedure. Crystal structures of side-chain and backbone grafting designs showed close agreement with both the computational models and the desired epitope structure. In two cases, backbone grafting scaffolds bound antibody 2F5 with 30- and 9-fold higher affinity than corresponding side-chain grafting designs. These results demonstrate that flexible backbone methods for epitope grafting can significantly improve binding affinities over those achieved by fixed backbone methods alone. Backbone grafting of linear motifs is a general method to transplant functional motifs when backbone remodeling of the target scaffold is necessary.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational grafting of functional motifs onto scaffold proteins is a promising way to engineer novel proteins with pre-specified functionalities. Typically, protein grafting involves the transplantation of protein side chains from a functional motif onto structurally homologous regions of scaffold proteins. Using this approach, we previously transplanted the human immunodeficiency virus 2F5 and 4E10 epitopes onto heterologous proteins to design novel "epitope-scaffold" antigens. However, side-chain grafting is limited by the availability of scaffolds with compatible backbone for a given epitope structure and offers no route to modify backbone structure to improve mimicry or binding affinity. To address this, we report here a new and more aggressive computational method-backbone grafting of linear motifs-that transplants the backbone and side chains of linear functional motifs onto scaffold proteins. To test this method, we first used side-chain grafting to design new 2F5 epitope scaffolds with improved biophysical characteristics. We then independently transplanted the 2F5 epitope onto three of the same parent scaffolds using the newly developed backbone grafting procedure. Crystal structures of side-chain and backbone grafting designs showed close agreement with both the computational models and the desired epitope structure. In two cases, backbone grafting scaffolds bound antibody 2F5 with 30- and 9-fold higher affinity than corresponding side-chain grafting designs. These results demonstrate that flexible backbone methods for epitope grafting can significantly improve binding affinities over those achieved by fixed backbone methods alone. Backbone grafting of linear motifs is a general method to transplant functional motifs when backbone remodeling of the target scaffold is necessary.
Justyna Aleksandra Wojdyla, Sarel J Fleishman, David Baker, Colin Kleanthous
Structure of the Ultra-High-Affinity Colicin E2 DNase-Im2 Complex Journal Article
In: Journal of molecular biology, 2012, ISSN: 1089-8638.
@article{432,
title = {Structure of the Ultra-High-Affinity Colicin E2 DNase-Im2 Complex},
author = { Justyna Aleksandra Wojdyla and Sarel J Fleishman and David Baker and Colin Kleanthous},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0022283612000733-main.pdf
https://www.sciencedirect.com/science/article/pii/S0022283612000733?via%3Dihub},
doi = {10.1016/j.jmb.2012.01.019},
issn = {1089-8638},
year = {2012},
date = {2012-01-01},
journal = {Journal of molecular biology},
abstract = {How proteins achieve high-affinity binding to a specific protein partner while simultaneously excluding all others is a major biological problem that has important implications for protein design. We report the crystal structure of the ultra-high-affinity protein-protein complex between the endonuclease domain of colicin E2 and its cognate immunity (Im) protein, Im2 (K(d)~10(-)(15)~M), which, by comparison to previous structural and biophysical data, provides unprecedented insight into how high affinity and selectivity are achieved in this model family of protein complexes. Our study pinpoints the role of structured water molecules in conjoining hotspot residues that govern stability with residues that control selectivity. A key finding is that a single residue, which in a noncognate context massively destabilizes the complex through frustration, does not participate in specificity directly but rather acts as an organizing center for a multitude of specificity interactions across the interface, many of which are water mediated.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
How proteins achieve high-affinity binding to a specific protein partner while simultaneously excluding all others is a major biological problem that has important implications for protein design. We report the crystal structure of the ultra-high-affinity protein-protein complex between the endonuclease domain of colicin E2 and its cognate immunity (Im) protein, Im2 (K(d)~10(-)(15)~M), which, by comparison to previous structural and biophysical data, provides unprecedented insight into how high affinity and selectivity are achieved in this model family of protein complexes. Our study pinpoints the role of structured water molecules in conjoining hotspot residues that govern stability with residues that control selectivity. A key finding is that a single residue, which in a noncognate context massively destabilizes the complex through frustration, does not participate in specificity directly but rather acts as an organizing center for a multitude of specificity interactions across the interface, many of which are water mediated.
Adam J Wargacki, Effendi Leonard, Maung Nyan Win, Drew D Regitsky, Christine Nicole S Santos, Peter B Kim, Susan R Cooper, Ryan M Raisner, Asael Herman, Alicia B Sivitz, Arun Lakshmanaswamy, Yuki Kashiyama, David Baker, Yasuo Yoshikuni
An engineered microbial platform for direct biofuel production from brown macroalgae Journal Article
In: Science, vol. 335, pp. 308-13, 2012, ISSN: 1095-9203.
@article{431,
title = {An engineered microbial platform for direct biofuel production from brown macroalgae},
author = { Adam J Wargacki and Effendi Leonard and Maung Nyan Win and Drew D Regitsky and Christine Nicole S Santos and Peter B Kim and Susan R Cooper and Ryan M Raisner and Asael Herman and Alicia B Sivitz and Arun Lakshmanaswamy and Yuki Kashiyama and David Baker and Yasuo Yoshikuni},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/308.full_.pdf
http://science.sciencemag.org/content/335/6066/308},
doi = {10.1126/science.1214547 },
issn = {1095-9203},
year = {2012},
date = {2012-01-01},
journal = {Science},
volume = {335},
pages = {308-13},
abstract = {Prospecting macroalgae (seaweeds) as feedstocks for bioconversion into biofuels and commodity chemical compounds is limited primarily by the availability of tractable microorganisms that can metabolize alginate polysaccharides. Here, we present the discovery of a 36-kilo-base pair DNA fragment from Vibrio splendidus encoding enzymes for alginate transport and metabolism. The genomic integration of this ensemble, together with an engineered system for extracellular alginate depolymerization, generated a microbial platform that can simultaneously degrade, uptake, and metabolize alginate. When further engineered for ethanol synthesis, this platform enables bioethanol production directly from macroalgae via a consolidated process, achieving a titer of 4.7% volume/volume and a yield of 0.281 weight ethanol/weight dry macroalgae (equivalent to ~80% of the maximum theoretical yield from the sugar composition in macroalgae).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Prospecting macroalgae (seaweeds) as feedstocks for bioconversion into biofuels and commodity chemical compounds is limited primarily by the availability of tractable microorganisms that can metabolize alginate polysaccharides. Here, we present the discovery of a 36-kilo-base pair DNA fragment from Vibrio splendidus encoding enzymes for alginate transport and metabolism. The genomic integration of this ensemble, together with an engineered system for extracellular alginate depolymerization, generated a microbial platform that can simultaneously degrade, uptake, and metabolize alginate. When further engineered for ethanol synthesis, this platform enables bioethanol production directly from macroalgae via a consolidated process, achieving a titer of 4.7% volume/volume and a yield of 0.281 weight ethanol/weight dry macroalgae (equivalent to ~80% of the maximum theoretical yield from the sugar composition in macroalgae).
Ling Wang, Eric A Althoff, Jill Bolduc, Lin Jiang, James Moody, Jonathan K Lassila, Lars Giger, Donald Hilvert, Barry Stoddard, David Baker
Structural analyses of covalent enzyme-substrate analog complexes reveal strengths and limitations of de novo enzyme design Journal Article
In: Journal of molecular biology, vol. 415, pp. 615-25, 2012, ISSN: 1089-8638.
@article{430,
title = {Structural analyses of covalent enzyme-substrate analog complexes reveal strengths and limitations of de novo enzyme design},
author = { Ling Wang and Eric A Althoff and Jill Bolduc and Lin Jiang and James Moody and Jonathan K Lassila and Lars Giger and Donald Hilvert and Barry Stoddard and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0022283611011910-main.pdf
https://www.sciencedirect.com/science/article/pii/S0022283611011910?via%3Dihub},
doi = {10.1016/j.jmb.2011.10.043},
issn = {1089-8638},
year = {2012},
date = {2012-01-01},
journal = {Journal of molecular biology},
volume = {415},
pages = {615-25},
abstract = {We report the cocrystal structures of a computationally designed and experimentally optimized retro-aldol enzyme with covalently bound substrate analogs. The structure with a covalently bound mechanism-based inhibitor is similar to, but not identical with, the design model, with an RMSD of 1.4~r A over active-site residues and equivalent substrate atoms. As in the design model, the binding pocket orients the substrate through hydrophobic interactions with the naphthyl moiety such that the oxygen atoms analogous to the carbinolamine and β-hydroxyl oxygens are positioned near a network of bound waters. However, there are differences between the design model and the structure: the orientation of the naphthyl group and the conformation of the catalytic lysine are slightly different; the bound water network appears to be more extensive; and the bound substrate analog exhibits more conformational heterogeneity than typical native enzyme-inhibitor complexes. Alanine scanning of the active-site residues shows that both the catalytic lysine and the residues around the binding pocket for the substrate naphthyl group make critical contributions to catalysis. Mutating the set of water-coordinating residues also significantly reduces catalytic activity. The crystal structure of the enzyme with a smaller substrate analog that lacks naphthyl ring shows the catalytic lysine to be more flexible than in the naphthyl-substrate complex; increased preorganization of the active site would likely improve catalysis. The covalently bound complex structures and mutagenesis data highlight the strengths and weaknesses of the de novo enzyme design strategy.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We report the cocrystal structures of a computationally designed and experimentally optimized retro-aldol enzyme with covalently bound substrate analogs. The structure with a covalently bound mechanism-based inhibitor is similar to, but not identical with, the design model, with an RMSD of 1.4~r A over active-site residues and equivalent substrate atoms. As in the design model, the binding pocket orients the substrate through hydrophobic interactions with the naphthyl moiety such that the oxygen atoms analogous to the carbinolamine and β-hydroxyl oxygens are positioned near a network of bound waters. However, there are differences between the design model and the structure: the orientation of the naphthyl group and the conformation of the catalytic lysine are slightly different; the bound water network appears to be more extensive; and the bound substrate analog exhibits more conformational heterogeneity than typical native enzyme-inhibitor complexes. Alanine scanning of the active-site residues shows that both the catalytic lysine and the residues around the binding pocket for the substrate naphthyl group make critical contributions to catalysis. Mutating the set of water-coordinating residues also significantly reduces catalytic activity. The crystal structure of the enzyme with a smaller substrate analog that lacks naphthyl ring shows the catalytic lysine to be more flexible than in the naphthyl-substrate complex; increased preorganization of the active site would likely improve catalysis. The covalently bound complex structures and mutagenesis data highlight the strengths and weaknesses of the de novo enzyme design strategy.
Christophe Schmitz, Robert Vernon, Gottfried Otting, David Baker, Thomas Huber
Protein Structure Determination from Pseudocontact Shifts Using ROSETTA Journal Article
In: Journal of molecular biology, 2012, ISSN: 1089-8638.
@article{429,
title = {Protein Structure Determination from Pseudocontact Shifts Using ROSETTA},
author = { Christophe Schmitz and Robert Vernon and Gottfried Otting and David Baker and Thomas Huber},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0022283611013945-main.pdf
https://www.sciencedirect.com/science/article/pii/S0022283611013945},
doi = {10.1016/j.jmb.2011.12.056},
issn = {1089-8638},
year = {2012},
date = {2012-01-01},
journal = {Journal of molecular biology},
abstract = {Paramagnetic metal ions generate pseudocontact shifts (PCSs) in nuclear magnetic resonance spectra that are manifested as easily measurable changes in chemical shifts. Metals can be incorporated into proteins through metal binding tags, and PCS data constitute powerful long-range restraints on the positions of nuclear spins relative to the coordinate system of the magnetic susceptibility anisotropy tensor (Δχ-tensor) of the metal ion. We show that three-dimensional structures of proteins can reliably be determined using PCS data from a single metal binding site combined with backbone chemical shifts. The program PCS-ROSETTA automatically determines the Δχ-tensor and metal position from the PCS data during the structure calculations, without any prior knowledge of the protein structure. The program can determine structures accurately for proteins of up to 150 residues, offering a powerful new approach to protein structure determination that relies exclusively on readily measurable backbone chemical shifts and easily discriminates between correctly and incorrectly folded conformations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Paramagnetic metal ions generate pseudocontact shifts (PCSs) in nuclear magnetic resonance spectra that are manifested as easily measurable changes in chemical shifts. Metals can be incorporated into proteins through metal binding tags, and PCS data constitute powerful long-range restraints on the positions of nuclear spins relative to the coordinate system of the magnetic susceptibility anisotropy tensor (Δχ-tensor) of the metal ion. We show that three-dimensional structures of proteins can reliably be determined using PCS data from a single metal binding site combined with backbone chemical shifts. The program PCS-ROSETTA automatically determines the Δχ-tensor and metal position from the PCS data during the structure calculations, without any prior knowledge of the protein structure. The program can determine structures accurately for proteins of up to 150 residues, offering a powerful new approach to protein structure determination that relies exclusively on readily measurable backbone chemical shifts and easily discriminates between correctly and incorrectly folded conformations.
Vladimir Yarov-Yarovoy, Paul G DeCaen, Ruth E Westenbroek, Chien-Yuan Pan, Todd Scheuer, David Baker, William A Catterall
Structural basis for gating charge movement in the voltage sensor of a sodium channel Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 109, pp. E93-102, 2012, ISSN: 1091-6490.
@article{433,
title = {Structural basis for gating charge movement in the voltage sensor of a sodium channel},
author = { Vladimir Yarov-Yarovoy and Paul G DeCaen and Ruth E Westenbroek and Chien-Yuan Pan and Todd Scheuer and David Baker and William A Catterall},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1.full_.pdf
http://www.pnas.org/content/109/2/E93/1},
doi = {10.1073/pnas.1118434109},
issn = {1091-6490},
year = {2012},
date = {2012-01-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {109},
pages = {E93-102},
abstract = {Voltage-dependent gating of ion channels is essential for electrical signaling in excitable cells, but the structural basis for voltage sensor function is unknown. We constructed high-resolution structural models of resting, intermediate, and activated states of the voltage-sensing domain of the bacterial sodium channel NaChBac using the Rosetta modeling method, crystal structures of related channels, and experimental data showing state-dependent interactions between the gating charge-carrying arginines in the S4 segment and negatively charged residues in neighboring transmembrane segments. The resulting structural models illustrate a network of ionic and hydrogen-bonding interactions that are made sequentially by the gating charges as they move out under the influence of the electric field. The S4 segment slides 6-8 r A outward through a narrow groove formed by the S1, S2, and S3 segments, rotates ~30textdegree, and tilts sideways at a pivot point formed by a highly conserved hydrophobic region near the middle of the voltage sensor. The S4 segment has a 3(10)-helical conformation in the narrow inner gating pore, which allows linear movement of the gating charges across the inner one-half of the membrane. Conformational changes of the intracellular one-half of S4 during activation are rigidly coupled to lateral movement of the S4-S5 linker, which could induce movement of the S5 and S6 segments and open the intracellular gate of the pore. We confirmed the validity of these structural models by comparing with a high-resolution structure of a NaChBac homolog and showing predicted molecular interactions of hydrophobic residues in the S4 segment in disulfide-locking studies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Voltage-dependent gating of ion channels is essential for electrical signaling in excitable cells, but the structural basis for voltage sensor function is unknown. We constructed high-resolution structural models of resting, intermediate, and activated states of the voltage-sensing domain of the bacterial sodium channel NaChBac using the Rosetta modeling method, crystal structures of related channels, and experimental data showing state-dependent interactions between the gating charge-carrying arginines in the S4 segment and negatively charged residues in neighboring transmembrane segments. The resulting structural models illustrate a network of ionic and hydrogen-bonding interactions that are made sequentially by the gating charges as they move out under the influence of the electric field. The S4 segment slides 6-8 r A outward through a narrow groove formed by the S1, S2, and S3 segments, rotates ~30textdegree, and tilts sideways at a pivot point formed by a highly conserved hydrophobic region near the middle of the voltage sensor. The S4 segment has a 3(10)-helical conformation in the narrow inner gating pore, which allows linear movement of the gating charges across the inner one-half of the membrane. Conformational changes of the intracellular one-half of S4 during activation are rigidly coupled to lateral movement of the S4-S5 linker, which could induce movement of the S5 and S6 segments and open the intracellular gate of the pore. We confirmed the validity of these structural models by comparing with a high-resolution structure of a NaChBac homolog and showing predicted molecular interactions of hydrophobic residues in the S4 segment in disulfide-locking studies.
Antoine Loquet, Nikolaos G Sgourakis, Rashmi Gupta, Karin Giller, Dietmar Riedel, Christian Goosmann, Christian Griesinger, Michael Kolbe, David Baker, Stefan Becker, Adam Lange
Atomic model of the type III secretion system needle Journal Article
In: Nature, 2012.
@article{443,
title = {Atomic model of the type III secretion system needle},
author = { Antoine Loquet and Nikolaos G Sgourakis and Rashmi Gupta and Karin Giller and Dietmar Riedel and Christian Goosmann and Christian Griesinger and Michael Kolbe and David Baker and Stefan Becker and Adam Lange},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/nature11079.pdf
https://www.nature.com/articles/nature11079},
doi = {10.1038/nature11079},
year = {2012},
date = {2012-01-01},
journal = {Nature},
abstract = {Pathogenic bacteria using a type III secretion system (T3SS) to manipulate host cells cause many different infections including Shigella dysentery, typhoid fever, enterohaemorrhagic colitis and bubonic plague. An essential part of the T3SS is a hollow needlelike protein filament through which effector proteins are injected into eukaryotic host cells3–6. Currently, the three-dimensional structure of the needle is unknown because it is not amenable to X-ray crystallography and solution NMR, as a result of its inherent non-crystallinity and insolubility. Cryo-electron microscopy combined with crystal or solution NMRsubunit structures has recently provided a powerful hybrid approach for studying supramolecular assemblies7–12, esulting in low-resolution and medium-resolution models13–17. However, such approaches cannot deliver atomic details, especially of the crucial subunit–subunit interfaces, because of the limited cryo-electron microscopic resolution obtained in these studies. Here we report an alternative approach combining recombinant wild-type needle production, solid-state NMR, electron microscopy and Rosetta modelling to reveal the supramolecular interfaces and ultimately the complete atomic structure of the Salmonella typhimurium T3SS needle. We show that the 80-residue subunits form a right-handed helical assembly with roughly 11 subunits per two turns, similar to that of the flagellar filament of S. typhimurium. In contrast to established models of the needle in which the amino terminus of the protein subunit was assumed to be a-helical and positioned inside the needle, our model reveals an extended amino-terminal domain that is positioned on the surface of the needle, while the highly conserved carboxy terminus points towards the lumen.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Pathogenic bacteria using a type III secretion system (T3SS) to manipulate host cells cause many different infections including Shigella dysentery, typhoid fever, enterohaemorrhagic colitis and bubonic plague. An essential part of the T3SS is a hollow needlelike protein filament through which effector proteins are injected into eukaryotic host cells3–6. Currently, the three-dimensional structure of the needle is unknown because it is not amenable to X-ray crystallography and solution NMR, as a result of its inherent non-crystallinity and insolubility. Cryo-electron microscopy combined with crystal or solution NMRsubunit structures has recently provided a powerful hybrid approach for studying supramolecular assemblies7–12, esulting in low-resolution and medium-resolution models13–17. However, such approaches cannot deliver atomic details, especially of the crucial subunit–subunit interfaces, because of the limited cryo-electron microscopic resolution obtained in these studies. Here we report an alternative approach combining recombinant wild-type needle production, solid-state NMR, electron microscopy and Rosetta modelling to reveal the supramolecular interfaces and ultimately the complete atomic structure of the Salmonella typhimurium T3SS needle. We show that the 80-residue subunits form a right-handed helical assembly with roughly 11 subunits per two turns, similar to that of the flagellar filament of S. typhimurium. In contrast to established models of the needle in which the amino terminus of the protein subunit was assumed to be a-helical and positioned inside the needle, our model reveals an extended amino-terminal domain that is positioned on the surface of the needle, while the highly conserved carboxy terminus points towards the lumen.
Christopher B Eiben, Justin B Siegel, Jacob B Bale, Seth Cooper, Firas Khatib, Betty W Shen, Foldit Players, Barry L Stoddard, Zoran Popovic, David Baker
Increased Diels-Alderase activity through backbone remodeling guided by Foldit players Journal Article
In: Nature biotechnology, vol. 30, pp. 190-2, 2012, ISSN: 1546-1696.
@article{434,
title = {Increased Diels-Alderase activity through backbone remodeling guided by Foldit players},
author = { Christopher B Eiben and Justin B Siegel and Jacob B Bale and Seth Cooper and Firas Khatib and Betty W Shen and Foldit Players and Barry L Stoddard and Zoran Popovic and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/nbt.2109.pdf
https://www.nature.com/articles/nbt.2109},
doi = {10.1038/nbt.2109},
issn = {1546-1696},
year = {2012},
date = {2012-00-01},
journal = {Nature biotechnology},
volume = {30},
pages = {190-2},
abstract = {Computational enzyme design holds promise for the production of renewable fuels, drugs and chemicals. De novo enzyme design has generated catalysts for several reactions, but with lower catalytic efficiencies than naturally occurring enzymes. Here we report the use of game-driven crowdsourcing to enhance the activity of a computationally designed enzyme through the functional remodeling of its structure. Players of the online game Foldit were challenged to remodel the backbone of a computationally designed bimolecular Diels-Alderase to enable additional interactions with substrates. Several iterations of design and characterization generated a 24-residue helix-turn-helix motif, including a 13-residue insertion, that increased enzyme activity >18-fold. X-ray crystallography showed that the large insertion adopts a helix-turn-helix structure positioned as in the Foldit model. These results demonstrate that human creativity can extend beyond the macroscopic challenges encountered in everyday life to molecular-scale design problems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational enzyme design holds promise for the production of renewable fuels, drugs and chemicals. De novo enzyme design has generated catalysts for several reactions, but with lower catalytic efficiencies than naturally occurring enzymes. Here we report the use of game-driven crowdsourcing to enhance the activity of a computationally designed enzyme through the functional remodeling of its structure. Players of the online game Foldit were challenged to remodel the backbone of a computationally designed bimolecular Diels-Alderase to enable additional interactions with substrates. Several iterations of design and characterization generated a 24-residue helix-turn-helix motif, including a 13-residue insertion, that increased enzyme activity >18-fold. X-ray crystallography showed that the large insertion adopts a helix-turn-helix structure positioned as in the Foldit model. These results demonstrate that human creativity can extend beyond the macroscopic challenges encountered in everyday life to molecular-scale design problems.
2011
Peter S Brzovic, Clemens C Heikaus, Leonid Kisselev, Robert Vernon, Eric Herbig, Derek Pacheco, Linda Warfield, Peter Littlefield, David Baker, Rachel E Klevit, Steven Hahn
The acidic transcription activator Gcn4 binds the mediator subunit Gal11/Med15 using a simple protein interface forming a fuzzy complex Journal Article
In: Molecular cell, vol. 44, pp. 942-53, 2011, ISSN: 1097-4164.
@article{426,
title = {The acidic transcription activator Gcn4 binds the mediator subunit Gal11/Med15 using a simple protein interface forming a fuzzy complex},
author = { Peter S Brzovic and Clemens C Heikaus and Leonid Kisselev and Robert Vernon and Eric Herbig and Derek Pacheco and Linda Warfield and Peter Littlefield and David Baker and Rachel E Klevit and Steven Hahn},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S1097276511008872-main.pdf
https://www.sciencedirect.com/science/article/pii/S1097276511008872?via%3Dihub},
doi = {10.1016/j.molcel.2011.11.008},
issn = {1097-4164},
year = {2011},
date = {2011-12-01},
journal = {Molecular cell},
volume = {44},
pages = {942-53},
abstract = {The structural basis for binding of the acidic transcription activator Gcn4 and one activator-binding domain of the Mediator subunit Gal11/Med15 was examined by NMR. Gal11 activator-binding domain 1 has a four-helix fold with a small shallow hydrophobic cleft at its center. In the bound complex, eight residues of Gcn4 adopt a helical conformation, allowing three Gcn4 aromatic/aliphatic residues to insert into the Gal11 cleft. The protein-protein interface is dynamic and surprisingly simple, involving only hydrophobic interactions. This allows Gcn4 to bind Gal11 in multiple conformations and orientations, an example of a "fuzzy" complex, where the Gcn4-Gal11 interface cannot be described by a single conformation. Gcn4 uses a similar mechanism to bind two other unrelated activator-binding domains. Functional studies in yeast show the importance of residues at the protein interface, define the minimal requirements for a functional activator, and suggest a mechanism by which activators bind to multiple unrelated targets.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The structural basis for binding of the acidic transcription activator Gcn4 and one activator-binding domain of the Mediator subunit Gal11/Med15 was examined by NMR. Gal11 activator-binding domain 1 has a four-helix fold with a small shallow hydrophobic cleft at its center. In the bound complex, eight residues of Gcn4 adopt a helical conformation, allowing three Gcn4 aromatic/aliphatic residues to insert into the Gal11 cleft. The protein-protein interface is dynamic and surprisingly simple, involving only hydrophobic interactions. This allows Gcn4 to bind Gal11 in multiple conformations and orientations, an example of a "fuzzy" complex, where the Gcn4-Gal11 interface cannot be described by a single conformation. Gcn4 uses a similar mechanism to bind two other unrelated activator-binding domains. Functional studies in yeast show the importance of residues at the protein interface, define the minimal requirements for a functional activator, and suggest a mechanism by which activators bind to multiple unrelated targets.
Firas Khatib, Seth Cooper, Michael D Tyka, Kefan Xu, Ilya Makedon, Zoran Popovic, David Baker, Foldit Players
Algorithm discovery by protein folding game players. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, 2011, ISSN: 1091-6490.
@article{419,
title = {Algorithm discovery by protein folding game players.},
author = { Firas Khatib and Seth Cooper and Michael D Tyka and Kefan Xu and Ilya Makedon and Zoran Popovic and David Baker and Foldit Players},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/18949.full_.pdf
http://www.pnas.org/content/108/47/18949},
doi = {10.1073/pnas.1115898108},
issn = {1091-6490},
year = {2011},
date = {2011-11-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
abstract = {Foldit is a multiplayer online game in which players collaborate and compete to create accurate protein structure models. For specific hard problems, Foldit player solutions can in some cases outperform state-of-the-art computational methods. However, very little is known about how collaborative gameplay produces these results and whether Foldit player strategies can be formalized and structured so that they can be used by computers. To determine whether high performing player strategies could be collectively codified, we augmented the Foldit gameplay mechanics with tools for players to encode their folding strategies as "recipes" and to share their recipes with other players, who are able to further modify and redistribute them. Here we describe the rapid social evolution of player-developed folding algorithms that took place in the year following the introduction of these tools. Players developed over 5,400 different recipes, both by creating new algorithms and by modifying and recombining successful recipes developed by other players. The most successful recipes rapidly spread through the Foldit player population, and two of the recipes became particularly dominant. Examination of the algorithms encoded in these two recipes revealed a striking similarity to an unpublished algorithm developed by scientists over the same period. Benchmark calculations show that the new algorithm independently discovered by scientists and by Foldit players outperforms previously published methods. Thus, online scientific game frameworks have the potential not only to solve hard scientific problems, but also to discover and formalize effective new strategies and algorithms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Foldit is a multiplayer online game in which players collaborate and compete to create accurate protein structure models. For specific hard problems, Foldit player solutions can in some cases outperform state-of-the-art computational methods. However, very little is known about how collaborative gameplay produces these results and whether Foldit player strategies can be formalized and structured so that they can be used by computers. To determine whether high performing player strategies could be collectively codified, we augmented the Foldit gameplay mechanics with tools for players to encode their folding strategies as "recipes" and to share their recipes with other players, who are able to further modify and redistribute them. Here we describe the rapid social evolution of player-developed folding algorithms that took place in the year following the introduction of these tools. Players developed over 5,400 different recipes, both by creating new algorithms and by modifying and recombining successful recipes developed by other players. The most successful recipes rapidly spread through the Foldit player population, and two of the recipes became particularly dominant. Examination of the algorithms encoded in these two recipes revealed a striking similarity to an unpublished algorithm developed by scientists over the same period. Benchmark calculations show that the new algorithm independently discovered by scientists and by Foldit players outperforms previously published methods. Thus, online scientific game frameworks have the potential not only to solve hard scientific problems, but also to discover and formalize effective new strategies and algorithms.
Sarel J Fleishman, Timothy A Whitehead, Eva-Maria Strauch, Jacob E Corn, Sanbo Qin, Huan-Xiang Zhou, Julie C Mitchell, Omar N A Demerdash, Mayuko Takeda-Shitaka, Genki Terashi, Iain H Moal, Xiaofan Li, Paul A Bates, Martin Zacharias, Hahnbeom Park, Jun-su Ko, Hasup Lee, Chaok Seok, Thomas Bourquard, Julie Bernauer, Anne Poupon, J’er^ome Az’e, Seren Soner, Sefik Kerem Ovali, Pemra Ozbek, Nir Ben Tal, T"urkan Haliloglu, Howook Hwang, Thom Vreven, Brian G Pierce, Zhiping Weng, Laura P’erez-Cano, Carles Pons, Juan Fern’andez-Recio, Fan Jiang, Feng Yang, Xinqi Gong, Libin Cao, Xianjin Xu, Bin Liu, Panwen Wang, Chunhua Li, Cunxin Wang, Charles H Robert, Mainak Guharoy, Shiyong Liu, Yangyu Huang, Lin Li, Dachuan Guo, Ying Chen, Yi Xiao, Nir London, Zohar Itzhaki, Ora Schueler-Furman, Yuval Inbar, Vladimir Potapov, Mati Cohen, Gideon Schreiber, Yuko Tsuchiya, Eiji Kanamori, Daron M Standley, Haruki Nakamura, Kengo Kinoshita, Camden M Driggers, Robert G Hall, Jessica L Morgan, Victor L Hsu, Jian Zhan, Yuedong Yang, Yaoqi Zhou, Panagiotis L Kastritis, Alexandre M J J Bonvin, Weiyi Zhang, Carlos J Camacho, Krishna P Kilambi, Aroop Sircar, Jeffrey J Gray, Masahito Ohue, Nobuyuki Uchikoga, Yuri Matsuzaki, Takashi Ishida, Yutaka Akiyama, Raed Khashan, Stephen Bush, Denis Fouches, Alexander Tropsha, Juan Esquivel-Rodr’iguez, Daisuke Kihara, P Benjamin Stranges, Ron Jacak, Brian Kuhlman, Sheng-You Huang, Xiaoqin Zou, Shoshana J Wodak, Joel Janin, David Baker
Community-wide assessment of protein-interface modeling suggests improvements to design methodology Journal Article
In: Journal of Molecular Biology, vol. 414, pp. 289-302, 2011, ISSN: 1089-8638.
@article{598,
title = {Community-wide assessment of protein-interface modeling suggests improvements to design methodology},
author = { Sarel J Fleishman and Timothy A Whitehead and Eva-Maria Strauch and Jacob E Corn and Sanbo Qin and Huan-Xiang Zhou and Julie C Mitchell and Omar N A Demerdash and Mayuko Takeda-Shitaka and Genki Terashi and Iain H Moal and Xiaofan Li and Paul A Bates and Martin Zacharias and Hahnbeom Park and Jun-su Ko and Hasup Lee and Chaok Seok and Thomas Bourquard and Julie Bernauer and Anne Poupon and J'er^ome Az'e and Seren Soner and Sefik Kerem Ovali and Pemra Ozbek and Nir Ben Tal and T"urkan Haliloglu and Howook Hwang and Thom Vreven and Brian G Pierce and Zhiping Weng and Laura P'erez-Cano and Carles Pons and Juan Fern'andez-Recio and Fan Jiang and Feng Yang and Xinqi Gong and Libin Cao and Xianjin Xu and Bin Liu and Panwen Wang and Chunhua Li and Cunxin Wang and Charles H Robert and Mainak Guharoy and Shiyong Liu and Yangyu Huang and Lin Li and Dachuan Guo and Ying Chen and Yi Xiao and Nir London and Zohar Itzhaki and Ora Schueler-Furman and Yuval Inbar and Vladimir Potapov and Mati Cohen and Gideon Schreiber and Yuko Tsuchiya and Eiji Kanamori and Daron M Standley and Haruki Nakamura and Kengo Kinoshita and Camden M Driggers and Robert G Hall and Jessica L Morgan and Victor L Hsu and Jian Zhan and Yuedong Yang and Yaoqi Zhou and Panagiotis L Kastritis and Alexandre M J J Bonvin and Weiyi Zhang and Carlos J Camacho and Krishna P Kilambi and Aroop Sircar and Jeffrey J Gray and Masahito Ohue and Nobuyuki Uchikoga and Yuri Matsuzaki and Takashi Ishida and Yutaka Akiyama and Raed Khashan and Stephen Bush and Denis Fouches and Alexander Tropsha and Juan Esquivel-Rodr'iguez and Daisuke Kihara and P Benjamin Stranges and Ron Jacak and Brian Kuhlman and Sheng-You Huang and Xiaoqin Zou and Shoshana J Wodak and Joel Janin and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0022283611010552-main.pdf
https://www.sciencedirect.com/science/article/pii/S0022283611010552?via%3Dihub},
doi = {10.1016/j.jmb.2011.09.031},
issn = {1089-8638},
year = {2011},
date = {2011-11-01},
journal = {Journal of Molecular Biology},
volume = {414},
pages = {289-302},
abstract = {The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.
Sarel J Fleishman, Jacob E Corn, Eva-Maria Strauch, Timothy A Whitehead, John Karanicolas, David Baker
Hotspot-centric de novo design of protein binders Journal Article
In: Journal of molecular biology, vol. 413, pp. 1047-62, 2011, ISSN: 1089-8638.
@article{592,
title = {Hotspot-centric de novo design of protein binders},
author = { Sarel J Fleishman and Jacob E Corn and Eva-Maria Strauch and Timothy A Whitehead and John Karanicolas and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0022283611009909-main.pdf
https://www.sciencedirect.com/science/article/pii/S0022283611009909?via%3Dihub},
doi = {10.1016/j.jmb.2011.09.001},
issn = {1089-8638},
year = {2011},
date = {2011-11-01},
journal = {Journal of molecular biology},
volume = {413},
pages = {1047-62},
abstract = {Protein-protein interactions play critical roles in biology, and computational design of interactions could be useful in a range of applications. We describe in detail a general approach to de novo design of protein interactions based on computed, energetically optimized interaction hotspots, which was recently used to produce high-affinity binders of influenza hemagglutinin. We present several alternative approaches to identify and build the key hotspot interactions within both core secondary structural elements and variable loop regions and evaluate the methodtextquoterights performance in natural-interface recapitulation. We show that the method generates binding surfaces that are more conformationally restricted than previous design methods, reducing opportunities for off-target interactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-protein interactions play critical roles in biology, and computational design of interactions could be useful in a range of applications. We describe in detail a general approach to de novo design of protein interactions based on computed, energetically optimized interaction hotspots, which was recently used to produce high-affinity binders of influenza hemagglutinin. We present several alternative approaches to identify and build the key hotspot interactions within both core secondary structural elements and variable loop regions and evaluate the methodtextquoterights performance in natural-interface recapitulation. We show that the method generates binding surfaces that are more conformationally restricted than previous design methods, reducing opportunities for off-target interactions.
Miroslaw Gilski, Maciej Kazmierczyk, Szymon Krzywda, Helena Z’abransk’a, Seth Cooper, Zoran Popovi’c, Firas Khatib, Frank DiMaio, James Thompson, David Baker, Iva Pichov’a, Mariusz Jaskolski
High-resolution structure of a retroviral protease folded as a monomer Journal Article
In: Acta Crystallographica. Section D, Biological Crystallography, vol. 67, pp. 907-14, 2011, ISSN: 1399-0047.
@article{593,
title = {High-resolution structure of a retroviral protease folded as a monomer},
author = { Miroslaw Gilski and Maciej Kazmierczyk and Szymon Krzywda and Helena Z'abransk'a and Seth Cooper and Zoran Popovi'c and Firas Khatib and Frank DiMaio and James Thompson and David Baker and Iva Pichov'a and Mariusz Jaskolski},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/lv5014.pdf
http://scripts.iucr.org/cgi-bin/paper?S0907444911035943},
doi = {10.1107/S0907444911035943},
issn = {1399-0047},
year = {2011},
date = {2011-11-01},
journal = {Acta Crystallographica. Section D, Biological Crystallography},
volume = {67},
pages = {907-14},
abstract = {Mason-Pfizer monkey virus (M-PMV), a D-type retrovirus assembling in the cytoplasm, causes simian acquired immunodeficiency syndrome (SAIDS) in rhesus monkeys. Its pepsin-like aspartic protease (retropepsin) is an integral part of the expressed retroviral polyproteins. As in all retroviral life cycles, release and dimerization of the protease (PR) is strictly required for polyprotein processing and virion maturation. Biophysical and NMR studies have indicated that in the absence of substrates or inhibitors M-PMV PR should fold into a stable monomer, but the crystal structure of this protein could not be solved by molecular replacement despite countless attempts. Ultimately, a solution was obtained in mr-rosetta using a model constructed by players of the online protein-folding game Foldit. The structure indeed shows a monomeric protein, with the N- and C-termini completely disordered. On the other hand, the flap loop, which normally gates access to the active site of homodimeric retropepsins, is clearly traceable in the electron density. The flap has an unusual curled shape and a different orientation from both the open and closed states known from dimeric retropepsins. The overall fold of the protein follows the retropepsin canon, but the C(α) deviations are large and the active-site textquoterightDTGtextquoteright loop (here NTG) deviates up to 2.7 r A from the standard conformation. This structure of a monomeric retropepsin determined at high resolution (1.6 r A) provides important extra information for the design of dimerization inhibitors that might be developed as drugs for the treatment of retroviral infections, including AIDS.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mason-Pfizer monkey virus (M-PMV), a D-type retrovirus assembling in the cytoplasm, causes simian acquired immunodeficiency syndrome (SAIDS) in rhesus monkeys. Its pepsin-like aspartic protease (retropepsin) is an integral part of the expressed retroviral polyproteins. As in all retroviral life cycles, release and dimerization of the protease (PR) is strictly required for polyprotein processing and virion maturation. Biophysical and NMR studies have indicated that in the absence of substrates or inhibitors M-PMV PR should fold into a stable monomer, but the crystal structure of this protein could not be solved by molecular replacement despite countless attempts. Ultimately, a solution was obtained in mr-rosetta using a model constructed by players of the online protein-folding game Foldit. The structure indeed shows a monomeric protein, with the N- and C-termini completely disordered. On the other hand, the flap loop, which normally gates access to the active site of homodimeric retropepsins, is clearly traceable in the electron density. The flap has an unusual curled shape and a different orientation from both the open and closed states known from dimeric retropepsins. The overall fold of the protein follows the retropepsin canon, but the C(α) deviations are large and the active-site textquoterightDTGtextquoteright loop (here NTG) deviates up to 2.7 r A from the standard conformation. This structure of a monomeric retropepsin determined at high resolution (1.6 r A) provides important extra information for the design of dimerization inhibitors that might be developed as drugs for the treatment of retroviral infections, including AIDS.
Mihai L Azoitei, Bruno E Correia, Yih-En Andrew Ban, Chris Carrico, Oleksandr Kalyuzhniy, Lei Chen, Alexandria Schroeter, Po-Ssu Huang, Jason S McLellan, Peter D Kwong, David Baker, Roland K Strong, William R Schief
Computation-guided backbone grafting of a discontinuous motif onto a protein scaffold Journal Article
In: Science, vol. 334, pp. 373-6, 2011, ISSN: 1095-9203.
@article{418,
title = {Computation-guided backbone grafting of a discontinuous motif onto a protein scaffold},
author = { Mihai L Azoitei and Bruno E Correia and Yih-En Andrew Ban and Chris Carrico and Oleksandr Kalyuzhniy and Lei Chen and Alexandria Schroeter and Po-Ssu Huang and Jason S McLellan and Peter D Kwong and David Baker and Roland K Strong and William R Schief},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/373.full_.pdf
http://science.sciencemag.org/content/334/6054/373},
issn = {1095-9203},
year = {2011},
date = {2011-10-01},
journal = {Science},
volume = {334},
pages = {373-6},
abstract = {The manipulation of protein backbone structure to control interaction and function is a challenge for protein engineering. We integrated computational design with experimental selection for grafting the backbone and side chains of a two-segment HIV gp120 epitope, targeted by the cross-neutralizing antibody b12, onto an unrelated scaffold protein. The final scaffolds bound b12 with high specificity and with affinity similar to that of gp120, and crystallographic analysis of a scaffold bound to b12 revealed high structural mimicry of the gp120-b12 complex structure. The method can be generalized to design other functional proteins through backbone grafting.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The manipulation of protein backbone structure to control interaction and function is a challenge for protein engineering. We integrated computational design with experimental selection for grafting the backbone and side chains of a two-segment HIV gp120 epitope, targeted by the cross-neutralizing antibody b12, onto an unrelated scaffold protein. The final scaffolds bound b12 with high specificity and with affinity similar to that of gp120, and crystallographic analysis of a scaffold bound to b12 revealed high structural mimicry of the gp120-b12 complex structure. The method can be generalized to design other functional proteins through backbone grafting.
Firas Khatib, Frank DiMaio, Seth Cooper, Maciej Kazmierczyk, Miroslaw Gilski, Szymon Krzywda, Helena Zabranska, Iva Pichova, James Thompson, Zoran Popovi’c, Mariusz Jaskolski, David Baker
Crystal structure of a monomeric retroviral protease solved by protein folding game players Journal Article
In: Nature structural & molecular biology, vol. 18, pp. 1175-7, 2011, ISSN: 1545-9985.
@article{435,
title = {Crystal structure of a monomeric retroviral protease solved by protein folding game players},
author = { Firas Khatib and Frank DiMaio and Seth Cooper and Maciej Kazmierczyk and Miroslaw Gilski and Szymon Krzywda and Helena Zabranska and Iva Pichova and James Thompson and Zoran Popovi'c and Mariusz Jaskolski and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/nsmb.2119.pdf
https://www.nature.com/articles/nsmb.2119},
doi = {10.1038/nsmb.2119},
issn = {1545-9985},
year = {2011},
date = {2011-10-01},
journal = {Nature structural & molecular biology},
volume = {18},
pages = {1175-7},
abstract = {Following the failure of a wide range of attempts to solve the crystal structure of M-PMV retroviral protease by molecular replacement, we challenged players of the protein folding game Foldit to produce accurate models of the protein. Remarkably, Foldit players were able to generate models of sufficient quality for successful molecular replacement and subsequent structure determination. The refined structure provides new insights for the design of antiretroviral drugs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Following the failure of a wide range of attempts to solve the crystal structure of M-PMV retroviral protease by molecular replacement, we challenged players of the protein folding game Foldit to produce accurate models of the protein. Remarkably, Foldit players were able to generate models of sufficient quality for successful molecular replacement and subsequent structure determination. The refined structure provides new insights for the design of antiretroviral drugs.
Eugene Valkov, Anna Stamp, Frank DiMaio, David Baker, Brett Verstak, Pietro Roversi, Stuart Kellie, Matthew J Sweet, Ashley Mansell, Nicholas J Gay, Jennifer L Martin, Bostjan Kobe
Crystal structure of Toll-like receptor adaptor MAL/TIRAP reveals the molecular basis for signal transduction and disease protection Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 108, pp. 14879-84, 2011, ISSN: 1091-6490.
@article{595,
title = {Crystal structure of Toll-like receptor adaptor MAL/TIRAP reveals the molecular basis for signal transduction and disease protection},
author = { Eugene Valkov and Anna Stamp and Frank DiMaio and David Baker and Brett Verstak and Pietro Roversi and Stuart Kellie and Matthew J Sweet and Ashley Mansell and Nicholas J Gay and Jennifer L Martin and Bostjan Kobe},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/14879.full_.pdf
http://www.pnas.org/content/108/36/14879},
doi = {10.1073/pnas.1104780108},
issn = {1091-6490},
year = {2011},
date = {2011-09-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {108},
pages = {14879-84},
abstract = {Initiation of the innate immune response requires agonist recognition by pathogen-recognition receptors such as the Toll-like receptors (TLRs). Toll/interleukin-1 receptor (TIR) domain-containing adaptors are critical in orchestrating the signal transduction pathways after TLR and interleukin-1 receptor activation. Myeloid differentiation primary response gene 88 (MyD88) adaptor-like (MAL)/TIR domain-containing adaptor protein (TIRAP) is involved in bridging MyD88 to TLR2 and TLR4 in response to bacterial infection. Genetic studies have associated a number of unique single-nucleotide polymorphisms in MAL with protection against invasive microbial infection, but a molecular understanding has been hampered by a lack of structural information. The present study describes the crystal structure of MAL TIR domain. Significant structural differences exist in the overall fold of MAL compared with other TIR domain structures: A sequence motif comprising a β-strand in other TIR domains instead corresponds to a long loop, placing the functionally important "BB loop" proline motif in a unique surface position in MAL. The structure suggests possible dimerization and MyD88-interacting interfaces, and we confirm the key interface residues by coimmunoprecipitation using site-directed mutants. Jointly, our results provide a molecular and structural basis for the role of MAL in TLR signaling and disease protection.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Initiation of the innate immune response requires agonist recognition by pathogen-recognition receptors such as the Toll-like receptors (TLRs). Toll/interleukin-1 receptor (TIR) domain-containing adaptors are critical in orchestrating the signal transduction pathways after TLR and interleukin-1 receptor activation. Myeloid differentiation primary response gene 88 (MyD88) adaptor-like (MAL)/TIR domain-containing adaptor protein (TIRAP) is involved in bridging MyD88 to TLR2 and TLR4 in response to bacterial infection. Genetic studies have associated a number of unique single-nucleotide polymorphisms in MAL with protection against invasive microbial infection, but a molecular understanding has been hampered by a lack of structural information. The present study describes the crystal structure of MAL TIR domain. Significant structural differences exist in the overall fold of MAL compared with other TIR domain structures: A sequence motif comprising a β-strand in other TIR domains instead corresponds to a long loop, placing the functionally important "BB loop" proline motif in a unique surface position in MAL. The structure suggests possible dimerization and MyD88-interacting interfaces, and we confirm the key interface residues by coimmunoprecipitation using site-directed mutants. Jointly, our results provide a molecular and structural basis for the role of MAL in TLR signaling and disease protection.
Piyali Saha, Bipasha Barua, Sanchari Bhattacharyya, M M Balamurali, William R Schief, David Baker, Raghavan Varadarajan
Design and characterization of stabilized derivatives of human CD4D12 and CD4D1 Journal Article
In: Biochemistry, vol. 50, pp. 7891-900, 2011, ISSN: 1520-4995.
@article{594,
title = {Design and characterization of stabilized derivatives of human CD4D12 and CD4D1},
author = { Piyali Saha and Bipasha Barua and Sanchari Bhattacharyya and M M Balamurali and William R Schief and David Baker and Raghavan Varadarajan},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/bi200870r.pdf
https://pubs.acs.org/doi/abs/10.1021/bi200870r},
doi = {10.1021/bi200870r},
issn = {1520-4995},
year = {2011},
date = {2011-09-01},
journal = {Biochemistry},
volume = {50},
pages = {7891-900},
abstract = {CD4 is present on the surface of T-lymphocytes and is the primary cellular receptor for HIV-1. CD4 consists of a cytoplasmic tail, one transmembrane region, and four extracellular domains, D1-D4. A construct consisting of the first two domains of CD4 (CD4D12) is folded and binds gp120 with similar affinity as soluble 4-domain CD4 (sCD4). However, the first domain alone (CD4D1) was previously shown to be largely unfolded and had 3-fold weaker affinity for gp120 when compared to sCD4 [Sharma, D.; et al. (2005) Biochemistry 44, 16192-16202]. We now report the design and characterization of three single-site mutants of CD4D12 (G6A, L51I, and V86L) and one multisite mutant of CD4D1 (G6A/L51I/L5K/F98T). G6A, L51I, and V86L are cavity-filling mutations while L5K and F98T are surface mutations which were introduced to minimize the aggregation of CD4D1 upon removal of the second domain. Two mutations, G6A and V86L in CD4D12 increased the stability and yield of the protein relative to the wild-type protein. The mutant CD4D1 (CD4D1a) with the 4 mutations was folded and more stable compared to the original CD4D1, but both bound gp120 with comparable affinity. In in vitro neutralization assays, both CD4D1a and G6A-CD4D12 were able to neutralize diverse HIV-1 viruses with similar IC(50)s as 4-domain CD4. These stabilized derivatives of human CD4 can be useful starting points for the design of other more complex viral entry inhibitors.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
CD4 is present on the surface of T-lymphocytes and is the primary cellular receptor for HIV-1. CD4 consists of a cytoplasmic tail, one transmembrane region, and four extracellular domains, D1-D4. A construct consisting of the first two domains of CD4 (CD4D12) is folded and binds gp120 with similar affinity as soluble 4-domain CD4 (sCD4). However, the first domain alone (CD4D1) was previously shown to be largely unfolded and had 3-fold weaker affinity for gp120 when compared to sCD4 [Sharma, D.; et al. (2005) Biochemistry 44, 16192-16202]. We now report the design and characterization of three single-site mutants of CD4D12 (G6A, L51I, and V86L) and one multisite mutant of CD4D1 (G6A/L51I/L5K/F98T). G6A, L51I, and V86L are cavity-filling mutations while L5K and F98T are surface mutations which were introduced to minimize the aggregation of CD4D1 upon removal of the second domain. Two mutations, G6A and V86L in CD4D12 increased the stability and yield of the protein relative to the wild-type protein. The mutant CD4D1 (CD4D1a) with the 4 mutations was folded and more stable compared to the original CD4D1, but both bound gp120 with comparable affinity. In in vitro neutralization assays, both CD4D1a and G6A-CD4D12 were able to neutralize diverse HIV-1 viruses with similar IC(50)s as 4-domain CD4. These stabilized derivatives of human CD4 can be useful starting points for the design of other more complex viral entry inhibitors.
Sean J Wu, Christopher B Eiben, John H Carra, Ivan Huang, David Zong, Peixian Liu, Cindy T Wu, Jeff Nivala, Josef Dunbar, Tomas Huber, Jeffrey Senft, Rowena Schokman, Matthew D Smith, Jeremy H Mills, Arthur M Friedlander, David Baker, Justin B Siegel
Improvement of a potential anthrax therapeutic by computational protein design Journal Article
In: The Journal of Biological Chemistry, vol. 286, pp. 32586-92, 2011, ISSN: 1083-351X.
@article{591,
title = {Improvement of a potential anthrax therapeutic by computational protein design},
author = { Sean J Wu and Christopher B Eiben and John H Carra and Ivan Huang and David Zong and Peixian Liu and Cindy T Wu and Jeff Nivala and Josef Dunbar and Tomas Huber and Jeffrey Senft and Rowena Schokman and Matthew D Smith and Jeremy H Mills and Arthur M Friedlander and David Baker and Justin B Siegel},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/J.-Biol.-Chem.-2011-Wu-32586-92.pdf
http://www.jbc.org/content/286/37/32586},
doi = {10.1074/jbc.M111.251041},
issn = {1083-351X},
year = {2011},
date = {2011-09-01},
journal = {The Journal of Biological Chemistry},
volume = {286},
pages = {32586-92},
abstract = {Past anthrax attacks in the United States have highlighted the need for improved measures against bioweapons. The virulence of anthrax stems from the shielding properties of the Bacillus anthracis poly-γ-d-glutamic acid capsule. In the presence of excess CapD, a B. anthracis γ-glutamyl transpeptidase, the protective capsule is degraded, and the immune system can successfully combat infection. Although CapD shows promise as a next generation protein therapeutic against anthrax, improvements in production, stability, and therapeutic formulation are needed. In this study, we addressed several of these problems through computational protein engineering techniques. We show that circular permutation of CapD improved production properties and dramatically increased kinetic thermostability. At 45 textdegreeC, CapD was completely inactive after 5 min, but circularly permuted CapD remained almost entirely active after 30 min. In addition, we identify an amino acid substitution that dramatically decreased transpeptidation activity but not hydrolysis. Subsequently, we show that this mutant had a diminished capsule degradation activity, suggesting that CapD catalyzes capsule degradation through a transpeptidation reaction with endogenous amino acids and peptides in serum rather than hydrolysis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Past anthrax attacks in the United States have highlighted the need for improved measures against bioweapons. The virulence of anthrax stems from the shielding properties of the Bacillus anthracis poly-γ-d-glutamic acid capsule. In the presence of excess CapD, a B. anthracis γ-glutamyl transpeptidase, the protective capsule is degraded, and the immune system can successfully combat infection. Although CapD shows promise as a next generation protein therapeutic against anthrax, improvements in production, stability, and therapeutic formulation are needed. In this study, we addressed several of these problems through computational protein engineering techniques. We show that circular permutation of CapD improved production properties and dramatically increased kinetic thermostability. At 45 textdegreeC, CapD was completely inactive after 5 min, but circularly permuted CapD remained almost entirely active after 30 min. In addition, we identify an amino acid substitution that dramatically decreased transpeptidation activity but not hydrolysis. Subsequently, we show that this mutant had a diminished capsule degradation activity, suggesting that CapD catalyzes capsule degradation through a transpeptidation reaction with endogenous amino acids and peptides in serum rather than hydrolysis.
Mindy D Szeto, Sandrine J S Boissel, David Baker, Summer B Thyme
Mining endonuclease cleavage determinants in genomic sequence data. Journal Article
In: The Journal of biological chemistry, vol. 286, pp. 32617-27, 2011, ISSN: 1083-351X.
@article{436,
title = {Mining endonuclease cleavage determinants in genomic sequence data.},
author = { Mindy D Szeto and Sandrine J S Boissel and David Baker and Summer B Thyme},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/J.-Biol.-Chem.-2011-Szeto-32617-27.pdf
http://www.jbc.org/content/286/37/32617},
doi = {10.1074/jbc.M111.259572},
issn = {1083-351X},
year = {2011},
date = {2011-09-01},
journal = {The Journal of biological chemistry},
volume = {286},
pages = {32617-27},
abstract = {Homing endonucleases have great potential as tools for targeted gene therapy and gene correction, but identifying variants of these enzymes capable of cleaving specific DNA targets of interest is necessary before the widespread use of such technologies is possible. We identified homologues of the LAGLIDADG homing endonuclease I-AniI and their putative target insertion sites by BLAST searches followed by examination of the sequences of the flanking genomic regions. Amino acid substitutions in these homologues that were located close to the target site DNA, and thus potentially conferring differences in target specificity, were grafted onto the I-AniI scaffold. Many of these grafts exhibited novel and unexpected specificities. These findings show that the information present in genomic data can be exploited for endonuclease specificity redesign.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Homing endonucleases have great potential as tools for targeted gene therapy and gene correction, but identifying variants of these enzymes capable of cleaving specific DNA targets of interest is necessary before the widespread use of such technologies is possible. We identified homologues of the LAGLIDADG homing endonuclease I-AniI and their putative target insertion sites by BLAST searches followed by examination of the sequences of the flanking genomic regions. Amino acid substitutions in these homologues that were located close to the target site DNA, and thus potentially conferring differences in target specificity, were grafted onto the I-AniI scaffold. Many of these grafts exhibited novel and unexpected specificities. These findings show that the information present in genomic data can be exploited for endonuclease specificity redesign.
Guillaume Bouvignies, Pramodh Vallurupalli, D Flemming Hansen, Bruno E Correia, Oliver Lange, Alaji Bah, Robert M Vernon, Frederick W Dahlquist, David Baker, Lewis E Kay
Solution structure of a minor and transiently formed state of a T4 lysozyme mutant Journal Article
In: Nature, vol. 477, pp. 111-4, 2011, ISSN: 1476-4687.
@article{411,
title = {Solution structure of a minor and transiently formed state of a T4 lysozyme mutant},
author = { Guillaume Bouvignies and Pramodh Vallurupalli and D Flemming Hansen and Bruno E Correia and Oliver Lange and Alaji Bah and Robert M Vernon and Frederick W Dahlquist and David Baker and Lewis E Kay},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/nature10349.pdf
https://www.nature.com/articles/nature10349},
doi = {10.1038/nature10349},
issn = {1476-4687},
year = {2011},
date = {2011-09-01},
journal = {Nature},
volume = {477},
pages = {111-4},
abstract = {Proteins are inherently plastic molecules, whose function often critically depends on excursions between different molecular conformations (conformers). However, a rigorous understanding of the relation between a proteintextquoterights structure, dynamics and function remains elusive. This is because many of the conformers on its energy landscape are only transiently formed and marginally populated (less than a few per cent of the total number of molecules), so that they cannot be individually characterized by most biophysical tools. Here we study a lysozyme mutant from phage T4 that binds hydrophobic molecules and populates an excited state transiently (about 1 ms) to about 3% at 25 textdegreeC (ref. 5). We show that such binding occurs only via the ground state, and present the atomic-level model of the textquoterightinvisibletextquoteright, excited state obtained using a combined strategy of relaxation-dispersion NMR (ref. 6) and CS-Rosetta model building that rationalizes this observation. The model was tested using structure-based design calculations identifying point mutants predicted to stabilize the excited state relative to the ground state. In this way a pair of mutations were introduced, inverting the relative populations of the ground and excited states and altering function. Our results suggest a mechanism for the evolution of a proteintextquoterights function by changing the delicate balance between the states on its energy landscape. More generally, they show that our approach can generate and validate models of excited protein states.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Proteins are inherently plastic molecules, whose function often critically depends on excursions between different molecular conformations (conformers). However, a rigorous understanding of the relation between a proteintextquoterights structure, dynamics and function remains elusive. This is because many of the conformers on its energy landscape are only transiently formed and marginally populated (less than a few per cent of the total number of molecules), so that they cannot be individually characterized by most biophysical tools. Here we study a lysozyme mutant from phage T4 that binds hydrophobic molecules and populates an excited state transiently (about 1 ms) to about 3% at 25 textdegreeC (ref. 5). We show that such binding occurs only via the ground state, and present the atomic-level model of the textquoterightinvisibletextquoteright, excited state obtained using a combined strategy of relaxation-dispersion NMR (ref. 6) and CS-Rosetta model building that rationalizes this observation. The model was tested using structure-based design calculations identifying point mutants predicted to stabilize the excited state relative to the ground state. In this way a pair of mutations were introduced, inverting the relative populations of the ground and excited states and altering function. Our results suggest a mechanism for the evolution of a proteintextquoterights function by changing the delicate balance between the states on its energy landscape. More generally, they show that our approach can generate and validate models of excited protein states.
Lisa R Warner, Krisztina Varga, Oliver F Lange, Susan L Baker, David Baker, Marcelo C Sousa, Arthur Pardi
Structure of the BamC two-domain protein obtained by Rosetta with a limited NMR data set Journal Article
In: Journal of Molecular Biology, vol. 411, pp. 83-95, 2011, ISSN: 1089-8638.
@article{586,
title = {Structure of the BamC two-domain protein obtained by Rosetta with a limited NMR data set},
author = { Lisa R Warner and Krisztina Varga and Oliver F Lange and Susan L Baker and David Baker and Marcelo C Sousa and Arthur Pardi},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0022283611005729-main.pdf
https://www.sciencedirect.com/science/article/pii/S0022283611005729?via%3Dihub},
doi = {10.1016/j.jmb.2011.05.022},
issn = {1089-8638},
year = {2011},
date = {2011-08-01},
journal = {Journal of Molecular Biology},
volume = {411},
pages = {83-95},
abstract = {The CS-RDC-NOE Rosetta program was used to generate the solution structure of a 27-kDa fragment of the Escherichia coli BamC protein from a limited set of NMR data. The BamC protein is a component of the essential five-protein β-barrel assembly machine in E. coli. The first 100 residues in BamC were disordered in solution. The Rosetta calculations showed that BamC$_1$$_0$$_1$$_-$$_3$$_4$$_4$ forms two well-defined domains connected by an ~18-residue linker, where the relative orientation of the domains was not defined. Both domains adopt a helix-grip fold previously observed in the Bet v 1 superfamily. textonesuperior$^5$N relaxation data indicated a high degree of conformational flexibility for the linker connecting the N-terminal domain and the C-terminal domain in BamC. The results here show that CS-RDC-NOE Rosetta is robust and has a high tolerance for misassigned nuclear Overhauser effect restraints, greatly simplifying NMR structure determinations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The CS-RDC-NOE Rosetta program was used to generate the solution structure of a 27-kDa fragment of the Escherichia coli BamC protein from a limited set of NMR data. The BamC protein is a component of the essential five-protein β-barrel assembly machine in E. coli. The first 100 residues in BamC were disordered in solution. The Rosetta calculations showed that BamC$_1$$_0$$_1$$_-$$_3$$_4$$_4$ forms two well-defined domains connected by an ~18-residue linker, where the relative orientation of the domains was not defined. Both domains adopt a helix-grip fold previously observed in the Bet v 1 superfamily. textonesuperior$^5$N relaxation data indicated a high degree of conformational flexibility for the linker connecting the N-terminal domain and the C-terminal domain in BamC. The results here show that CS-RDC-NOE Rosetta is robust and has a high tolerance for misassigned nuclear Overhauser effect restraints, greatly simplifying NMR structure determinations.
James Thompson, David Baker
Incorporation of evolutionary information into Rosetta comparative modeling. Journal Article
In: Proteins, vol. 79, pp. 2380-8, 2011, ISSN: 1097-0134.
@article{421,
title = {Incorporation of evolutionary information into Rosetta comparative modeling.},
author = { James Thompson and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/7a8a6bd9c93cfb06e1f3c0416a914b7494ffd1d2e15654117ed9e259a487cf33.pdf
https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.23046},
doi = {10.1002/prot.23046},
issn = {1097-0134},
year = {2011},
date = {2011-08-01},
journal = {Proteins},
volume = {79},
pages = {2380-8},
abstract = {Prediction of protein structures from sequences is a fundamental problem in computational biology. Algorithms that attempt to predict a structure from sequence primarily use two sources of information. The first source is physical in nature: proteins fold into their lowest energy state. Given an energy function that describes the interactions governing folding, a method for constructing models of protein structures, and the amino acid sequence of a protein of interest, the structure prediction problem becomes a search for the lowest energy structure. Evolution provides an orthogonal source of information: proteins of similar sequences have similar structure, and therefore proteins of known structure can guide modeling. The relatively successful Rosetta approach takes advantage of the first, but not the second source of information during model optimization. Following the classic work by Andrej Sali and colleagues, we develop a probabilistic approach to derive spatial restraints from proteins of known structure using advances in alignment technology and the growth in the number of structures in the Protein Data Bank. These restraints define a region of conformational space that is high-probability, given the template information, and we incorporate them into Rosettatextquoterights comparative modeling protocol. The combined approach performs considerably better on a benchmark based on previous CASP experiments. Incorporating evolutionary information into Rosetta is analogous to incorporating sparse experimental data: in both cases, the additional information eliminates large regions of conformational space and increases the probability that energy-based refinement will hone in on the deep energy minimum at the native state.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Prediction of protein structures from sequences is a fundamental problem in computational biology. Algorithms that attempt to predict a structure from sequence primarily use two sources of information. The first source is physical in nature: proteins fold into their lowest energy state. Given an energy function that describes the interactions governing folding, a method for constructing models of protein structures, and the amino acid sequence of a protein of interest, the structure prediction problem becomes a search for the lowest energy structure. Evolution provides an orthogonal source of information: proteins of similar sequences have similar structure, and therefore proteins of known structure can guide modeling. The relatively successful Rosetta approach takes advantage of the first, but not the second source of information during model optimization. Following the classic work by Andrej Sali and colleagues, we develop a probabilistic approach to derive spatial restraints from proteins of known structure using advances in alignment technology and the growth in the number of structures in the Protein Data Bank. These restraints define a region of conformational space that is high-probability, given the template information, and we incorporate them into Rosettatextquoterights comparative modeling protocol. The combined approach performs considerably better on a benchmark based on previous CASP experiments. Incorporating evolutionary information into Rosetta is analogous to incorporating sparse experimental data: in both cases, the additional information eliminates large regions of conformational space and increases the probability that energy-based refinement will hone in on the deep energy minimum at the native state.
Dmitry M Korzhnev, Robert M Vernon, Tomasz L Religa, Alexandar L Hansen, David Baker, Alan R Fersht, Lewis E Kay
In: Journal of the American Chemical Society, vol. 133, pp. 10974-82, 2011, ISSN: 1520-5126.
@article{589,
title = {Nonnative interactions in the FF domain folding pathway from an atomic resolution structure of a sparsely populated intermediate: an NMR relaxation dispersion study.},
author = { Dmitry M Korzhnev and Robert M Vernon and Tomasz L Religa and Alexandar L Hansen and David Baker and Alan R Fersht and Lewis E Kay},
doi = {10.1021/ja203686t},
issn = {1520-5126},
year = {2011},
date = {2011-07-01},
journal = {Journal of the American Chemical Society},
volume = {133},
pages = {10974-82},
abstract = {Several all-helical single-domain proteins have been shown to fold rapidly (microsecond time scale) to a compact intermediate state and subsequently rearrange more slowly to the native conformation. An understanding of this process has been hindered by difficulties in experimental studies of intermediates in cases where they are both low-populated and only transiently formed. One such example is provided by the on-pathway folding intermediate of the small four-helix bundle FF domain from HYPA/FBP11 that is populated at several percent with a millisecond lifetime at room temperature. Here we have studied the L24A mutant that has been shown previously to form nonnative interactions in the folding transition state. A suite of Carr-Purcell-Meiboom-Gill relaxation dispersion NMR experiments have been used to measure backbone chemical shifts and amide bond vector orientations of the invisible folding intermediate that form the input restraints in calculations of atomic resolution models of its structure. Despite the fact that the intermediate structure has many features that are similar to that of the native state, a set of nonnative contacts is observed that is even more extensive than noted previously for the wild-type (WT) folding intermediate. Such nonnative interactions, which must be broken prior to adoption of the native conformation, explain why the transition from the intermediate state to the native conformer (millisecond time scale) is significantly slower than from the unfolded ensemble to the intermediate and why the L24A mutant folds more slowly than the WT.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Several all-helical single-domain proteins have been shown to fold rapidly (microsecond time scale) to a compact intermediate state and subsequently rearrange more slowly to the native conformation. An understanding of this process has been hindered by difficulties in experimental studies of intermediates in cases where they are both low-populated and only transiently formed. One such example is provided by the on-pathway folding intermediate of the small four-helix bundle FF domain from HYPA/FBP11 that is populated at several percent with a millisecond lifetime at room temperature. Here we have studied the L24A mutant that has been shown previously to form nonnative interactions in the folding transition state. A suite of Carr-Purcell-Meiboom-Gill relaxation dispersion NMR experiments have been used to measure backbone chemical shifts and amide bond vector orientations of the invisible folding intermediate that form the input restraints in calculations of atomic resolution models of its structure. Despite the fact that the intermediate structure has many features that are similar to that of the native state, a set of nonnative contacts is observed that is even more extensive than noted previously for the wild-type (WT) folding intermediate. Such nonnative interactions, which must be broken prior to adoption of the native conformation, explain why the transition from the intermediate state to the native conformer (millisecond time scale) is significantly slower than from the unfolded ensemble to the intermediate and why the L24A mutant folds more slowly than the WT.
Stuart A Sievers, John Karanicolas, Howard W Chang, Anni Zhao, Lin Jiang, Onofrio Zirafi, Jason T Stevens, Jan M”unch, David Baker, David Eisenberg
Structure-based design of non-natural amino-acid inhibitors of amyloid fibril formation Journal Article
In: Nature, 2011, ISSN: 1476-4687.
@article{401,
title = {Structure-based design of non-natural amino-acid inhibitors of amyloid fibril formation},
author = { Stuart A Sievers and John Karanicolas and Howard W Chang and Anni Zhao and Lin Jiang and Onofrio Zirafi and Jason T Stevens and Jan M"unch and David Baker and David Eisenberg},
doi = {10.1038/nature10154},
issn = {1476-4687},
year = {2011},
date = {2011-06-01},
journal = {Nature},
abstract = {Many globular and natively disordered proteins can convert into amyloid fibrils. These fibrils are associated with numerous pathologies as well as with normal cellular functions, and frequently form during protein denaturation. Inhibitors of pathological amyloid fibril formation could be useful in the development of therapeutics, provided that the inhibitors were specific enough to avoid interfering with normal processes. Here we show that computer-aided, structure-based design can yield highly specific peptide inhibitors of amyloid formation. Using known atomic structures of segments of amyloid fibrils as templates, we have designed and characterized an all-d-amino-acid inhibitor of the fibril formation of the tau protein associated with Alzheimertextquoterights disease, and a non-natural l-amino-acid inhibitor of an amyloid fibril that enhances sexual transmission of human immunodeficiency virus. Our results indicate that peptides from structure-based designs can disrupt the fibril formation of full-length proteins, including those, such as tau protein, that lack fully ordered native structures. Because the inhibiting peptides have been designed on structures of dual-β-sheet textquoterightsteric zipperstextquoteright, the successful inhibition of amyloid fibril formation strengthens the hypothesis that amyloid spines contain steric zippers.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many globular and natively disordered proteins can convert into amyloid fibrils. These fibrils are associated with numerous pathologies as well as with normal cellular functions, and frequently form during protein denaturation. Inhibitors of pathological amyloid fibril formation could be useful in the development of therapeutics, provided that the inhibitors were specific enough to avoid interfering with normal processes. Here we show that computer-aided, structure-based design can yield highly specific peptide inhibitors of amyloid formation. Using known atomic structures of segments of amyloid fibrils as templates, we have designed and characterized an all-d-amino-acid inhibitor of the fibril formation of the tau protein associated with Alzheimertextquoterights disease, and a non-natural l-amino-acid inhibitor of an amyloid fibril that enhances sexual transmission of human immunodeficiency virus. Our results indicate that peptides from structure-based designs can disrupt the fibril formation of full-length proteins, including those, such as tau protein, that lack fully ordered native structures. Because the inhibiting peptides have been designed on structures of dual-β-sheet textquoterightsteric zipperstextquoteright, the successful inhibition of amyloid fibril formation strengthens the hypothesis that amyloid spines contain steric zippers.
Yifan Song, Michael Tyka, Andrew Leaver-Fay, James Thompson, David Baker
Structure-guided forcefield optimization Journal Article
In: Proteins, vol. 79, pp. 1898-909, 2011, ISSN: 1097-0134.
@article{585,
title = {Structure-guided forcefield optimization},
author = { Yifan Song and Michael Tyka and Andrew Leaver-Fay and James Thompson and David Baker},
doi = {10.1002/prot.23013},
issn = {1097-0134},
year = {2011},
date = {2011-06-01},
journal = {Proteins},
volume = {79},
pages = {1898-909},
abstract = {Accurate modeling of biomolecular systems requires accurate forcefields. Widely used molecular mechanics (MM) forcefields obtain parameters from experimental data and quantum chemistry calculations on small molecules but do not have a clear way to take advantage of the information in high-resolution macromolecular structures. In contrast, knowledge-based methods largely ignore the physical chemistry of interatomic interactions, and instead derive parameters almost exclusively from macromolecular structures. This can involve considerable double counting of the same physical interactions. Here, we describe a method for forcefield improvement that combines the strengths of the two approaches. We use this method to improve the Rosetta all-atom forcefield, in which the total energy is expressed as the sum of terms representing different physical interactions as in MM forcefields and the parameters are tuned to reproduce the properties of macromolecular structures. To resolve inaccuracies resulting from possible double counting of interactions, we compare distribution functions from low-energy modeled structures to those from crystal structures. The structural and physical bases of the deviations between the modeled and reference structures are identified and used to guide forcefield improvements. We describe improvements resolving double counting between backbone hydrogen bond interactions and Lennard-Jones interactions in helices; between sidechain-backbone hydrogen bonds and the backbone torsion potential; and between the sidechain torsion potential and Lennard-Jones interactions. Discrepancies between computed and observed distributions are also used to guide the incorporation of an explicit Cα-hydrogen bond in β sheets. The method can be used generally to integrate different sources of information for forcefield improvement.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Accurate modeling of biomolecular systems requires accurate forcefields. Widely used molecular mechanics (MM) forcefields obtain parameters from experimental data and quantum chemistry calculations on small molecules but do not have a clear way to take advantage of the information in high-resolution macromolecular structures. In contrast, knowledge-based methods largely ignore the physical chemistry of interatomic interactions, and instead derive parameters almost exclusively from macromolecular structures. This can involve considerable double counting of the same physical interactions. Here, we describe a method for forcefield improvement that combines the strengths of the two approaches. We use this method to improve the Rosetta all-atom forcefield, in which the total energy is expressed as the sum of terms representing different physical interactions as in MM forcefields and the parameters are tuned to reproduce the properties of macromolecular structures. To resolve inaccuracies resulting from possible double counting of interactions, we compare distribution functions from low-energy modeled structures to those from crystal structures. The structural and physical bases of the deviations between the modeled and reference structures are identified and used to guide forcefield improvements. We describe improvements resolving double counting between backbone hydrogen bond interactions and Lennard-Jones interactions in helices; between sidechain-backbone hydrogen bonds and the backbone torsion potential; and between the sidechain torsion potential and Lennard-Jones interactions. Discrepancies between computed and observed distributions are also used to guide the incorporation of an explicit Cα-hydrogen bond in β sheets. The method can be used generally to integrate different sources of information for forcefield improvement.
Richter, Florian AND Leaver-Fay, Andrew AND Khare, Sagar D. AND Bjelic, Sinisa AND Baker, David
De Novo Enzyme Design Using Rosetta3 Journal Article
In: PLoS, 2011.
@article{Richter2011,
title = {De Novo Enzyme Design Using Rosetta3},
author = {Richter, Florian AND Leaver-Fay, Andrew AND Khare, Sagar D. AND Bjelic, Sinisa AND Baker, David
},
url = {https://doi.org/10.1371/journal.pone.0019230},
doi = {10.1371/journal.pone.0019230},
year = {2011},
date = {2011-05-11},
journal = {PLoS},
abstract = {The Rosetta de novo enzyme design protocol has been used to design enzyme catalysts for a variety of chemical reactions, and in principle can be applied to any arbitrary chemical reaction of interest, The process has four stages: 1) choice of a catalytic mechanism and corresponding minimal model active site, 2) identification of sites in a set of scaffold proteins where this minimal active site can be realized, 3) optimization of the identities of the surrounding residues for stabilizing interactions with the transition state and primary catalytic residues, and 4) evaluation and ranking the resulting designed sequences. Stages two through four of this process can be carried out with the Rosetta package, while stage one needs to be done externally. Here, we demonstrate how to carry out the Rosetta enzyme design protocol from start to end in detail using for illustration the triosephosphate isomerase reaction.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Rosetta de novo enzyme design protocol has been used to design enzyme catalysts for a variety of chemical reactions, and in principle can be applied to any arbitrary chemical reaction of interest, The process has four stages: 1) choice of a catalytic mechanism and corresponding minimal model active site, 2) identification of sites in a set of scaffold proteins where this minimal active site can be realized, 3) optimization of the identities of the surrounding residues for stabilizing interactions with the transition state and primary catalytic residues, and 4) evaluation and ranking the resulting designed sequences. Stages two through four of this process can be carried out with the Rosetta package, while stage one needs to be done externally. Here, we demonstrate how to carry out the Rosetta enzyme design protocol from start to end in detail using for illustration the triosephosphate isomerase reaction.
Sarel J Fleishman, Timothy A Whitehead, Damian C Ekiert, Cyrille Dreyfus, Jacob E Corn, Eva-Maria Strauch, Ian A Wilson, David Baker
Computational design of proteins targeting the conserved stem region of influenza hemagglutinin Journal Article
In: Science, vol. 332, pp. 816-21, 2011, ISSN: 1095-9203.
@article{394,
title = {Computational design of proteins targeting the conserved stem region of influenza hemagglutinin},
author = { Sarel J Fleishman and Timothy A Whitehead and Damian C Ekiert and Cyrille Dreyfus and Jacob E Corn and Eva-Maria Strauch and Ian A Wilson and David Baker},
issn = {1095-9203},
year = {2011},
date = {2011-05-01},
journal = {Science},
volume = {332},
pages = {816-21},
abstract = {We describe a general computational method for designing proteins that bind a surface patch of interest on a target macromolecule. Favorable interactions between disembodied amino acid residues and the target surface are identified and used to anchor de novo designed interfaces. The method was used to design proteins that bind a conserved surface patch on the stem of the influenza hemagglutinin (HA) from the 1918 H1N1 pandemic virus. After affinity maturation, two of the designed proteins, HB36 and HB80, bind H1 and H5 HAs with low nanomolar affinity. Further, HB80 inhibits the HA fusogenic conformational changes induced at low pH. The crystal structure of HB36 in complex with 1918/H1 HA revealed that the actual binding interface is nearly identical to that in the computational design model. Such designed binding proteins may be useful for both diagnostics and therapeutics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a general computational method for designing proteins that bind a surface patch of interest on a target macromolecule. Favorable interactions between disembodied amino acid residues and the target surface are identified and used to anchor de novo designed interfaces. The method was used to design proteins that bind a conserved surface patch on the stem of the influenza hemagglutinin (HA) from the 1918 H1N1 pandemic virus. After affinity maturation, two of the designed proteins, HB36 and HB80, bind H1 and H5 HAs with low nanomolar affinity. Further, HB80 inhibits the HA fusogenic conformational changes induced at low pH. The crystal structure of HB36 in complex with 1918/H1 HA revealed that the actual binding interface is nearly identical to that in the computational design model. Such designed binding proteins may be useful for both diagnostics and therapeutics.
Nikolai Windbichler, Miriam Menichelli, Philippos Aris Papathanos, Summer B Thyme, Hui Li, Umut Y Ulge, Blake T Hovde, David Baker, Raymond J Monnat, Austin Burt, Andrea Crisanti
A synthetic homing endonuclease-based gene drive system in the human malaria mosquito Journal Article
In: Nature, vol. 473, pp. 212-5, 2011, ISSN: 1476-4687.
@article{393,
title = {A synthetic homing endonuclease-based gene drive system in the human malaria mosquito},
author = { Nikolai Windbichler and Miriam Menichelli and Philippos Aris Papathanos and Summer B Thyme and Hui Li and Umut Y Ulge and Blake T Hovde and David Baker and Raymond J Monnat and Austin Burt and Andrea Crisanti},
issn = {1476-4687},
year = {2011},
date = {2011-05-01},
journal = {Nature},
volume = {473},
pages = {212-5},
abstract = {Genetic methods of manipulating or eradicating disease vector populations have long been discussed as an attractive alternative to existing control measures because of their potential advantages in terms of effectiveness and species specificity. The development of genetically engineered malaria-resistant mosquitoes has shown, as a proof of principle, the possibility of targeting the mosquitotextquoterights ability to serve as a disease vector. The translation of these achievements into control measures requires an effective technology to spread a genetic modification from laboratory mosquitoes to field populations. We have suggested previously that homing endonuclease genes (HEGs), a class of simple selfish genetic elements, could be exploited for this purpose. Here we demonstrate that a synthetic genetic element, consisting of mosquito regulatory regions and the homing endonuclease gene I-SceI, can substantially increase its transmission to the progeny in transgenic mosquitoes of the human malaria vector Anopheles gambiae. We show that the I-SceI element is able to invade receptive mosquito cage populations rapidly, validating mathematical models for the transmission dynamics of HEGs. Molecular analyses confirm that expression of I-SceI in the male germline induces high rates of site-specific chromosomal cleavage and gene conversion, which results in the gain of the I-SceI gene, and underlies the observed genetic drive. These findings demonstrate a new mechanism by which genetic control measures can be implemented. Our results also show in principle how sequence-specific genetic drive elements like HEGs could be used to take the step from the genetic engineering of individuals to the genetic engineering of populations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Genetic methods of manipulating or eradicating disease vector populations have long been discussed as an attractive alternative to existing control measures because of their potential advantages in terms of effectiveness and species specificity. The development of genetically engineered malaria-resistant mosquitoes has shown, as a proof of principle, the possibility of targeting the mosquitotextquoterights ability to serve as a disease vector. The translation of these achievements into control measures requires an effective technology to spread a genetic modification from laboratory mosquitoes to field populations. We have suggested previously that homing endonuclease genes (HEGs), a class of simple selfish genetic elements, could be exploited for this purpose. Here we demonstrate that a synthetic genetic element, consisting of mosquito regulatory regions and the homing endonuclease gene I-SceI, can substantially increase its transmission to the progeny in transgenic mosquitoes of the human malaria vector Anopheles gambiae. We show that the I-SceI element is able to invade receptive mosquito cage populations rapidly, validating mathematical models for the transmission dynamics of HEGs. Molecular analyses confirm that expression of I-SceI in the male germline induces high rates of site-specific chromosomal cleavage and gene conversion, which results in the gain of the I-SceI gene, and underlies the observed genetic drive. These findings demonstrate a new mechanism by which genetic control measures can be implemented. Our results also show in principle how sequence-specific genetic drive elements like HEGs could be used to take the step from the genetic engineering of individuals to the genetic engineering of populations.
Junjie Zhang, Boxue Ma, Frank DiMaio, Nicholai R Douglas, Lukasz A Joachimiak, David Baker, Judith Frydman, Michael Levitt, Wah Chiu
Cryo-EM structure of a group II chaperonin in the prehydrolysis ATP-bound state leading to lid closure Journal Article
In: Structure (London, England : 1993), vol. 19, pp. 633-9, 2011, ISSN: 1878-4186.
@article{596,
title = {Cryo-EM structure of a group II chaperonin in the prehydrolysis ATP-bound state leading to lid closure},
author = { Junjie Zhang and Boxue Ma and Frank DiMaio and Nicholai R Douglas and Lukasz A Joachimiak and David Baker and Judith Frydman and Michael Levitt and Wah Chiu},
doi = {10.1016/j.str.2011.03.005},
issn = {1878-4186},
year = {2011},
date = {2011-05-01},
journal = {Structure (London, England : 1993)},
volume = {19},
pages = {633-9},
abstract = {Chaperonins are large ATP-driven molecular machines that mediate cellular protein folding. Group II chaperonins use their "built-in lid" to close their central folding chamber. Here we report the structure of an archaeal group II chaperonin in its prehydrolysis ATP-bound state at subnanometer resolution using single particle cryo-electron microscopy (cryo-EM). Structural comparison of Mm-cpn in ATP-free, ATP-bound, and ATP-hydrolysis states reveals that ATP binding alone causes the chaperonin to close slightly with a ~45textdegree counterclockwise rotation of the apical domain. The subsequent ATP hydrolysis drives each subunit to rock toward the folding chamber and to close the lid completely. These motions are attributable to the local interactions of specific active site residues with the nucleotide, the tight couplings between the apical and intermediate domains within the subunit, and the aligned interactions between two subunits across the rings. This mechanism of structural changes in response to ATP is entirely different from those found in group I chaperonins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Chaperonins are large ATP-driven molecular machines that mediate cellular protein folding. Group II chaperonins use their “built-in lid” to close their central folding chamber. Here we report the structure of an archaeal group II chaperonin in its prehydrolysis ATP-bound state at subnanometer resolution using single particle cryo-electron microscopy (cryo-EM). Structural comparison of Mm-cpn in ATP-free, ATP-bound, and ATP-hydrolysis states reveals that ATP binding alone causes the chaperonin to close slightly with a ~45textdegree counterclockwise rotation of the apical domain. The subsequent ATP hydrolysis drives each subunit to rock toward the folding chamber and to close the lid completely. These motions are attributable to the local interactions of specific active site residues with the nucleotide, the tight couplings between the apical and intermediate domains within the subunit, and the aligned interactions between two subunits across the rings. This mechanism of structural changes in response to ATP is entirely different from those found in group I chaperonins.
Andrzej Lyskowski, Jesper S Oeemig, Anniina Jaakkonen, Katariina Rommi, Frank DiMaio, Dongwen Zhou, Tommi Kajander, David Baker, Alexander Wlodawer, Adrian Goldman, Hideo Iwa”i
Cloning, expression, purification, crystallization and preliminary X-ray diffraction data of the Pyrococcus horikoshii RadA intein Journal Article
In: Acta Crystallographica. Section F, Structural Biology and Crystallization Communications, vol. 67, pp. 623-6, 2011, ISSN: 1744-3091.
@article{599,
title = {Cloning, expression, purification, crystallization and preliminary X-ray diffraction data of the Pyrococcus horikoshii RadA intein},
author = { Andrzej Lyskowski and Jesper S Oeemig and Anniina Jaakkonen and Katariina Rommi and Frank DiMaio and Dongwen Zhou and Tommi Kajander and David Baker and Alexander Wlodawer and Adrian Goldman and Hideo Iwa"i},
doi = {10.1107/S1744309111008372},
issn = {1744-3091},
year = {2011},
date = {2011-05-01},
journal = {Acta Crystallographica. Section F, Structural Biology and Crystallization Communications},
volume = {67},
pages = {623-6},
abstract = {The RadA intein from the hyperthermophilic archaebacterium Pyrococcus horikoshii was cloned, expressed and purified for subsequent structure determination. The protein crystallized rapidly in several conditions. The best crystals, which diffracted to 1.75 r A resolution, were harvested from drops consisting of 0.1 M HEPES pH 7.5, 3.0 M NaCl and were cryoprotected with Paratone-N before flash-cooling. The collected data were processed in the orthorhombic space group P2(1)2(1)2(1), with unit-cell parameters a = 58.1},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The RadA intein from the hyperthermophilic archaebacterium Pyrococcus horikoshii was cloned, expressed and purified for subsequent structure determination. The protein crystallized rapidly in several conditions. The best crystals, which diffracted to 1.75 r A resolution, were harvested from drops consisting of 0.1 M HEPES pH 7.5, 3.0 M NaCl and were cryoprotected with Paratone-N before flash-cooling. The collected data were processed in the orthorhombic space group P2(1)2(1)2(1), with unit-cell parameters a = 58.1
Frank DiMaio, Thomas C Terwilliger, Randy J Read, Alexander Wlodawer, Gustav Oberdorfer, Ulrike Wagner, Eugene Valkov, Assaf Alon, Deborah Fass, Herbert L Axelrod, Debanu Das, Sergey M Vorobiev, Hideo Iwa”i, P Raj Pokkuluri, David Baker
Improved molecular replacement by density- and energy-guided protein structure optimization Journal Article
In: Nature, 2011, ISSN: 1476-4687.
@article{389,
title = {Improved molecular replacement by density- and energy-guided protein structure optimization},
author = { Frank DiMaio and Thomas C Terwilliger and Randy J Read and Alexander Wlodawer and Gustav Oberdorfer and Ulrike Wagner and Eugene Valkov and Assaf Alon and Deborah Fass and Herbert L Axelrod and Debanu Das and Sergey M Vorobiev and Hideo Iwa"i and P Raj Pokkuluri and David Baker},
issn = {1476-4687},
year = {2011},
date = {2011-05-01},
journal = {Nature},
abstract = {Molecular replacement procedures, which search for placements of a starting model within the crystallographic unit cell that best account for the measured diffraction amplitudes, followed by automatic chain tracing methods, have allowed the rapid solution of large numbers of protein crystal structures. Despite extensive work, molecular replacement or the subsequent rebuilding usually fail with more divergent starting models based on remote homologues with less than 30% sequence identity. Here we show that this limitation can be substantially reduced by combining algorithms for protein structure modelling with those developed for crystallographic structure determination. An approach integrating Rosetta structure modelling with Autobuild chain tracing yielded high-resolution structures for 8 of 13 X-ray diffraction data sets that could not be solved in the laboratories of expert crystallographers and that remained unsolved after application of an extensive array of alternative approaches. We estimate that the new method should allow rapid structure determination without experimental phase information for over half the cases where current methods fail, given diffraction data sets of better than 3.2 r A resolution, four or fewer copies in the asymmetric unit, and the availability of structures of homologous proteins with >20% sequence identity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Molecular replacement procedures, which search for placements of a starting model within the crystallographic unit cell that best account for the measured diffraction amplitudes, followed by automatic chain tracing methods, have allowed the rapid solution of large numbers of protein crystal structures. Despite extensive work, molecular replacement or the subsequent rebuilding usually fail with more divergent starting models based on remote homologues with less than 30% sequence identity. Here we show that this limitation can be substantially reduced by combining algorithms for protein structure modelling with those developed for crystallographic structure determination. An approach integrating Rosetta structure modelling with Autobuild chain tracing yielded high-resolution structures for 8 of 13 X-ray diffraction data sets that could not be solved in the laboratories of expert crystallographers and that remained unsolved after application of an extensive array of alternative approaches. We estimate that the new method should allow rapid structure determination without experimental phase information for over half the cases where current methods fail, given diffraction data sets of better than 3.2 r A resolution, four or fewer copies in the asymmetric unit, and the availability of structures of homologous proteins with >20% sequence identity.
Nikolaos G Sgourakis, Oliver F Lange, Frank DiMaio, Ingemar André, Nicholas C Fitzkee, Paolo Rossi, Gaetano T Montelione, Ad Bax, David Baker
Determination of the Structures of Symmetric Protein Oligomers from NMR Chemical Shifts and Residual Dipolar Couplings Journal Article
In: Journal of the American Chemical Society, 2011, ISSN: 1520-5126.
@article{350,
title = {Determination of the Structures of Symmetric Protein Oligomers from NMR Chemical Shifts and Residual Dipolar Couplings},
author = { Nikolaos G Sgourakis and Oliver F Lange and Frank DiMaio and Ingemar André and Nicholas C Fitzkee and Paolo Rossi and Gaetano T Montelione and Ad Bax and David Baker},
issn = {1520-5126},
year = {2011},
date = {2011-04-01},
journal = {Journal of the American Chemical Society},
abstract = {Symmetric protein dimers, trimers, and higher-order cyclic oligomers play key roles in many biological processes. However, structural studies of oligomeric systems by solution NMR can be difficult due to slow tumbling of the system and the difficulty in identifying NOE interactions across protein interfaces. Here, we present an automated method (RosettaOligomers) for determining the solution structures of oligomeric systems using only chemical shifts, sparse NOEs, and domain orientation restraints from residual dipolar couplings (RDCs) without a need for a previously determined structure of the monomeric subunit. The method integrates previously developed Rosetta protocols for solving the structures of monomeric proteins using sparse NMR data and for predicting the structures of both nonintertwined and intertwined symmetric oligomers. We illustrated the performance of the method using a benchmark set of nine protein dimers, one trimer, and one tetramer with available experimental data and various interface topologies. The final converged structures are found to be in good agreement with both experimental data and previously published high-resolution structures. The new approach is more readily applicable to large oligomeric systems than conventional structure-determination protocols, which often require a large number of NOEs, and will likely become increasingly relevant as more high-molecular weight systems are studied by NMR.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Symmetric protein dimers, trimers, and higher-order cyclic oligomers play key roles in many biological processes. However, structural studies of oligomeric systems by solution NMR can be difficult due to slow tumbling of the system and the difficulty in identifying NOE interactions across protein interfaces. Here, we present an automated method (RosettaOligomers) for determining the solution structures of oligomeric systems using only chemical shifts, sparse NOEs, and domain orientation restraints from residual dipolar couplings (RDCs) without a need for a previously determined structure of the monomeric subunit. The method integrates previously developed Rosetta protocols for solving the structures of monomeric proteins using sparse NMR data and for predicting the structures of both nonintertwined and intertwined symmetric oligomers. We illustrated the performance of the method using a benchmark set of nine protein dimers, one trimer, and one tetramer with available experimental data and various interface topologies. The final converged structures are found to be in good agreement with both experimental data and previously published high-resolution structures. The new approach is more readily applicable to large oligomeric systems than conventional structure-determination protocols, which often require a large number of NOEs, and will likely become increasingly relevant as more high-molecular weight systems are studied by NMR.
Olga Khersonsky, Daniela R”othlisberger, Andrew M Wollacott, Paul Murphy, Orly Dym, Shira Albeck, Gert Kiss, K N Houk, David Baker, Dan S Tawfik
Optimization of the In-Silico-Designed Kemp Eliminase KE70 by Computational Design and Directed Evolution Journal Article
In: Journal of molecular biology, vol. 407, pp. 391-412, 2011, ISSN: 1089-8638.
@article{351,
title = {Optimization of the In-Silico-Designed Kemp Eliminase KE70 by Computational Design and Directed Evolution},
author = { Olga Khersonsky and Daniela R"othlisberger and Andrew M Wollacott and Paul Murphy and Orly Dym and Shira Albeck and Gert Kiss and K N Houk and David Baker and Dan S Tawfik},
issn = {1089-8638},
year = {2011},
date = {2011-04-01},
journal = {Journal of molecular biology},
volume = {407},
pages = {391-412},
abstract = {Although de novo computational enzyme design has been shown to be feasible, the field is still in its infancy: the kinetic parameters of designed enzymes are still orders of magnitude lower than those of naturally occurring ones. Nonetheless, designed enzymes can be improved by directed evolution, as recently exemplified for the designed Kemp eliminase KE07. Random mutagenesis and screening resulted in variants with >200-fold higher catalytic efficiency and provided insights about features missing in the designed enzyme. Here we describe the optimization of KE70, another designed Kemp eliminase. Amino acid substitutions predicted to improve catalysis in design calculations involving extensive backbone sampling were individually tested. Those proven beneficial were combinatorially incorporated into the originally designed KE70 along with random mutations, and the resulting libraries were screened for improved eliminase activity. Nine rounds of mutation and selection resulted in >400-fold improvement in the catalytic efficiency of the original KE70 design, reflected in both higher k(cat) values and lower K(m) values, with the best variants exhibiting k(cat)/K(m) values of >5texttimes10(4)~s(-)(1) M(-1). The optimized KE70 variants were characterized structurally and biochemically, providing insights into the origins of the improvements in catalysis. Three primary contributions were identified: first, the reshaping of the active-site cavity to achieve tighter substrate binding; second, the fine-tuning of electrostatics around the catalytic His-Asp dyad; and, third, the stabilization of the active-site dyad in a conformation optimal for catalysis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Although de novo computational enzyme design has been shown to be feasible, the field is still in its infancy: the kinetic parameters of designed enzymes are still orders of magnitude lower than those of naturally occurring ones. Nonetheless, designed enzymes can be improved by directed evolution, as recently exemplified for the designed Kemp eliminase KE07. Random mutagenesis and screening resulted in variants with >200-fold higher catalytic efficiency and provided insights about features missing in the designed enzyme. Here we describe the optimization of KE70, another designed Kemp eliminase. Amino acid substitutions predicted to improve catalysis in design calculations involving extensive backbone sampling were individually tested. Those proven beneficial were combinatorially incorporated into the originally designed KE70 along with random mutations, and the resulting libraries were screened for improved eliminase activity. Nine rounds of mutation and selection resulted in >400-fold improvement in the catalytic efficiency of the original KE70 design, reflected in both higher k(cat) values and lower K(m) values, with the best variants exhibiting k(cat)/K(m) values of >5texttimes10(4)~s(-)(1) M(-1). The optimized KE70 variants were characterized structurally and biochemically, providing insights into the origins of the improvements in catalysis. Three primary contributions were identified: first, the reshaping of the active-site cavity to achieve tighter substrate binding; second, the fine-tuning of electrostatics around the catalytic His-Asp dyad; and, third, the stabilization of the active-site dyad in a conformation optimal for catalysis.
Sarel J Fleishman, Sagar D Khare, Nobuyasu Koga, David Baker
Restricted sidechain plasticity in the structures of native proteins and complexes Journal Article
In: Protein science, vol. 20, pp. 753-7, 2011, ISSN: 1469-896X.
@article{352,
title = {Restricted sidechain plasticity in the structures of native proteins and complexes},
author = { Sarel J Fleishman and Sagar D Khare and Nobuyasu Koga and David Baker},
doi = {10.1002/pro.604},
issn = {1469-896X},
year = {2011},
date = {2011-04-01},
journal = {Protein science},
volume = {20},
pages = {753-7},
abstract = {Protein-design methodology can now generate models of protein structures and interfaces with computed energies in the range of those of naturally occurring structures. Comparison of the properties of native structures and complexes to isoenergetic design models can provide insight into the properties of the former that reflect selection pressure for factors beyond the energy of the native state. We report here that sidechains in native structures and interfaces are significantly more constrained than designed interfaces and structures with equal computed binding energy or stability, which may reflect selection against potentially deleterious non-native interactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-design methodology can now generate models of protein structures and interfaces with computed energies in the range of those of naturally occurring structures. Comparison of the properties of native structures and complexes to isoenergetic design models can provide insight into the properties of the former that reflect selection pressure for factors beyond the energy of the native state. We report here that sidechains in native structures and interfaces are significantly more constrained than designed interfaces and structures with equal computed binding energy or stability, which may reflect selection against potentially deleterious non-native interactions.
John Karanicolas, Jacob E Corn, Irwin Chen, Lukasz A Joachimiak, Orly Dym, Sun H Peck, Shira Albeck, Tamar Unger, Wenxin Hu, Gaohua Liu, Scott Delbecq, Gaetano T Montelione, Clint P Spiegel, David R Liu, David Baker
A De Novo Protein Binding Pair By Computational Design and Directed Evolution Journal Article
In: Molecular cell, 2011, ISSN: 1097-4164.
@article{353,
title = {A De Novo Protein Binding Pair By Computational Design and Directed Evolution},
author = { John Karanicolas and Jacob E Corn and Irwin Chen and Lukasz A Joachimiak and Orly Dym and Sun H Peck and Shira Albeck and Tamar Unger and Wenxin Hu and Gaohua Liu and Scott Delbecq and Gaetano T Montelione and Clint P Spiegel and David R Liu and David Baker},
issn = {1097-4164},
year = {2011},
date = {2011-03-01},
journal = {Molecular cell},
abstract = {The de novo design of protein-protein interfaces is a stringent test of our understanding of the principles underlying protein-protein interactions and would enable unique approaches to biological and medical challenges. Here we describe a motif-based method to computationally design protein-protein complexes with native-like interface composition and interaction density. Using this method we designed a pair of proteins, Prb and Pdar, that heterodimerize with a Kd of 130~nM, 1000-fold tighter than any previously designed de novo protein-protein complex. Directed evolution identified two point mutations that improve affinity to 180 pM. Crystal structures of an affinity-matured complex reveal binding is entirely through the designed interface residues. Surprisingly, in the in~vitro evolved complex one of the partners is rotated 180textdegree relative to the original design model, yet still maintains the central computationally designed hotspot interaction and preserves the character of many peripheral interactions. This work demonstrates that high-affinity protein interfaces can be created by designing complementary interaction surfaces on two noninteracting partners and underscores remaining challenges.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The de novo design of protein-protein interfaces is a stringent test of our understanding of the principles underlying protein-protein interactions and would enable unique approaches to biological and medical challenges. Here we describe a motif-based method to computationally design protein-protein complexes with native-like interface composition and interaction density. Using this method we designed a pair of proteins, Prb and Pdar, that heterodimerize with a Kd of 130~nM, 1000-fold tighter than any previously designed de novo protein-protein complex. Directed evolution identified two point mutations that improve affinity to 180 pM. Crystal structures of an affinity-matured complex reveal binding is entirely through the designed interface residues. Surprisingly, in the in~vitro evolved complex one of the partners is rotated 180textdegree relative to the original design model, yet still maintains the central computationally designed hotspot interaction and preserves the character of many peripheral interactions. This work demonstrates that high-affinity protein interfaces can be created by designing complementary interaction surfaces on two noninteracting partners and underscores remaining challenges.
Elizabeth H Kellogg, Andrew Leaver-Fay, David Baker
Role of conformational sampling in computing mutation-induced changes in protein structure and stability Journal Article
In: Proteins, vol. 79, pp. 830-8, 2011, ISSN: 1097-0134.
@article{354,
title = {Role of conformational sampling in computing mutation-induced changes in protein structure and stability},
author = { Elizabeth H Kellogg and Andrew Leaver-Fay and David Baker},
doi = {10.1002/prot.22921},
issn = {1097-0134},
year = {2011},
date = {2011-03-01},
journal = {Proteins},
volume = {79},
pages = {830-8},
abstract = {The prediction of changes in protein stability and structure resulting from single amino acid substitutions is both a fundamental test of macromolecular modeling methodology and an important current problem as high throughput sequencing reveals sequence polymorphisms at an increasing rate. In principle, given the structure of a wild-type protein and a point mutation whose effects are to be predicted, an accurate method should recapitulate both the structural changes and the change in the folding-free energy. Here, we explore the performance of protocols which sample an increasing diversity of conformations. We find that surprisingly similar performances in predicting changes in stability are achieved using protocols that involve very different amounts of conformational sampling, provided that the resolution of the force field is matched to the resolution of the sampling method. Methods involving backbone sampling can in some cases closely recapitulate the structural changes accompanying mutations but not surprisingly tend to do more harm than good in cases where structural changes are negligible. Analysis of the outliers in the stability change calculations suggests areas needing particular improvement; these include the balance between desolvation and the formation of favorable buried polar interactions, and unfolded state modeling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The prediction of changes in protein stability and structure resulting from single amino acid substitutions is both a fundamental test of macromolecular modeling methodology and an important current problem as high throughput sequencing reveals sequence polymorphisms at an increasing rate. In principle, given the structure of a wild-type protein and a point mutation whose effects are to be predicted, an accurate method should recapitulate both the structural changes and the change in the folding-free energy. Here, we explore the performance of protocols which sample an increasing diversity of conformations. We find that surprisingly similar performances in predicting changes in stability are achieved using protocols that involve very different amounts of conformational sampling, provided that the resolution of the force field is matched to the resolution of the sampling method. Methods involving backbone sampling can in some cases closely recapitulate the structural changes accompanying mutations but not surprisingly tend to do more harm than good in cases where structural changes are negligible. Analysis of the outliers in the stability change calculations suggests areas needing particular improvement; these include the balance between desolvation and the formation of favorable buried polar interactions, and unfolded state modeling.
Umut Y Ulge, David A Baker, Raymond J Monnat
Comprehensive computational design of mCreI homing endonuclease cleavage specificity for genome engineering Journal Article
In: Nucleic acids research, 2011, ISSN: 1362-4962.
@article{356,
title = {Comprehensive computational design of mCreI homing endonuclease cleavage specificity for genome engineering},
author = { Umut Y Ulge and David A Baker and Raymond J Monnat},
issn = {1362-4962},
year = {2011},
date = {2011-02-01},
journal = {Nucleic acids research},
abstract = {Homing endonucleases (HEs) cleave long (~20 bp) DNA target sites with high site specificity to catalyze the lateral transfer of parasitic DNA elements. In order to determine whether comprehensive computational design could be used as a general strategy to engineer new HE target site specificities, we used RosettaDesign (RD) to generate 3200 different variants of the mCreI LAGLIDADG HE towards 16 different base pair positions in the 22 bp mCreI target site. Experimental verification of a range of these designs demonstrated that over 2/3 (24 of 35 designs, 69%) had the intended new site specificity, and that 14 of the 15 attempted specificity shifts (93%) were achieved. These results demonstrate the feasibility of using structure-based computational design to engineer HE variants with novel target site specificities to facilitate genome engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Homing endonucleases (HEs) cleave long (~20 bp) DNA target sites with high site specificity to catalyze the lateral transfer of parasitic DNA elements. In order to determine whether comprehensive computational design could be used as a general strategy to engineer new HE target site specificities, we used RosettaDesign (RD) to generate 3200 different variants of the mCreI LAGLIDADG HE towards 16 different base pair positions in the 22 bp mCreI target site. Experimental verification of a range of these designs demonstrated that over 2/3 (24 of 35 designs, 69%) had the intended new site specificity, and that 14 of the 15 attempted specificity shifts (93%) were achieved. These results demonstrate the feasibility of using structure-based computational design to engineer HE variants with novel target site specificities to facilitate genome engineering.
Mi Li, Frank DiMaio, Dongwen Zhou, Alla Gustchina, Jacek Lubkowski, Zbigniew Dauter, David Baker, Alexander Wlodawer
Crystal structure of XMRV protease differs from the structures of other retropepsins Journal Article
In: Nature structural & molecular biology, vol. 18, pp. 227-9, 2011, ISSN: 1545-9985.
@article{355,
title = {Crystal structure of XMRV protease differs from the structures of other retropepsins},
author = { Mi Li and Frank DiMaio and Dongwen Zhou and Alla Gustchina and Jacek Lubkowski and Zbigniew Dauter and David Baker and Alexander Wlodawer},
issn = {1545-9985},
year = {2011},
date = {2011-02-01},
journal = {Nature structural & molecular biology},
volume = {18},
pages = {227-9},
abstract = {Using energy and density guided Rosetta refinement to improve molecular replacement, we determined the crystal structure of the protease encoded by xenotropic murine leukemia virus-related virus (XMRV). Despite overall similarity of XMRV protease to other retropepsins, the topology of its dimer interface more closely resembles those of the monomeric, pepsin-like enzymes. Thus, XMRV protease may represent a distinct branch of the aspartic protease family.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Using energy and density guided Rosetta refinement to improve molecular replacement, we determined the crystal structure of the protease encoded by xenotropic murine leukemia virus-related virus (XMRV). Despite overall similarity of XMRV protease to other retropepsins, the topology of its dimer interface more closely resembles those of the monomeric, pepsin-like enzymes. Thus, XMRV protease may represent a distinct branch of the aspartic protease family.
Dong-Hua Chen, Matthew L Baker, Corey F Hryc, Frank DiMaio, Joanita Jakana, Weimin Wu, Matthew Dougherty, Cameron Haase-Pettingell, Michael F Schmid, Wen Jiang, David Baker, Jonathan A King, Wah Chiu
Structural basis for scaffolding-mediated assembly and maturation of a dsDNA virus Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 108, pp. 1355-60, 2011, ISSN: 1091-6490.
@article{358,
title = {Structural basis for scaffolding-mediated assembly and maturation of a dsDNA virus},
author = { Dong-Hua Chen and Matthew L Baker and Corey F Hryc and Frank DiMaio and Joanita Jakana and Weimin Wu and Matthew Dougherty and Cameron Haase-Pettingell and Michael F Schmid and Wen Jiang and David Baker and Jonathan A King and Wah Chiu},
issn = {1091-6490},
year = {2011},
date = {2011-01-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {108},
pages = {1355-60},
abstract = {Formation of many dsDNA viruses begins with the assembly of a procapsid, containing scaffolding proteins and a multisubunit portal but lacking DNA, which matures into an infectious virion. This process, conserved among dsDNA viruses such as herpes viruses and bacteriophages, is key to forming infectious virions. Bacteriophage P22 has served as a model system for this study in the past several decades. However, how capsid assembly is initiated, where and how scaffolding proteins bind to coat proteins in the procapsid, and the conformational changes upon capsid maturation still remain elusive. Here, we report Cα backbone models for the P22 procapsid and infectious virion derived from electron cryomicroscopy density maps determined at 3.8- and 4.0-A resolution, respectively, and the first procapsid structure at subnanometer resolution without imposing symmetry. The procapsid structures show the scaffolding protein interacting electrostatically with the N terminus (N arm) of the coat protein through its C-terminal helix-loop-helix motif, as well as unexpected interactions between 10 scaffolding proteins and the 12-fold portal located at a unique vertex. These suggest a critical role for the scaffolding proteins both in initiating the capsid assembly at the portal vertex and propagating its growth on a T = 7 icosahedral lattice. Comparison of the procapsid and the virion backbone models reveals coordinated and complex conformational changes. These structural observations allow us to propose a more detailed molecular mechanism for the scaffolding-mediated capsid assembly initiation including portal incorporation, release of scaffolding proteins upon DNA packaging, and maturation into infectious virions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Formation of many dsDNA viruses begins with the assembly of a procapsid, containing scaffolding proteins and a multisubunit portal but lacking DNA, which matures into an infectious virion. This process, conserved among dsDNA viruses such as herpes viruses and bacteriophages, is key to forming infectious virions. Bacteriophage P22 has served as a model system for this study in the past several decades. However, how capsid assembly is initiated, where and how scaffolding proteins bind to coat proteins in the procapsid, and the conformational changes upon capsid maturation still remain elusive. Here, we report Cα backbone models for the P22 procapsid and infectious virion derived from electron cryomicroscopy density maps determined at 3.8- and 4.0-A resolution, respectively, and the first procapsid structure at subnanometer resolution without imposing symmetry. The procapsid structures show the scaffolding protein interacting electrostatically with the N terminus (N arm) of the coat protein through its C-terminal helix-loop-helix motif, as well as unexpected interactions between 10 scaffolding proteins and the 12-fold portal located at a unique vertex. These suggest a critical role for the scaffolding proteins both in initiating the capsid assembly at the portal vertex and propagating its growth on a T = 7 icosahedral lattice. Comparison of the procapsid and the virion backbone models reveals coordinated and complex conformational changes. These structural observations allow us to propose a more detailed molecular mechanism for the scaffolding-mediated capsid assembly initiation including portal incorporation, release of scaffolding proteins upon DNA packaging, and maturation into infectious virions.
Javier Guenaga, Pia Dosenovic, Gilad Ofek, David Baker, William R Schief, Peter D Kwong, Gunilla B Karlsson Hedestam, Richard T Wyatt
Heterologous epitope-scaffold prime:boosting immuno-focuses B cell responses to the HIV-1 gp41 2F5 neutralization determinant Journal Article
In: PloS one, vol. 6, pp. e16074, 2011, ISSN: 1932-6203.
@article{357,
title = {Heterologous epitope-scaffold prime:boosting immuno-focuses B cell responses to the HIV-1 gp41 2F5 neutralization determinant},
author = { Javier Guenaga and Pia Dosenovic and Gilad Ofek and David Baker and William R Schief and Peter D Kwong and Gunilla B Karlsson Hedestam and Richard T Wyatt},
issn = {1932-6203},
year = {2011},
date = {2011-00-01},
journal = {PloS one},
volume = {6},
pages = {e16074},
abstract = {The HIV-1 envelope glycoproteins (Env) gp120 and gp41 mediate entry and are the targets for neutralizing antibodies. Within gp41, a continuous epitope defined by the broadly neutralizing antibody 2F5, is one of the few conserved sites accessible to antibodies on the functional HIV Env spike. Recently, as an initial attempt at structure-guided design, we transplanted the 2F5 epitope onto several non-HIV acceptor scaffold proteins that we termed epitope scaffolds (ES). As immunogens, these ES proteins elicited antibodies with exquisite binding specificity matching that of the 2F5 antibody. These novel 2F5 epitope scaffolds presented us with the opportunity to test heterologous prime:boost immunization strategies to selectively boost antibody responses against the engrafted gp41 2F5 epitope. Such strategies might be employed to target conserved but poorly immunogenic sites on the HIV-1 Env, and, more generally, other structurally defined pathogen targets. Here, we assessed ES prime:boosting by measuring epitope specific serum antibody titers by ELISA and B cell responses by ELISpot analysis using both free 2F5 peptide and an unrelated ES protein as probes. We found that the heterologous ES prime:boosting immunization regimen elicits cross-reactive humoral responses to the structurally constrained 2F5 epitope target, and that incorporating a promiscuous T cell helper epitope in the immunogens resulted in higher antibody titers against the 2F5 graft, but did not result in virus neutralization. Interestingly, two epitope scaffolds (ES1 and ES2), which did not elicit a detectable 2F5 epitope-specific response on their own, boosted such responses when primed with the ES5. Together, these results indicate that heterologous ES prime:boost immunization regimens effectively focus the humoral immune response on the structurally defined and immunogen-conserved HIV-1 2F5 epitope.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The HIV-1 envelope glycoproteins (Env) gp120 and gp41 mediate entry and are the targets for neutralizing antibodies. Within gp41, a continuous epitope defined by the broadly neutralizing antibody 2F5, is one of the few conserved sites accessible to antibodies on the functional HIV Env spike. Recently, as an initial attempt at structure-guided design, we transplanted the 2F5 epitope onto several non-HIV acceptor scaffold proteins that we termed epitope scaffolds (ES). As immunogens, these ES proteins elicited antibodies with exquisite binding specificity matching that of the 2F5 antibody. These novel 2F5 epitope scaffolds presented us with the opportunity to test heterologous prime:boost immunization strategies to selectively boost antibody responses against the engrafted gp41 2F5 epitope. Such strategies might be employed to target conserved but poorly immunogenic sites on the HIV-1 Env, and, more generally, other structurally defined pathogen targets. Here, we assessed ES prime:boosting by measuring epitope specific serum antibody titers by ELISA and B cell responses by ELISpot analysis using both free 2F5 peptide and an unrelated ES protein as probes. We found that the heterologous ES prime:boosting immunization regimen elicits cross-reactive humoral responses to the structurally constrained 2F5 epitope target, and that incorporating a promiscuous T cell helper epitope in the immunogens resulted in higher antibody titers against the 2F5 graft, but did not result in virus neutralization. Interestingly, two epitope scaffolds (ES1 and ES2), which did not elicit a detectable 2F5 epitope-specific response on their own, boosted such responses when primed with the ES5. Together, these results indicate that heterologous ES prime:boost immunization regimens effectively focus the humoral immune response on the structurally defined and immunogen-conserved HIV-1 2F5 epitope.
Frank DiMaio, Andrew Leaver-Fay, Phil Bradley, David Baker, Ingemar Andr’e
Modeling symmetric macromolecular structures in Rosetta3 Journal Article
In: PloS One, vol. 6, pp. e20450, 2011, ISSN: 1932-6203.
@article{590,
title = {Modeling symmetric macromolecular structures in Rosetta3},
author = { Frank DiMaio and Andrew Leaver-Fay and Phil Bradley and David Baker and Ingemar Andr'e},
doi = {10.1371/journal.pone.0020450},
issn = {1932-6203},
year = {2011},
date = {2011-00-01},
journal = {PloS One},
volume = {6},
pages = {e20450},
abstract = {Symmetric protein assemblies play important roles in many biochemical processes. However, the large size of such systems is challenging for traditional structure modeling methods. This paper describes the implementation of a general framework for modeling arbitrary symmetric systems in Rosetta3. We describe the various types of symmetries relevant to the study of protein structure that may be modeled using Rosettatextquoterights symmetric framework. We then describe how this symmetric framework is efficiently implemented within Rosetta, which restricts the conformational search space by sampling only symmetric degrees of freedom, and explicitly simulates only a subset of the interacting monomers. Finally, we describe structure prediction and design applications that utilize the Rosetta3 symmetric modeling capabilities, and provide a guide to running simulations on symmetric systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Symmetric protein assemblies play important roles in many biochemical processes. However, the large size of such systems is challenging for traditional structure modeling methods. This paper describes the implementation of a general framework for modeling arbitrary symmetric systems in Rosetta3. We describe the various types of symmetries relevant to the study of protein structure that may be modeled using Rosettatextquoterights symmetric framework. We then describe how this symmetric framework is efficiently implemented within Rosetta, which restricts the conformational search space by sampling only symmetric degrees of freedom, and explicitly simulates only a subset of the interacting monomers. Finally, we describe structure prediction and design applications that utilize the Rosetta3 symmetric modeling capabilities, and provide a guide to running simulations on symmetric systems.
Andrew Leaver-Fay, Michael Tyka, Steven M Lewis, Oliver F Lange, James Thompson, Ron Jacak, Kristian Kaufman, P Douglas Renfrew, Colin A Smith, Will Sheffler, Ian W Davis, Seth Cooper, Adrien Treuille, Daniel J Mandell, Florian Richter, Yih-En Andrew Ban, Sarel J Fleishman, Jacob E Corn, David E Kim, Sergey Lyskov, Monica Berrondo, Stuart Mentzer, Zoran Popovi’c, James J Havranek, John Karanicolas, Rhiju Das, Jens Meiler, Tanja Kortemme, Jeffrey J Gray, Brian Kuhlman, David Baker, Philip Bradley
ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules Journal Article
In: Methods in enzymology, vol. 487, pp. 545-74, 2011, ISSN: 1557-7988.
@article{359,
title = {ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules},
author = { Andrew Leaver-Fay and Michael Tyka and Steven M Lewis and Oliver F Lange and James Thompson and Ron Jacak and Kristian Kaufman and P Douglas Renfrew and Colin A Smith and Will Sheffler and Ian W Davis and Seth Cooper and Adrien Treuille and Daniel J Mandell and Florian Richter and Yih-En Andrew Ban and Sarel J Fleishman and Jacob E Corn and David E Kim and Sergey Lyskov and Monica Berrondo and Stuart Mentzer and Zoran Popovi'c and James J Havranek and John Karanicolas and Rhiju Das and Jens Meiler and Tanja Kortemme and Jeffrey J Gray and Brian Kuhlman and David Baker and Philip Bradley},
issn = {1557-7988},
year = {2011},
date = {2011-00-01},
journal = {Methods in enzymology},
volume = {487},
pages = {545-74},
abstract = {We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.
Po-Ssu Huang, Yih-En Andrew Ban, Florian Richter, Ingemar Andre, Robert Vernon, William R Schief, David Baker
RosettaRemodel: a generalized framework for flexible backbone protein design. Journal Article
In: PloS One, vol. 6, pp. e24109, 2011, ISSN: 1932-6203.
@article{588,
title = {RosettaRemodel: a generalized framework for flexible backbone protein design.},
author = { Po-Ssu Huang and Yih-En Andrew Ban and Florian Richter and Ingemar Andre and Robert Vernon and William R Schief and David Baker},
doi = {10.1371/journal.pone.0024109},
issn = {1932-6203},
year = {2011},
date = {2011-00-01},
journal = {PloS One},
volume = {6},
pages = {e24109},
abstract = {We describe RosettaRemodel, a generalized framework for flexible protein design that provides a versatile and convenient interface to the Rosetta modeling suite. RosettaRemodel employs a unified interface, called a blueprint, which allows detailed control over many aspects of flexible backbone protein design calculations. RosettaRemodel allows the construction and elaboration of customized protocols for a wide range of design problems ranging from loop insertion and deletion, disulfide engineering, domain assembly, loop remodeling, motif grafting, symmetrical units, to de novo structure modeling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe RosettaRemodel, a generalized framework for flexible protein design that provides a versatile and convenient interface to the Rosetta modeling suite. RosettaRemodel employs a unified interface, called a blueprint, which allows detailed control over many aspects of flexible backbone protein design calculations. RosettaRemodel allows the construction and elaboration of customized protocols for a wide range of design problems ranging from loop insertion and deletion, disulfide engineering, domain assembly, loop remodeling, motif grafting, symmetrical units, to de novo structure modeling.
Sarel J Fleishman, Andrew Leaver-Fay, Jacob E Corn, Eva-Maria Strauch, Sagar D Khare, Nobuyasu Koga, Justin Ashworth, Paul Murphy, Florian Richter, Gordon Lemmon, Jens Meiler, David Baker
RosettaScripts: a scripting language interface to the Rosetta macromolecular modeling suite Journal Article
In: PloS one, vol. 6, pp. e20161, 2011, ISSN: 1932-6203.
@article{587,
title = {RosettaScripts: a scripting language interface to the Rosetta macromolecular modeling suite},
author = { Sarel J Fleishman and Andrew Leaver-Fay and Jacob E Corn and Eva-Maria Strauch and Sagar D Khare and Nobuyasu Koga and Justin Ashworth and Paul Murphy and Florian Richter and Gordon Lemmon and Jens Meiler and David Baker},
doi = {10.1371/journal.pone.0020161},
issn = {1932-6203},
year = {2011},
date = {2011-00-01},
journal = {PloS one},
volume = {6},
pages = {e20161},
abstract = {Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins.
2010
Eranthie Weerapana, Chu Wang, Gabriel M Simon, Florian Richter, Sagar Khare, Myles B D Dillon, Daniel A Bachovchin, Kerri Mowen, David Baker, Benjamin F Cravatt
Quantitative reactivity profiling predicts functional cysteines in proteomes Journal Article
In: Nature, vol. 468, pp. 790-5, 2010, ISSN: 1476-4687.
@article{266,
title = {Quantitative reactivity profiling predicts functional cysteines in proteomes},
author = { Eranthie Weerapana and Chu Wang and Gabriel M Simon and Florian Richter and Sagar Khare and Myles B D Dillon and Daniel A Bachovchin and Kerri Mowen and David Baker and Benjamin F Cravatt},
issn = {1476-4687},
year = {2010},
date = {2010-12-01},
journal = {Nature},
volume = {468},
pages = {790-5},
abstract = {Cysteine is the most intrinsically nucleophilic amino acid in proteins, where its reactivity is tuned to perform diverse biochemical functions. The absence of a consensus sequence that defines functional cysteines in proteins has hindered their discovery and characterization. Here we describe a proteomics method to profile quantitatively the intrinsic reactivity of cysteine residues en masse directly in native biological systems. Hyper-reactivity was a rare feature among cysteines and it was found to specify a wide range of activities, including nucleophilic and reductive catalysis and sites of oxidative modification. Hyper-reactive cysteines were identified in several proteins of uncharacterized function, including a residue conserved across eukaryotic phylogeny that we show is required for yeast viability and is involved in iron-sulphur protein biogenesis. We also demonstrate that quantitative reactivity profiling can form the basis for screening and functional assignment of cysteines in computationally designed proteins, where it discriminated catalytically active from inactive cysteine hydrolase designs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cysteine is the most intrinsically nucleophilic amino acid in proteins, where its reactivity is tuned to perform diverse biochemical functions. The absence of a consensus sequence that defines functional cysteines in proteins has hindered their discovery and characterization. Here we describe a proteomics method to profile quantitatively the intrinsic reactivity of cysteine residues en masse directly in native biological systems. Hyper-reactivity was a rare feature among cysteines and it was found to specify a wide range of activities, including nucleophilic and reductive catalysis and sites of oxidative modification. Hyper-reactive cysteines were identified in several proteins of uncharacterized function, including a residue conserved across eukaryotic phylogeny that we show is required for yeast viability and is involved in iron-sulphur protein biogenesis. We also demonstrate that quantitative reactivity profiling can form the basis for screening and functional assignment of cysteines in computationally designed proteins, where it discriminated catalytically active from inactive cysteine hydrolase designs.
Lingfeng Liu, Paul Murphy, David Baker, Stefan Lutz
Computational design of orthogonal nucleoside kinases Journal Article
In: Chemical communications, vol. 46, pp. 8803-5, 2010, ISSN: 1364-548X.
@article{268,
title = {Computational design of orthogonal nucleoside kinases},
author = { Lingfeng Liu and Paul Murphy and David Baker and Stefan Lutz},
issn = {1364-548X},
year = {2010},
date = {2010-12-01},
journal = {Chemical communications},
volume = {46},
pages = {8803-5},
abstract = {We report the computational enzyme design of an orthogonal nucleoside analog kinase for 3textquoteright-deoxythymidine. The best kinase variant shows an 8500-fold change in substrate specificity, resulting from a 4.6-fold gain in catalytic efficiency for the nucleoside analog and a 2000-fold decline for the native substrate thymidine.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We report the computational enzyme design of an orthogonal nucleoside analog kinase for 3textquoteright-deoxythymidine. The best kinase variant shows an 8500-fold change in substrate specificity, resulting from a 4.6-fold gain in catalytic efficiency for the nucleoside analog and a 2000-fold decline for the native substrate thymidine.
Yuefeng Tang, William M Schneider, Yang Shen, Srivatsan Raman, Masayori Inouye, David Baker, Monica J Roth, Gaetano T Montelione
Fully automated high-quality NMR structure determination of small (2)H-enriched proteins Journal Article
In: Journal of structural and functional genomics, vol. 11, pp. 223-32, 2010, ISSN: 1570-0267.
@article{264,
title = {Fully automated high-quality NMR structure determination of small (2)H-enriched proteins},
author = { Yuefeng Tang and William M Schneider and Yang Shen and Srivatsan Raman and Masayori Inouye and David Baker and Monica J Roth and Gaetano T Montelione},
issn = {1570-0267},
year = {2010},
date = {2010-12-01},
journal = {Journal of structural and functional genomics},
volume = {11},
pages = {223-32},
abstract = {Determination of high-quality small protein structures by nuclear magnetic resonance (NMR) methods generally requires acquisition and analysis of an extensive set of structural constraints. The process generally demands extensive backbone and sidechain resonance assignments, and weeks or even months of data collection and interpretation. Here we demonstrate rapid and high-quality protein NMR structure generation using CS-Rosetta with a perdeuterated protein sample made at a significantly reduced cost using new bacterial culture condensation methods. Our strategy provides the basis for a high-throughput approach for routine, rapid, high-quality structure determination of small proteins. As an example, we demonstrate the determination of a high-quality 3D structure of a small 8~kDa protein, E. coli cold shock protein A (CspA), using <4~days of data collection and fully automated data analysis methods together with CS-Rosetta. The resulting CspA structure is highly converged and in excellent agreement with the published crystal structure, with a backbone RMSD value of 0.5~r A, an all atom RMSD value of 1.2~r A to the crystal structure for well-defined regions, and RMSD value of 1.1~r A to crystal structure for core, non-solvent exposed sidechain atoms. Cross validation of the structure with (15)N- and (13)C-edited NOESY data obtained with a perdeuterated (15)N, (13)C-enriched (13)CH(3) methyl protonated CspA sample confirms that essentially all of these independently-interpreted NOE-based constraints are already satisfied in each of the 10 CS-Rosetta structures. By these criteria, the CS-Rosetta structure generated by fully automated analysis of data for a perdeuterated sample provides an accurate structure of CspA. This represents a general approach for rapid, automated structure determination of small proteins by NMR.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Determination of high-quality small protein structures by nuclear magnetic resonance (NMR) methods generally requires acquisition and analysis of an extensive set of structural constraints. The process generally demands extensive backbone and sidechain resonance assignments, and weeks or even months of data collection and interpretation. Here we demonstrate rapid and high-quality protein NMR structure generation using CS-Rosetta with a perdeuterated protein sample made at a significantly reduced cost using new bacterial culture condensation methods. Our strategy provides the basis for a high-throughput approach for routine, rapid, high-quality structure determination of small proteins. As an example, we demonstrate the determination of a high-quality 3D structure of a small 8~kDa protein, E. coli cold shock protein A (CspA), using <4~days of data collection and fully automated data analysis methods together with CS-Rosetta. The resulting CspA structure is highly converged and in excellent agreement with the published crystal structure, with a backbone RMSD value of 0.5~r A, an all atom RMSD value of 1.2~r A to the crystal structure for well-defined regions, and RMSD value of 1.1~r A to crystal structure for core, non-solvent exposed sidechain atoms. Cross validation of the structure with (15)N- and (13)C-edited NOESY data obtained with a perdeuterated (15)N, (13)C-enriched (13)CH(3) methyl protonated CspA sample confirms that essentially all of these independently-interpreted NOE-based constraints are already satisfied in each of the 10 CS-Rosetta structures. By these criteria, the CS-Rosetta structure generated by fully automated analysis of data for a perdeuterated sample provides an accurate structure of CspA. This represents a general approach for rapid, automated structure determination of small proteins by NMR.
Sarel J Fleishman, Jacob E Corn, Eva M Strauch, Tim A Whitehead, Ingemar Andre, James Thompson, James J Havranek, Rhiju Das, Philip Bradley, David Baker
Rosetta in CAPRI rounds 13-19. Journal Article
In: Proteins, vol. 78, pp. 3212-8, 2010, ISSN: 1097-0134.
@article{578,
title = {Rosetta in CAPRI rounds 13-19.},
author = { Sarel J Fleishman and Jacob E Corn and Eva M Strauch and Tim A Whitehead and Ingemar Andre and James Thompson and James J Havranek and Rhiju Das and Philip Bradley and David Baker},
doi = {10.1002/prot.22784},
issn = {1097-0134},
year = {2010},
date = {2010-11-01},
journal = {Proteins},
volume = {78},
pages = {3212-8},
abstract = {Modeling the conformational changes that occur on binding of macromolecules is an unsolved challenge. In previous rounds of the Critical Assessment of PRediction of Interactions (CAPRI), it was demonstrated that the Rosetta approach to macromolecular modeling could capture side chain conformational changes on binding with high accuracy. In rounds 13-19 we tested the ability of various backbone remodeling strategies to capture the main-chain conformational changes observed during binding events. These approaches span a wide range of backbone motions, from limited refinement of loops to relieve clashes in homologous docking, through extensive remodeling of loop segments, to large-scale remodeling of RNA. Although the results are encouraging, major improvements in sampling and energy evaluation are clearly required for consistent high accuracy modeling. Analysis of our failures in the CAPRI challenges suggest that conformational sampling at the termini of exposed beta strands is a particularly pressing area for improvement.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Modeling the conformational changes that occur on binding of macromolecules is an unsolved challenge. In previous rounds of the Critical Assessment of PRediction of Interactions (CAPRI), it was demonstrated that the Rosetta approach to macromolecular modeling could capture side chain conformational changes on binding with high accuracy. In rounds 13-19 we tested the ability of various backbone remodeling strategies to capture the main-chain conformational changes observed during binding events. These approaches span a wide range of backbone motions, from limited refinement of loops to relieve clashes in homologous docking, through extensive remodeling of loop segments, to large-scale remodeling of RNA. Although the results are encouraging, major improvements in sampling and energy evaluation are clearly required for consistent high accuracy modeling. Analysis of our failures in the CAPRI challenges suggest that conformational sampling at the termini of exposed beta strands is a particularly pressing area for improvement.
Michael D Tyka, Daniel A Keedy, Ingemar Andr’e, Frank DiMaio, Yifan Song, David C Richardson, Jane S Richardson, David Baker
Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping Journal Article
In: Journal of molecular biology, 2010, ISSN: 1089-8638.
@article{260,
title = {Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping},
author = { Michael D Tyka and Daniel A Keedy and Ingemar Andr'e and Frank DiMaio and Yifan Song and David C Richardson and Jane S Richardson and David Baker},
issn = {1089-8638},
year = {2010},
date = {2010-11-01},
journal = {Journal of molecular biology},
abstract = {What conformations do protein molecules populate in solution? Crystallography provides a high-resolution description of protein structure in the crystal environment, while NMR describes structure in solution but using less data. NMR structures display more variability, but is this because crystal contacts are absent or because of fewer data constraints? Here we report unexpected insight into this issue obtained through analysis of detailed protein energy landscapes generated by large-scale, native-enhanced sampling of conformational space with Rosetta@home for 111 protein domains. In the absence of tightly associating binding partners or ligands, the lowest-energy Rosetta models were nearly all <2.5~r A C(α)RMSD from the experimental structure; this result demonstrates that structure prediction accuracy for globular proteins is limited mainly by the ability to sample close to the native structure. While the lowest-energy models are similar to deposited structures, they are not identical; the largest deviations are most often in regions involved in ligand, quaternary, or crystal contacts. For ligand binding proteins, the low energy models may resemble the apo structures, and for oligomeric proteins, the monomeric assembly intermediates. The deviations between the low energy models and crystal structures largely disappear when landscapes are computed in the context of the crystal lattice or multimer. The computed low-energy ensembles, with tight crystal-structure-like packing in the core, but more NMR-structure-like variability in loops, may in some cases resemble the native state ensembles of proteins better than individual crystal or NMR structures, and can suggest experimentally testable hypotheses relating alternative states and structural heterogeneity to function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
What conformations do protein molecules populate in solution? Crystallography provides a high-resolution description of protein structure in the crystal environment, while NMR describes structure in solution but using less data. NMR structures display more variability, but is this because crystal contacts are absent or because of fewer data constraints? Here we report unexpected insight into this issue obtained through analysis of detailed protein energy landscapes generated by large-scale, native-enhanced sampling of conformational space with Rosetta@home for 111 protein domains. In the absence of tightly associating binding partners or ligands, the lowest-energy Rosetta models were nearly all <2.5~r A C(α)RMSD from the experimental structure; this result demonstrates that structure prediction accuracy for globular proteins is limited mainly by the ability to sample close to the native structure. While the lowest-energy models are similar to deposited structures, they are not identical; the largest deviations are most often in regions involved in ligand, quaternary, or crystal contacts. For ligand binding proteins, the low energy models may resemble the apo structures, and for oligomeric proteins, the monomeric assembly intermediates. The deviations between the low energy models and crystal structures largely disappear when landscapes are computed in the context of the crystal lattice or multimer. The computed low-energy ensembles, with tight crystal-structure-like packing in the core, but more NMR-structure-like variability in loops, may in some cases resemble the native state ensembles of proteins better than individual crystal or NMR structures, and can suggest experimentally testable hypotheses relating alternative states and structural heterogeneity to function.
Parthasarathy Sampathkumar, Frances Lu, Xun Zhao, Zhenzhen Li, Jeremiah Gilmore, Kevin Bain, Marc E Rutter, Tarun Gheyi, Kenneth D Schwinn, Jeffrey B Bonanno, Ursula Pieper, J Eduardo Fajardo, Andras Fiser, Steven C Almo, Subramanyam Swaminathan, Mark R Chance, David Baker, Shane Atwell, Devon A Thompson, J Spencer Emtage, Stephen R Wasserman, Andrej Sali, J Michael Sauder, Stephen K Burley
Structure of a putative BenF-like porin from Pseudomonas fluorescens Pf-5 at 2.6 A resolution Journal Article
In: Proteins, vol. 78, pp. 3056-62, 2010, ISSN: 1097-0134.
@article{263,
title = {Structure of a putative BenF-like porin from Pseudomonas fluorescens Pf-5 at 2.6 A resolution},
author = { Parthasarathy Sampathkumar and Frances Lu and Xun Zhao and Zhenzhen Li and Jeremiah Gilmore and Kevin Bain and Marc E Rutter and Tarun Gheyi and Kenneth D Schwinn and Jeffrey B Bonanno and Ursula Pieper and J Eduardo Fajardo and Andras Fiser and Steven C Almo and Subramanyam Swaminathan and Mark R Chance and David Baker and Shane Atwell and Devon A Thompson and J Spencer Emtage and Stephen R Wasserman and Andrej Sali and J Michael Sauder and Stephen K Burley},
issn = {1097-0134},
year = {2010},
date = {2010-11-01},
journal = {Proteins},
volume = {78},
pages = {3056-62},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Benoit J Smagghe, Po-Ssu Huang, Yih-En Andrew Ban, David Baker, Timothy A Springer
Modulation of integrin activation by an entropic spring in the beta-knee. Journal Article
In: The Journal of biological chemistry, vol. 285, pp. 32954-66, 2010, ISSN: 1083-351X.
@article{581,
title = {Modulation of integrin activation by an entropic spring in the beta-knee.},
author = { Benoit J Smagghe and Po-Ssu Huang and Yih-En Andrew Ban and David Baker and Timothy A Springer},
doi = {10.1074/jbc.M110.145177},
issn = {1083-351X},
year = {2010},
date = {2010-10-01},
journal = {The Journal of biological chemistry},
volume = {285},
pages = {32954-66},
abstract = {We show that the length of a loop in the β-knee, between the first and second cysteines (C1-C2) in integrin EGF-like (I-EGF) domain 2, modulates integrin activation. Three independent sets of mutants, including swaps among different integrin β-subunits, show that C1-C2 loop lengths of 12 and longer favor the low affinity state and masking of ligand-induced binding site (LIBS) epitopes. Shortening length from 12 to 4 residues progressively increases ligand binding and LIBS epitope exposure. Compared with length, the loop sequence had a smaller effect, which was ascribable to stabilizing loop conformation, and not interactions with the α-subunit. The data together with structural calculations support the concept that the C1-C2 loop is an entropic spring and an emerging theme that disordered regions can regulate allostery. Diversity in the length of this loop may have evolved among integrin β-subunits to adjust the equilibrium between the bent and extended conformations at different set points.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We show that the length of a loop in the β-knee, between the first and second cysteines (C1-C2) in integrin EGF-like (I-EGF) domain 2, modulates integrin activation. Three independent sets of mutants, including swaps among different integrin β-subunits, show that C1-C2 loop lengths of 12 and longer favor the low affinity state and masking of ligand-induced binding site (LIBS) epitopes. Shortening length from 12 to 4 residues progressively increases ligand binding and LIBS epitope exposure. Compared with length, the loop sequence had a smaller effect, which was ascribable to stabilizing loop conformation, and not interactions with the α-subunit. The data together with structural calculations support the concept that the C1-C2 loop is an entropic spring and an emerging theme that disordered regions can regulate allostery. Diversity in the length of this loop may have evolved among integrin β-subunits to adjust the equilibrium between the bent and extended conformations at different set points.
Gilad Ofek, F Javier Guenaga, William R Schief, Jeff Skinner, David Baker, Richard Wyatt, Peter D Kwong
Elicitation of structure-specific antibodies by epitope scaffolds Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 107, pp. 17880-7, 2010, ISSN: 1091-6490.
@article{270,
title = {Elicitation of structure-specific antibodies by epitope scaffolds},
author = { Gilad Ofek and F Javier Guenaga and William R Schief and Jeff Skinner and David Baker and Richard Wyatt and Peter D Kwong},
issn = {1091-6490},
year = {2010},
date = {2010-10-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {107},
pages = {17880-7},
abstract = {Elicitation of antibodies against targets that are immunorecessive, cryptic, or transient in their native context has been a challenge for vaccine design. Here we demonstrate the elicitation of structure-specific antibodies against the HIV-1 gp41 epitope of the broadly neutralizing antibody 2F5. This conformationally flexible region of gp41 assumes mostly helical conformations but adopts a kinked, extended structure when bound by antibody 2F5. Computational techniques were employed to transplant the 2F5 epitope into select acceptor scaffolds. The resultant "2F5-epitope scaffolds" possessed nanomolar affinity for antibody 2F5 and a range of epitope flexibilities and antigenic specificities. Crystallographic characterization of the epitope scaffold with highest affinity and antigenic discrimination confirmed good to near perfect attainment of the target conformation for the gp41 molecular graft in free and 2F5-bound states, respectively. Animals immunized with 2F5-epitope scaffolds showed levels of graft-specific immune responses that correlated with graft flexibility (p~<~0.04), while antibody responses against the graft-as dissected residue-by-residue with alanine substitutions-resembled more closely those of 2F5 than sera elicited with flexible or cyclized peptides, a resemblance heightened by heterologous prime-boost. Lastly, crystal structures of a gp41 peptide in complex with monoclonal antibodies elicited by the 2F5-epitope scaffolds revealed that the elicited antibodies induce gp41 to assume its 2F5-recognized shape. Epitope scaffolds thus provide a means to elicit antibodies that recognize a predetermined target shape and sequence, even if that shape is transient in nature, and a means by which to dissect factors influencing such elicitation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Elicitation of antibodies against targets that are immunorecessive, cryptic, or transient in their native context has been a challenge for vaccine design. Here we demonstrate the elicitation of structure-specific antibodies against the HIV-1 gp41 epitope of the broadly neutralizing antibody 2F5. This conformationally flexible region of gp41 assumes mostly helical conformations but adopts a kinked, extended structure when bound by antibody 2F5. Computational techniques were employed to transplant the 2F5 epitope into select acceptor scaffolds. The resultant “2F5-epitope scaffolds” possessed nanomolar affinity for antibody 2F5 and a range of epitope flexibilities and antigenic specificities. Crystallographic characterization of the epitope scaffold with highest affinity and antigenic discrimination confirmed good to near perfect attainment of the target conformation for the gp41 molecular graft in free and 2F5-bound states, respectively. Animals immunized with 2F5-epitope scaffolds showed levels of graft-specific immune responses that correlated with graft flexibility (p~<~0.04), while antibody responses against the graft-as dissected residue-by-residue with alanine substitutions-resembled more closely those of 2F5 than sera elicited with flexible or cyclized peptides, a resemblance heightened by heterologous prime-boost. Lastly, crystal structures of a gp41 peptide in complex with monoclonal antibodies elicited by the 2F5-epitope scaffolds revealed that the elicited antibodies induce gp41 to assume its 2F5-recognized shape. Epitope scaffolds thus provide a means to elicit antibodies that recognize a predetermined target shape and sequence, even if that shape is transient in nature, and a means by which to dissect factors influencing such elicitation.
William Sheffler, David Baker
RosettaHoles2: a volumetric packing measure for protein structure refinement and validation Journal Article
In: Protein science, vol. 19, pp. 1991-5, 2010, ISSN: 1469-896X.
@article{269,
title = {RosettaHoles2: a volumetric packing measure for protein structure refinement and validation},
author = { William Sheffler and David Baker},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/pro.458
https://www.bakerlab.org/wp-content/uploads/2020/08/pro.458.pdf},
doi = {10.1002/pro.458},
issn = {1469-896X},
year = {2010},
date = {2010-10-01},
journal = {Protein science},
volume = {19},
pages = {1991-5},
abstract = {We present an improved version of RosettaHoles, a methodology for quantitative and visual characterization of protein core packing. RosettaHoles2 features a packing measure more rapidly computable, accurate and physically transparent, as well as a new validation score intended for structures submitted to the Protein Data Bank. The differential packing measure is parameterized to maximize the gap between computationally generated and experimentally determined X-ray structures, and can be used in refinement of protein structure models. The parameters of the model provide insight into components missing in current force fields, and the validation score gives an upper bound on the X-ray resolution of Protein Data Bank structures; a crystal structure should have a validation score as good as or better than its resolution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present an improved version of RosettaHoles, a methodology for quantitative and visual characterization of protein core packing. RosettaHoles2 features a packing measure more rapidly computable, accurate and physically transparent, as well as a new validation score intended for structures submitted to the Protein Data Bank. The differential packing measure is parameterized to maximize the gap between computationally generated and experimentally determined X-ray structures, and can be used in refinement of protein structure models. The parameters of the model provide insight into components missing in current force fields, and the validation score gives an upper bound on the X-ray resolution of Protein Data Bank structures; a crystal structure should have a validation score as good as or better than its resolution.
Bruno E Correia, Yih-En Andrew Ban, Margaret A Holmes, Hengyu Xu, Katharine Ellingson, Zane Kraft, Chris Carrico, Erica Boni, D Noah Sather, Camille Zenobia, Katherine Y Burke, Tyler Bradley-Hewitt, Jessica F Bruhn-Johannsen, Oleksandr Kalyuzhniy, David Baker, Roland K Strong, Leonidas Stamatatos, William R Schief
Computational design of epitope-scaffolds allows induction of antibodies specific for a poorly immunogenic HIV vaccine epitope Journal Article
In: Structure, vol. 18, pp. 1116-26, 2010, ISSN: 1878-4186.
@article{228,
title = {Computational design of epitope-scaffolds allows induction of antibodies specific for a poorly immunogenic HIV vaccine epitope},
author = { Bruno E Correia and Yih-En Andrew Ban and Margaret A Holmes and Hengyu Xu and Katharine Ellingson and Zane Kraft and Chris Carrico and Erica Boni and D Noah Sather and Camille Zenobia and Katherine Y Burke and Tyler Bradley-Hewitt and Jessica F Bruhn-Johannsen and Oleksandr Kalyuzhniy and David Baker and Roland K Strong and Leonidas Stamatatos and William R Schief},
issn = {1878-4186},
year = {2010},
date = {2010-09-01},
journal = {Structure},
volume = {18},
pages = {1116-26},
abstract = {Broadly cross-reactive monoclonal antibodies define epitopes for vaccine development against HIV and other highly mutable viruses. Crystal structures are available for several such antibody-epitope complexes, but methods are needed to translate that structural information into immunogens that re-elicit similar antibodies. We describe a general computational method to design epitope-scaffolds in which contiguous structural epitopes are transplanted to scaffold proteins for conformational stabilization and immune presentation. Epitope-scaffolds designed for the poorly immunogenic but conserved HIV epitope 4E10 exhibited high epitope structural mimicry, bound with higher affinities to monoclonal antibody (mAb) 4E10 than the cognate peptide, and inhibited HIV neutralization by HIV+ sera. Rabbit immunization with an epitope-scaffold induced antibodies with structural specificity highly similar to mAb 4E10, an important advance toward elicitation of neutralizing activity. The results demonstrate that computationally designed epitope-scaffolds are valuable as structure-specific serological reagents and as immunogens to elicit antibodies with predetermined structural specificity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Broadly cross-reactive monoclonal antibodies define epitopes for vaccine development against HIV and other highly mutable viruses. Crystal structures are available for several such antibody-epitope complexes, but methods are needed to translate that structural information into immunogens that re-elicit similar antibodies. We describe a general computational method to design epitope-scaffolds in which contiguous structural epitopes are transplanted to scaffold proteins for conformational stabilization and immune presentation. Epitope-scaffolds designed for the poorly immunogenic but conserved HIV epitope 4E10 exhibited high epitope structural mimicry, bound with higher affinities to monoclonal antibody (mAb) 4E10 than the cognate peptide, and inhibited HIV neutralization by HIV+ sera. Rabbit immunization with an epitope-scaffold induced antibodies with structural specificity highly similar to mAb 4E10, an important advance toward elicitation of neutralizing activity. The results demonstrate that computationally designed epitope-scaffolds are valuable as structure-specific serological reagents and as immunogens to elicit antibodies with predetermined structural specificity.
Justin Ashworth, Gregory K Taylor, James J Havranek, S Arshiya Quadri, Barry L Stoddard, David Baker
Computational reprogramming of homing endonuclease specificity at multiple adjacent base pairs Journal Article
In: Nucleic acids research, vol. 38, pp. 5601-8, 2010, ISSN: 1362-4962.
@article{252,
title = {Computational reprogramming of homing endonuclease specificity at multiple adjacent base pairs},
author = { Justin Ashworth and Gregory K Taylor and James J Havranek and S Arshiya Quadri and Barry L Stoddard and David Baker},
issn = {1362-4962},
year = {2010},
date = {2010-09-01},
journal = {Nucleic acids research},
volume = {38},
pages = {5601-8},
abstract = {Site-specific homing endonucleases are capable of inducing gene conversion via homologous recombination. Reprogramming their cleavage specificities allows the targeting of specific biological sites for gene correction or conversion. We used computational protein design to alter the cleavage specificity of I-MsoI for three contiguous base pair substitutions, resulting in an endonuclease whose activity and specificity for its new site rival that of wild-type I-MsoI for the original site. Concerted design for all simultaneous substitutions was more successful than a modular approach against individual substitutions, highlighting the importance of context-dependent redesign and optimization of protein-DNA interactions. We then used computational design based on the crystal structure of the designed complex, which revealed significant unanticipated shifts in DNA conformation, to create an endonuclease that specifically cleaves a site with four contiguous base pair substitutions. Our results demonstrate that specificity switches for multiple concerted base pair substitutions can be computationally designed, and that iteration between design and structure determination provides a route to large scale reprogramming of specificity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Site-specific homing endonucleases are capable of inducing gene conversion via homologous recombination. Reprogramming their cleavage specificities allows the targeting of specific biological sites for gene correction or conversion. We used computational protein design to alter the cleavage specificity of I-MsoI for three contiguous base pair substitutions, resulting in an endonuclease whose activity and specificity for its new site rival that of wild-type I-MsoI for the original site. Concerted design for all simultaneous substitutions was more successful than a modular approach against individual substitutions, highlighting the importance of context-dependent redesign and optimization of protein-DNA interactions. We then used computational design based on the crystal structure of the designed complex, which revealed significant unanticipated shifts in DNA conformation, to create an endonuclease that specifically cleaves a site with four contiguous base pair substitutions. Our results demonstrate that specificity switches for multiple concerted base pair substitutions can be computationally designed, and that iteration between design and structure determination provides a route to large scale reprogramming of specificity.
Gert Kiss, Daniela R”othlisberger, David Baker, K N Houk
Evaluation and ranking of enzyme designs Journal Article
In: Protein science, vol. 19, pp. 1760-73, 2010, ISSN: 1469-896X.
@article{265,
title = {Evaluation and ranking of enzyme designs},
author = { Gert Kiss and Daniela R"othlisberger and David Baker and K N Houk},
doi = {10.1002/pro.462},
issn = {1469-896X},
year = {2010},
date = {2010-09-01},
journal = {Protein science},
volume = {19},
pages = {1760-73},
abstract = {In 2008, a successful computational design procedure was reported that yielded active enzyme catalysts for the Kemp elimination. Here, we studied these proteins together with a set of previously unpublished inactive designs to determine the sources of activity or lack thereof, and to predict which of the designed structures are most likely to be catalytic. Methods that range from quantum mechanics (QM) on truncated model systems to the treatment of the full protein with ONIOM QM/MM and AMBER molecular dynamics (MD) were explored. The most effective procedure involved molecular dynamics, and a general MD protocol was established. Substantial deviations from the ideal catalytic geometries were observed for a number of designs. Penetration of water into the catalytic site and insufficient residue-packing around the active site are the main factors that can cause enzyme designs to be inactive. Where in the past, computational evaluations of designed enzymes were too time-extensive for practical considerations, it has now become feasible to rank and refine candidates computationally prior to and in conjunction with experimentation, thus markedly increasing the efficiency of the enzyme design process.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In 2008, a successful computational design procedure was reported that yielded active enzyme catalysts for the Kemp elimination. Here, we studied these proteins together with a set of previously unpublished inactive designs to determine the sources of activity or lack thereof, and to predict which of the designed structures are most likely to be catalytic. Methods that range from quantum mechanics (QM) on truncated model systems to the treatment of the full protein with ONIOM QM/MM and AMBER molecular dynamics (MD) were explored. The most effective procedure involved molecular dynamics, and a general MD protocol was established. Substantial deviations from the ideal catalytic geometries were observed for a number of designs. Penetration of water into the catalytic site and insufficient residue-packing around the active site are the main factors that can cause enzyme designs to be inactive. Where in the past, computational evaluations of designed enzymes were too time-extensive for practical considerations, it has now become feasible to rank and refine candidates computationally prior to and in conjunction with experimentation, thus markedly increasing the efficiency of the enzyme design process.
Douglas M Fowler, Carlos L Araya, Sarel J Fleishman, Elizabeth H Kellogg, Jason J Stephany, David Baker, Stanley Fields
High-resolution mapping of protein sequence-function relationships Journal Article
In: Nature methods, vol. 7, pp. 741-6, 2010, ISSN: 1548-7105.
@article{267,
title = {High-resolution mapping of protein sequence-function relationships},
author = { Douglas M Fowler and Carlos L Araya and Sarel J Fleishman and Elizabeth H Kellogg and Jason J Stephany and David Baker and Stanley Fields},
issn = {1548-7105},
year = {2010},
date = {2010-09-01},
journal = {Nature methods},
volume = {7},
pages = {741-6},
abstract = {We present a large-scale approach to investigate the functional consequences of sequence variation in a protein. The approach entails the display of hundreds of thousands of protein variants, moderate selection for activity and high-throughput DNA sequencing to quantify the performance of each variant. Using this strategy, we tracked the performance of >600,000 variants of a human WW domain after three and six rounds of selection by phage display for binding to its peptide ligand. Binding properties of these variants defined a high-resolution map of mutational preference across the WW domain; each position had unique features that could not be captured by a few representative mutations. Our approach could be applied to many in vitro or in vivo protein assays, providing a general means for understanding how protein function relates to sequence.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present a large-scale approach to investigate the functional consequences of sequence variation in a protein. The approach entails the display of hundreds of thousands of protein variants, moderate selection for activity and high-throughput DNA sequencing to quantify the performance of each variant. Using this strategy, we tracked the performance of >600,000 variants of a human WW domain after three and six rounds of selection by phage display for binding to its peptide ligand. Binding properties of these variants defined a high-resolution map of mutational preference across the WW domain; each position had unique features that could not be captured by a few representative mutations. Our approach could be applied to many in vitro or in vivo protein assays, providing a general means for understanding how protein function relates to sequence.
Seth Cooper, Firas Khatib, Adrien Treuille, Janos Barbero, Jeehyung Lee, Michael Beenen, Andrew Leaver-Fay, David Baker, Zoran Popovi’c, Foldit Players
Predicting protein structures with a multiplayer online game Journal Article
In: Nature, vol. 466, pp. 756-60, 2010, ISSN: 1476-4687.
@article{16,
title = {Predicting protein structures with a multiplayer online game},
author = { Seth Cooper and Firas Khatib and Adrien Treuille and Janos Barbero and Jeehyung Lee and Michael Beenen and Andrew Leaver-Fay and David Baker and Zoran Popovi'c and Foldit Players},
issn = {1476-4687},
year = {2010},
date = {2010-08-01},
journal = {Nature},
volume = {466},
pages = {756-60},
abstract = {People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully textquoterightcrowd-sourcedtextquoteright through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully textquoterightcrowd-sourcedtextquoteright through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.
David Baker
An exciting but challenging road ahead for computational enzyme design Journal Article
In: Protein science, 2010, ISSN: 1469-896X.
@article{229,
title = {An exciting but challenging road ahead for computational enzyme design},
author = { David Baker},
issn = {1469-896X},
year = {2010},
date = {2010-08-01},
journal = {Protein science},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Justin B Siegel, Alexandre Zanghellini, Helena M Lovick, Gert Kiss, Abigail R Lambert, Jennifer L St Clair, Jasmine L Gallaher, Donald Hilvert, Michael H Gelb, Barry L Stoddard, Kendall N Houk, Forrest E Michael, David Baker
Computational design of an enzyme catalyst for a stereoselective bimolecular Diels-Alder reaction Journal Article
In: Science, vol. 329, pp. 309-13, 2010, ISSN: 1095-9203.
@article{91,
title = {Computational design of an enzyme catalyst for a stereoselective bimolecular Diels-Alder reaction},
author = { Justin B Siegel and Alexandre Zanghellini and Helena M Lovick and Gert Kiss and Abigail R Lambert and Jennifer L St Clair and Jasmine L Gallaher and Donald Hilvert and Michael H Gelb and Barry L Stoddard and Kendall N Houk and Forrest E Michael and David Baker},
issn = {1095-9203},
year = {2010},
date = {2010-07-01},
journal = {Science},
volume = {329},
pages = {309-13},
abstract = {The Diels-Alder reaction is a cornerstone in organic synthesis, forming two carbon-carbon bonds and up to four new stereogenic centers in one step. No naturally occurring enzymes have been shown to catalyze bimolecular Diels-Alder reactions. We describe the de novo computational design and experimental characterization of enzymes catalyzing a bimolecular Diels-Alder reaction with high stereoselectivity and substrate specificity. X-ray crystallography confirms that the structure matches the design for the most active of the enzymes, and binding site substitutions reprogram the substrate specificity. Designed stereoselective catalysts for carbon-carbon bond-forming reactions should be broadly useful in synthetic chemistry.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Diels-Alder reaction is a cornerstone in organic synthesis, forming two carbon-carbon bonds and up to four new stereogenic centers in one step. No naturally occurring enzymes have been shown to catalyze bimolecular Diels-Alder reactions. We describe the de novo computational design and experimental characterization of enzymes catalyzing a bimolecular Diels-Alder reaction with high stereoselectivity and substrate specificity. X-ray crystallography confirms that the structure matches the design for the most active of the enzymes, and binding site substitutions reprogram the substrate specificity. Designed stereoselective catalysts for carbon-carbon bond-forming reactions should be broadly useful in synthetic chemistry.
Nicola A G Meenan, Amit Sharma, Sarel J Fleishman, Colin J Macdonald, Bertrand Morel, Ruth Boetzel, Geoffrey R Moore, David Baker, Colin Kleanthous
The structural and energetic basis for high selectivity in a high-affinity protein-protein interaction. Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 107, pp. 10080-5, 2010, ISSN: 1091-6490.
@article{577,
title = {The structural and energetic basis for high selectivity in a high-affinity protein-protein interaction.},
author = { Nicola A G Meenan and Amit Sharma and Sarel J Fleishman and Colin J Macdonald and Bertrand Morel and Ruth Boetzel and Geoffrey R Moore and David Baker and Colin Kleanthous},
doi = {10.1073/pnas.0910756107},
issn = {1091-6490},
year = {2010},
date = {2010-06-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {107},
pages = {10080-5},
abstract = {High-affinity, high-selectivity protein-protein interactions that are critical for cell survival present an evolutionary paradox: How does selectivity evolve when acquired mutations risk a lethal loss of high-affinity binding? A detailed understanding of selectivity in such complexes requires structural information on weak, noncognate complexes which can be difficult to obtain due to their transient and dynamic nature. Using NMR-based docking as a guide, we deployed a disulfide-trapping strategy on a noncognate complex between the colicin E9 endonuclease (E9 DNase) and immunity protein 2 (Im2), which is seven orders of magnitude weaker binding than the cognate femtomolar E9 DNase-Im9 interaction. The 1.77 A crystal structure of the E9 DNase-Im2 complex reveals an entirely noncovalent interface where the intersubunit disulfide merely supports the crystal lattice. In combination with computational alanine scanning of interfacial residues, the structure reveals that the driving force for binding is so strong that a severely unfavorable specificity contact is tolerated at the interface and as a result the complex becomes weakened through "frustration." As well as rationalizing past mutational and thermodynamic data, comparing our noncognate structure with previous cognate complexes highlights the importance of loop regions in developing selectivity and accentuates the multiple roles of buried water molecules that stabilize, ameliorate, or aggravate interfacial contacts. The study provides direct support for dual-recognition in colicin DNase-Im protein complexes and shows that weakened noncognate complexes are primed for high-affinity binding, which can be achieved by economical mutation of a limited number of residues at the interface.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
High-affinity, high-selectivity protein-protein interactions that are critical for cell survival present an evolutionary paradox: How does selectivity evolve when acquired mutations risk a lethal loss of high-affinity binding? A detailed understanding of selectivity in such complexes requires structural information on weak, noncognate complexes which can be difficult to obtain due to their transient and dynamic nature. Using NMR-based docking as a guide, we deployed a disulfide-trapping strategy on a noncognate complex between the colicin E9 endonuclease (E9 DNase) and immunity protein 2 (Im2), which is seven orders of magnitude weaker binding than the cognate femtomolar E9 DNase-Im9 interaction. The 1.77 A crystal structure of the E9 DNase-Im2 complex reveals an entirely noncovalent interface where the intersubunit disulfide merely supports the crystal lattice. In combination with computational alanine scanning of interfacial residues, the structure reveals that the driving force for binding is so strong that a severely unfavorable specificity contact is tolerated at the interface and as a result the complex becomes weakened through “frustration.” As well as rationalizing past mutational and thermodynamic data, comparing our noncognate structure with previous cognate complexes highlights the importance of loop regions in developing selectivity and accentuates the multiple roles of buried water molecules that stabilize, ameliorate, or aggravate interfacial contacts. The study provides direct support for dual-recognition in colicin DNase-Im protein complexes and shows that weakened noncognate complexes are primed for high-affinity binding, which can be achieved by economical mutation of a limited number of residues at the interface.
Ben Blum, Michael I Jordan, David Baker
Feature space resampling for protein conformational search Journal Article
In: Proteins, vol. 78, pp. 1583-93, 2010, ISSN: 1097-0134.
@article{271,
title = {Feature space resampling for protein conformational search},
author = { Ben Blum and Michael I Jordan and David Baker},
issn = {1097-0134},
year = {2010},
date = {2010-05-01},
journal = {Proteins},
volume = {78},
pages = {1583-93},
abstract = {De novo protein structure prediction requires location of the lowest energy state of the polypeptide chain among a vast set of possible conformations. Powerful approaches include conformational space annealing, in which search progressively focuses on the most promising regions of conformational space, and genetic algorithms, in which features of the best conformations thus far identified are recombined. We describe a new approach that combines the strengths of these two approaches. Protein conformations are projected onto a discrete feature space which includes backbone torsion angles, secondary structure, and beta pairings. For each of these there is one "native" value: the one found in the native structure. We begin with a large number of conformations generated in independent Monte Carlo structure prediction trajectories from Rosetta. Native values for each feature are predicted from the frequencies of feature value occurrences and the energy distribution in conformations containing them. A second round of structure prediction trajectories are then guided by the predicted native feature distributions. We show that native features can be predicted at much higher than background rates, and that using the predicted feature distributions improves structure prediction in a benchmark of 28 proteins. The advantages of our approach are that features from many different input structures can be combined simultaneously without producing atomic clashes or otherwise physically inviable models, and that the features being recombined have a relatively high chance of being correct.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
De novo protein structure prediction requires location of the lowest energy state of the polypeptide chain among a vast set of possible conformations. Powerful approaches include conformational space annealing, in which search progressively focuses on the most promising regions of conformational space, and genetic algorithms, in which features of the best conformations thus far identified are recombined. We describe a new approach that combines the strengths of these two approaches. Protein conformations are projected onto a discrete feature space which includes backbone torsion angles, secondary structure, and beta pairings. For each of these there is one “native” value: the one found in the native structure. We begin with a large number of conformations generated in independent Monte Carlo structure prediction trajectories from Rosetta. Native values for each feature are predicted from the frequencies of feature value occurrences and the energy distribution in conformations containing them. A second round of structure prediction trajectories are then guided by the predicted native feature distributions. We show that native features can be predicted at much higher than background rates, and that using the predicted feature distributions improves structure prediction in a benchmark of 28 proteins. The advantages of our approach are that features from many different input structures can be combined simultaneously without producing atomic clashes or otherwise physically inviable models, and that the features being recombined have a relatively high chance of being correct.
Rhiju Das, John Karanicolas, David Baker
Atomic accuracy in predicting and designing noncanonical RNA structure Journal Article
In: Nature methods, vol. 7, pp. 291-4, 2010, ISSN: 1548-7105.
@article{362,
title = {Atomic accuracy in predicting and designing noncanonical RNA structure},
author = { Rhiju Das and John Karanicolas and David Baker},
issn = {1548-7105},
year = {2010},
date = {2010-04-01},
journal = {Nature methods},
volume = {7},
pages = {291-4},
abstract = {We present fragment assembly of RNA with full-atom refinement (FARFAR), a Rosetta framework for predicting and designing noncanonical motifs that define RNA tertiary structure. In a test set of thirty-two 6-20-nucleotide motifs, FARFAR recapitulated 50% of the experimental structures at near-atomic accuracy. Sequence redesign calculations recovered native bases at 65% of residues engaged in noncanonical interactions, and we experimentally validated mutations predicted to stabilize a signal recognition particle domain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present fragment assembly of RNA with full-atom refinement (FARFAR), a Rosetta framework for predicting and designing noncanonical motifs that define RNA tertiary structure. In a test set of thirty-two 6-20-nucleotide motifs, FARFAR recapitulated 50% of the experimental structures at near-atomic accuracy. Sequence redesign calculations recovered native bases at 65% of residues engaged in noncanonical interactions, and we experimentally validated mutations predicted to stabilize a signal recognition particle domain.
Olga Khersonsky, Daniela R”othlisberger, Orly Dym, Shira Albeck, Colin J Jackson, David Baker, Dan S Tawfik
Evolutionary optimization of computationally designed enzymes: Kemp eliminases of the KE07 series Journal Article
In: Journal of Molecular Biology, vol. 396, pp. 1025-42, 2010, ISSN: 1089-8638.
@article{583,
title = {Evolutionary optimization of computationally designed enzymes: Kemp eliminases of the KE07 series},
author = { Olga Khersonsky and Daniela R"othlisberger and Orly Dym and Shira Albeck and Colin J Jackson and David Baker and Dan S Tawfik},
doi = {10.1016/j.jmb.2009.12.031},
issn = {1089-8638},
year = {2010},
date = {2010-03-01},
journal = {Journal of Molecular Biology},
volume = {396},
pages = {1025-42},
abstract = {Understanding enzyme catalysis through the analysis of natural enzymes is a daunting challenge-their active sites are complex and combine numerous interactions and catalytic forces that are finely coordinated. Study of more rudimentary (wo)man-made enzymes provides a unique opportunity for better understanding of enzymatic catalysis. KE07, a computationally designed Kemp eliminase that employs a glutamate side chain as the catalytic base for the critical proton abstraction step and an apolar binding site to guide substrate binding, was optimized by seven rounds of random mutagenesis and selection, resulting in a >200-fold increase in catalytic efficiency. Here, we describe the directed evolution process in detail and the biophysical and crystallographic studies of the designed KE07 and its evolved variants. The optimization of KE07textquoterights activity to give a k(cat)/K(M) value of approximately 2600 s(-1) M(-1) and an approximately 10(6)-fold rate acceleration (k(cat)/k(uncat)) involved the incorporation of up to eight mutations. These mutations led to a marked decrease in the overall thermodynamic stability of the evolved KE07s and in the configurational stability of their active sites. We identified two primary contributions of the mutations to KE07textquoterights improved activity: (i) the introduction of new salt bridges to correct a mistake in the original design that placed a lysine for leaving-group protonation without consideration of its "quenching" interactions with the catalytic glutamate, and (ii) the tuning of the environment, the pK(a) of the catalytic base, and its interactions with the substrate through the evolution of a network of hydrogen bonds consisting of several charged residues surrounding the active site.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Understanding enzyme catalysis through the analysis of natural enzymes is a daunting challenge-their active sites are complex and combine numerous interactions and catalytic forces that are finely coordinated. Study of more rudimentary (wo)man-made enzymes provides a unique opportunity for better understanding of enzymatic catalysis. KE07, a computationally designed Kemp eliminase that employs a glutamate side chain as the catalytic base for the critical proton abstraction step and an apolar binding site to guide substrate binding, was optimized by seven rounds of random mutagenesis and selection, resulting in a >200-fold increase in catalytic efficiency. Here, we describe the directed evolution process in detail and the biophysical and crystallographic studies of the designed KE07 and its evolved variants. The optimization of KE07textquoterights activity to give a k(cat)/K(M) value of approximately 2600 s(-1) M(-1) and an approximately 10(6)-fold rate acceleration (k(cat)/k(uncat)) involved the incorporation of up to eight mutations. These mutations led to a marked decrease in the overall thermodynamic stability of the evolved KE07s and in the configurational stability of their active sites. We identified two primary contributions of the mutations to KE07textquoterights improved activity: (i) the introduction of new salt bridges to correct a mistake in the original design that placed a lysine for leaving-group protonation without consideration of its “quenching” interactions with the catalytic glutamate, and (ii) the tuning of the environment, the pK(a) of the catalytic base, and its interactions with the substrate through the evolution of a network of hydrogen bonds consisting of several charged residues surrounding the active site.
Chu Wang, Robert Vernon, Oliver Lange, Michael Tyka, David Baker
Prediction of structures of zinc-binding proteins through explicit modeling of metal coordination geometry Journal Article
In: Protein science, vol. 19, pp. 494-506, 2010, ISSN: 1469-896X.
@article{257,
title = {Prediction of structures of zinc-binding proteins through explicit modeling of metal coordination geometry},
author = { Chu Wang and Robert Vernon and Oliver Lange and Michael Tyka and David Baker},
issn = {1469-896X},
year = {2010},
date = {2010-03-01},
journal = {Protein science},
volume = {19},
pages = {494-506},
abstract = {Metal ions play an essential role in stabilizing protein structures and contributing to protein function. Ions such as zinc have well-defined coordination geometries, but it has not been easy to take advantage of this knowledge in protein structure prediction efforts. Here, we present a computational method to predict structures of zinc-binding proteins given knowledge of the positions of zinc-coordinating residues in the amino acid sequence. The method takes advantage of the "atom-tree" representation of molecular systems and modular architecture of the Rosetta3 software suite to incorporate explicit metal ion coordination geometry into previously developed de novo prediction and loop modeling protocols. Zinc cofactors are tethered to their interacting residues based on coordination geometries observed in natural zinc-binding proteins. The incorporation of explicit zinc atoms and their coordination geometry in both de novo structure prediction and loop modeling significantly improves sampling near the native conformation. The method can be readily extended to predict protein structures bound to other metal and/or small chemical cofactors with well-defined coordination or ligation geometry.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Metal ions play an essential role in stabilizing protein structures and contributing to protein function. Ions such as zinc have well-defined coordination geometries, but it has not been easy to take advantage of this knowledge in protein structure prediction efforts. Here, we present a computational method to predict structures of zinc-binding proteins given knowledge of the positions of zinc-coordinating residues in the amino acid sequence. The method takes advantage of the “atom-tree” representation of molecular systems and modular architecture of the Rosetta3 software suite to incorporate explicit metal ion coordination geometry into previously developed de novo prediction and loop modeling protocols. Zinc cofactors are tethered to their interacting residues based on coordination geometries observed in natural zinc-binding proteins. The incorporation of explicit zinc atoms and their coordination geometry in both de novo structure prediction and loop modeling significantly improves sampling near the native conformation. The method can be readily extended to predict protein structures bound to other metal and/or small chemical cofactors with well-defined coordination or ligation geometry.
Srivatsan Raman, Oliver F Lange, Paolo Rossi, Michael Tyka, Xu Wang, James Aramini, Gaohua Liu, Theresa A Ramelot, Alexander Eletsky, Thomas Szyperski, Michael A Kennedy, James Prestegard, Gaetano T Montelione, David Baker
NMR structure determination for larger proteins using backbone-only data Journal Article
In: Science, vol. 327, pp. 1014-8, 2010, ISSN: 1095-9203.
@article{55,
title = {NMR structure determination for larger proteins using backbone-only data},
author = { Srivatsan Raman and Oliver F Lange and Paolo Rossi and Michael Tyka and Xu Wang and James Aramini and Gaohua Liu and Theresa A Ramelot and Alexander Eletsky and Thomas Szyperski and Michael A Kennedy and James Prestegard and Gaetano T Montelione and David Baker},
issn = {1095-9203},
year = {2010},
date = {2010-02-01},
journal = {Science},
volume = {327},
pages = {1014-8},
abstract = {Conventional protein structure determination from nuclear magnetic resonance data relies heavily on side-chain proton-to-proton distances. The necessary side-chain resonance assignment, however, is labor intensive and prone to error. Here we show that structures can be accurately determined without nuclear magnetic resonance (NMR) information on the side chains for proteins up to 25 kilodaltons by incorporating backbone chemical shifts, residual dipolar couplings, and amide proton distances into the Rosetta protein structure modeling methodology. These data, which are too sparse for conventional methods, serve only to guide conformational search toward the lowest-energy conformations in the folding landscape; the details of the computed models are determined by the physical chemistry implicit in the Rosetta all-atom energy function. The new method is not hindered by the deuteration required to suppress nuclear relaxation processes for proteins greater than 15 kilodaltons and should enable routine NMR structure determination for larger proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Conventional protein structure determination from nuclear magnetic resonance data relies heavily on side-chain proton-to-proton distances. The necessary side-chain resonance assignment, however, is labor intensive and prone to error. Here we show that structures can be accurately determined without nuclear magnetic resonance (NMR) information on the side chains for proteins up to 25 kilodaltons by incorporating backbone chemical shifts, residual dipolar couplings, and amide proton distances into the Rosetta protein structure modeling methodology. These data, which are too sparse for conventional methods, serve only to guide conformational search toward the lowest-energy conformations in the folding landscape; the details of the computed models are determined by the physical chemistry implicit in the Rosetta all-atom energy function. The new method is not hindered by the deuteration required to suppress nuclear relaxation processes for proteins greater than 15 kilodaltons and should enable routine NMR structure determination for larger proteins.
Yang Shen, Philip N Bryan, Yanan He, John Orban, David Baker, Ad Bax
De novo structure generation using chemical shifts for proteins with high-sequence identity but different folds Journal Article
In: Protein Science : A Publication of the Protein Society, vol. 19, pp. 349-56, 2010, ISSN: 1469-896X.
@article{584,
title = {De novo structure generation using chemical shifts for proteins with high-sequence identity but different folds},
author = { Yang Shen and Philip N Bryan and Yanan He and John Orban and David Baker and Ad Bax},
doi = {10.1002/pro.303},
issn = {1469-896X},
year = {2010},
date = {2010-02-01},
journal = {Protein Science : A Publication of the Protein Society},
volume = {19},
pages = {349-56},
abstract = {Proteins with high-sequence identity but very different folds present a special challenge to sequence-based protein structure prediction methods. In particular, a 56-residue three-helical bundle protein (GA(95)) and an alpha/beta-fold protein (GB(95)), which share 95% sequence identity, were targets in the CASP-8 structure prediction contest. With only 12 out of 300 submitted server-CASP8 models for GA(95) exhibiting the correct fold, this protein proved particularly challenging despite its small size. Here, we demonstrate that the information contained in NMR chemical shifts can readily be exploited by the CS-Rosetta structure prediction program and yields adequate convergence, even when input chemical shifts are limited to just amide (1)H(N) and (15)N or (1)H(N) and (1)H(alpha) values.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Proteins with high-sequence identity but very different folds present a special challenge to sequence-based protein structure prediction methods. In particular, a 56-residue three-helical bundle protein (GA(95)) and an alpha/beta-fold protein (GB(95)), which share 95% sequence identity, were targets in the CASP-8 structure prediction contest. With only 12 out of 300 submitted server-CASP8 models for GA(95) exhibiting the correct fold, this protein proved particularly challenging despite its small size. Here, we demonstrate that the information contained in NMR chemical shifts can readily be exploited by the CS-Rosetta structure prediction program and yields adequate convergence, even when input chemical shifts are limited to just amide (1)H(N) and (15)N or (1)H(N) and (1)H(alpha) values.
Srivatsan Raman, Yuanpeng J Huang, Binchen Mao, Paolo Rossi, James M Aramini, Gaohua Liu, Gaetano T Montelione, David Baker
Accurate automated protein NMR structure determination using unassigned NOESY data Journal Article
In: Journal of the American Chemical Society, vol. 132, pp. 202-7, 2010, ISSN: 1520-5126.
@article{258,
title = {Accurate automated protein NMR structure determination using unassigned NOESY data},
author = { Srivatsan Raman and Yuanpeng J Huang and Binchen Mao and Paolo Rossi and James M Aramini and Gaohua Liu and Gaetano T Montelione and David Baker},
issn = {1520-5126},
year = {2010},
date = {2010-01-01},
journal = {Journal of the American Chemical Society},
volume = {132},
pages = {202-7},
abstract = {Conventional NMR structure determination requires nearly complete assignment of the cross peaks of a refined NOESY peak list. Depending on the size of the protein and quality of the spectral data, this can be a time-consuming manual process requiring several rounds of peak list refinement and structure determination. Programs such as Aria, CYANA, and AutoStructure can generate models using unassigned NOESY data but are very sensitive to the quality of the input peak lists and can converge to inaccurate structures if the signal-to-noise of the peak lists is low. Here, we show that models with high accuracy and reliability can be produced by combining the strengths of the high-resolution structure prediction program Rosetta with global measures of the agreement between structure models and experimental data. A first round of models generated using CS-Rosetta (Rosetta supplemented with backbone chemical shift information) are filtered on the basis of their goodness-of-fit with unassigned NOESY peak lists using the DP-score, and the best fitting models are subjected to high resolution refinement with the Rosetta rebuild-and-refine protocol. This hybrid approach uses both local backbone chemical shift and the unassigned NOESY data to direct Rosetta trajectories toward the native structure and produces more accurate models than AutoStructure/CYANA or CS-Rosetta alone, particularly when using raw unedited NOESY peak lists. We also show that when accurate manually refined NOESY peak lists are available, Rosetta refinement can consistently increase the accuracy of models generated using CYANA and AutoStructure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Conventional NMR structure determination requires nearly complete assignment of the cross peaks of a refined NOESY peak list. Depending on the size of the protein and quality of the spectral data, this can be a time-consuming manual process requiring several rounds of peak list refinement and structure determination. Programs such as Aria, CYANA, and AutoStructure can generate models using unassigned NOESY data but are very sensitive to the quality of the input peak lists and can converge to inaccurate structures if the signal-to-noise of the peak lists is low. Here, we show that models with high accuracy and reliability can be produced by combining the strengths of the high-resolution structure prediction program Rosetta with global measures of the agreement between structure models and experimental data. A first round of models generated using CS-Rosetta (Rosetta supplemented with backbone chemical shift information) are filtered on the basis of their goodness-of-fit with unassigned NOESY peak lists using the DP-score, and the best fitting models are subjected to high resolution refinement with the Rosetta rebuild-and-refine protocol. This hybrid approach uses both local backbone chemical shift and the unassigned NOESY data to direct Rosetta trajectories toward the native structure and produces more accurate models than AutoStructure/CYANA or CS-Rosetta alone, particularly when using raw unedited NOESY peak lists. We also show that when accurate manually refined NOESY peak lists are available, Rosetta refinement can consistently increase the accuracy of models generated using CYANA and AutoStructure.
Charles Chung Yun Leung, Elizabeth Kellogg, Anja Kuhnert, Frank H”anel, David Baker, J N Mark Glover
Insights from the crystal structure of the sixth BRCT domain of topoisomerase IIbeta binding protein 1 Journal Article
In: Protein science : a publication of the Protein Society, vol. 19, pp. 162-7, 2010, ISSN: 1469-896X.
@article{582,
title = {Insights from the crystal structure of the sixth BRCT domain of topoisomerase IIbeta binding protein 1},
author = { Charles Chung Yun Leung and Elizabeth Kellogg and Anja Kuhnert and Frank H"anel and David Baker and J N Mark Glover},
doi = {10.1002/pro.290},
issn = {1469-896X},
year = {2010},
date = {2010-01-01},
journal = {Protein science : a publication of the Protein Society},
volume = {19},
pages = {162-7},
abstract = {Topoisomerase IIbeta binding protein 1 (TopBP1) is a major player in the DNA damage response and interacts with a number of protein partners via its eight BRCA1 carboxy-terminal (BRCT) domains. In particular, the sixth BRCT domain of TopBP1 has been implicated in binding to the phosphorylated transcription factor, E2F1, and poly(ADP-ribose) polymerase 1 (PARP-1), where the latter interaction is responsible for the poly(ADP-ribosyl)ation of TopBP1. To gain a better understanding of the nature of TopBP1 BRCT6 interactions, we solved the crystal structure of BRCT6 to 1.34 A. The crystal structure reveals a degenerate phospho-peptide binding pocket and lacks conserved hydrophobic residues involved in packing of tandem BRCT repeats, which, together with results from phospho-peptide binding studies, strongly suggest that TopBP1 BRCT6 independently does not function as a phospho-peptide binding domain. We further provide insight into poly(ADP-ribose) binding and sites of potential modification by PARP-1.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Topoisomerase IIbeta binding protein 1 (TopBP1) is a major player in the DNA damage response and interacts with a number of protein partners via its eight BRCA1 carboxy-terminal (BRCT) domains. In particular, the sixth BRCT domain of TopBP1 has been implicated in binding to the phosphorylated transcription factor, E2F1, and poly(ADP-ribose) polymerase 1 (PARP-1), where the latter interaction is responsible for the poly(ADP-ribosyl)ation of TopBP1. To gain a better understanding of the nature of TopBP1 BRCT6 interactions, we solved the crystal structure of BRCT6 to 1.34 A. The crystal structure reveals a degenerate phospho-peptide binding pocket and lacks conserved hydrophobic residues involved in packing of tandem BRCT repeats, which, together with results from phospho-peptide binding studies, strongly suggest that TopBP1 BRCT6 independently does not function as a phospho-peptide binding domain. We further provide insight into poly(ADP-ribose) binding and sites of potential modification by PARP-1.
Seth Cooper, Adrien Treuille, Janos Barbero, Andrew Leaver-Fay, Kathleen Tuite, Firas Khatib, Alex Cho Snyder, Michael Beenen, David Salesin, David Baker, Zoran Popovi’c, 000 Foldit playes >57
The Challenge of Designing Scientific Discovery Games Journal Article
In: Proceedings of the Fifth international Conference on the Foundations of Digital Games, 2010.
@article{363,
title = {The Challenge of Designing Scientific Discovery Games},
author = { Seth Cooper and Adrien Treuille and Janos Barbero and Andrew Leaver-Fay and Kathleen Tuite and Firas Khatib and Alex Cho Snyder and Michael Beenen and David Salesin and David Baker and Zoran Popovi'c and 000 Foldit playes >57},
url = {http://doi.acm.org/10.1145/1822348.1822354},
year = {2010},
date = {2010-00-01},
journal = {Proceedings of the Fifth international Conference on the Foundations of Digital Games},
abstract = {Incorporating the individual and collective problem solving skills of non-experts into the scientific discovery process could potentially accelerate the advancement of science. This paper discusses the design process used for Foldit, a multiplayer online biochemistry game that presents players with computationally difficult protein folding problems in the form of puzzles, allowing ordinary players to gain expertise and help solve these problems. The principle challenge of designing such scientific discovery games is harnessing the enormous collective problem-solving potential of the game playing population, who have not been previously introduced to the specific problem, or, often, the entire scientific discipline. To address this challenge, we took an iterative approach to designing the game, incorporating feedback from players and biochemical experts alike. Feedback was gathered both before and after releasing the game, to create the rules, interactions, and visualizations in Foldit that maximize contributions from game players. We present several examples of how this approach guided the gametextquoterights design, and allowed us to improve both the quality of the gameplay and the application of player problem-solving.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Incorporating the individual and collective problem solving skills of non-experts into the scientific discovery process could potentially accelerate the advancement of science. This paper discusses the design process used for Foldit, a multiplayer online biochemistry game that presents players with computationally difficult protein folding problems in the form of puzzles, allowing ordinary players to gain expertise and help solve these problems. The principle challenge of designing such scientific discovery games is harnessing the enormous collective problem-solving potential of the game playing population, who have not been previously introduced to the specific problem, or, often, the entire scientific discipline. To address this challenge, we took an iterative approach to designing the game, incorporating feedback from players and biochemical experts alike. Feedback was gathered both before and after releasing the game, to create the rules, interactions, and visualizations in Foldit that maximize contributions from game players. We present several examples of how this approach guided the gametextquoterights design, and allowed us to improve both the quality of the gameplay and the application of player problem-solving.
Sarah Sanowar, Pragya Singh, Richard A Pfuetzner, Ingemar Andr’e, Hongjin Zheng, Thomas Spreter, Natalie C J Strynadka, Tamir Gonen, David Baker, David R Goodlett, Samuel I Miller
Interactions of the Transmembrane Polymeric Rings of the Salmonella enterica Serovar Typhimurium Type III Secretion System Journal Article
In: mBio, vol. 1, 2010, ISSN: 2150-7511.
@article{261,
title = {Interactions of the Transmembrane Polymeric Rings of the Salmonella enterica Serovar Typhimurium Type III Secretion System},
author = { Sarah Sanowar and Pragya Singh and Richard A Pfuetzner and Ingemar Andr'e and Hongjin Zheng and Thomas Spreter and Natalie C J Strynadka and Tamir Gonen and David Baker and David R Goodlett and Samuel I Miller},
issn = {2150-7511},
year = {2010},
date = {2010-00-01},
journal = {mBio},
volume = {1},
abstract = {The type III secretion system (T3SS) is an interspecies protein transport machine that plays a major role in interactions of Gram-negative bacteria with animals and plants by delivering bacterial effector proteins into host cells. T3SSs span both membranes of Gram-negative bacteria by forming a structure of connected oligomeric rings termed the needle complex (NC). Here, the localization of subunits in the Salmonella enterica serovar Typhimurium T3SS NC were probed via mass spectrometry-assisted identification of chemical cross-links in intact NC preparations. Cross-links between amino acids near the amino terminus of the outer membrane ring component InvG and the carboxyl terminus of the inner membrane ring component PrgH and between the two inner membrane components PrgH and PrgK allowed for spatial localization of the three ring components within the electron density map structures of NCs. Mutational and biochemical analysis demonstrated that the amino terminus of InvG and the carboxyl terminus of PrgH play a critical role in the assembly and function of the T3SS apparatus. Analysis of an InvG mutant indicates that the structure of the InvG oligomer can affect the switching of the T3SS substrate to translocon and effector components. This study provides insights into how structural organization of needle complex base components promotes T3SS assembly and function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The type III secretion system (T3SS) is an interspecies protein transport machine that plays a major role in interactions of Gram-negative bacteria with animals and plants by delivering bacterial effector proteins into host cells. T3SSs span both membranes of Gram-negative bacteria by forming a structure of connected oligomeric rings termed the needle complex (NC). Here, the localization of subunits in the Salmonella enterica serovar Typhimurium T3SS NC were probed via mass spectrometry-assisted identification of chemical cross-links in intact NC preparations. Cross-links between amino acids near the amino terminus of the outer membrane ring component InvG and the carboxyl terminus of the inner membrane ring component PrgH and between the two inner membrane components PrgH and PrgK allowed for spatial localization of the three ring components within the electron density map structures of NCs. Mutational and biochemical analysis demonstrated that the amino terminus of InvG and the carboxyl terminus of PrgH play a critical role in the assembly and function of the T3SS apparatus. Analysis of an InvG mutant indicates that the structure of the InvG oligomer can affect the switching of the T3SS substrate to translocon and effector components. This study provides insights into how structural organization of needle complex base components promotes T3SS assembly and function.
2009
Rhiju Das, Ingemar Andr’e, Yang Shen, Yibing Wu, Alexander Lemak, Sonal Bansal, Cheryl H Arrowsmith, Thomas Szyperski, David Baker
Simultaneous prediction of protein folding and docking at high resolution Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 106, pp. 18978-83, 2009, ISSN: 1091-6490.
@article{124,
title = {Simultaneous prediction of protein folding and docking at high resolution},
author = { Rhiju Das and Ingemar Andr'e and Yang Shen and Yibing Wu and Alexander Lemak and Sonal Bansal and Cheryl H Arrowsmith and Thomas Szyperski and David Baker},
issn = {1091-6490},
year = {2009},
date = {2009-11-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {106},
pages = {18978-83},
abstract = {Interleaved dimers and higher order symmetric oligomers are ubiquitous in biology but present a challenge to de novo structure prediction methodology: The structure adopted by a monomer can be stabilized largely by interactions with other monomers and hence not the lowest energy state of a single chain. Building on the Rosetta framework, we present a general method to simultaneously model the folding and docking of multiple-chain interleaved homo-oligomers. For more than a third of the cases in a benchmark set of interleaved homo-oligomers, the method generates near-native models of large alpha-helical bundles, interlocking beta sandwiches, and interleaved alpha/beta motifs with an accuracy high enough for molecular replacement based phasing. With the incorporation of NMR chemical shift information, accurate models can be obtained consistently for symmetric complexes with as many as 192 total amino acids; a blind prediction was within 1 A rmsd of the traditionally determined NMR structure, and fit independently collected RDC data equally well. Together, these results show that the Rosetta "fold-and-dock" protocol can produce models of homo-oligomeric complexes with near-atomic-level accuracy and should be useful for crystallographic phasing and the rapid determination of the structures of multimers with limited NMR information.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Interleaved dimers and higher order symmetric oligomers are ubiquitous in biology but present a challenge to de novo structure prediction methodology: The structure adopted by a monomer can be stabilized largely by interactions with other monomers and hence not the lowest energy state of a single chain. Building on the Rosetta framework, we present a general method to simultaneously model the folding and docking of multiple-chain interleaved homo-oligomers. For more than a third of the cases in a benchmark set of interleaved homo-oligomers, the method generates near-native models of large alpha-helical bundles, interlocking beta sandwiches, and interleaved alpha/beta motifs with an accuracy high enough for molecular replacement based phasing. With the incorporation of NMR chemical shift information, accurate models can be obtained consistently for symmetric complexes with as many as 192 total amino acids; a blind prediction was within 1 A rmsd of the traditionally determined NMR structure, and fit independently collected RDC data equally well. Together, these results show that the Rosetta “fold-and-dock” protocol can produce models of homo-oligomeric complexes with near-atomic-level accuracy and should be useful for crystallographic phasing and the rapid determination of the structures of multimers with limited NMR information.
Summer B Thyme, Jordan Jarjour, Ryo Takeuchi, James J Havranek, Justin Ashworth, Andrew M Scharenberg, Barry L Stoddard, David Baker
Exploitation of binding energy for catalysis and design Journal Article
In: Nature, vol. 461, pp. 1300-4, 2009, ISSN: 1476-4687.
@article{138,
title = {Exploitation of binding energy for catalysis and design},
author = { Summer B Thyme and Jordan Jarjour and Ryo Takeuchi and James J Havranek and Justin Ashworth and Andrew M Scharenberg and Barry L Stoddard and David Baker},
issn = {1476-4687},
year = {2009},
date = {2009-10-01},
journal = {Nature},
volume = {461},
pages = {1300-4},
abstract = {Enzymes use substrate-binding energy both to promote ground-state association and to stabilize the reaction transition state selectively. The monomeric homing endonuclease I-AniI cleaves with high sequence specificity in the centre of a 20-base-pair (bp) DNA target site, with the amino (N)-terminal domain of the enzyme making extensive binding interactions with the left (-) side of the target site and the similarly structured carboxy (C)-terminal domain interacting with the right (+) side. Here we show that, despite the approximate twofold symmetry of the enzyme-DNA complex, there is almost complete segregation of interactions responsible for substrate binding to the (-) side of the interface and interactions responsible for transition-state stabilization to the (+) side. Although single base-pair substitutions throughout the entire DNA target site reduce catalytic efficiency, mutations in the (-) DNA half-site almost exclusively increase the dissociation constant (K(D)) and the Michaelis constant under single-turnover conditions (K(M)*), and those in the (+) half-site primarily decrease the turnover number (k(cat)*). The reduction of activity produced by mutations on the (-) side, but not mutations on the (+) side, can be suppressed by tethering the substrate to the endonuclease displayed on the surface of yeast. This dramatic asymmetry in the use of enzyme-substrate binding energy for catalysis has direct relevance to the redesign of endonucleases to cleave genomic target sites for gene therapy and other applications. Computationally redesigned enzymes that achieve new specificities on the (-) side do so by modulating K(M)*, whereas redesigns with altered specificities on the (+) side modulate k(cat)*. Our results illustrate how classical enzymology and modern protein design can each inform the other.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Enzymes use substrate-binding energy both to promote ground-state association and to stabilize the reaction transition state selectively. The monomeric homing endonuclease I-AniI cleaves with high sequence specificity in the centre of a 20-base-pair (bp) DNA target site, with the amino (N)-terminal domain of the enzyme making extensive binding interactions with the left (-) side of the target site and the similarly structured carboxy (C)-terminal domain interacting with the right (+) side. Here we show that, despite the approximate twofold symmetry of the enzyme-DNA complex, there is almost complete segregation of interactions responsible for substrate binding to the (-) side of the interface and interactions responsible for transition-state stabilization to the (+) side. Although single base-pair substitutions throughout the entire DNA target site reduce catalytic efficiency, mutations in the (-) DNA half-site almost exclusively increase the dissociation constant (K(D)) and the Michaelis constant under single-turnover conditions (K(M)*), and those in the (+) half-site primarily decrease the turnover number (k(cat)*). The reduction of activity produced by mutations on the (-) side, but not mutations on the (+) side, can be suppressed by tethering the substrate to the endonuclease displayed on the surface of yeast. This dramatic asymmetry in the use of enzyme-substrate binding energy for catalysis has direct relevance to the redesign of endonucleases to cleave genomic target sites for gene therapy and other applications. Computationally redesigned enzymes that achieve new specificities on the (-) side do so by modulating K(M)*, whereas redesigns with altered specificities on the (+) side modulate k(cat)*. Our results illustrate how classical enzymology and modern protein design can each inform the other.
David E Kim, Ben Blum, Philip Bradley, David Baker
Sampling bottlenecks in de novo protein structure prediction Journal Article
In: Journal of molecular biology, vol. 393, pp. 249-60, 2009, ISSN: 1089-8638.
@article{131,
title = {Sampling bottlenecks in de novo protein structure prediction},
author = { David E Kim and Ben Blum and Philip Bradley and David Baker},
issn = {1089-8638},
year = {2009},
date = {2009-10-01},
journal = {Journal of molecular biology},
volume = {393},
pages = {249-60},
abstract = {The primary obstacle to de novo protein structure prediction is conformational sampling: the native state generally has lower free energy than nonnative structures but is exceedingly difficult to locate. Structure predictions with atomic level accuracy have been made for small proteins using the Rosetta structure prediction method, but for larger and more complex proteins, the native state is virtually never sampled, and it has been unclear how much of an increase in computing power would be required to successfully predict the structures of such proteins. In this paper, we develop an approach to determining how much computer power is required to accurately predict the structure of a protein, based on a reformulation of the conformational search problem as a combinatorial sampling problem in a discrete feature space. We find that conformational sampling for many proteins is limited by critical "linchpin" features, often the backbone torsion angles of individual residues, which are sampled very rarely in unbiased trajectories and, when constrained, dramatically increase the sampling of the native state. These critical features frequently occur in less regular and likely strained regions of proteins that contribute to protein function. In a number of proteins, the linchpin features are in regions found experimentally to form late in folding, suggesting a correspondence between folding in silico and in reality.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The primary obstacle to de novo protein structure prediction is conformational sampling: the native state generally has lower free energy than nonnative structures but is exceedingly difficult to locate. Structure predictions with atomic level accuracy have been made for small proteins using the Rosetta structure prediction method, but for larger and more complex proteins, the native state is virtually never sampled, and it has been unclear how much of an increase in computing power would be required to successfully predict the structures of such proteins. In this paper, we develop an approach to determining how much computer power is required to accurately predict the structure of a protein, based on a reformulation of the conformational search problem as a combinatorial sampling problem in a discrete feature space. We find that conformational sampling for many proteins is limited by critical “linchpin” features, often the backbone torsion angles of individual residues, which are sampled very rarely in unbiased trajectories and, when constrained, dramatically increase the sampling of the native state. These critical features frequently occur in less regular and likely strained regions of proteins that contribute to protein function. In a number of proteins, the linchpin features are in regions found experimentally to form late in folding, suggesting a correspondence between folding in silico and in reality.
YA Ban, BE Correia, M Holmes, E Boni, N Sather, C Bretz, O Kalyuzhniy, C Xu2, D Baker, L Stamatatos, R Strong, W Sc
4e10 epitope-scaffolds mimic the antibody-bound epitope conformation and block neutralization by sera from rare HIV+ individuals Journal Article
In: Retrovirology, vol. 6, 2009.
@article{278,
title = {4e10 epitope-scaffolds mimic the antibody-bound epitope conformation and block neutralization by sera from rare HIV+ individuals},
author = { YA Ban and BE Correia and M Holmes and E Boni and N Sather and C Bretz and O Kalyuzhniy and C Xu2 and D Baker and L Stamatatos and R Strong and W Sc},
year = {2009},
date = {2009-10-01},
journal = {Retrovirology},
volume = {6},
chapter = {85},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Frank DiMaio, Michael D Tyka, Matthew L Baker, Wah Chiu, David Baker
Refinement of protein structures into low-resolution density maps using rosetta Journal Article
In: Journal of molecular biology, vol. 392, pp. 181-90, 2009, ISSN: 1089-8638.
@article{128,
title = {Refinement of protein structures into low-resolution density maps using rosetta},
author = { Frank DiMaio and Michael D Tyka and Matthew L Baker and Wah Chiu and David Baker},
issn = {1089-8638},
year = {2009},
date = {2009-09-01},
journal = {Journal of molecular biology},
volume = {392},
pages = {181-90},
abstract = {We describe a method based on Rosetta structure refinement for generating high-resolution, all-atom protein models from electron cryomicroscopy density maps. A local measure of the fit of a model to the density is used to directly guide structure refinement and to identify regions incompatible with the density that are then targeted for extensive rebuilding. Over a range of test cases using both simulated and experimentally generated data, the method consistently increases the accuracy of starting models generated either by comparative modeling or by hand-tracing the density. The method can achieve near-atomic resolution starting from density maps at 4-6 A resolution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a method based on Rosetta structure refinement for generating high-resolution, all-atom protein models from electron cryomicroscopy density maps. A local measure of the fit of a model to the density is used to directly guide structure refinement and to identify regions incompatible with the density that are then targeted for extensive rebuilding. Over a range of test cases using both simulated and experimentally generated data, the method consistently increases the accuracy of starting models generated either by comparative modeling or by hand-tracing the density. The method can achieve near-atomic resolution starting from density maps at 4-6 A resolution.
Ian W Davis, Kaushik Raha, Martha S Head, David Baker
Blind docking of pharmaceutically relevant compounds using RosettaLigand Journal Article
In: Protein science, vol. 18, pp. 1998-2002, 2009, ISSN: 1469-896X.
@article{126,
title = {Blind docking of pharmaceutically relevant compounds using RosettaLigand},
author = { Ian W Davis and Kaushik Raha and Martha S Head and David Baker},
issn = {1469-896X},
year = {2009},
date = {2009-09-01},
journal = {Protein science},
volume = {18},
pages = {1998-2002},
abstract = {It is difficult to properly validate algorithms that dock a small molecule ligand into its protein receptor using data from the public domain: the predictions are not blind because the correct binding mode is already known, and public test cases may not be representative of compounds of interest such as drug leads. Here, we use private data from a real drug discovery program to carry out a blind evaluation of the RosettaLigand docking methodology and find that its performance is on average comparable with that of the best commercially available current small molecule docking programs. The strength of RosettaLigand is the use of the Rosetta sampling methodology to simultaneously optimize protein sidechain, protein backbone and ligand degrees of freedom; the extensive benchmark test described here identifies shortcomings in other aspects of the protocol and suggests clear routes to improving the method.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
It is difficult to properly validate algorithms that dock a small molecule ligand into its protein receptor using data from the public domain: the predictions are not blind because the correct binding mode is already known, and public test cases may not be representative of compounds of interest such as drug leads. Here, we use private data from a real drug discovery program to carry out a blind evaluation of the RosettaLigand docking methodology and find that its performance is on average comparable with that of the best commercially available current small molecule docking programs. The strength of RosettaLigand is the use of the Rosetta sampling methodology to simultaneously optimize protein sidechain, protein backbone and ligand degrees of freedom; the extensive benchmark test described here identifies shortcomings in other aspects of the protocol and suggests clear routes to improving the method.
Antonio Rosato, Anurag Bagaria, David Baker, Benjamin Bardiaux, Andrea Cavalli, Jurgen F Doreleijers, Andrea Giachetti, Paul Guerry, Peter G”untert, Torsten Herrmann, Yuanpeng J Huang, Hendrik R A Jonker, Binchen Mao, Th’er`ese E Malliavin, Gaetano T Montelione, Michael Nilges, Srivatsan Raman, Gijs van der Schot, Wim F Vranken, Geerten W Vuister, Alexandre M J J Bonvin
CASD-NMR: critical assessment of automated structure determination by NMR Journal Article
In: Nature methods, vol. 6, pp. 625-6, 2009, ISSN: 1548-7105.
@article{277,
title = {CASD-NMR: critical assessment of automated structure determination by NMR},
author = { Antonio Rosato and Anurag Bagaria and David Baker and Benjamin Bardiaux and Andrea Cavalli and Jurgen F Doreleijers and Andrea Giachetti and Paul Guerry and Peter G"untert and Torsten Herrmann and Yuanpeng J Huang and Hendrik R A Jonker and Binchen Mao and Th'er`ese E Malliavin and Gaetano T Montelione and Michael Nilges and Srivatsan Raman and Gijs van der Schot and Wim F Vranken and Geerten W Vuister and Alexandre M J J Bonvin},
issn = {1548-7105},
year = {2009},
date = {2009-09-01},
journal = {Nature methods},
volume = {6},
pages = {625-6},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Brian A Kidd, David Baker, Wendy E Thomas
Computation of conformational coupling in allosteric proteins Journal Article
In: PLoS computational biology, vol. 5, pp. e1000484, 2009, ISSN: 1553-7358.
@article{130,
title = {Computation of conformational coupling in allosteric proteins},
author = { Brian A Kidd and David Baker and Wendy E Thomas},
issn = {1553-7358},
year = {2009},
date = {2009-08-01},
journal = {PLoS computational biology},
volume = {5},
pages = {e1000484},
abstract = {In allosteric regulation, an effector molecule binding a protein at one site induces conformational changes, which alter structure and function at a distant active site. Two key challenges in the computational modeling of allostery are the prediction of the structure of one allosteric state starting from the structure of the other, and elucidating the mechanisms underlying the conformational coupling of the effector and active sites. Here we approach these two challenges using the Rosetta high-resolution structure prediction methodology. We find that the method can recapitulate the relaxation of effector-bound forms of single domain allosteric proteins into the corresponding ligand-free states, particularly when sampling is focused on regions known to change conformation most significantly. Analysis of the coupling between contacting pairs of residues in large ensembles of conformations spread throughout the landscape between and around the two allosteric states suggests that the transitions are built up from blocks of tightly coupled interacting sets of residues that are more loosely coupled to one another.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In allosteric regulation, an effector molecule binding a protein at one site induces conformational changes, which alter structure and function at a distant active site. Two key challenges in the computational modeling of allostery are the prediction of the structure of one allosteric state starting from the structure of the other, and elucidating the mechanisms underlying the conformational coupling of the effector and active sites. Here we approach these two challenges using the Rosetta high-resolution structure prediction methodology. We find that the method can recapitulate the relaxation of effector-bound forms of single domain allosteric proteins into the corresponding ligand-free states, particularly when sampling is focused on regions known to change conformation most significantly. Analysis of the coupling between contacting pairs of residues in large ensembles of conformations spread throughout the landscape between and around the two allosteric states suggests that the transitions are built up from blocks of tightly coupled interacting sets of residues that are more loosely coupled to one another.
Paul M Murphy, Jill M Bolduc, Jasmine L Gallaher, Barry L Stoddard, David Baker
Alteration of enzyme specificity by computational loop remodeling and design Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 106, pp. 9215-20, 2009, ISSN: 1091-6490.
@article{133,
title = {Alteration of enzyme specificity by computational loop remodeling and design},
author = { Paul M Murphy and Jill M Bolduc and Jasmine L Gallaher and Barry L Stoddard and David Baker},
issn = {1091-6490},
year = {2009},
date = {2009-06-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {106},
pages = {9215-20},
abstract = {Altering the specificity of an enzyme requires precise positioning of side-chain functional groups that interact with the modified groups of the new substrate. This requires not only sequence changes that introduce the new functional groups but also sequence changes that remodel the structure of the protein backbone so that the functional groups are properly positioned. We describe a computational design method for introducing specific enzyme-substrate interactions by directed remodeling of loops near the active site. Benchmark tests on 8 native protein-ligand complexes show that the method can recover native loop lengths and, often, native loop conformations. We then use the method to redesign a critical loop in human guanine deaminase such that a key side-chain interaction is made with the substrate ammelide. The redesigned enzyme is 100-fold more active on ammelide and 2.5e4-fold less active on guanine than wild-type enzyme: The net change in specificity is 2.5e6-fold. The structure of the designed protein was confirmed by X-ray crystallographic analysis: The remodeled loop adopts a conformation that is within 1-A Calpha RMSD of the computational model.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Altering the specificity of an enzyme requires precise positioning of side-chain functional groups that interact with the modified groups of the new substrate. This requires not only sequence changes that introduce the new functional groups but also sequence changes that remodel the structure of the protein backbone so that the functional groups are properly positioned. We describe a computational design method for introducing specific enzyme-substrate interactions by directed remodeling of loops near the active site. Benchmark tests on 8 native protein-ligand complexes show that the method can recover native loop lengths and, often, native loop conformations. We then use the method to redesign a critical loop in human guanine deaminase such that a key side-chain interaction is made with the substrate ammelide. The redesigned enzyme is 100-fold more active on ammelide and 2.5e4-fold less active on guanine than wild-type enzyme: The net change in specificity is 2.5e6-fold. The structure of the designed protein was confirmed by X-ray crystallographic analysis: The remodeled loop adopts a conformation that is within 1-A Calpha RMSD of the computational model.
Justin Ashworth, David Baker
Assessment of the optimization of affinity and specificity at protein-DNA interfaces Journal Article
In: Nucleic acids research, vol. 37, pp. e73, 2009, ISSN: 1362-4962.
@article{19,
title = {Assessment of the optimization of affinity and specificity at protein-DNA interfaces},
author = { Justin Ashworth and David Baker},
issn = {1362-4962},
year = {2009},
date = {2009-06-01},
journal = {Nucleic acids research},
volume = {37},
pages = {e73},
abstract = {The biological functions of DNA-binding proteins often require that they interact with their targets with high affinity and/or high specificity. Here, we describe a computational method that estimates the extent of optimization for affinity and specificity of amino acids at a protein-DNA interface based on the crystal structure of the complex, by modeling the changes in binding-free energy associated with all individual amino acid and base substitutions at the interface. The extent to which residues are predicted to be optimal for specificity versus affinity varies within a given protein-DNA interface and between different complexes, and in many cases recapitulates previous experimental observations. The approach provides a complement to traditional methods of mutational analysis, and should be useful for rapidly formulating hypotheses about the roles of amino acid residues in protein-DNA interfaces.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The biological functions of DNA-binding proteins often require that they interact with their targets with high affinity and/or high specificity. Here, we describe a computational method that estimates the extent of optimization for affinity and specificity of amino acids at a protein-DNA interface based on the crystal structure of the complex, by modeling the changes in binding-free energy associated with all individual amino acid and base substitutions at the interface. The extent to which residues are predicted to be optimal for specificity versus affinity varies within a given protein-DNA interface and between different complexes, and in many cases recapitulates previous experimental observations. The approach provides a complement to traditional methods of mutational analysis, and should be useful for rapidly formulating hypotheses about the roles of amino acid residues in protein-DNA interfaces.
James J Havranek, David Baker
Motif-directed flexible backbone design of functional interactions Journal Article
In: Protein science, vol. 18, pp. 1293-305, 2009, ISSN: 1469-896X.
@article{129,
title = {Motif-directed flexible backbone design of functional interactions},
author = { James J Havranek and David Baker},
issn = {1469-896X},
year = {2009},
date = {2009-06-01},
journal = {Protein science},
volume = {18},
pages = {1293-305},
abstract = {Computational protein design relies on a number of approximations to efficiently search the huge sequence space available to proteins. The fixed backbone and rotamer approximations in particular are important for formulating protein design as a discrete combinatorial optimization problem. However, the resulting coarse-grained sampling of possible side-chain terminal positions is problematic for the design of protein function, which depends on precise positioning of side-chain atoms. Although backbone flexibility can greatly increase the conformation freedom of side-chain functional groups, it is not obvious which backbone movements will generate the critical constellation of atoms responsible for protein function. Here, we report an automated method for identifying protein backbone movements that can give rise to any specified set of desired side-chain atomic placements and interactions, using protein-DNA interfaces as a model system. We use a library of previously observed protein-DNA interactions (motifs) and a rotamer-based description of side-chain conformation freedom to identify placements for the protein backbone that can give rise to a favorable side-chain interaction with DNA. We describe a tree-search algorithm for identifying those combinations of interactions from the library that can be realized with minimal perturbation of the protein backbone. We compare the efficiency of this method with the alternative approach of building and screening alternate backbone conformations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational protein design relies on a number of approximations to efficiently search the huge sequence space available to proteins. The fixed backbone and rotamer approximations in particular are important for formulating protein design as a discrete combinatorial optimization problem. However, the resulting coarse-grained sampling of possible side-chain terminal positions is problematic for the design of protein function, which depends on precise positioning of side-chain atoms. Although backbone flexibility can greatly increase the conformation freedom of side-chain functional groups, it is not obvious which backbone movements will generate the critical constellation of atoms responsible for protein function. Here, we report an automated method for identifying protein backbone movements that can give rise to any specified set of desired side-chain atomic placements and interactions, using protein-DNA interfaces as a model system. We use a library of previously observed protein-DNA interactions (motifs) and a rotamer-based description of side-chain conformation freedom to identify placements for the protein backbone that can give rise to a favorable side-chain interaction with DNA. We describe a tree-search algorithm for identifying those combinations of interactions from the library that can be realized with minimal perturbation of the protein backbone. We compare the efficiency of this method with the alternative approach of building and screening alternate backbone conformations.
Ruslan I Sadreyev, ShuoYong Shi, David Baker, Nick V Grishin
Structure similarity measure with penalty for close non-equivalent residues Journal Article
In: Bioinformatics, vol. 25, pp. 1259-63, 2009, ISSN: 1367-4811.
@article{135,
title = {Structure similarity measure with penalty for close non-equivalent residues},
author = { Ruslan I Sadreyev and ShuoYong Shi and David Baker and Nick V Grishin},
issn = {1367-4811},
year = {2009},
date = {2009-05-01},
journal = {Bioinformatics},
volume = {25},
pages = {1259-63},
abstract = {MOTIVATION: Recent improvement in homology-based structure modeling emphasizes the importance of sensitive evaluation measures that help identify and correct modest distortions in models compared with the target structures. Global Distance Test Total Score (GDT_TS), otherwise a very powerful and effective measure for model evaluation, is still insensitive to and can even reward such distortions, as observed for remote homology modeling in the latest CASP8 (Comparative Assessment of Structure Prediction). RESULTS: We develop a new measure that balances GDT_TS reward for the closeness of equivalent model and target residues (textquoterightattractiontextquoteright term) with the penalty for the closeness of non-equivalent residues (textquoterightrepulsiontextquoteright term). Compared with GDT_TS, the resulting score, TR (total score with repulsion), is much more sensitive to structure compression both in real remote homologs and in CASP models. TR is correlated yet different from other measures of structure similarity. The largest difference from GDT_TS is observed in models of mid-range quality based on remote homology modeling. AVAILABILITY: The script for TR calculation is included in Supplementary Material. TR scores for all server models in CASP8 are available at http://prodata.swmed.edu/CASP8.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
MOTIVATION: Recent improvement in homology-based structure modeling emphasizes the importance of sensitive evaluation measures that help identify and correct modest distortions in models compared with the target structures. Global Distance Test Total Score (GDT_TS), otherwise a very powerful and effective measure for model evaluation, is still insensitive to and can even reward such distortions, as observed for remote homology modeling in the latest CASP8 (Comparative Assessment of Structure Prediction). RESULTS: We develop a new measure that balances GDT_TS reward for the closeness of equivalent model and target residues (textquoterightattractiontextquoteright term) with the penalty for the closeness of non-equivalent residues (textquoterightrepulsiontextquoteright term). Compared with GDT_TS, the resulting score, TR (total score with repulsion), is much more sensitive to structure compression both in real remote homologs and in CASP models. TR is correlated yet different from other measures of structure similarity. The largest difference from GDT_TS is observed in models of mid-range quality based on remote homology modeling. AVAILABILITY: The script for TR calculation is included in Supplementary Material. TR scores for all server models in CASP8 are available at http://prodata.swmed.edu/CASP8.
Thomas Spreter, Calvin K Yip, Sarah Sanowar, Ingemar Andr’e, Tyler G Kimbrough, Marija Vuckovic, Richard A Pfuetzner, Wanyin Deng, Angel C Yu, B Brett Finlay, David Baker, Samuel I Miller, Natalie C J Strynadka
A conserved structural motif mediates formation of the periplasmic rings in the type III secretion system Journal Article
In: Nature structural & molecular biology, vol. 16, pp. 468-76, 2009, ISSN: 1545-9985.
@article{274,
title = {A conserved structural motif mediates formation of the periplasmic rings in the type III secretion system},
author = { Thomas Spreter and Calvin K Yip and Sarah Sanowar and Ingemar Andr'e and Tyler G Kimbrough and Marija Vuckovic and Richard A Pfuetzner and Wanyin Deng and Angel C Yu and B Brett Finlay and David Baker and Samuel I Miller and Natalie C J Strynadka},
issn = {1545-9985},
year = {2009},
date = {2009-05-01},
journal = {Nature structural & molecular biology},
volume = {16},
pages = {468-76},
abstract = {The type III secretion system (T3SS) is a macromolecular textquoterightinjectisometextquoteright that allows bacterial pathogens to transport virulence proteins into the eukaryotic host cell. This macromolecular complex is composed of connected ring-like structures that span both bacterial membranes. The crystal structures of the periplasmic domain of the outer membrane secretin EscC and the inner membrane protein PrgH reveal the conservation of a modular fold among the three proteins that form the outer membrane and inner membrane rings of the T3SS. This leads to the hypothesis that this conserved fold provides a common ring-building motif that allows for the assembly of the variably sized outer membrane and inner membrane rings characteristic of the T3SS. Using an integrated structural and experimental approach, we generated ring models for the periplasmic domain of EscC and placed them in the context of the assembled T3SS, providing evidence for direct interaction between the outer membrane and inner membrane ring components and an unprecedented span of the outer membrane secretin.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The type III secretion system (T3SS) is a macromolecular textquoterightinjectisometextquoteright that allows bacterial pathogens to transport virulence proteins into the eukaryotic host cell. This macromolecular complex is composed of connected ring-like structures that span both bacterial membranes. The crystal structures of the periplasmic domain of the outer membrane secretin EscC and the inner membrane protein PrgH reveal the conservation of a modular fold among the three proteins that form the outer membrane and inner membrane rings of the T3SS. This leads to the hypothesis that this conserved fold provides a common ring-building motif that allows for the assembly of the variably sized outer membrane and inner membrane rings characteristic of the T3SS. Using an integrated structural and experimental approach, we generated ring models for the periplasmic domain of EscC and placed them in the context of the assembled T3SS, providing evidence for direct interaction between the outer membrane and inner membrane ring components and an unprecedented span of the outer membrane secretin.
Jieqing Zhu, Bing-Hao Luo, Patrick Barth, Jack Schonbrun, David Baker, Timothy A Springer
The structure of a receptor with two associating transmembrane domains on the cell surface: integrin alphaIIbbeta3 Journal Article
In: Molecular cell, vol. 34, pp. 234-49, 2009, ISSN: 1097-4164.
@article{139,
title = {The structure of a receptor with two associating transmembrane domains on the cell surface: integrin alphaIIbbeta3},
author = { Jieqing Zhu and Bing-Hao Luo and Patrick Barth and Jack Schonbrun and David Baker and Timothy A Springer},
issn = {1097-4164},
year = {2009},
date = {2009-04-01},
journal = {Molecular cell},
volume = {34},
pages = {234-49},
abstract = {Structures of intact receptors with single-pass transmembrane domains are essential to understand how extracellular and cytoplasmic domains regulate association and signaling through transmembrane domains. A chemical and computational method to determine structures of the membrane regions of such receptors on the cell surface is developed here and validated with glycophorin A. An integrin heterodimer structure reveals association over most of the lengths of the alpha and beta transmembrane domains and shows that the principles governing association of hetero and homo transmembrane dimers differ. A turn at the Gly of the juxtamembrane GFFKR motif caps the alpha TM helix and brings the two Phe of GFFKR into the alpha/beta interface. A juxtamembrane Lys residue in beta also has an important role in the interface. The structure shows how transmembrane association/dissociation regulates integrin signaling. A joint ectodomain and membrane structure shows that substantial flexibility between the extracellular and TM domains is compatible with TM signaling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Structures of intact receptors with single-pass transmembrane domains are essential to understand how extracellular and cytoplasmic domains regulate association and signaling through transmembrane domains. A chemical and computational method to determine structures of the membrane regions of such receptors on the cell surface is developed here and validated with glycophorin A. An integrin heterodimer structure reveals association over most of the lengths of the alpha and beta transmembrane domains and shows that the principles governing association of hetero and homo transmembrane dimers differ. A turn at the Gly of the juxtamembrane GFFKR motif caps the alpha TM helix and brings the two Phe of GFFKR into the alpha/beta interface. A juxtamembrane Lys residue in beta also has an important role in the interface. The structure shows how transmembrane association/dissociation regulates integrin signaling. A joint ectodomain and membrane structure shows that substantial flexibility between the extracellular and TM domains is compatible with TM signaling.
Kathryn E Muratore, Markus A Seeliger, Zhihong Wang, Dina Fomina, Johnathan Neiswinger, James J Havranek, David Baker, John Kuriyan, Philip A Cole
Comparative analysis of mutant tyrosine kinase chemical rescue Journal Article
In: Biochemistry, vol. 48, pp. 3378-86, 2009, ISSN: 1520-4995.
@article{276,
title = {Comparative analysis of mutant tyrosine kinase chemical rescue},
author = { Kathryn E Muratore and Markus A Seeliger and Zhihong Wang and Dina Fomina and Johnathan Neiswinger and James J Havranek and David Baker and John Kuriyan and Philip A Cole},
issn = {1520-4995},
year = {2009},
date = {2009-04-01},
journal = {Biochemistry},
volume = {48},
pages = {3378-86},
abstract = {Protein tyrosine kinases are critical cell signaling enzymes. These enzymes have a highly conserved Arg residue in their catalytic loop which is present two residues or four residues downstream from an absolutely conserved Asp catalytic base. Prior studies on protein tyrosine kinases Csk and Src revealed the potential for chemical rescue of catalytically deficient mutant kinases (Arg to Ala mutations) by small diamino compounds, particularly imidazole; however, the potency and efficiency of rescue was greater for Src. This current study further examines the structural and kinetic basis of rescue for mutant Src as compared to mutant Abl tyrosine kinase. An X-ray crystal structure of R388A Src revealed the surprising finding that a histidine residue of the N-terminus of a symmetry-related kinase inserts into the active site of the adjacent Src and mimics the hydrogen-bonding pattern seen in wild-type protein tyrosine kinases. Abl R367A shows potent and efficient rescue more comparable to Src, even though its catalytic loop is more like that of Csk. Various enzyme redesigns of the active sites indicate that the degree and specificity of rescue are somewhat flexible, but the overall properties of the enzymes and rescue agents play an overarching role. The newly discovered rescue agent 2-aminoimidazole is about as efficient as imidazole in rescuing R/A Src and Abl. Rate vs pH studies with these imidazole analogues suggest that the protonated imidazolium is the preferred form for chemical rescue, consistent with structural models. The efficient rescue seen with mutant Abl points to the potential of this approach to be used effectively to analyze Abl phosphorylation pathways in cells.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein tyrosine kinases are critical cell signaling enzymes. These enzymes have a highly conserved Arg residue in their catalytic loop which is present two residues or four residues downstream from an absolutely conserved Asp catalytic base. Prior studies on protein tyrosine kinases Csk and Src revealed the potential for chemical rescue of catalytically deficient mutant kinases (Arg to Ala mutations) by small diamino compounds, particularly imidazole; however, the potency and efficiency of rescue was greater for Src. This current study further examines the structural and kinetic basis of rescue for mutant Src as compared to mutant Abl tyrosine kinase. An X-ray crystal structure of R388A Src revealed the surprising finding that a histidine residue of the N-terminus of a symmetry-related kinase inserts into the active site of the adjacent Src and mimics the hydrogen-bonding pattern seen in wild-type protein tyrosine kinases. Abl R367A shows potent and efficient rescue more comparable to Src, even though its catalytic loop is more like that of Csk. Various enzyme redesigns of the active sites indicate that the degree and specificity of rescue are somewhat flexible, but the overall properties of the enzymes and rescue agents play an overarching role. The newly discovered rescue agent 2-aminoimidazole is about as efficient as imidazole in rescuing R/A Src and Abl. Rate vs pH studies with these imidazole analogues suggest that the protonated imidazolium is the preferred form for chemical rescue, consistent with structural models. The efficient rescue seen with mutant Abl points to the potential of this approach to be used effectively to analyze Abl phosphorylation pathways in cells.
Jeffrey A Dietrich, Yasuo Yoshikuni, Karl J Fisher, Frank X Woolard, Denise Ockey, Derek J McPhee, Neil S Renninger, Michelle C Y Chang, David Baker, Jay D Keasling
A novel semi-biosynthetic route for artemisinin production using engineered substrate-promiscuous P450(BM3) Journal Article
In: ACS chemical biology, vol. 4, pp. 261-7, 2009, ISSN: 1554-8937.
@article{275,
title = {A novel semi-biosynthetic route for artemisinin production using engineered substrate-promiscuous P450(BM3)},
author = { Jeffrey A Dietrich and Yasuo Yoshikuni and Karl J Fisher and Frank X Woolard and Denise Ockey and Derek J McPhee and Neil S Renninger and Michelle C Y Chang and David Baker and Jay D Keasling},
issn = {1554-8937},
year = {2009},
date = {2009-04-01},
journal = {ACS chemical biology},
volume = {4},
pages = {261-7},
abstract = {Production of fine chemicals from heterologous pathways in microbial hosts is frequently hindered by insufficient knowledge of the native metabolic pathway and its cognate enzymes; often the pathway is unresolved, and the enzymes lack detailed characterization. An alternative paradigm to using native pathways is de novo pathway design using well-characterized, substrate-promiscuous enzymes. We demonstrate this concept using P450(BM3) from Bacillus megaterium. Using a computer model, we illustrate how key P450(BM3) active site mutations enable binding of the non-native substrate amorphadiene. Incorporating these mutations into P450(BM3) enabled the selective oxidation of amorphadiene artemisinic-11S,12-epoxide, at titers of 250 mg L(-1) in E. coli. We also demonstrate high-yielding, selective transformations to dihydroartemisinic acid, the immediate precursor to the high-value antimalarial drug artemisinin.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Production of fine chemicals from heterologous pathways in microbial hosts is frequently hindered by insufficient knowledge of the native metabolic pathway and its cognate enzymes; often the pathway is unresolved, and the enzymes lack detailed characterization. An alternative paradigm to using native pathways is de novo pathway design using well-characterized, substrate-promiscuous enzymes. We demonstrate this concept using P450(BM3) from Bacillus megaterium. Using a computer model, we illustrate how key P450(BM3) active site mutations enable binding of the non-native substrate amorphadiene. Incorporating these mutations into P450(BM3) enabled the selective oxidation of amorphadiene artemisinic-11S,12-epoxide, at titers of 250 mg L(-1) in E. coli. We also demonstrate high-yielding, selective transformations to dihydroartemisinic acid, the immediate precursor to the high-value antimalarial drug artemisinin.
Theresa A Ramelot, Srivatsan Raman, Alexandre P Kuzin, Rong Xiao, Li-Chung Ma, Thomas B Acton, John F Hunt, Gaetano T Montelione, David Baker, Michael A Kennedy
Improving NMR protein structure quality by Rosetta refinement: a molecular replacement study Journal Article
In: Proteins, vol. 75, pp. 147-67, 2009, ISSN: 1097-0134.
@article{134,
title = {Improving NMR protein structure quality by Rosetta refinement: a molecular replacement study},
author = { Theresa A Ramelot and Srivatsan Raman and Alexandre P Kuzin and Rong Xiao and Li-Chung Ma and Thomas B Acton and John F Hunt and Gaetano T Montelione and David Baker and Michael A Kennedy},
issn = {1097-0134},
year = {2009},
date = {2009-04-01},
journal = {Proteins},
volume = {75},
pages = {147-67},
abstract = {The structure of human protein HSPC034 has been determined by both solution nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography. Refinement of the NMR structure ensemble, using a Rosetta protocol in the absence of NMR restraints, resulted in significant improvements not only in structure quality, but also in molecular replacement (MR) performance with the raw X-ray diffraction data using MOLREP and Phaser. This method has recently been shown to be generally applicable with improved MR performance demonstrated for eight NMR structures refined using Rosetta (Qian et al., Nature 2007;450:259-264). Additionally, NMR structures of HSPC034 calculated by standard methods that include NMR restraints have improvements in the RMSD to the crystal structure and MR performance in the order DYANA, CYANA, XPLOR-NIH, and CNS with explicit water refinement (CNSw). Further Rosetta refinement of the CNSw structures, perhaps due to more thorough conformational sampling and/or a superior force field, was capable of finding alternative low energy protein conformations that were equally consistent with the NMR data according to the Recall, Precision, and F-measure (RPF) scores. On further examination, the additional MR-performance shortfall for NMR refined structures as compared with the X-ray structure were attributed, in part, to crystal-packing effects, real structural differences, and inferior hydrogen bonding in the NMR structures. A good correlation between a decrease in the number of buried unsatisfied hydrogen-bond donors and improved MR performance demonstrates the importance of hydrogen-bond terms in the force field for improving NMR structures. The superior hydrogen-bond network in Rosetta-refined structures demonstrates that correct identification of hydrogen bonds should be a critical goal of NMR structure refinement. Inclusion of nonbivalent hydrogen bonds identified from Rosetta structures as additional restraints in the structure calculation results in NMR structures with improved MR performance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The structure of human protein HSPC034 has been determined by both solution nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography. Refinement of the NMR structure ensemble, using a Rosetta protocol in the absence of NMR restraints, resulted in significant improvements not only in structure quality, but also in molecular replacement (MR) performance with the raw X-ray diffraction data using MOLREP and Phaser. This method has recently been shown to be generally applicable with improved MR performance demonstrated for eight NMR structures refined using Rosetta (Qian et al., Nature 2007;450:259-264). Additionally, NMR structures of HSPC034 calculated by standard methods that include NMR restraints have improvements in the RMSD to the crystal structure and MR performance in the order DYANA, CYANA, XPLOR-NIH, and CNS with explicit water refinement (CNSw). Further Rosetta refinement of the CNSw structures, perhaps due to more thorough conformational sampling and/or a superior force field, was capable of finding alternative low energy protein conformations that were equally consistent with the NMR data according to the Recall, Precision, and F-measure (RPF) scores. On further examination, the additional MR-performance shortfall for NMR refined structures as compared with the X-ray structure were attributed, in part, to crystal-packing effects, real structural differences, and inferior hydrogen bonding in the NMR structures. A good correlation between a decrease in the number of buried unsatisfied hydrogen-bond donors and improved MR performance demonstrates the importance of hydrogen-bond terms in the force field for improving NMR structures. The superior hydrogen-bond network in Rosetta-refined structures demonstrates that correct identification of hydrogen bonds should be a critical goal of NMR structure refinement. Inclusion of nonbivalent hydrogen bonds identified from Rosetta structures as additional restraints in the structure calculation results in NMR structures with improved MR performance.
Bing-Hao Luo, John Karanicolas, Laura D Harmacek, David Baker, Timothy A Springer
Rationally designed integrin beta3 mutants stabilized in the high affinity conformation Journal Article
In: The Journal of biological chemistry, vol. 284, pp. 3917-24, 2009, ISSN: 0021-9258.
@article{132,
title = {Rationally designed integrin beta3 mutants stabilized in the high affinity conformation},
author = { Bing-Hao Luo and John Karanicolas and Laura D Harmacek and David Baker and Timothy A Springer},
issn = {0021-9258},
year = {2009},
date = {2009-02-01},
journal = {The Journal of biological chemistry},
volume = {284},
pages = {3917-24},
abstract = {Integrins are important cell surface receptors that transmit bidirectional signals across the membrane. It has been shown that a conformational change of the integrin beta-subunit headpiece (i.e. the beta I domain and the hybrid domain) plays a critical role in regulating integrin ligand binding affinity and function. Previous studies have used coarse methods (a glycan wedge, mutations in transmembrane contacts) to force the beta-subunit into either the open or closed conformation. Here, we demonstrate a detailed understanding of this conformational change by applying computational design techniques to select five amino acid side chains that play an important role in the energetic balance between the open and closed conformations of alphaIIbbeta3. Eight single-point mutants were designed at these sites, of which five bound ligands much better than wild type. Further, these mutants were found to be in a more extended conformation than wild type, suggesting that the conformational change at the ligand binding headpiece was propagated to the legs of the integrin. This detailed understanding of the conformational change will assist in the development of allosteric drugs that either stabilize or destabilize specific integrin conformations without occluding the ligand-binding site.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Integrins are important cell surface receptors that transmit bidirectional signals across the membrane. It has been shown that a conformational change of the integrin beta-subunit headpiece (i.e. the beta I domain and the hybrid domain) plays a critical role in regulating integrin ligand binding affinity and function. Previous studies have used coarse methods (a glycan wedge, mutations in transmembrane contacts) to force the beta-subunit into either the open or closed conformation. Here, we demonstrate a detailed understanding of this conformational change by applying computational design techniques to select five amino acid side chains that play an important role in the energetic balance between the open and closed conformations of alphaIIbbeta3. Eight single-point mutants were designed at these sites, of which five bound ligands much better than wild type. Further, these mutants were found to be in a more extended conformation than wild type, suggesting that the conformational change at the ligand binding headpiece was propagated to the legs of the integrin. This detailed understanding of the conformational change will assist in the development of allosteric drugs that either stabilize or destabilize specific integrin conformations without occluding the ligand-binding site.
P Barth, B Wallner, David Baker
Prediction of membrane protein structures with complex topologies using limited constraints Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 106, pp. 1409-14, 2009, ISSN: 1091-6490.
@article{123,
title = {Prediction of membrane protein structures with complex topologies using limited constraints},
author = { P Barth and B Wallner and David Baker},
issn = {1091-6490},
year = {2009},
date = {2009-02-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {106},
pages = {1409-14},
abstract = {Reliable structure-prediction methods for membrane proteins are important because the experimental determination of high-resolution membrane protein structures remains very difficult, especially for eukaryotic proteins. However, membrane proteins are typically longer than 200 aa and represent a formidable challenge for structure prediction. We have developed a method for predicting the structures of large membrane proteins by constraining helix-helix packing arrangements at particular positions predicted from sequence or identified by experiments. We tested the method on 12 membrane proteins of diverse topologies and functions with lengths ranging between 190 and 300 residues. Enforcing a single constraint during the folding simulations enriched the population of near-native models for 9 proteins. In 4 of the cases in which the constraint was predicted from the sequence, 1 of the 5 lowest energy models was superimposable within 4 A on the native structure. Near-native structures could also be selected for heme-binding and pore-forming domains from simulations in which pairs of conserved histidine-chelating hemes and one experimentally determined salt bridge were constrained, respectively. These results suggest that models within 4 A of the native structure can be achieved for complex membrane proteins if even limited information on residue-residue interactions can be obtained from protein structure databases or experiments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Reliable structure-prediction methods for membrane proteins are important because the experimental determination of high-resolution membrane protein structures remains very difficult, especially for eukaryotic proteins. However, membrane proteins are typically longer than 200 aa and represent a formidable challenge for structure prediction. We have developed a method for predicting the structures of large membrane proteins by constraining helix-helix packing arrangements at particular positions predicted from sequence or identified by experiments. We tested the method on 12 membrane proteins of diverse topologies and functions with lengths ranging between 190 and 300 residues. Enforcing a single constraint during the folding simulations enriched the population of near-native models for 9 proteins. In 4 of the cases in which the constraint was predicted from the sequence, 1 of the 5 lowest energy models was superimposable within 4 A on the native structure. Near-native structures could also be selected for heme-binding and pore-forming domains from simulations in which pairs of conserved histidine-chelating hemes and one experimentally determined salt bridge were constrained, respectively. These results suggest that models within 4 A of the native structure can be achieved for complex membrane proteins if even limited information on residue-residue interactions can be obtained from protein structure databases or experiments.
Yang Shen, Robert Vernon, David Baker, Ad Bax
De novo protein structure generation from incomplete chemical shift assignments Journal Article
In: Journal of biomolecular NMR, vol. 43, pp. 63-78, 2009, ISSN: 1573-5001.
@article{137,
title = {De novo protein structure generation from incomplete chemical shift assignments},
author = { Yang Shen and Robert Vernon and David Baker and Ad Bax},
issn = {1573-5001},
year = {2009},
date = {2009-02-01},
journal = {Journal of biomolecular NMR},
volume = {43},
pages = {63-78},
abstract = {NMR chemical shifts provide important local structural information for proteins. Consistent structure generation from NMR chemical shift data has recently become feasible for proteins with sizes of up to 130 residues, and such structures are of a quality comparable to those obtained with the standard NMR protocol. This study investigates the influence of the completeness of chemical shift assignments on structures generated from chemical shifts. The Chemical-Shift-Rosetta (CS-Rosetta) protocol was used for de novo protein structure generation with various degrees of completeness of the chemical shift assignment, simulated by omission of entries in the experimental chemical shift data previously used for the initial demonstration of the CS-Rosetta approach. In addition, a new CS-Rosetta protocol is described that improves robustness of the method for proteins with missing or erroneous NMR chemical shift input data. This strategy, which uses traditional Rosetta for pre-filtering of the fragment selection process, is demonstrated for two paramagnetic proteins and also for two proteins with solid-state NMR chemical shift assignments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
NMR chemical shifts provide important local structural information for proteins. Consistent structure generation from NMR chemical shift data has recently become feasible for proteins with sizes of up to 130 residues, and such structures are of a quality comparable to those obtained with the standard NMR protocol. This study investigates the influence of the completeness of chemical shift assignments on structures generated from chemical shifts. The Chemical-Shift-Rosetta (CS-Rosetta) protocol was used for de novo protein structure generation with various degrees of completeness of the chemical shift assignment, simulated by omission of entries in the experimental chemical shift data previously used for the initial demonstration of the CS-Rosetta approach. In addition, a new CS-Rosetta protocol is described that improves robustness of the method for proteins with missing or erroneous NMR chemical shift input data. This strategy, which uses traditional Rosetta for pre-filtering of the fragment selection process, is demonstrated for two paramagnetic proteins and also for two proteins with solid-state NMR chemical shift assignments.
Rhiju Das, David Baker
Prospects for de novo phasing with de novo protein models Journal Article
In: Acta crystallographica, vol. 65, pp. 169-75, 2009, ISSN: 1399-0047.
@article{125,
title = {Prospects for de novo phasing with de novo protein models},
author = { Rhiju Das and David Baker},
issn = {1399-0047},
year = {2009},
date = {2009-02-01},
journal = {Acta crystallographica},
volume = {65},
pages = {169-75},
abstract = {The prospect of phasing diffraction data sets ;de novotextquoteright for proteins with previously unseen folds is appealing but largely untested. In a first systematic exploration of phasing with Rosetta de novo models, it is shown that all-atom refinement of coarse-grained models significantly improves both the model quality and performance in molecular replacement with the Phaser software. 15 new cases of diffraction data sets that are unambiguously phased with de novo models are presented. These diffraction data sets represent nine space groups and span a large range of solvent contents (33-79%) and asymmetric unit copy numbers (1-4). No correlation is observed between the ease of phasing and the solvent content or asymmetric unit copy number. Instead, a weak correlation is found with the length of the modeled protein: larger proteins required somewhat less accurate models to give successful molecular replacement. Overall, the results of this survey suggest that de novo models can phase diffraction data for approximately one sixth of proteins with sizes of 100 residues or less. However, for many of these cases, ;de novo phasing with de novo modelstextquoteright requires significant investment of computational power, much greater than 10(3) CPU days per target. Improvements in conformational search methods will be necessary if molecular replacement with de novo models is to become a practical tool for targets without homology to previously solved protein structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The prospect of phasing diffraction data sets ;de novotextquoteright for proteins with previously unseen folds is appealing but largely untested. In a first systematic exploration of phasing with Rosetta de novo models, it is shown that all-atom refinement of coarse-grained models significantly improves both the model quality and performance in molecular replacement with the Phaser software. 15 new cases of diffraction data sets that are unambiguously phased with de novo models are presented. These diffraction data sets represent nine space groups and span a large range of solvent contents (33-79%) and asymmetric unit copy numbers (1-4). No correlation is observed between the ease of phasing and the solvent content or asymmetric unit copy number. Instead, a weak correlation is found with the length of the modeled protein: larger proteins required somewhat less accurate models to give successful molecular replacement. Overall, the results of this survey suggest that de novo models can phase diffraction data for approximately one sixth of proteins with sizes of 100 residues or less. However, for many of these cases, ;de novo phasing with de novo modelstextquoteright requires significant investment of computational power, much greater than 10(3) CPU days per target. Improvements in conformational search methods will be necessary if molecular replacement with de novo models is to become a practical tool for targets without homology to previously solved protein structures.
Ian W Davis, David Baker
RosettaLigand docking with full ligand and receptor flexibility Journal Article
In: Journal of molecular biology, vol. 385, pp. 381-92, 2009, ISSN: 1089-8638.
@article{127,
title = {RosettaLigand docking with full ligand and receptor flexibility},
author = { Ian W Davis and David Baker},
issn = {1089-8638},
year = {2009},
date = {2009-01-01},
journal = {Journal of molecular biology},
volume = {385},
pages = {381-92},
abstract = {Computational docking of small-molecule ligands into protein receptors is an important tool for modern drug discovery. Although conformational adjustments are frequently observed between the free and ligand-bound states, the conformational flexibility of the protein is typically ignored in protein-small molecule docking programs. We previously described the program RosettaLigand, which leverages the Rosetta energy function and side-chain repacking algorithm to account for flexibility of all side chains in the binding site. Here we present extensions to RosettaLigand that incorporate full ligand flexibility as well as receptor backbone flexibility. Including receptor backbone flexibility is found to produce more correct docked complexes and to lower the average RMSD of the best-scoring docked poses relative to the rigid-backbone results. On a challenging set of retrospective and prospective cross-docking tests, we find that the top-scoring ligand pose is correctly positioned within 2 A RMSD for 64% (54/85) of cases overall.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational docking of small-molecule ligands into protein receptors is an important tool for modern drug discovery. Although conformational adjustments are frequently observed between the free and ligand-bound states, the conformational flexibility of the protein is typically ignored in protein-small molecule docking programs. We previously described the program RosettaLigand, which leverages the Rosetta energy function and side-chain repacking algorithm to account for flexibility of all side chains in the binding site. Here we present extensions to RosettaLigand that incorporate full ligand flexibility as well as receptor backbone flexibility. Including receptor backbone flexibility is found to produce more correct docked complexes and to lower the average RMSD of the best-scoring docked poses relative to the rigid-backbone results. On a challenging set of retrospective and prospective cross-docking tests, we find that the top-scoring ligand pose is correctly positioned within 2 A RMSD for 64% (54/85) of cases overall.
Will Sheffler, David Baker
RosettaHoles: rapid assessment of protein core packing for structure prediction, refinement, design, and validation Journal Article
In: Protein science, vol. 18, pp. 229-39, 2009, ISSN: 1469-896X.
@article{136,
title = {RosettaHoles: rapid assessment of protein core packing for structure prediction, refinement, design, and validation},
author = { Will Sheffler and David Baker},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/pro.8
https://www.bakerlab.org/wp-content/uploads/2020/08/pro.8.pdf},
doi = {10.1002/pro.8},
issn = {1469-896X},
year = {2009},
date = {2009-01-01},
journal = {Protein science},
volume = {18},
pages = {229-39},
abstract = {We present a novel method called RosettaHoles for visual and quantitative assessment of underpacking in the protein core. RosettaHoles generates a set of spherical cavity balls that fill the empty volume between atoms in the protein interior. For visualization, the cavity balls are aggregated into contiguous overlapping clusters and small cavities are discarded, leaving an uncluttered representation of the unfilled regions of space in a structure. For quantitative analysis, the cavity ball data are used to estimate the probability of observing a given cavity in a high-resolution crystal structure. RosettaHoles provides excellent discrimination between real and computationally generated structures, is predictive of incorrect regions in models, identifies problematic structures in the Protein Data Bank, and promises to be a useful validation tool for newly solved experimental structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present a novel method called RosettaHoles for visual and quantitative assessment of underpacking in the protein core. RosettaHoles generates a set of spherical cavity balls that fill the empty volume between atoms in the protein interior. For visualization, the cavity balls are aggregated into contiguous overlapping clusters and small cavities are discarded, leaving an uncluttered representation of the unfilled regions of space in a structure. For quantitative analysis, the cavity ball data are used to estimate the probability of observing a given cavity in a high-resolution crystal structure. RosettaHoles provides excellent discrimination between real and computationally generated structures, is predictive of incorrect regions in models, identifies problematic structures in the Protein Data Bank, and promises to be a useful validation tool for newly solved experimental structures.
Elmar Krieger, Keehyoung Joo, Jinwoo Lee, Jooyoung Lee, Srivatsan Raman, James Thompson, Mike Tyka, David Baker, Kevin Karplus
Improving physical realism, stereochemistry, and side-chain accuracy in homology modeling: Four approaches that performed well in CASP8 Journal Article
In: Proteins, vol. 77 Suppl 9, pp. 114-22, 2009, ISSN: 1097-0134.
@article{279,
title = {Improving physical realism, stereochemistry, and side-chain accuracy in homology modeling: Four approaches that performed well in CASP8},
author = { Elmar Krieger and Keehyoung Joo and Jinwoo Lee and Jooyoung Lee and Srivatsan Raman and James Thompson and Mike Tyka and David Baker and Kevin Karplus},
issn = {1097-0134},
year = {2009},
date = {2009-00-01},
journal = {Proteins},
volume = {77 Suppl 9},
pages = {114-22},
abstract = {A correct alignment is an essential requirement in homology modeling. Yet in order to bridge the structural gap between template and target, which may not only involve loop rearrangements, but also shifts of secondary structure elements and repacking of core residues, high-resolution refinement methods with full atomic details are needed. Here, we describe four approaches that address this "last mile of the protein folding problem" and have performed well during CASP8, yielding physically realistic models: YASARA, which runs molecular dynamics simulations of models in explicit solvent, using a new partly knowledge-based all atom force field derived from Amber, whose parameters have been optimized to minimize the damage done to protein crystal structures. The LEE-SERVER, which makes extensive use of conformational space annealing to create alignments, to help Modeller build physically realistic models while satisfying input restraints from templates and CHARMM stereochemistry, and to remodel the side-chains. ROSETTA, whose high resolution refinement protocol combines a physically realistic all atom force field with Monte Carlo minimization to allow the large conformational space to be sampled quickly. And finally UNDERTAKER, which creates a pool of candidate models from various templates and then optimizes them with an adaptive genetic algorithm, using a primarily empirical cost function that does not include bond angle, bond length, or other physics-like terms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A correct alignment is an essential requirement in homology modeling. Yet in order to bridge the structural gap between template and target, which may not only involve loop rearrangements, but also shifts of secondary structure elements and repacking of core residues, high-resolution refinement methods with full atomic details are needed. Here, we describe four approaches that address this “last mile of the protein folding problem” and have performed well during CASP8, yielding physically realistic models: YASARA, which runs molecular dynamics simulations of models in explicit solvent, using a new partly knowledge-based all atom force field derived from Amber, whose parameters have been optimized to minimize the damage done to protein crystal structures. The LEE-SERVER, which makes extensive use of conformational space annealing to create alignments, to help Modeller build physically realistic models while satisfying input restraints from templates and CHARMM stereochemistry, and to remodel the side-chains. ROSETTA, whose high resolution refinement protocol combines a physically realistic all atom force field with Monte Carlo minimization to allow the large conformational space to be sampled quickly. And finally UNDERTAKER, which creates a pool of candidate models from various templates and then optimizes them with an adaptive genetic algorithm, using a primarily empirical cost function that does not include bond angle, bond length, or other physics-like terms.
Srivatsan Raman, Robert Vernon, James Thompson, Michael Tyka, Ruslan Sadreyev, Jimin Pei, David Kim, Elizabeth Kellogg, Frank DiMaio, Oliver Lange, Lisa Kinch, Will Sheffler, Bong-Hyun Kim, Rhiju Das, Nick V Grishin, David Baker
Structure prediction for CASP8 with all-atom refinement using Rosetta Journal Article
In: Proteins, vol. 77 Suppl 9, pp. 89-99, 2009, ISSN: 1097-0134.
@article{273,
title = {Structure prediction for CASP8 with all-atom refinement using Rosetta},
author = { Srivatsan Raman and Robert Vernon and James Thompson and Michael Tyka and Ruslan Sadreyev and Jimin Pei and David Kim and Elizabeth Kellogg and Frank DiMaio and Oliver Lange and Lisa Kinch and Will Sheffler and Bong-Hyun Kim and Rhiju Das and Nick V Grishin and David Baker},
issn = {1097-0134},
year = {2009},
date = {2009-00-01},
journal = {Proteins},
volume = {77 Suppl 9},
pages = {89-99},
abstract = {We describe predictions made using the Rosetta structure prediction methodology for the Eighth Critical Assessment of Techniques for Protein Structure Prediction. Aggressive sampling and all-atom refinement were carried out for nearly all targets. A combination of alignment methodologies was used to generate starting models from a range of templates, and the models were then subjected to Rosetta all atom refinement. For the 64 domains with readily identified templates, the best submitted model was better than the best alignment to the best template in the Protein Data Bank for 24 cases, and improved over the best starting model for 43 cases. For 13 targets where only very distant sequence relationships to proteins of known structure were detected, models were generated using the Rosetta de novo structure prediction methodology followed by all-atom refinement; in several cases the submitted models were better than those based on the available templates. Of the 12 refinement challenges, the best submitted model improved on the starting model in seven cases. These improvements over the starting template-based models and refinement tests demonstrate the power of Rosetta structure refinement in improving model accuracy.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe predictions made using the Rosetta structure prediction methodology for the Eighth Critical Assessment of Techniques for Protein Structure Prediction. Aggressive sampling and all-atom refinement were carried out for nearly all targets. A combination of alignment methodologies was used to generate starting models from a range of templates, and the models were then subjected to Rosetta all atom refinement. For the 64 domains with readily identified templates, the best submitted model was better than the best alignment to the best template in the Protein Data Bank for 24 cases, and improved over the best starting model for 43 cases. For 13 targets where only very distant sequence relationships to proteins of known structure were detected, models were generated using the Rosetta de novo structure prediction methodology followed by all-atom refinement; in several cases the submitted models were better than those based on the available templates. Of the 12 refinement challenges, the best submitted model improved on the starting model in seven cases. These improvements over the starting template-based models and refinement tests demonstrate the power of Rosetta structure refinement in improving model accuracy.
2008
Anastassia N Alexandrova, Daniela R”othlisberger, David Baker, William L Jorgensen
Catalytic mechanism and performance of computationally designed enzymes for Kemp elimination Journal Article
In: Journal of the American Chemical Society, vol. 130, pp. 15907-15, 2008, ISSN: 1520-5126.
@article{145,
title = {Catalytic mechanism and performance of computationally designed enzymes for Kemp elimination},
author = { Anastassia N Alexandrova and Daniela R"othlisberger and David Baker and William L Jorgensen},
issn = {1520-5126},
year = {2008},
date = {2008-11-01},
journal = {Journal of the American Chemical Society},
volume = {130},
pages = {15907-15},
abstract = {A series of enzymes for Kemp elimination of 5-nitrobenzisoxazole has been recently designed and tested. In conjunction with the design process, extensive computational analyses were carried out to evaluate the potential performance of four of the designs, as presented here. The enzyme-catalyzed reactions were modeled using mixed quantum and molecular mechanics (QM/MM) calculations in the context of Monte Carlo (MC) statistical mechanics simulations. Free-energy perturbation (FEP) calculations were used to characterize the free-energy surfaces for the catalyzed reactions as well as for reference processes in water. The simulations yielded detailed information about the catalytic mechanisms, activation barriers, and structural evolution of the active sites over the course of the reactions. The catalytic mechanism for the designed enzymes KE07, KE10(V131N), and KE15 was found to be concerted with proton transfer, generally more advanced in the transition state than breaking of the isoxazolyl N-O bond. On the basis of the free-energy results, all three enzymes were anticipated to be active. Ideas for further improvement of the enzyme designs also emerged. On the technical side, the synergy of parallel QM/MM and experimental efforts in the design of artificial enzymes is well illustrated.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A series of enzymes for Kemp elimination of 5-nitrobenzisoxazole has been recently designed and tested. In conjunction with the design process, extensive computational analyses were carried out to evaluate the potential performance of four of the designs, as presented here. The enzyme-catalyzed reactions were modeled using mixed quantum and molecular mechanics (QM/MM) calculations in the context of Monte Carlo (MC) statistical mechanics simulations. Free-energy perturbation (FEP) calculations were used to characterize the free-energy surfaces for the catalyzed reactions as well as for reference processes in water. The simulations yielded detailed information about the catalytic mechanisms, activation barriers, and structural evolution of the active sites over the course of the reactions. The catalytic mechanism for the designed enzymes KE07, KE10(V131N), and KE15 was found to be concerted with proton transfer, generally more advanced in the transition state than breaking of the isoxazolyl N-O bond. On the basis of the free-energy results, all three enzymes were anticipated to be active. Ideas for further improvement of the enzyme designs also emerged. On the technical side, the synergy of parallel QM/MM and experimental efforts in the design of artificial enzymes is well illustrated.
Ingemar Andr’e, Charlie E M Strauss, David B Kaplan, Philip Bradley, David Baker
Emergence of symmetry in homooligomeric biological assemblies Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 105, pp. 16148-52, 2008, ISSN: 1091-6490.
@article{146,
title = {Emergence of symmetry in homooligomeric biological assemblies},
author = { Ingemar Andr'e and Charlie E M Strauss and David B Kaplan and Philip Bradley and David Baker},
issn = {1091-6490},
year = {2008},
date = {2008-10-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {105},
pages = {16148-52},
abstract = {Naturally occurring homooligomeric protein complexes exhibit striking internal symmetry. The evolutionary origins of this symmetry have been the subject of considerable speculation; proposals for the advantages associated with symmetry include greater folding efficiency, reduced aggregation, amenability to allosteric regulation, and greater adaptability. An alternative possibility stems from the idea that to contribute to fitness, and hence be subject to evolutionary optimization, a complex must be significantly populated, which implies that the interaction energy between monomers in the ancestors of modern-day complexes must have been sufficient to at least partially overcome the entropic cost of association. Here, we investigate the effects of this bias toward very-low-energy complexes on the distribution of symmetry in primordial homooligomers modeled as randomly interacting pairs of monomers. We demonstrate quantitatively that a bias toward very-low-energy complexes can result in the emergence of symmetry from random ensembles in which the overall frequency of symmetric complexes is vanishingly small. This result is corroborated by using explicit protein-protein docking calculations to generate ensembles of randomly docked complexes: the fraction of these that are symmetric increases from 0.02% in the overall population to >50% in very low energy subpopulations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Naturally occurring homooligomeric protein complexes exhibit striking internal symmetry. The evolutionary origins of this symmetry have been the subject of considerable speculation; proposals for the advantages associated with symmetry include greater folding efficiency, reduced aggregation, amenability to allosteric regulation, and greater adaptability. An alternative possibility stems from the idea that to contribute to fitness, and hence be subject to evolutionary optimization, a complex must be significantly populated, which implies that the interaction energy between monomers in the ancestors of modern-day complexes must have been sufficient to at least partially overcome the entropic cost of association. Here, we investigate the effects of this bias toward very-low-energy complexes on the distribution of symmetry in primordial homooligomers modeled as randomly interacting pairs of monomers. We demonstrate quantitatively that a bias toward very-low-energy complexes can result in the emergence of symmetry from random ensembles in which the overall frequency of symmetric complexes is vanishingly small. This result is corroborated by using explicit protein-protein docking calculations to generate ensembles of randomly docked complexes: the fraction of these that are symmetric increases from 0.02% in the overall population to >50% in very low energy subpopulations.
Michael R Sawaya, Woj M Wojtowicz, Ingemar Andre, Bin Qian, Wei Wu, David Baker, David Eisenberg, S Lawrence Zipursky
A double S shape provides the structural basis for the extraordinary binding specificity of Dscam isoforms Journal Article
In: Cell, vol. 134, pp. 1007-18, 2008, ISSN: 1097-4172.
@article{231,
title = {A double S shape provides the structural basis for the extraordinary binding specificity of Dscam isoforms},
author = { Michael R Sawaya and Woj M Wojtowicz and Ingemar Andre and Bin Qian and Wei Wu and David Baker and David Eisenberg and S Lawrence Zipursky},
issn = {1097-4172},
year = {2008},
date = {2008-09-01},
journal = {Cell},
volume = {134},
pages = {1007-18},
abstract = {Drosophila Dscam encodes a vast family of immunoglobulin (Ig)-containing proteins that exhibit isoform-specific homophilic binding. This diversity is essential for cell recognition events required for wiring the brain. Each isoform binds to itself but rarely to other isoforms. Specificity is determined by "matching" of three variable Ig domains within an approximately 220 kD ectodomain. Here, we present the structure of the homophilic binding region of Dscam, comprising the eight N-terminal Ig domains (Dscam(1-8)). Dscam(1-8) forms a symmetric homodimer of S-shaped molecules. This conformation, comprising two reverse turns, allows each pair of the three variable domains to "match" in an antiparallel fashion. Structural, genetic, and biochemical studies demonstrate that, in addition to variable domain "matching," intramolecular interactions between constant domains promote homophilic binding. These studies provide insight into how "matching" at all three pairs of variable domains in Dscam mediates isoform-specific recognition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Drosophila Dscam encodes a vast family of immunoglobulin (Ig)-containing proteins that exhibit isoform-specific homophilic binding. This diversity is essential for cell recognition events required for wiring the brain. Each isoform binds to itself but rarely to other isoforms. Specificity is determined by “matching” of three variable Ig domains within an approximately 220 kD ectodomain. Here, we present the structure of the homophilic binding region of Dscam, comprising the eight N-terminal Ig domains (Dscam(1-8)). Dscam(1-8) forms a symmetric homodimer of S-shaped molecules. This conformation, comprising two reverse turns, allows each pair of the three variable domains to “match” in an antiparallel fashion. Structural, genetic, and biochemical studies demonstrate that, in addition to variable domain “matching,” intramolecular interactions between constant domains promote homophilic binding. These studies provide insight into how “matching” at all three pairs of variable domains in Dscam mediates isoform-specific recognition.
Hyundae D Cho, Vanita D Sood, David Baker, Alan M Weiner
On the role of a conserved, potentially helix-breaking residue in the tRNA-binding alpha-helix of archaeal CCA-adding enzymes Journal Article
In: RNA, vol. 14, pp. 1284-9, 2008, ISSN: 1469-9001.
@article{147,
title = {On the role of a conserved, potentially helix-breaking residue in the tRNA-binding alpha-helix of archaeal CCA-adding enzymes},
author = { Hyundae D Cho and Vanita D Sood and David Baker and Alan M Weiner},
issn = {1469-9001},
year = {2008},
date = {2008-07-01},
journal = {RNA},
volume = {14},
pages = {1284-9},
abstract = {Archaeal class I CCA-adding enzymes use a ribonucleoprotein template to build and repair the universally conserved 3textquoteright-terminal CCA sequence of the acceptor stem of all tRNAs. A wealth of structural and biochemical data indicate that the Archaeoglobus fulgidus CCA-adding enzyme binds primarily to the tRNA acceptor stem through a long, highly conserved alpha-helix that lies nearly parallel to the acceptor stem and makes many contacts with its sugar-phosphate backbone. Although the geometry of this alpha-helix is nearly ideal in all available cocrystal structures, the helix contains a highly conserved, potentially helix-breaking proline or glycine near the N terminus. We performed a mutational analysis to dissect the role of this residue in CCA-addition activity. We found that the phylogenetically permissible P295G mutant and the phylogenetically absent P295T had little effect on CCA addition, whereas P295A and P295S progressively interfered with CCA addition (C74>C75>A76 addition). We also examined the effects of these mutations on tRNA binding and the kinetics of CCA addition, and performed a computational analysis using Rosetta Design to better understand the role of P295 in nucleotide transfer. Our data indicate that CCA-adding activity does not correlate with the stability of the pre-addition cocrystal structures visualized by X-ray crystallography. Rather, the data are consistent with a transient conformational change involving P295 of the tRNA-binding alpha-helix during or between one or more steps in CCA addition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Archaeal class I CCA-adding enzymes use a ribonucleoprotein template to build and repair the universally conserved 3textquoteright-terminal CCA sequence of the acceptor stem of all tRNAs. A wealth of structural and biochemical data indicate that the Archaeoglobus fulgidus CCA-adding enzyme binds primarily to the tRNA acceptor stem through a long, highly conserved alpha-helix that lies nearly parallel to the acceptor stem and makes many contacts with its sugar-phosphate backbone. Although the geometry of this alpha-helix is nearly ideal in all available cocrystal structures, the helix contains a highly conserved, potentially helix-breaking proline or glycine near the N terminus. We performed a mutational analysis to dissect the role of this residue in CCA-addition activity. We found that the phylogenetically permissible P295G mutant and the phylogenetically absent P295T had little effect on CCA addition, whereas P295A and P295S progressively interfered with CCA addition (C74>C75>A76 addition). We also examined the effects of these mutations on tRNA binding and the kinetics of CCA addition, and performed a computational analysis using Rosetta Design to better understand the role of P295 in nucleotide transfer. Our data indicate that CCA-adding activity does not correlate with the stability of the pre-addition cocrystal structures visualized by X-ray crystallography. Rather, the data are consistent with a transient conformational change involving P295 of the tRNA-binding alpha-helix during or between one or more steps in CCA addition.
Anthony H Keeble, Lukasz A Joachimiak, Mar’ia Jesus Mat’e, Nicola Meenan, Nadine Kirkpatrick, David Baker, Colin Kleanthous
Experimental and computational analyses of the energetic basis for dual recognition of immunity proteins by colicin endonucleases Journal Article
In: Journal of molecular biology, vol. 379, pp. 745-59, 2008, ISSN: 1089-8638.
@article{221,
title = {Experimental and computational analyses of the energetic basis for dual recognition of immunity proteins by colicin endonucleases},
author = { Anthony H Keeble and Lukasz A Joachimiak and Mar'ia Jesus Mat'e and Nicola Meenan and Nadine Kirkpatrick and David Baker and Colin Kleanthous},
issn = {1089-8638},
year = {2008},
date = {2008-06-01},
journal = {Journal of molecular biology},
volume = {379},
pages = {745-59},
abstract = {Colicin endonucleases (DNases) are bound and inactivated by immunity (Im) proteins. Im proteins are broadly cross-reactive yet specific inhibitors binding cognate and non-cognate DNases with K(d) values that vary between 10(-4) and 10(-14) M, characteristics that are explained by a textquoterightdual-recognitiontextquoteright mechanism. In this work, we addressed for the first time the energetics of Im protein recognition by colicin DNases through a combination of E9 DNase alanine scanning and double-mutant cycles (DMCs) coupled with kinetic and calorimetric analyses of cognate Im9 and non-cognate Im2 binding, as well as computational analysis of alanine scanning and DMC data. We show that differential DeltaDeltaGs observed for four E9 DNase residues cumulatively distinguish cognate Im9 association from non-cognate Im2 association. E9 DNase Phe86 is the primary specificity hotspot residue in the centre of the interface, which is coordinated by conserved and variable hotspot residues of the cognate Im protein. Experimental DMC analysis reveals that only modest coupling energies to Im9 residues are observed, in agreement with calculated DMCs using the program ROSETTA and consistent with the largely hydrophobic nature of E9 DNase-Im9 specificity contacts. Computed values for the 12 E9 DNase alanine mutants showed reasonable agreement with experimental DeltaDeltaG data, particularly for interactions not mediated by interfacial water molecules. DeltaDeltaG predictions for residues that contact buried water molecules calculated using solvated rotamer models met with mixed success; however, we were able to predict with a high degree of accuracy the location and energetic contribution of one such contact. Our study highlights how colicin DNases are able to utilise both conserved and variable amino acids to distinguish cognate from non-cognate Im proteins, with the energetic contributions of the conserved residues modulated by neighbouring specificity sites.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Colicin endonucleases (DNases) are bound and inactivated by immunity (Im) proteins. Im proteins are broadly cross-reactive yet specific inhibitors binding cognate and non-cognate DNases with K(d) values that vary between 10(-4) and 10(-14) M, characteristics that are explained by a textquoterightdual-recognitiontextquoteright mechanism. In this work, we addressed for the first time the energetics of Im protein recognition by colicin DNases through a combination of E9 DNase alanine scanning and double-mutant cycles (DMCs) coupled with kinetic and calorimetric analyses of cognate Im9 and non-cognate Im2 binding, as well as computational analysis of alanine scanning and DMC data. We show that differential DeltaDeltaGs observed for four E9 DNase residues cumulatively distinguish cognate Im9 association from non-cognate Im2 association. E9 DNase Phe86 is the primary specificity hotspot residue in the centre of the interface, which is coordinated by conserved and variable hotspot residues of the cognate Im protein. Experimental DMC analysis reveals that only modest coupling energies to Im9 residues are observed, in agreement with calculated DMCs using the program ROSETTA and consistent with the largely hydrophobic nature of E9 DNase-Im9 specificity contacts. Computed values for the 12 E9 DNase alanine mutants showed reasonable agreement with experimental DeltaDeltaG data, particularly for interactions not mediated by interfacial water molecules. DeltaDeltaG predictions for residues that contact buried water molecules calculated using solvated rotamer models met with mixed success; however, we were able to predict with a high degree of accuracy the location and energetic contribution of one such contact. Our study highlights how colicin DNases are able to utilise both conserved and variable amino acids to distinguish cognate from non-cognate Im proteins, with the energetic contributions of the conserved residues modulated by neighbouring specificity sites.
Daniela R”othlisberger, Olga Khersonsky, Andrew M Wollacott, Lin Jiang, Jason DeChancie, Jamie Betker, Jasmine L Gallaher, Eric A Althoff, Alexandre Zanghellini, Orly Dym, Shira Albeck, Kendall N Houk, Dan S Tawfik, David Baker
Kemp elimination catalysts by computational enzyme design Journal Article
In: Nature, vol. 453, pp. 190-5, 2008, ISSN: 1476-4687.
@article{230,
title = {Kemp elimination catalysts by computational enzyme design},
author = { Daniela R"othlisberger and Olga Khersonsky and Andrew M Wollacott and Lin Jiang and Jason DeChancie and Jamie Betker and Jasmine L Gallaher and Eric A Althoff and Alexandre Zanghellini and Orly Dym and Shira Albeck and Kendall N Houk and Dan S Tawfik and David Baker},
issn = {1476-4687},
year = {2008},
date = {2008-05-01},
journal = {Nature},
volume = {453},
pages = {190-5},
abstract = {The design of new enzymes for reactions not catalysed by naturally occurring biocatalysts is a challenge for protein engineering and is a critical test of our understanding of enzyme catalysis. Here we describe the computational design of eight enzymes that use two different catalytic motifs to catalyse the Kemp elimination-a model reaction for proton transfer from carbon-with measured rate enhancements of up to 10(5) and multiple turnovers. Mutational analysis confirms that catalysis depends on the computationally designed active sites, and a high-resolution crystal structure suggests that the designs have close to atomic accuracy. Application of in vitro evolution to enhance the computational designs produced a >200-fold increase in k(cat)/K(m) (k(cat)/K(m) of 2,600 M(-1)s(-1) and k(cat)/k(uncat) of >10(6)). These results demonstrate the power of combining computational protein design with directed evolution for creating new enzymes, and we anticipate the creation of a wide range of useful new catalysts in the future.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The design of new enzymes for reactions not catalysed by naturally occurring biocatalysts is a challenge for protein engineering and is a critical test of our understanding of enzyme catalysis. Here we describe the computational design of eight enzymes that use two different catalytic motifs to catalyse the Kemp elimination-a model reaction for proton transfer from carbon-with measured rate enhancements of up to 10(5) and multiple turnovers. Mutational analysis confirms that catalysis depends on the computationally designed active sites, and a high-resolution crystal structure suggests that the designs have close to atomic accuracy. Application of in vitro evolution to enhance the computational designs produced a >200-fold increase in k(cat)/K(m) (k(cat)/K(m) of 2,600 M(-1)s(-1) and k(cat)/k(uncat) of >10(6)). These results demonstrate the power of combining computational protein design with directed evolution for creating new enzymes, and we anticipate the creation of a wide range of useful new catalysts in the future.
Jian Qiu, Will Sheffler, David Baker, William Stafford Noble
Ranking predicted protein structures with support vector regression Journal Article
In: Proteins, vol. 71, pp. 1175-82, 2008, ISSN: 1097-0134.
@article{220,
title = {Ranking predicted protein structures with support vector regression},
author = { Jian Qiu and Will Sheffler and David Baker and William Stafford Noble},
issn = {1097-0134},
year = {2008},
date = {2008-05-01},
journal = {Proteins},
volume = {71},
pages = {1175-82},
abstract = {Protein structure prediction is an important problem of both intellectual and practical interest. Most protein structure prediction approaches generate multiple candidate models first, and then use a scoring function to select the best model among these candidates. In this work, we develop a scoring function using support vector regression (SVR). Both consensus-based features and features from individual structures are extracted from a training data set containing native protein structures and predicted structural models submitted to CASP5 and CASP6. The SVR learns a scoring function that is a linear combination of these features. We test this scoring function on two data sets. First, when used to rank server models submitted to CASP7, the SVR score selects predictions that are comparable to the best performing server in CASP7, Zhang-Server, and significantly better than all the other servers. Even if the SVR score is not allowed to select Zhang-Server models, the SVR score still selects predictions that are significantly better than all the other servers. In addition, the SVR is able to select significantly better models and yield significantly better Pearson correlation coefficients than the two best Quality Assessment groups in CASP7, QA556 (LEE), and QA634 (Pcons). Second, this work aims to improve the ability of the Robetta server to select best models, and hence we evaluate the performance of the SVR score on ranking the Robetta server template-based models for the CASP7 targets. The SVR selects significantly better models than the Robetta K*Sync consensus alignment score.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein structure prediction is an important problem of both intellectual and practical interest. Most protein structure prediction approaches generate multiple candidate models first, and then use a scoring function to select the best model among these candidates. In this work, we develop a scoring function using support vector regression (SVR). Both consensus-based features and features from individual structures are extracted from a training data set containing native protein structures and predicted structural models submitted to CASP5 and CASP6. The SVR learns a scoring function that is a linear combination of these features. We test this scoring function on two data sets. First, when used to rank server models submitted to CASP7, the SVR score selects predictions that are comparable to the best performing server in CASP7, Zhang-Server, and significantly better than all the other servers. Even if the SVR score is not allowed to select Zhang-Server models, the SVR score still selects predictions that are significantly better than all the other servers. In addition, the SVR is able to select significantly better models and yield significantly better Pearson correlation coefficients than the two best Quality Assessment groups in CASP7, QA556 (LEE), and QA634 (Pcons). Second, this work aims to improve the ability of the Robetta server to select best models, and hence we evaluate the performance of the SVR score on ranking the Robetta server template-based models for the CASP7 targets. The SVR selects significantly better models than the Robetta K*Sync consensus alignment score.
Lin Jiang, Eric A Althoff, Fernando R Clemente, Lindsey Doyle, Daniela R”othlisberger, Alexandre Zanghellini, Jasmine L Gallaher, Jamie L Betker, Fujie Tanaka, Carlos F Barbas, Donald Hilvert, Kendall N Houk, Barry L Stoddard, David Baker
De novo computational design of retro-aldol enzymes Journal Article
In: Science, vol. 319, pp. 1387-91, 2008, ISSN: 1095-9203.
@article{151,
title = {De novo computational design of retro-aldol enzymes},
author = { Lin Jiang and Eric A Althoff and Fernando R Clemente and Lindsey Doyle and Daniela R"othlisberger and Alexandre Zanghellini and Jasmine L Gallaher and Jamie L Betker and Fujie Tanaka and Carlos F Barbas and Donald Hilvert and Kendall N Houk and Barry L Stoddard and David Baker},
issn = {1095-9203},
year = {2008},
date = {2008-03-01},
journal = {Science},
volume = {319},
pages = {1387-91},
abstract = {The creation of enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Using new algorithms that rely on hashing techniques to construct active sites for multistep reactions, we designed retro-aldolases that use four different catalytic motifs to catalyze the breaking of a carbon-carbon bond in a nonnatural substrate. Of the 72 designs that were experimentally characterized, 32, spanning a range of protein folds, had detectable retro-aldolase activity. Designs that used an explicit water molecule to mediate proton shuffling were significantly more successful, with rate accelerations of up to four orders of magnitude and multiple turnovers, than those involving charged side-chain networks. The atomic accuracy of the design process was confirmed by the x-ray crystal structure of active designs embedded in two protein scaffolds, both of which were nearly superimposable on the design model.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The creation of enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Using new algorithms that rely on hashing techniques to construct active sites for multistep reactions, we designed retro-aldolases that use four different catalytic motifs to catalyze the breaking of a carbon-carbon bond in a nonnatural substrate. Of the 72 designs that were experimentally characterized, 32, spanning a range of protein folds, had detectable retro-aldolase activity. Designs that used an explicit water molecule to mediate proton shuffling were significantly more successful, with rate accelerations of up to four orders of magnitude and multiple turnovers, than those involving charged side-chain networks. The atomic accuracy of the design process was confirmed by the x-ray crystal structure of active designs embedded in two protein scaffolds, both of which were nearly superimposable on the design model.
Yang Shen, Oliver Lange, Frank Delaglio, Paolo Rossi, James M Aramini, Gaohua Liu, Alexander Eletsky, Yibing Wu, Kiran K Singarapu, Alexander Lemak, Alexandr Ignatchenko, Cheryl H Arrowsmith, Thomas Szyperski, Gaetano T Montelione, David Baker, Ad Bax
Consistent blind protein structure generation from NMR chemical shift data Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 105, pp. 4685-90, 2008, ISSN: 1091-6490.
@article{232,
title = {Consistent blind protein structure generation from NMR chemical shift data},
author = { Yang Shen and Oliver Lange and Frank Delaglio and Paolo Rossi and James M Aramini and Gaohua Liu and Alexander Eletsky and Yibing Wu and Kiran K Singarapu and Alexander Lemak and Alexandr Ignatchenko and Cheryl H Arrowsmith and Thomas Szyperski and Gaetano T Montelione and David Baker and Ad Bax},
issn = {1091-6490},
year = {2008},
date = {2008-03-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {105},
pages = {4685-90},
abstract = {Protein NMR chemical shifts are highly sensitive to local structure. A robust protocol is described that exploits this relation for de novo protein structure generation, using as input experimental parameters the (13)C(alpha), (13)C(beta), (13)Ctextquoteright, (15)N, (1)H(alpha) and (1)H(N) NMR chemical shifts. These shifts are generally available at the early stage of the traditional NMR structure determination process, before the collection and analysis of structural restraints. The chemical shift based structure determination protocol uses an empirically optimized procedure to select protein fragments from the Protein Data Bank, in conjunction with the standard ROSETTA Monte Carlo assembly and relaxation methods. Evaluation of 16 proteins, varying in size from 56 to 129 residues, yielded full-atom models that have 0.7-1.8 A root mean square deviations for the backbone atoms relative to the experimentally determined x-ray or NMR structures. The strategy also has been successfully applied in a blind manner to nine protein targets with molecular masses up to 15.4 kDa, whose conventional NMR structure determination was conducted in parallel by the Northeast Structural Genomics Consortium. This protocol potentially provides a new direction for high-throughput NMR structure determination.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein NMR chemical shifts are highly sensitive to local structure. A robust protocol is described that exploits this relation for de novo protein structure generation, using as input experimental parameters the (13)C(alpha), (13)C(beta), (13)Ctextquoteright, (15)N, (1)H(alpha) and (1)H(N) NMR chemical shifts. These shifts are generally available at the early stage of the traditional NMR structure determination process, before the collection and analysis of structural restraints. The chemical shift based structure determination protocol uses an empirically optimized procedure to select protein fragments from the Protein Data Bank, in conjunction with the standard ROSETTA Monte Carlo assembly and relaxation methods. Evaluation of 16 proteins, varying in size from 56 to 129 residues, yielded full-atom models that have 0.7-1.8 A root mean square deviations for the backbone atoms relative to the experimentally determined x-ray or NMR structures. The strategy also has been successfully applied in a blind manner to nine protein targets with molecular masses up to 15.4 kDa, whose conventional NMR structure determination was conducted in parallel by the Northeast Structural Genomics Consortium. This protocol potentially provides a new direction for high-throughput NMR structure determination.
Rhiju Das, Madhuri Kudaravalli, Magdalena Jonikas, Alain Laederach, Robert Fong, Jason P Schwans, David Baker, Joseph A Piccirilli, Russ B Altman, Daniel Herschlag
Structural inference of native and partially folded RNA by high-throughput contact mapping Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 105, pp. 4144-9, 2008, ISSN: 1091-6490.
@article{226,
title = {Structural inference of native and partially folded RNA by high-throughput contact mapping},
author = { Rhiju Das and Madhuri Kudaravalli and Magdalena Jonikas and Alain Laederach and Robert Fong and Jason P Schwans and David Baker and Joseph A Piccirilli and Russ B Altman and Daniel Herschlag},
issn = {1091-6490},
year = {2008},
date = {2008-03-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {105},
pages = {4144-9},
abstract = {The biological behaviors of ribozymes, riboswitches, and numerous other functional RNA molecules are critically dependent on their tertiary folding and their ability to sample multiple functional states. The conformational heterogeneity and partially folded nature of most of these states has rendered their characterization by high-resolution structural approaches difficult or even intractable. Here we introduce a method to rapidly infer the tertiary helical arrangements of large RNA molecules in their native and non-native solution states. Multiplexed hydroxyl radical (.OH) cleavage analysis (MOHCA) enables the high-throughput detection of numerous pairs of contacting residues via random incorporation of radical cleavage agents followed by two-dimensional gel electrophoresis. We validated this technology by recapitulating the unfolded and native states of a well studied model RNA, the P4-P6 domain of the Tetrahymena ribozyme, at subhelical resolution. We then applied MOHCA to a recently discovered third state of the P4-P6 RNA that is stabilized by high concentrations of monovalent salt and whose partial order precludes conventional techniques for structure determination. The three-dimensional portrait of a compact, non-native RNA state reveals a well ordered subset of native tertiary contacts, in contrast to the dynamic but otherwise similar molten globule states of proteins. With its applicability to nearly any solution state, we expect MOHCA to be a powerful tool for illuminating the many functional structures of large RNA molecules and RNA/protein complexes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The biological behaviors of ribozymes, riboswitches, and numerous other functional RNA molecules are critically dependent on their tertiary folding and their ability to sample multiple functional states. The conformational heterogeneity and partially folded nature of most of these states has rendered their characterization by high-resolution structural approaches difficult or even intractable. Here we introduce a method to rapidly infer the tertiary helical arrangements of large RNA molecules in their native and non-native solution states. Multiplexed hydroxyl radical (.OH) cleavage analysis (MOHCA) enables the high-throughput detection of numerous pairs of contacting residues via random incorporation of radical cleavage agents followed by two-dimensional gel electrophoresis. We validated this technology by recapitulating the unfolded and native states of a well studied model RNA, the P4-P6 domain of the Tetrahymena ribozyme, at subhelical resolution. We then applied MOHCA to a recently discovered third state of the P4-P6 RNA that is stabilized by high concentrations of monovalent salt and whose partial order precludes conventional techniques for structure determination. The three-dimensional portrait of a compact, non-native RNA state reveals a well ordered subset of native tertiary contacts, in contrast to the dynamic but otherwise similar molten globule states of proteins. With its applicability to nearly any solution state, we expect MOHCA to be a powerful tool for illuminating the many functional structures of large RNA molecules and RNA/protein complexes.
Christine McBeth, Audrey Seamons, Juan C Pizarro, Sarel J Fleishman, David Baker, Tanja Kortemme, Joan M Goverman, Roland K Strong
A new twist in TCR diversity revealed by a forbidden alphabeta TCR Journal Article
In: Journal of molecular biology, vol. 375, pp. 1306-19, 2008, ISSN: 1089-8638.
@article{219,
title = {A new twist in TCR diversity revealed by a forbidden alphabeta TCR},
author = { Christine McBeth and Audrey Seamons and Juan C Pizarro and Sarel J Fleishman and David Baker and Tanja Kortemme and Joan M Goverman and Roland K Strong},
issn = {1089-8638},
year = {2008},
date = {2008-02-01},
journal = {Journal of molecular biology},
volume = {375},
pages = {1306-19},
abstract = {We report crystal structures of a negatively selected T cell receptor (TCR) that recognizes two I-A(u)-restricted myelin basic protein peptides and one of its peptide/major histocompatibility complex (pMHC) ligands. Unusual complementarity-determining region (CDR) structural features revealed by our analyses identify a previously unrecognized mechanism by which the highly variable CDR3 regions define ligand specificity. In addition to the pMHC contact residues contributed by CDR3, the CDR3 residues buried deep within the V alpha/V beta interface exert indirect effects on recognition by influencing the V alpha/V beta interdomain angle. This phenomenon represents an additional mechanism for increasing the potential diversity of the TCR repertoire. Both the direct and indirect effects exerted by CDR residues can impact global TCR/MHC docking. Analysis of the available TCR structures in light of these results highlights the significance of the V alpha/V beta interdomain angle in determining specificity and indicates that TCR/pMHC interface features do not distinguish autoimmune from non-autoimmune class II-restricted TCRs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We report crystal structures of a negatively selected T cell receptor (TCR) that recognizes two I-A(u)-restricted myelin basic protein peptides and one of its peptide/major histocompatibility complex (pMHC) ligands. Unusual complementarity-determining region (CDR) structural features revealed by our analyses identify a previously unrecognized mechanism by which the highly variable CDR3 regions define ligand specificity. In addition to the pMHC contact residues contributed by CDR3, the CDR3 residues buried deep within the V alpha/V beta interface exert indirect effects on recognition by influencing the V alpha/V beta interdomain angle. This phenomenon represents an additional mechanism for increasing the potential diversity of the TCR repertoire. Both the direct and indirect effects exerted by CDR residues can impact global TCR/MHC docking. Analysis of the available TCR structures in light of these results highlights the significance of the V alpha/V beta interdomain angle in determining specificity and indicates that TCR/pMHC interface features do not distinguish autoimmune from non-autoimmune class II-restricted TCRs.
Gil Goobes, Rivka Goobes, Wendy J Shaw, James M Gibson, Joanna R Long, Vinodhkumar Raghunathan, Ora Schueler-Furman, Jennifer M Popham, David Baker, Charles T Campbell, Patrick S Stayton, Gary P Drobny
The structure, dynamics, and energetics of protein adsorption-lessons learned from adsorption of statherin to hydroxyapatite Journal Article
In: Magnetic resonance in chemistry, vol. 45, pp. S32-S47, 2008, ISSN: 1097-458X.
@article{223,
title = {The structure, dynamics, and energetics of protein adsorption-lessons learned from adsorption of statherin to hydroxyapatite},
author = { Gil Goobes and Rivka Goobes and Wendy J Shaw and James M Gibson and Joanna R Long and Vinodhkumar Raghunathan and Ora Schueler-Furman and Jennifer M Popham and David Baker and Charles T Campbell and Patrick S Stayton and Gary P Drobny},
issn = {1097-458X},
year = {2008},
date = {2008-01-01},
journal = {Magnetic resonance in chemistry},
volume = {45},
pages = {S32-S47},
abstract = {Proteins are found to be involved in interaction with solid surfaces in numerous natural events. Acidic proteins that adsorb to crystal faces of a biomineral to control the growth and morphology of hard tissue are only one example. Deducing the mechanisms of surface recognition exercised by proteins has implications to osteogenesis, pathological calcification and other proteins functions at their adsorbed state. Statherin is an enamel pellicle protein that inhibits hydroxyapatite nucleation and growth, lubricates the enamel surface, and is recognized by oral bacteria in periodontal diseases. Here, we highlight some of the insights we obtained recently using both thermodynamic and solid state NMR measurements to the adsorption process of statherin to hydroxyapatite. We combine macroscopic energy characterization with microscopic structural findings to present our views of protein adsorption mechanisms and the structural changes accompanying it and discuss the implications of these studies to understanding the functions of the protein adsorbed to the enamel surfaces. Copyright (c) 2007 John Wiley & Sons, Ltd.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Proteins are found to be involved in interaction with solid surfaces in numerous natural events. Acidic proteins that adsorb to crystal faces of a biomineral to control the growth and morphology of hard tissue are only one example. Deducing the mechanisms of surface recognition exercised by proteins has implications to osteogenesis, pathological calcification and other proteins functions at their adsorbed state. Statherin is an enamel pellicle protein that inhibits hydroxyapatite nucleation and growth, lubricates the enamel surface, and is recognized by oral bacteria in periodontal diseases. Here, we highlight some of the insights we obtained recently using both thermodynamic and solid state NMR measurements to the adsorption process of statherin to hydroxyapatite. We combine macroscopic energy characterization with microscopic structural findings to present our views of protein adsorption mechanisms and the structural changes accompanying it and discuss the implications of these studies to understanding the functions of the protein adsorbed to the enamel surfaces. Copyright (c) 2007 John Wiley & Sons, Ltd.
Raman S, Qian B, Baker D, Walker RC
Advances in Rosetta Protein Structure Prediction on Massively Parallel Systems Journal Article
In: Journal of Research and Development, vol. 52(1-2):7-17, 2008.
@article{280,
title = {Advances in Rosetta Protein Structure Prediction on Massively Parallel Systems},
author = { Raman S and Qian B and Baker D and Walker RC},
year = {2008},
date = {2008-01-01},
journal = {Journal of Research and Development},
volume = {52(1-2):7-17},
abstract = {One of the key challenges in computational biology is prediction of three-dimensional protein structures from amino-acid sequences. For most proteins, the "native state" lies at the bottom of a free-energy landscape. Protein structure prediction involves varying the degrees of freedom of the protein in a constrained manner until it approaches its native state. In the Rosetta protein structure prediction protocols, a large number of independent folding trajectories are simulated, and several lowest-energy results are likely to be close to the native state. The availability of hundred-teraflop, and shortly, petaflop, computing resources is revolutionizing the approaches available for protein structure prediction. Here, we discuss issues involved in utilizing such machines efficiently with the Rosetta code, including an overview of recent results of the Critical Assessment of Techniques for Protein Structure Prediction 7 (CASP7) in which the computationally demanding structure-refinement process was run on 16 racks of the IBM Blue Gene/L (TM) system at the IBM T. J. Watson Research Center. We highlight recent advances in high-performance computing and discuss,future development paths that make use of the next-generation petascale (> 10(12) floating-point operations per second) machines.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
One of the key challenges in computational biology is prediction of three-dimensional protein structures from amino-acid sequences. For most proteins, the “native state” lies at the bottom of a free-energy landscape. Protein structure prediction involves varying the degrees of freedom of the protein in a constrained manner until it approaches its native state. In the Rosetta protein structure prediction protocols, a large number of independent folding trajectories are simulated, and several lowest-energy results are likely to be close to the native state. The availability of hundred-teraflop, and shortly, petaflop, computing resources is revolutionizing the approaches available for protein structure prediction. Here, we discuss issues involved in utilizing such machines efficiently with the Rosetta code, including an overview of recent results of the Critical Assessment of Techniques for Protein Structure Prediction 7 (CASP7) in which the computationally demanding structure-refinement process was run on 16 racks of the IBM Blue Gene/L (TM) system at the IBM T. J. Watson Research Center. We highlight recent advances in high-performance computing and discuss,future development paths that make use of the next-generation petascale (> 10(12) floating-point operations per second) machines.
Rhiju Das, David Baker
Macromolecular modeling with rosetta Journal Article
In: Annual review of biochemistry, vol. 77, pp. 363-82, 2008, ISSN: 0066-4154.
@article{227,
title = {Macromolecular modeling with rosetta},
author = { Rhiju Das and David Baker},
issn = {0066-4154},
year = {2008},
date = {2008-00-01},
journal = {Annual review of biochemistry},
volume = {77},
pages = {363-82},
abstract = {Advances over the past few years have begun to enable prediction and design of macromolecular structures at near-atomic accuracy. Progress has stemmed from the development of reasonably accurate and efficiently computed all-atom potential functions as well as effective conformational sampling strategies appropriate for searching a highly rugged energy landscape, both driven by feedback from structure prediction and design tests. A unified energetic and kinematic framework in the Rosetta program allows a wide range of molecular modeling problems, from fibril structure prediction to RNA folding to the design of new protein interfaces, to be readily investigated and highlights areas for improvement. The methodology enables the creation of novel molecules with useful functions and holds promise for accelerating experimental structural inference. Emerging connections to crystallographic phasing, NMR modeling, and lower-resolution approaches are described and critically assessed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Advances over the past few years have begun to enable prediction and design of macromolecular structures at near-atomic accuracy. Progress has stemmed from the development of reasonably accurate and efficiently computed all-atom potential functions as well as effective conformational sampling strategies appropriate for searching a highly rugged energy landscape, both driven by feedback from structure prediction and design tests. A unified energetic and kinematic framework in the Rosetta program allows a wide range of molecular modeling problems, from fibril structure prediction to RNA folding to the design of new protein interfaces, to be readily investigated and highlights areas for improvement. The methodology enables the creation of novel molecules with useful functions and holds promise for accelerating experimental structural inference. Emerging connections to crystallographic phasing, NMR modeling, and lower-resolution approaches are described and critically assessed.
Erkang Fan, David Baker, Stanley Fields, Michael H Gelb, Frederick S Buckner, Wesley C Van Voorhis, Eric Phizicky, Mark Dumont, Christopher Mehlin, Elizabeth Grayhack, Mark Sullivan, Christophe Verlinde, George Detitta, Deirdre R Meldrum, Ethan A Merritt, Thomas Earnest, Michael Soltis, Frank Zucker, Peter J Myler, Lori Schoenfeld, David E Kim, Liz Worthey, Doug Lacount, Marissa Vignali, Jizhen Li, Somnath Mondal, Archna Massey, Brian Carroll, Stacey Gulde, Joseph Luft, Larry Desoto, Mark Holl, Jonathan Caruthers, J”urgen Bosch, Mark Robien, Tracy Arakaki, Margaret Holmes, Isolde Le Trong, Wim G J Hol
Structural genomics of pathogenic protozoa: an overview Journal Article
In: Methods in molecular biology, vol. 426, pp. 497-513, 2008, ISSN: 1064-3745.
@article{225,
title = {Structural genomics of pathogenic protozoa: an overview},
author = { Erkang Fan and David Baker and Stanley Fields and Michael H Gelb and Frederick S Buckner and Wesley C Van Voorhis and Eric Phizicky and Mark Dumont and Christopher Mehlin and Elizabeth Grayhack and Mark Sullivan and Christophe Verlinde and George Detitta and Deirdre R Meldrum and Ethan A Merritt and Thomas Earnest and Michael Soltis and Frank Zucker and Peter J Myler and Lori Schoenfeld and David E Kim and Liz Worthey and Doug Lacount and Marissa Vignali and Jizhen Li and Somnath Mondal and Archna Massey and Brian Carroll and Stacey Gulde and Joseph Luft and Larry Desoto and Mark Holl and Jonathan Caruthers and J"urgen Bosch and Mark Robien and Tracy Arakaki and Margaret Holmes and Isolde Le Trong and Wim G J Hol},
issn = {1064-3745},
year = {2008},
date = {2008-00-01},
journal = {Methods in molecular biology},
volume = {426},
pages = {497-513},
abstract = {The Structural Genomics of Pathogenic Protozoa (SGPP) Consortium aimed to determine crystal structures of proteins from trypanosomatid and malaria parasites in a high throughput manner. The pipeline of target selection, protein production, crystallization, and structure determination, is sketched. Special emphasis is given to a number of technology developments including domain prediction, the use of "co-crystallants," and capillary crystallization. "Fragment cocktail crystallography" for medical structural genomics is also described.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Structural Genomics of Pathogenic Protozoa (SGPP) Consortium aimed to determine crystal structures of proteins from trypanosomatid and malaria parasites in a high throughput manner. The pipeline of target selection, protein production, crystallization, and structure determination, is sketched. Special emphasis is given to a number of technology developments including domain prediction, the use of “co-crystallants,” and capillary crystallization. “Fragment cocktail crystallography” for medical structural genomics is also described.
2007
Chu Wang, Ora Schueler-Furman, Ingemar Andre, Nir London, Sarel J Fleishman, Philip Bradley, Bin Qian, David Baker
RosettaDock in CAPRI rounds 6-12 Journal Article
In: Proteins, vol. 69, pp. 758-63, 2007, ISSN: 1097-0134.
@article{112,
title = {RosettaDock in CAPRI rounds 6-12},
author = { Chu Wang and Ora Schueler-Furman and Ingemar Andre and Nir London and Sarel J Fleishman and Philip Bradley and Bin Qian and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/wang07B.pdf},
issn = {1097-0134},
year = {2007},
date = {2007-12-01},
journal = {Proteins},
volume = {69},
pages = {758-63},
abstract = {A challenge in protein-protein docking is to account for the conformational changes in the monomers that occur upon binding. The RosettaDock method, which incorporates sidechain flexibility but keeps the backbone fixed, was found in previous CAPRI rounds (4 and 5) to generate docking models with atomic accuracy, provided that conformational changes were mainly restricted to protein sidechains. In the recent rounds of CAPRI (6-12), large backbone conformational changes occur upon binding for several target complexes. To address these challenges, we explicitly introduced backbone flexibility in our modeling procedures by combining rigid-body docking with protein structure prediction techniques such as modeling variable loops and building homology models. Encouragingly, using this approach we were able to correctly predict a significant backbone conformational change of an interface loop for Target 20 (12 A rmsd between those in the unbound monomer and complex structures), but accounting for backbone flexibility in protein-protein docking is still very challenging because of the significantly larger conformational space, which must be surveyed. Motivated by these CAPRI challenges, we have made progress in reformulating RosettaDock using a "fold-tree" representation, which provides a general framework for treating a wide variety of flexible-backbone docking problems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A challenge in protein-protein docking is to account for the conformational changes in the monomers that occur upon binding. The RosettaDock method, which incorporates sidechain flexibility but keeps the backbone fixed, was found in previous CAPRI rounds (4 and 5) to generate docking models with atomic accuracy, provided that conformational changes were mainly restricted to protein sidechains. In the recent rounds of CAPRI (6-12), large backbone conformational changes occur upon binding for several target complexes. To address these challenges, we explicitly introduced backbone flexibility in our modeling procedures by combining rigid-body docking with protein structure prediction techniques such as modeling variable loops and building homology models. Encouragingly, using this approach we were able to correctly predict a significant backbone conformational change of an interface loop for Target 20 (12 A rmsd between those in the unbound monomer and complex structures), but accounting for backbone flexibility in protein-protein docking is still very challenging because of the significantly larger conformational space, which must be surveyed. Motivated by these CAPRI challenges, we have made progress in reformulating RosettaDock using a "fold-tree" representation, which provides a general framework for treating a wide variety of flexible-backbone docking problems.
Bin Qian, Srivatsan Raman, Rhiju Das, Philip Bradley, Airlie J McCoy, Randy J Read, David Baker
High-resolution structure prediction and the crystallographic phase problem Journal Article
In: Nature, vol. 450, pp. 259-64, 2007, ISSN: 1476-4687.
@article{115,
title = {High-resolution structure prediction and the crystallographic phase problem},
author = { Bin Qian and Srivatsan Raman and Rhiju Das and Philip Bradley and Airlie J McCoy and Randy J Read and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/qian07A.pdf},
issn = {1476-4687},
year = {2007},
date = {2007-11-01},
journal = {Nature},
volume = {450},
pages = {259-64},
abstract = {The energy-based refinement of low-resolution protein structure models to atomic-level accuracy is a major challenge for computational structural biology. Here we describe a new approach to refining protein structure models that focuses sampling in regions most likely to contain errors while allowing the whole structure to relax in a physically realistic all-atom force field. In applications to models produced using nuclear magnetic resonance data and to comparative models based on distant structural homologues, the method can significantly improve the accuracy of the structures in terms of both the backbone conformations and the placement of core side chains. Furthermore, the resulting models satisfy a particularly stringent test: they provide significantly better solutions to the X-ray crystallographic phase problem in molecular replacement trials. Finally, we show that all-atom refinement can produce de novo protein structure predictions that reach the high accuracy required for molecular replacement without any experimental phase information and in the absence of templates suitable for molecular replacement from the Protein Data Bank. These results suggest that the combination of high-resolution structure prediction with state-of-the-art phasing tools may be unexpectedly powerful in phasing crystallographic data for which molecular replacement is hindered by the absence of sufficiently accurate previous models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The energy-based refinement of low-resolution protein structure models to atomic-level accuracy is a major challenge for computational structural biology. Here we describe a new approach to refining protein structure models that focuses sampling in regions most likely to contain errors while allowing the whole structure to relax in a physically realistic all-atom force field. In applications to models produced using nuclear magnetic resonance data and to comparative models based on distant structural homologues, the method can significantly improve the accuracy of the structures in terms of both the backbone conformations and the placement of core side chains. Furthermore, the resulting models satisfy a particularly stringent test: they provide significantly better solutions to the X-ray crystallographic phase problem in molecular replacement trials. Finally, we show that all-atom refinement can produce de novo protein structure predictions that reach the high accuracy required for molecular replacement without any experimental phase information and in the absence of templates suitable for molecular replacement from the Protein Data Bank. These results suggest that the combination of high-resolution structure prediction with state-of-the-art phasing tools may be unexpectedly powerful in phasing crystallographic data for which molecular replacement is hindered by the absence of sufficiently accurate previous models.
Ingemar Andr’e, Philip Bradley, Chu Wang, David Baker
Prediction of the structure of symmetrical protein assemblies Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 104, pp. 17656-61, 2007, ISSN: 0027-8424.
@article{121,
title = {Prediction of the structure of symmetrical protein assemblies},
author = { Ingemar Andr'e and Philip Bradley and Chu Wang and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/André07A.pdf},
issn = {0027-8424},
year = {2007},
date = {2007-11-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {104},
pages = {17656-61},
abstract = {Biological supramolecular systems are commonly built up by the self-assembly of identical protein subunits to produce symmetrical oligomers with cyclical, icosahedral, or helical symmetry that play roles in processes ranging from allosteric control and molecular transport to motor action. The large size of these systems often makes them difficult to structurally characterize using experimental techniques. We have developed a computational protocol to predict the structure of symmetrical protein assemblies based on the structure of a single subunit. The method carries out simultaneous optimization of backbone, side chain, and rigid-body degrees of freedom, while restricting the search space to symmetrical conformations. Using this protocol, we can reconstruct, starting from the structure of a single subunit, the structure of cyclic oligomers and the icosahedral virus capsid of satellite panicum virus using a rigid backbone approximation. We predict the oligomeric state of EscJ from the type III secretion system both in its proposed cyclical and crystallized helical form. Finally, we show that the method can recapitulate the structure of an amyloid-like fibril formed by the peptide NNQQNY from the yeast prion protein Sup35 starting from the amino acid sequence alone and searching the complete space of backbone, side chain, and rigid-body degrees of freedom.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Biological supramolecular systems are commonly built up by the self-assembly of identical protein subunits to produce symmetrical oligomers with cyclical, icosahedral, or helical symmetry that play roles in processes ranging from allosteric control and molecular transport to motor action. The large size of these systems often makes them difficult to structurally characterize using experimental techniques. We have developed a computational protocol to predict the structure of symmetrical protein assemblies based on the structure of a single subunit. The method carries out simultaneous optimization of backbone, side chain, and rigid-body degrees of freedom, while restricting the search space to symmetrical conformations. Using this protocol, we can reconstruct, starting from the structure of a single subunit, the structure of cyclic oligomers and the icosahedral virus capsid of satellite panicum virus using a rigid backbone approximation. We predict the oligomeric state of EscJ from the type III secretion system both in its proposed cyclical and crystallized helical form. Finally, we show that the method can recapitulate the structure of an amyloid-like fibril formed by the peptide NNQQNY from the yeast prion protein Sup35 starting from the amino acid sequence alone and searching the complete space of backbone, side chain, and rigid-body degrees of freedom.
P Barth, J Schonbrun, David Baker
Toward high-resolution prediction and design of transmembrane helical protein structures Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 104, pp. 15682-7, 2007, ISSN: 0027-8424.
@article{120,
title = {Toward high-resolution prediction and design of transmembrane helical protein structures},
author = { P Barth and J Schonbrun and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/barth07A.pdf},
issn = {0027-8424},
year = {2007},
date = {2007-10-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {104},
pages = {15682-7},
abstract = {The prediction and design at the atomic level of membrane protein structures and interactions is a critical but unsolved challenge. To address this problem, we have developed an all-atom physical model that describes intraprotein and protein-solvent interactions in the membrane environment. We evaluated the ability of the model to recapitulate the energetics and structural specificities of polytopic membrane proteins by using a battery of in silico prediction and design tests. First, in side-chain packing and design tests, the model successfully predicts the side-chain conformations at 73% of nonexposed positions and the native amino acid identities at 34% of positions in naturally occurring membrane proteins. Second, the model predicts significant energy gaps between native and nonnative structures of transmembrane helical interfaces and polytopic membrane proteins. Third, distortions in transmembrane helices are successfully recapitulated in docking experiments by using fragments of ideal helices judiciously defined around helical kinks. Finally, de novo structure prediction reaches near-atomic accuracy (<2.5 A) for several small membrane protein domains (<150 residues). The success of the model highlights the critical role of van der Waals and hydrogen-bonding interactions in the stability and structural specificity of membrane protein structures and sets the stage for the high-resolution prediction and design of complex membrane protein architectures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The prediction and design at the atomic level of membrane protein structures and interactions is a critical but unsolved challenge. To address this problem, we have developed an all-atom physical model that describes intraprotein and protein-solvent interactions in the membrane environment. We evaluated the ability of the model to recapitulate the energetics and structural specificities of polytopic membrane proteins by using a battery of in silico prediction and design tests. First, in side-chain packing and design tests, the model successfully predicts the side-chain conformations at 73% of nonexposed positions and the native amino acid identities at 34% of positions in naturally occurring membrane proteins. Second, the model predicts significant energy gaps between native and nonnative structures of transmembrane helical interfaces and polytopic membrane proteins. Third, distortions in transmembrane helices are successfully recapitulated in docking experiments by using fragments of ideal helices judiciously defined around helical kinks. Finally, de novo structure prediction reaches near-atomic accuracy (<2.5 A) for several small membrane protein domains (<150 residues). The success of the model highlights the critical role of van der Waals and hydrogen-bonding interactions in the stability and structural specificity of membrane protein structures and sets the stage for the high-resolution prediction and design of complex membrane protein architectures.
Candice S E Lengyel, Lindsey J Willis, Patrick Mann, David Baker, Tanja Kortemme, Roland K Strong, Benjamin J McFarland
Mutations designed to destabilize the receptor-bound conformation increase MICA-NKG2D association rate and affinity Journal Article
In: The Journal of biological chemistry, vol. 282, pp. 30658-66, 2007, ISSN: 0021-9258.
@article{282,
title = {Mutations designed to destabilize the receptor-bound conformation increase MICA-NKG2D association rate and affinity},
author = { Candice S E Lengyel and Lindsey J Willis and Patrick Mann and David Baker and Tanja Kortemme and Roland K Strong and Benjamin J McFarland},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/lengyel07A.pdf},
issn = {0021-9258},
year = {2007},
date = {2007-10-01},
journal = {The Journal of biological chemistry},
volume = {282},
pages = {30658-66},
abstract = {MICA is a major histocompatibility complex-like protein that undergoes a structural transition from disorder to order upon binding its immunoreceptor, NKG2D. We redesigned the disordered region of MICA with RosettaDesign to increase NKG2D binding. Mutations that stabilize this region were expected to increase association kinetics without changing dissociation kinetics, increase affinity of interaction, and reduce entropy loss upon binding. MICA mutants were stable in solution, and they were amenable to surface plasmon resonance evaluation of NKG2D binding kinetics and thermodynamics. Several MICA mutants bound NKG2D with enhanced affinity, kinetic changes were primarily observed during association, and thermodynamic changes in entropy were as expected. However, none of the 15 combinations of mutations predicted to stabilize the receptor-bound MICA conformation enhanced NKG2D affinity, whereas all 10 mutants predicted to be destabilized bound NKG2D with increased on-rates. Five of these had affinities enhanced by 0.9-1.8 kcal/mol over wild type by one to three non-contacting substitutions. Therefore, in this case, mutations designed to mildly destabilize a protein enhanced association and affinity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
MICA is a major histocompatibility complex-like protein that undergoes a structural transition from disorder to order upon binding its immunoreceptor, NKG2D. We redesigned the disordered region of MICA with RosettaDesign to increase NKG2D binding. Mutations that stabilize this region were expected to increase association kinetics without changing dissociation kinetics, increase affinity of interaction, and reduce entropy loss upon binding. MICA mutants were stable in solution, and they were amenable to surface plasmon resonance evaluation of NKG2D binding kinetics and thermodynamics. Several MICA mutants bound NKG2D with enhanced affinity, kinetic changes were primarily observed during association, and thermodynamic changes in entropy were as expected. However, none of the 15 combinations of mutations predicted to stabilize the receptor-bound MICA conformation enhanced NKG2D affinity, whereas all 10 mutants predicted to be destabilized bound NKG2D with increased on-rates. Five of these had affinities enhanced by 0.9-1.8 kcal/mol over wild type by one to three non-contacting substitutions. Therefore, in this case, mutations designed to mildly destabilize a protein enhanced association and affinity.
Chu Wang, Philip Bradley, David Baker
Protein-protein docking with backbone flexibility Journal Article
In: Journal of molecular biology, vol. 373, pp. 503-19, 2007, ISSN: 0022-2836.
@article{113,
title = {Protein-protein docking with backbone flexibility},
author = { Chu Wang and Philip Bradley and David Baker},
issn = {0022-2836},
year = {2007},
date = {2007-10-01},
journal = {Journal of molecular biology},
volume = {373},
pages = {503-19},
abstract = {Computational protein-protein docking methods currently can create models with atomic accuracy for protein complexes provided that the conformational changes upon association are restricted to the side chains. However, it remains very challenging to account for backbone conformational changes during docking, and most current methods inherently keep monomer backbones rigid for algorithmic simplicity and computational efficiency. Here we present a reformulation of the Rosetta docking method that incorporates explicit backbone flexibility in protein-protein docking. The new method is based on a "fold-tree" representation of the molecular system, which seamlessly integrates internal torsional degrees of freedom and rigid-body degrees of freedom. Problems with internal flexible regions ranging from one or more loops or hinge regions to all of one or both partners can be readily treated using appropriately constructed fold trees. The explicit treatment of backbone flexibility improves both sampling in the vicinity of the native docked conformation and the energetic discrimination between near-native and incorrect models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational protein-protein docking methods currently can create models with atomic accuracy for protein complexes provided that the conformational changes upon association are restricted to the side chains. However, it remains very challenging to account for backbone conformational changes during docking, and most current methods inherently keep monomer backbones rigid for algorithmic simplicity and computational efficiency. Here we present a reformulation of the Rosetta docking method that incorporates explicit backbone flexibility in protein-protein docking. The new method is based on a “fold-tree” representation of the molecular system, which seamlessly integrates internal torsional degrees of freedom and rigid-body degrees of freedom. Problems with internal flexible regions ranging from one or more loops or hinge regions to all of one or both partners can be readily treated using appropriately constructed fold trees. The explicit treatment of backbone flexibility improves both sampling in the vicinity of the native docked conformation and the energetic discrimination between near-native and incorrect models.
Woj M Wojtowicz, Wei Wu, Ingemar Andre, Bin Qian, David Baker, S Lawrence Zipursky
A vast repertoire of Dscam binding specificities arises from modular interactions of variable Ig domains Journal Article
In: Cell, vol. 130, pp. 1134-45, 2007, ISSN: 0092-8674.
@article{110,
title = {A vast repertoire of Dscam binding specificities arises from modular interactions of variable Ig domains},
author = { Woj M Wojtowicz and Wei Wu and Ingemar Andre and Bin Qian and David Baker and S Lawrence Zipursky},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/wojtowicz07A.pdf},
issn = {0092-8674},
year = {2007},
date = {2007-09-01},
journal = {Cell},
volume = {130},
pages = {1134-45},
abstract = {Dscam encodes a family of cell surface proteins required for establishing neural circuits in Drosophila. Alternative splicing of Drosophila Dscam can generate 19,008 distinct extracellular domains containing different combinations of three variable immunoglobulin domains. To test the binding properties of many Dscam isoforms, we developed a high-throughput ELISA-based binding assay. We provide evidence that 95% (>18,000) of Dscam isoforms exhibit striking isoform-specific homophilic binding. We demonstrate that each of the three variable domains binds to the same variable domain in an opposing isoform and identify the structural elements that mediate this self-binding of each domain. These studies demonstrate that self-binding domains can assemble in different combinations to generate an enormous family of homophilic binding proteins. We propose that this vast repertoire of Dscam recognition molecules is sufficient to provide each neuron with a unique identity and homotypic binding specificity, thereby allowing neuronal processes to distinguish between self and nonself.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dscam encodes a family of cell surface proteins required for establishing neural circuits in Drosophila. Alternative splicing of Drosophila Dscam can generate 19,008 distinct extracellular domains containing different combinations of three variable immunoglobulin domains. To test the binding properties of many Dscam isoforms, we developed a high-throughput ELISA-based binding assay. We provide evidence that 95% (>18,000) of Dscam isoforms exhibit striking isoform-specific homophilic binding. We demonstrate that each of the three variable domains binds to the same variable domain in an opposing isoform and identify the structural elements that mediate this self-binding of each domain. These studies demonstrate that self-binding domains can assemble in different combinations to generate an enormous family of homophilic binding proteins. We propose that this vast repertoire of Dscam recognition molecules is sufficient to provide each neuron with a unique identity and homotypic binding specificity, thereby allowing neuronal processes to distinguish between self and nonself.
Rhiju Das, David Baker
Automated de novo prediction of native-like RNA tertiary structures Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 104, pp. 14664-9, 2007, ISSN: 0027-8424.
@article{117,
title = {Automated de novo prediction of native-like RNA tertiary structures},
author = { Rhiju Das and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/das07A.pdf},
issn = {0027-8424},
year = {2007},
date = {2007-09-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {104},
pages = {14664-9},
abstract = {RNA tertiary structure prediction has been based almost entirely on base-pairing constraints derived from phylogenetic covariation analysis. We describe here a complementary approach, inspired by the Rosetta low-resolution protein structure prediction method, that seeks the lowest energy tertiary structure for a given RNA sequence without using evolutionary information. In a benchmark test of 20 RNA sequences with known structure and lengths of approximately 30 nt, the new method reproduces better than 90% of Watson-Crick base pairs, comparable with the accuracy of secondary structure prediction methods. In more than half the cases, at least one of the top five models agrees with the native structure to better than 4 A rmsd over the backbone. Most importantly, the method recapitulates more than one-third of non-Watson-Crick base pairs seen in the native structures. Tandem stacks of "sheared" base pairs, base triplets, and pseudoknots are among the noncanonical features reproduced in the models. In the cases in which none of the top five models were native-like, higher energy conformations similar to the native structures are still sampled frequently but not assigned low energies. These results suggest that modest improvements in the energy function, together with the incorporation of information from phylogenetic covariance, may allow confident and accurate structure prediction for larger and more complex RNA chains.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
RNA tertiary structure prediction has been based almost entirely on base-pairing constraints derived from phylogenetic covariation analysis. We describe here a complementary approach, inspired by the Rosetta low-resolution protein structure prediction method, that seeks the lowest energy tertiary structure for a given RNA sequence without using evolutionary information. In a benchmark test of 20 RNA sequences with known structure and lengths of approximately 30 nt, the new method reproduces better than 90% of Watson-Crick base pairs, comparable with the accuracy of secondary structure prediction methods. In more than half the cases, at least one of the top five models agrees with the native structure to better than 4 A rmsd over the backbone. Most importantly, the method recapitulates more than one-third of non-Watson-Crick base pairs seen in the native structures. Tandem stacks of "sheared" base pairs, base triplets, and pseudoknots are among the noncanonical features reproduced in the models. In the cases in which none of the top five models were native-like, higher energy conformations similar to the native structures are still sampled frequently but not assigned low energies. These results suggest that modest improvements in the energy function, together with the incorporation of information from phylogenetic covariance, may allow confident and accurate structure prediction for larger and more complex RNA chains.
Kryn Stankunas, J Henri Bayle, James J Havranek, Thomas J Wandless, David Baker, Gerald R Crabtree, Jason E Gestwicki
Rescue of degradation-prone mutants of the FK506-rapamycin binding (FRB) protein with chemical ligands Journal Article
In: Chembiochem : a European journal of chemical biology, vol. 8, pp. 1162-9, 2007, ISSN: 1439-4227.
@article{285,
title = {Rescue of degradation-prone mutants of the FK506-rapamycin binding (FRB) protein with chemical ligands},
author = { Kryn Stankunas and J Henri Bayle and James J Havranek and Thomas J Wandless and David Baker and Gerald R Crabtree and Jason E Gestwicki},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/stankunas07A.pdf},
issn = {1439-4227},
year = {2007},
date = {2007-07-01},
journal = {Chembiochem : a European journal of chemical biology},
volume = {8},
pages = {1162-9},
abstract = {We recently reported that certain mutations in the FK506-rapamycin binding (FRB) domain disrupt its stability in vitro and in vivo (Stankunas et al. Mol. Cell, 2003, 12, 1615). To determine the precise residues that cause instability, we calculated the folding free energy (Delta G) of a collection of FRB mutants by measuring their intrinsic tryptophan fluorescence during reversible chaotropic denaturation. Our results implicate the T2098L point mutation as a key determinant of instability. Further, we found that some of the mutants in this collection were destabilized by up to 6 kcal mol(-1) relative to the wild type. To investigate how these mutants behave in cells, we expressed firefly luciferase fused to FRB mutants in African green monkey kidney (COS) cell lines and mouse embryonic fibroblasts (MEFs). When unstable FRB mutants were used, we found that the protein levels and the luminescence intensities were low. However, addition of a chemical ligand for FRB, rapamycin, restored luciferase activity. Interestingly, we found a roughly linear relationship between the Delta G of the FRB mutants calculated in vitro and the relative chemical rescue in cells. Because rapamycin is capable of simultaneously binding both FRB and the chaperone, FK506-binding protein (FKBP), we next examined whether FKBP might contribute to the protection of FRB mutants. Using both in vitro experiments and a cell-based model, we found that FKBP stabilizes the mutants. These findings are consistent with recent models that suggest damage to intrinsic Delta G can be corrected by pharmacological chaperones. Further, these results provide a collection of conditionally stable fusion partners for use in controlling protein stability.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We recently reported that certain mutations in the FK506-rapamycin binding (FRB) domain disrupt its stability in vitro and in vivo (Stankunas et al. Mol. Cell, 2003, 12, 1615). To determine the precise residues that cause instability, we calculated the folding free energy (Delta G) of a collection of FRB mutants by measuring their intrinsic tryptophan fluorescence during reversible chaotropic denaturation. Our results implicate the T2098L point mutation as a key determinant of instability. Further, we found that some of the mutants in this collection were destabilized by up to 6 kcal mol(-1) relative to the wild type. To investigate how these mutants behave in cells, we expressed firefly luciferase fused to FRB mutants in African green monkey kidney (COS) cell lines and mouse embryonic fibroblasts (MEFs). When unstable FRB mutants were used, we found that the protein levels and the luminescence intensities were low. However, addition of a chemical ligand for FRB, rapamycin, restored luciferase activity. Interestingly, we found a roughly linear relationship between the Delta G of the FRB mutants calculated in vitro and the relative chemical rescue in cells. Because rapamycin is capable of simultaneously binding both FRB and the chaperone, FK506-binding protein (FKBP), we next examined whether FKBP might contribute to the protection of FRB mutants. Using both in vitro experiments and a cell-based model, we found that FKBP stabilizes the mutants. These findings are consistent with recent models that suggest damage to intrinsic Delta G can be corrected by pharmacological chaperones. Further, these results provide a collection of conditionally stable fusion partners for use in controlling protein stability.
Andriy S Yatsenko, Elizabeth E Gray, Halyna R Shcherbata, Larissa B Patterson, Vanita D Sood, Mariya M Kucherenko, David Baker, Hannele Ruohola-Baker
In: The Journal of biological chemistry, vol. 282, pp. 15159-69, 2007, ISSN: 0021-9258.
@article{576,
title = {A putative Src homology 3 domain binding motif but not the C-terminal dystrophin WW domain binding motif is required for dystroglycan function in cellular polarity in Drosophila.},
author = { Andriy S Yatsenko and Elizabeth E Gray and Halyna R Shcherbata and Larissa B Patterson and Vanita D Sood and Mariya M Kucherenko and David Baker and Hannele Ruohola-Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/aputativesrc_Baker2007.pdf},
doi = {10.1074/jbc.M608800200},
issn = {0021-9258},
year = {2007},
date = {2007-05-01},
journal = {The Journal of biological chemistry},
volume = {282},
pages = {15159-69},
abstract = {The conserved dystroglycan-dystrophin (Dg.Dys) complex connects the extracellular matrix to the cytoskeleton. In humans as well as Drosophila, perturbation of this complex results in muscular dystrophies and brain malformations and in some cases cellular polarity defects. However, the regulation of the Dg.Dys complex is poorly understood in any cell type. We now find that in loss-of-function and overexpression studies more than half (34 residues) of the Dg proline-rich conserved C-terminal regions can be truncated without significantly compromising its function in regulating cellular polarity in Drosophila. Notably, the truncation eliminates the WW domain binding motif at the very C terminus of the protein thought to mediate interactions with dystrophin, suggesting that a second, internal WW binding motif can also mediate this interaction. We confirm this hypothesis by using a sensitive fluorescence polarization assay to show that both WW domain binding sites of Dg bind to Dys in humans (K(d) = 7.6 and 81 microM, respectively) and Drosophila (K(d) = 16 and 46 microM, respectively). In contrast to the large deletion mentioned above, a single proline to an alanine point mutation within a predicted Src homology 3 domain (SH3) binding site abolishes Dg function in cellular polarity. This suggests that an SH3-containing protein, which has yet to be identified, functionally interacts with Dg.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The conserved dystroglycan-dystrophin (Dg.Dys) complex connects the extracellular matrix to the cytoskeleton. In humans as well as Drosophila, perturbation of this complex results in muscular dystrophies and brain malformations and in some cases cellular polarity defects. However, the regulation of the Dg.Dys complex is poorly understood in any cell type. We now find that in loss-of-function and overexpression studies more than half (34 residues) of the Dg proline-rich conserved C-terminal regions can be truncated without significantly compromising its function in regulating cellular polarity in Drosophila. Notably, the truncation eliminates the WW domain binding motif at the very C terminus of the protein thought to mediate interactions with dystrophin, suggesting that a second, internal WW binding motif can also mediate this interaction. We confirm this hypothesis by using a sensitive fluorescence polarization assay to show that both WW domain binding sites of Dg bind to Dys in humans (K(d) = 7.6 and 81 microM, respectively) and Drosophila (K(d) = 16 and 46 microM, respectively). In contrast to the large deletion mentioned above, a single proline to an alanine point mutation within a predicted Src homology 3 domain (SH3) binding site abolishes Dg function in cellular polarity. This suggests that an SH3-containing protein, which has yet to be identified, functionally interacts with Dg.
Jinsong Li, Masaji Shinjo, Yoshitaka Matsumura, Masayuki Morita, David Baker, Masamichi Ikeguchi, Hiroshi Kihara
An alpha-helical burst in the src SH3 folding pathway Journal Article
In: Biochemistry, vol. 46, pp. 5072-82, 2007, ISSN: 0006-2960.
@article{283,
title = {An alpha-helical burst in the src SH3 folding pathway},
author = { Jinsong Li and Masaji Shinjo and Yoshitaka Matsumura and Masayuki Morita and David Baker and Masamichi Ikeguchi and Hiroshi Kihara},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/li07A.pdf},
issn = {0006-2960},
year = {2007},
date = {2007-05-01},
journal = {Biochemistry},
volume = {46},
pages = {5072-82},
abstract = {Src SH3 is a small all-beta-sheet protein composed of a single domain. We studied the folding behavior of src SH3 at various conditions by circular dichroism (CD), fluorescence, and X-ray solution scattering methods. On the src SH3 folding pathway, an alpha-helix-rich intermediate appeared not only at subzero temperatures but also above 0 degrees C. The fraction of alpha-helix in the kinetically observed intermediate is ca. 26% based on the kinetic CD experiment. X-ray solution scattering revealed that the intermediate was compact but not fully packed. The analysis of CD implies that the amplitude of the burst phase is proportional to the helical fraction calculated according to the helix-coil transition theory. This strongly suggests that the initial folding core is formed by the collapse of much less stably existing alpha-helices.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Src SH3 is a small all-beta-sheet protein composed of a single domain. We studied the folding behavior of src SH3 at various conditions by circular dichroism (CD), fluorescence, and X-ray solution scattering methods. On the src SH3 folding pathway, an alpha-helix-rich intermediate appeared not only at subzero temperatures but also above 0 degrees C. The fraction of alpha-helix in the kinetically observed intermediate is ca. 26% based on the kinetic CD experiment. X-ray solution scattering revealed that the intermediate was compact but not fully packed. The analysis of CD implies that the amplitude of the burst phase is proportional to the helical fraction calculated according to the helix-coil transition theory. This strongly suggests that the initial folding core is formed by the collapse of much less stably existing alpha-helices.
Kiril Tsemekhman, Lukasz Goldschmidt, David Eisenberg, David Baker
Cooperative hydrogen bonding in amyloid formation Journal Article
In: Protein science, vol. 16, pp. 761-4, 2007, ISSN: 0961-8368.
@article{114,
title = {Cooperative hydrogen bonding in amyloid formation},
author = { Kiril Tsemekhman and Lukasz Goldschmidt and David Eisenberg and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/tsemekhman07A.pdf},
issn = {0961-8368},
year = {2007},
date = {2007-04-01},
journal = {Protein science},
volume = {16},
pages = {761-4},
abstract = {Amyloid diseases, including Alzheimertextquoterights and prion diseases, are each associated with unbranched protein fibrils. Each fibril is made of a particular protein, yet they share common properties. One such property is nucleation-dependent fibril growth. Monomers of amyloid-forming proteins can remain in dissolved form for long periods, before rapidly assembly into fibrils. The lag before growth has been attributed to slow kinetics of formation of a nucleus, on which other molecules can deposit to form the fibril. We have explored the energetics of fibril formation, based on the known molecular structure of a fibril-forming peptide from the yeast prion, Sup35, using both classical and quantum (density functional theory) methods. We find that the energetics of fibril formation for the first three layers are cooperative using both methods. This cooperativity is consistent with the observation that formation of amyloid fibrils involves slow nucleation and faster growth.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Amyloid diseases, including Alzheimertextquoterights and prion diseases, are each associated with unbranched protein fibrils. Each fibril is made of a particular protein, yet they share common properties. One such property is nucleation-dependent fibril growth. Monomers of amyloid-forming proteins can remain in dissolved form for long periods, before rapidly assembly into fibrils. The lag before growth has been attributed to slow kinetics of formation of a nucleus, on which other molecules can deposit to form the fibril. We have explored the energetics of fibril formation, based on the known molecular structure of a fibril-forming peptide from the yeast prion, Sup35, using both classical and quantum (density functional theory) methods. We find that the energetics of fibril formation for the first three layers are cooperative using both methods. This cooperativity is consistent with the observation that formation of amyloid fibrils involves slow nucleation and faster growth.
Lars Malmstrom, Michael Riffle, Charlie E M Strauss, Dylan Chivian, Trisha N Davis, Richard Bonneau, David Baker
Superfamily assignments for the yeast proteome through integration of structure prediction with the gene ontology Journal Article
In: PLoS biology, vol. 5, pp. e76, 2007, ISSN: 1545-7885.
@article{116,
title = {Superfamily assignments for the yeast proteome through integration of structure prediction with the gene ontology},
author = { Lars Malmstrom and Michael Riffle and Charlie E M Strauss and Dylan Chivian and Trisha N Davis and Richard Bonneau and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/malmström07A.pdf},
issn = {1545-7885},
year = {2007},
date = {2007-04-01},
journal = {PLoS biology},
volume = {5},
pages = {e76},
abstract = {Saccharomyces cerevisiae is one of the best-studied model organisms, yet the three-dimensional structure and molecular function of many yeast proteins remain unknown. Yeast proteins were parsed into 14,934 domains, and those lacking sequence similarity to proteins of known structure were folded using the Rosetta de novo structure prediction method on the World Community Grid. This structural data was integrated with process, component, and function annotations from the Saccharomyces Genome Database to assign yeast protein domains to SCOP superfamilies using a simple Bayesian approach. We have predicted the structure of 3,338 putative domains and assigned SCOP superfamily annotations to 581 of them. We have also assigned structural annotations to 7,094 predicted domains based on fold recognition and homology modeling methods. The domain predictions and structural information are available in an online database at http://rd.plos.org/10.1371_journal.pbio.0050076_01.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Saccharomyces cerevisiae is one of the best-studied model organisms, yet the three-dimensional structure and molecular function of many yeast proteins remain unknown. Yeast proteins were parsed into 14,934 domains, and those lacking sequence similarity to proteins of known structure were folded using the Rosetta de novo structure prediction method on the World Community Grid. This structural data was integrated with process, component, and function annotations from the Saccharomyces Genome Database to assign yeast protein domains to SCOP superfamilies using a simple Bayesian approach. We have predicted the structure of 3,338 putative domains and assigned SCOP superfamily annotations to 581 of them. We have also assigned structural annotations to 7,094 predicted domains based on fold recognition and homology modeling methods. The domain predictions and structural information are available in an online database at http://rd.plos.org/10.1371_journal.pbio.0050076_01.
Gautam Dantas, Colin Corrent, Steve L Reichow, James J Havranek, Ziad M Eletr, Nancy G Isern, Brian Kuhlman, Gabriele Varani, Ethan A Merritt, David Baker
High-resolution structural and thermodynamic analysis of extreme stabilization of human procarboxypeptidase by computational protein design Journal Article
In: Journal of molecular biology, vol. 366, pp. 1209-21, 2007, ISSN: 0022-2836.
@article{119,
title = {High-resolution structural and thermodynamic analysis of extreme stabilization of human procarboxypeptidase by computational protein design},
author = { Gautam Dantas and Colin Corrent and Steve L Reichow and James J Havranek and Ziad M Eletr and Nancy G Isern and Brian Kuhlman and Gabriele Varani and Ethan A Merritt and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/dantas07A.pdf},
issn = {0022-2836},
year = {2007},
date = {2007-03-01},
journal = {Journal of molecular biology},
volume = {366},
pages = {1209-21},
abstract = {Recent efforts to design de novo or redesign the sequence and structure of proteins using computational techniques have met with significant success. Most, if not all, of these computational methodologies attempt to model atomic-level interactions, and hence high-resolution structural characterization of the designed proteins is critical for evaluating the atomic-level accuracy of the underlying design force-fields. We previously used our computational protein design protocol RosettaDesign to completely redesign the sequence of the activation domain of human procarboxypeptidase A2. With 68% of the wild-type sequence changed, the designed protein, AYEdesign, is over 10 kcal/mol more stable than the wild-type protein. Here, we describe the high-resolution crystal structure and solution NMR structure of AYEdesign, which show that the experimentally determined backbone and side-chains conformations are effectively superimposable with the computational model at atomic resolution. To isolate the origins of the remarkable stabilization, we have designed and characterized a new series of procarboxypeptidase mutants that gain significant thermodynamic stability with a minimal number of mutations; one mutant gains more than 5 kcal/mol of stability over the wild-type protein with only four amino acid changes. We explore the relationship between force-field smoothing and conformational sampling by comparing the experimentally determined free energies of the overall design and these focused subsets of mutations to those predicted using modified force-fields, and both fixed and flexible backbone sampling protocols.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent efforts to design de novo or redesign the sequence and structure of proteins using computational techniques have met with significant success. Most, if not all, of these computational methodologies attempt to model atomic-level interactions, and hence high-resolution structural characterization of the designed proteins is critical for evaluating the atomic-level accuracy of the underlying design force-fields. We previously used our computational protein design protocol RosettaDesign to completely redesign the sequence of the activation domain of human procarboxypeptidase A2. With 68% of the wild-type sequence changed, the designed protein, AYEdesign, is over 10 kcal/mol more stable than the wild-type protein. Here, we describe the high-resolution crystal structure and solution NMR structure of AYEdesign, which show that the experimentally determined backbone and side-chains conformations are effectively superimposable with the computational model at atomic resolution. To isolate the origins of the remarkable stabilization, we have designed and characterized a new series of procarboxypeptidase mutants that gain significant thermodynamic stability with a minimal number of mutations; one mutant gains more than 5 kcal/mol of stability over the wild-type protein with only four amino acid changes. We explore the relationship between force-field smoothing and conformational sampling by comparing the experimentally determined free energies of the overall design and these focused subsets of mutations to those predicted using modified force-fields, and both fixed and flexible backbone sampling protocols.
Alexander L Watters, Pritilekha Deka, Colin Corrent, David Callender, Gabriele Varani, Tobin Sosnick, David Baker
The highly cooperative folding of small naturally occurring proteins is likely the result of natural selection Journal Article
In: Cell, vol. 128, pp. 613-24, 2007, ISSN: 0092-8674.
@article{111,
title = {The highly cooperative folding of small naturally occurring proteins is likely the result of natural selection},
author = { Alexander L Watters and Pritilekha Deka and Colin Corrent and David Callender and Gabriele Varani and Tobin Sosnick and David Baker},
issn = {0092-8674},
year = {2007},
date = {2007-02-01},
journal = {Cell},
volume = {128},
pages = {613-24},
abstract = {To illuminate the evolutionary pressure acting on the folding free energy landscapes of naturally occurring proteins, we have systematically characterized the folding free energy landscape of Top7, a computationally designed protein lacking an evolutionary history. Stopped-flow kinetics, circular dichroism, and NMR experiments reveal that there are at least three distinct phases in the folding of Top7, that a nonnative conformation is stable at equilibrium, and that multiple fragments of Top7 are stable in isolation. These results indicate that the folding of Top7 is significantly less cooperative than the folding of similarly sized naturally occurring proteins, suggesting that the cooperative folding and smooth free energy landscapes observed for small naturally occurring proteins are not general properties of polypeptide chains that fold to unique stable structures but are instead a product of natural selection.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To illuminate the evolutionary pressure acting on the folding free energy landscapes of naturally occurring proteins, we have systematically characterized the folding free energy landscape of Top7, a computationally designed protein lacking an evolutionary history. Stopped-flow kinetics, circular dichroism, and NMR experiments reveal that there are at least three distinct phases in the folding of Top7, that a nonnative conformation is stable at equilibrium, and that multiple fragments of Top7 are stable in isolation. These results indicate that the folding of Top7 is significantly less cooperative than the folding of similarly sized naturally occurring proteins, suggesting that the cooperative folding and smooth free energy landscapes observed for small naturally occurring proteins are not general properties of polypeptide chains that fold to unique stable structures but are instead a product of natural selection.
Andrew M Wollacott, Alexandre Zanghellini, Paul Murphy, David Baker
Prediction of structures of multidomain proteins from structures of the individual domains Journal Article
In: Protein science, vol. 16, pp. 165-75, 2007, ISSN: 0961-8368.
@article{109,
title = {Prediction of structures of multidomain proteins from structures of the individual domains},
author = { Andrew M Wollacott and Alexandre Zanghellini and Paul Murphy and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/wollacott07A.pdf},
issn = {0961-8368},
year = {2007},
date = {2007-02-01},
journal = {Protein science},
volume = {16},
pages = {165-75},
abstract = {We describe the development of a method for assembling structures of multidomain proteins from structures of isolated domains. The method consists of an initial low-resolution search in which the conformational space of the domain linker is explored using the Rosetta de novo structure prediction method, followed by a high-resolution search in which all atoms are treated explicitly and backbone and side chain degrees of freedom are simultaneously optimized. The method recapitulates, often with very high accuracy, the structures of existing multidomain proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe the development of a method for assembling structures of multidomain proteins from structures of isolated domains. The method consists of an initial low-resolution search in which the conformational space of the domain linker is explored using the Rosetta de novo structure prediction method, followed by a high-resolution search in which all atoms are treated explicitly and backbone and side chain degrees of freedom are simultaneously optimized. The method recapitulates, often with very high accuracy, the structures of existing multidomain proteins.
Halyna R Shcherbata, Andriy S Yatsenko, Larissa Patterson, Vanita D Sood, Uri Nudel, David Yaffe, David Baker, Hannele Ruohola-Baker
Dissecting muscle and neuronal disorders in a Drosophila model of muscular dystrophy Journal Article
In: The EMBO journal, vol. 26, pp. 481-93, 2007, ISSN: 0261-4189.
@article{284,
title = {Dissecting muscle and neuronal disorders in a Drosophila model of muscular dystrophy},
author = { Halyna R Shcherbata and Andriy S Yatsenko and Larissa Patterson and Vanita D Sood and Uri Nudel and David Yaffe and David Baker and Hannele Ruohola-Baker},
issn = {0261-4189},
year = {2007},
date = {2007-01-01},
journal = {The EMBO journal},
volume = {26},
pages = {481-93},
abstract = {Perturbation in the Dystroglycan (Dg)-Dystrophin (Dys) complex results in muscular dystrophies and brain abnormalities in human. Here we report that Drosophila is an excellent genetically tractable model to study muscular dystrophies and neuronal abnormalities caused by defects in this complex. Using a fluorescence polarization assay, we show a high conservation in Dg-Dys interaction between human and Drosophila. Genetic and RNAi-induced perturbations of Dg and Dys in Drosophila cause cell polarity and muscular dystrophy phenotypes: decreased mobility, age-dependent muscle degeneration and defective photoreceptor path-finding. Dg and Dys are required in targeting glial cells and neurons for correct neuronal migration. Importantly, we now report that Dg interacts with insulin receptor and Nck/Dock SH2/SH3-adaptor molecule in photoreceptor path-finding. This is the first demonstration of a genetic interaction between Dg and InR.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Perturbation in the Dystroglycan (Dg)-Dystrophin (Dys) complex results in muscular dystrophies and brain abnormalities in human. Here we report that Drosophila is an excellent genetically tractable model to study muscular dystrophies and neuronal abnormalities caused by defects in this complex. Using a fluorescence polarization assay, we show a high conservation in Dg-Dys interaction between human and Drosophila. Genetic and RNAi-induced perturbations of Dg and Dys in Drosophila cause cell polarity and muscular dystrophy phenotypes: decreased mobility, age-dependent muscle degeneration and defective photoreceptor path-finding. Dg and Dys are required in targeting glial cells and neurons for correct neuronal migration. Importantly, we now report that Dg interacts with insulin receptor and Nck/Dock SH2/SH3-adaptor molecule in photoreceptor path-finding. This is the first demonstration of a genetic interaction between Dg and InR.
Michael Tress, Jianlin Cheng, Pierre Baldi, Keehyoung Joo, Jinwoo Lee, Joo-Hyun Seo, Jooyoung Lee, David Baker, Dylan Chivian, David Kim, Iakes Ezkurdia
Assessment of predictions submitted for the CASP7 domain prediction category Journal Article
In: Proteins, vol. 69 Suppl 8, pp. 137-51, 2007, ISSN: 1097-0134.
@article{286,
title = {Assessment of predictions submitted for the CASP7 domain prediction category},
author = { Michael Tress and Jianlin Cheng and Pierre Baldi and Keehyoung Joo and Jinwoo Lee and Joo-Hyun Seo and Jooyoung Lee and David Baker and Dylan Chivian and David Kim and Iakes Ezkurdia},
issn = {1097-0134},
year = {2007},
date = {2007-00-01},
journal = {Proteins},
volume = {69 Suppl 8},
pages = {137-51},
abstract = {This paper details the assessment process and evaluation results for the Critical Assessment of Protein Structure Prediction (CASP7) domain prediction category. Domain predictions were assessed using the Normalized Domain Overlap score introduced in CASP6 and the accuracy of prediction of domain break points. The results of the analysis clearly demonstrate that the best methods are able to make consistently reliable predictions when the target has a structural template, although they are less good when the domain break occurs in a region not covered by a template. The conditions of the experiment meant that it was impossible to draw any conclusions about domain prediction for free modeling targets and it was also difficult to draw many distinctions between the best groups. Two thirds of the targets submitted were single domains and hence regarded as easy to predict. Even those targets defined as having multiple domains always had at least one domain with a similar template structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper details the assessment process and evaluation results for the Critical Assessment of Protein Structure Prediction (CASP7) domain prediction category. Domain predictions were assessed using the Normalized Domain Overlap score introduced in CASP6 and the accuracy of prediction of domain break points. The results of the analysis clearly demonstrate that the best methods are able to make consistently reliable predictions when the target has a structural template, although they are less good when the domain break occurs in a region not covered by a template. The conditions of the experiment meant that it was impossible to draw any conclusions about domain prediction for free modeling targets and it was also difficult to draw many distinctions between the best groups. Two thirds of the targets submitted were single domains and hence regarded as easy to predict. Even those targets defined as having multiple domains always had at least one domain with a similar template structure.
James D R Knight, Bin Qian, David Baker, Rashmi Kothary
Conservation, variability and the modeling of active protein kinases Journal Article
In: PloS one, vol. 2, pp. e982, 2007, ISSN: 1932-6203.
@article{281,
title = {Conservation, variability and the modeling of active protein kinases},
author = { James D R Knight and Bin Qian and David Baker and Rashmi Kothary},
issn = {1932-6203},
year = {2007},
date = {2007-00-01},
journal = {PloS one},
volume = {2},
pages = {e982},
abstract = {The human proteome is rich with protein kinases, and this richness has made the kinase of crucial importance in initiating and maintaining cell behavior. Elucidating cell signaling networks and manipulating their components to understand and alter behavior require well designed inhibitors. These inhibitors are needed in culture to cause and study network perturbations, and the same compounds can be used as drugs to treat disease. Understanding the structural biology of protein kinases in detail, including their commonalities, differences and modes of substrate interaction, is necessary for designing high quality inhibitors that will be of true use for cell biology and disease therapy. To this end, we here report on a structural analysis of all available active-conformation protein kinases, discussing residue conservation, the novel features of such conservation, unique properties of atypical kinases and variability in the context of substrate binding. We also demonstrate how this information can be used for structure prediction. Our findings will be of use not only in understanding protein kinase function and evolution, but they highlight the flaws inherent in kinase drug design as commonly practiced and dictate an appropriate strategy for the sophisticated design of specific inhibitors for use in the laboratory and disease therapy.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The human proteome is rich with protein kinases, and this richness has made the kinase of crucial importance in initiating and maintaining cell behavior. Elucidating cell signaling networks and manipulating their components to understand and alter behavior require well designed inhibitors. These inhibitors are needed in culture to cause and study network perturbations, and the same compounds can be used as drugs to treat disease. Understanding the structural biology of protein kinases in detail, including their commonalities, differences and modes of substrate interaction, is necessary for designing high quality inhibitors that will be of true use for cell biology and disease therapy. To this end, we here report on a structural analysis of all available active-conformation protein kinases, discussing residue conservation, the novel features of such conservation, unique properties of atypical kinases and variability in the context of substrate binding. We also demonstrate how this information can be used for structure prediction. Our findings will be of use not only in understanding protein kinase function and evolution, but they highlight the flaws inherent in kinase drug design as commonly practiced and dictate an appropriate strategy for the sophisticated design of specific inhibitors for use in the laboratory and disease therapy.
Rhiju Das, Bin Qian, Srivatsan Raman, Robert Vernon, James Thompson, Philip Bradley, Sagar Khare, Michael D Tyka, Divya Bhat, Dylan Chivian, David E Kim, William H Sheffler, Lars Malmstr”om, Andrew M Wollacott, Chu Wang, Ingemar Andre, David Baker
Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home Journal Article
In: Proteins, vol. 69 Suppl 8, pp. 118-28, 2007, ISSN: 1097-0134.
@article{118,
title = {Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home},
author = { Rhiju Das and Bin Qian and Srivatsan Raman and Robert Vernon and James Thompson and Philip Bradley and Sagar Khare and Michael D Tyka and Divya Bhat and Dylan Chivian and David E Kim and William H Sheffler and Lars Malmstr"om and Andrew M Wollacott and Chu Wang and Ingemar Andre and David Baker},
issn = {1097-0134},
year = {2007},
date = {2007-00-01},
journal = {Proteins},
volume = {69 Suppl 8},
pages = {118-28},
abstract = {We describe predictions made using the Rosetta structure prediction methodology for both template-based modeling and free modeling categories in the Seventh Critical Assessment of Techniques for Protein Structure Prediction. For the first time, aggressive sampling and all-atom refinement could be carried out for the majority of targets, an advance enabled by the Rosetta@home distributed computing network. Template-based modeling predictions using an iterative refinement algorithm improved over the best existing templates for the majority of proteins with less than 200 residues. Free modeling methods gave near-atomic accuracy predictions for several targets under 100 residues from all secondary structure classes. These results indicate that refinement with an all-atom energy function, although computationally expensive, is a powerful method for obtaining accurate structure predictions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe predictions made using the Rosetta structure prediction methodology for both template-based modeling and free modeling categories in the Seventh Critical Assessment of Techniques for Protein Structure Prediction. For the first time, aggressive sampling and all-atom refinement could be carried out for the majority of targets, an advance enabled by the Rosetta@home distributed computing network. Template-based modeling predictions using an iterative refinement algorithm improved over the best existing templates for the majority of proteins with less than 200 residues. Free modeling methods gave near-atomic accuracy predictions for several targets under 100 residues from all secondary structure classes. These results indicate that refinement with an all-atom energy function, although computationally expensive, is a powerful method for obtaining accurate structure predictions.
2006
Philip Bradley, David Baker
Improved beta-protein structure prediction by multilevel optimization of nonlocal strand pairings and local backbone conformation Journal Article
In: Proteins, vol. 65, pp. 922-9, 2006, ISSN: 1097-0134.
@article{154,
title = {Improved beta-protein structure prediction by multilevel optimization of nonlocal strand pairings and local backbone conformation},
author = { Philip Bradley and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/bradley06A.pdf},
issn = {1097-0134},
year = {2006},
date = {2006-12-01},
journal = {Proteins},
volume = {65},
pages = {922-9},
abstract = {Proteins with complex, nonlocal beta-sheets are challenging for de novo structure prediction, due in part to the difficulty of efficiently sampling long-range strand pairings. We present a new, multilevel approach to beta-sheet structure prediction that circumvents this difficulty by reformulating structure generation in terms of a folding tree. Nonlocal connections in this tree allow us to explicitly sample alternative beta-strand pairings while simultaneously exploring local conformational space using backbone torsion-space moves. An iterative, energy-biased resampling strategy is used to explore the space of beta-strand pairings; we expect that such a strategy will be generally useful for searching large conformational spaces with a high degree of combinatorial complexity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Proteins with complex, nonlocal beta-sheets are challenging for de novo structure prediction, due in part to the difficulty of efficiently sampling long-range strand pairings. We present a new, multilevel approach to beta-sheet structure prediction that circumvents this difficulty by reformulating structure generation in terms of a folding tree. Nonlocal connections in this tree allow us to explicitly sample alternative beta-strand pairings while simultaneously exploring local conformational space using backbone torsion-space moves. An iterative, energy-biased resampling strategy is used to explore the space of beta-strand pairings; we expect that such a strategy will be generally useful for searching large conformational spaces with a high degree of combinatorial complexity.
Alexandre Zanghellini, Lin Jiang, Andrew M Wollacott, Gong Cheng, Jens Meiler, Eric A Althoff, Daniela R"othlisberger, David Baker
New algorithms and an in silico benchmark for computational enzyme design Journal Article
In: Protein science : a publication of the Protein Society, vol. 15, pp. 2785-94, 2006, ISSN: 0961-8368.
@article{166,
title = {New algorithms and an in silico benchmark for computational enzyme design},
author = { Alexandre Zanghellini and Lin Jiang and Andrew M Wollacott and Gong Cheng and Jens Meiler and Eric A Althoff and Daniela R"othlisberger and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/zanghellini06A.pdf},
issn = {0961-8368},
year = {2006},
date = {2006-12-01},
journal = {Protein science : a publication of the Protein Society},
volume = {15},
pages = {2785-94},
abstract = {The creation of novel enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Here we describe two new algorithms for enzyme design that employ hashing techniques to allow searching through large numbers of protein scaffolds for optimal catalytic site placement. We also describe an in silico benchmark, based on the recapitulation of the active sites of native enzymes, that allows rapid evaluation and testing of enzyme design methodologies. In the benchmark test, which consists of designing sites for each of 10 different chemical reactions in backbone scaffolds derived from 10 enzymes catalyzing the reactions, the new methods succeed in identifying the native site in the native scaffold and ranking it within the top five designs for six of the 10 reactions. The new methods can be directly applied to the design of new enzymes, and the benchmark provides a powerful in silico test for guiding improvements in computational enzyme design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The creation of novel enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Here we describe two new algorithms for enzyme design that employ hashing techniques to allow searching through large numbers of protein scaffolds for optimal catalytic site placement. We also describe an in silico benchmark, based on the recapitulation of the active sites of native enzymes, that allows rapid evaluation and testing of enzyme design methodologies. In the benchmark test, which consists of designing sites for each of 10 different chemical reactions in backbone scaffolds derived from 10 enzymes catalyzing the reactions, the new methods succeed in identifying the native site in the native scaffold and ranking it within the top five designs for six of the 10 reactions. The new methods can be directly applied to the design of new enzymes, and the benchmark provides a powerful in silico test for guiding improvements in computational enzyme design.
Jens Meiler, David Baker
ROSETTALIGAND: protein-small molecule docking with full side-chain flexibility Journal Article
In: Proteins, vol. 65, pp. 538-48, 2006, ISSN: 1097-0134.
@article{159,
title = {ROSETTALIGAND: protein-small molecule docking with full side-chain flexibility},
author = { Jens Meiler and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/meiler06A.pdf},
issn = {1097-0134},
year = {2006},
date = {2006-11-01},
journal = {Proteins},
volume = {65},
pages = {538-48},
abstract = {Protein-small molecule docking algorithms provide a means to model the structure of protein-small molecule complexes in structural detail and play an important role in drug development. In recent years the necessity of simulating protein side-chain flexibility for an accurate prediction of the protein-small molecule interfaces has become apparent, and an increasing number of docking algorithms probe different approaches to include protein flexibility. Here we describe a new method for docking small molecules into protein binding sites employing a Monte Carlo minimization procedure in which the rigid body position and orientation of the small molecule and the protein side-chain conformations are optimized simultaneously. The energy function comprises van der Waals (VDW) interactions, an implicit solvation model, an explicit orientation hydrogen bonding potential, and an electrostatics model. In an evaluation of the scoring function the computed energy correlated with experimental small molecule binding energy with a correlation coefficient of 0.63 across a diverse set of 229 protein- small molecule complexes. The docking method produced lowest energy models with a root mean square deviation (RMSD) smaller than 2 A in 71 out of 100 protein-small molecule crystal structure complexes (self-docking). In cross-docking calculations in which both protein side-chain and small molecule internal degrees of freedom were varied the lowest energy predictions had RMSDs less than 2 A in 14 of 20 test cases.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-small molecule docking algorithms provide a means to model the structure of protein-small molecule complexes in structural detail and play an important role in drug development. In recent years the necessity of simulating protein side-chain flexibility for an accurate prediction of the protein-small molecule interfaces has become apparent, and an increasing number of docking algorithms probe different approaches to include protein flexibility. Here we describe a new method for docking small molecules into protein binding sites employing a Monte Carlo minimization procedure in which the rigid body position and orientation of the small molecule and the protein side-chain conformations are optimized simultaneously. The energy function comprises van der Waals (VDW) interactions, an implicit solvation model, an explicit orientation hydrogen bonding potential, and an electrostatics model. In an evaluation of the scoring function the computed energy correlated with experimental small molecule binding energy with a correlation coefficient of 0.63 across a diverse set of 229 protein- small molecule complexes. The docking method produced lowest energy models with a root mean square deviation (RMSD) smaller than 2 A in 71 out of 100 protein-small molecule crystal structure complexes (self-docking). In cross-docking calculations in which both protein side-chain and small molecule internal degrees of freedom were varied the lowest energy predictions had RMSDs less than 2 A in 14 of 20 test cases.
Gautam Dantas, Alexander L Watters, Bradley M Lunde, Ziad M Eletr, Nancy G Isern, Toby Roseman, Jan Lipfert, Sebastian Doniach, Martin Tompa, Brian Kuhlman, Barry L Stoddard, Gabriele Varani, David Baker
In: Journal of molecular biology, vol. 362, pp. 1004-24, 2006, ISSN: 0022-2836.
@article{156,
title = {Mis-translation of a computationally designed protein yields an exceptionally stable homodimer: implications for protein engineering and evolution},
author = { Gautam Dantas and Alexander L Watters and Bradley M Lunde and Ziad M Eletr and Nancy G Isern and Toby Roseman and Jan Lipfert and Sebastian Doniach and Martin Tompa and Brian Kuhlman and Barry L Stoddard and Gabriele Varani and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/dantas06A.pdf},
issn = {0022-2836},
year = {2006},
date = {2006-10-01},
journal = {Journal of molecular biology},
volume = {362},
pages = {1004-24},
abstract = {We recently used computational protein design to create an extremely stable, globular protein, Top7, with a sequence and fold not observed previously in nature. Since Top7 was created in the absence of genetic selection, it provides a rare opportunity to investigate aspects of the cellular protein production and surveillance machinery that are subject to natural selection. Here we show that a portion of the Top7 protein corresponding to the final 49 C-terminal residues is efficiently mis-translated and accumulates at high levels in Escherichia coli. We used circular dichroism, size-exclusion chromatography, small-angle X-ray scattering, analytical ultra-centrifugation, and NMR spectroscopy to show that the resulting C-terminal fragment (CFr) protein adopts a compact, extremely stable, homo-dimeric structure. Based on the solution structure, we engineered an even more stable variant of CFr by disulfide-induced covalent circularisation that should be an excellent platform for design of novel functions. The accumulation of high levels of CFr exposes the high error rate of the protein translation machinery. The rarity of correspondingly stable fragments in natural proteins coupled with the observation that high quality ribosome binding sites are found to occur within E. coli protein-coding regions significantly less often than expected by random chance implies a stringent evolutionary pressure against protein sub-fragments that can independently fold into stable structures. The symmetric self-association between two identical mis-translated CFr sub-domains to generate an extremely stable structure parallels a mechanism for natural protein-fold evolution by modular recombination of protein sub-structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We recently used computational protein design to create an extremely stable, globular protein, Top7, with a sequence and fold not observed previously in nature. Since Top7 was created in the absence of genetic selection, it provides a rare opportunity to investigate aspects of the cellular protein production and surveillance machinery that are subject to natural selection. Here we show that a portion of the Top7 protein corresponding to the final 49 C-terminal residues is efficiently mis-translated and accumulates at high levels in Escherichia coli. We used circular dichroism, size-exclusion chromatography, small-angle X-ray scattering, analytical ultra-centrifugation, and NMR spectroscopy to show that the resulting C-terminal fragment (CFr) protein adopts a compact, extremely stable, homo-dimeric structure. Based on the solution structure, we engineered an even more stable variant of CFr by disulfide-induced covalent circularisation that should be an excellent platform for design of novel functions. The accumulation of high levels of CFr exposes the high error rate of the protein translation machinery. The rarity of correspondingly stable fragments in natural proteins coupled with the observation that high quality ribosome binding sites are found to occur within E. coli protein-coding regions significantly less often than expected by random chance implies a stringent evolutionary pressure against protein sub-fragments that can independently fold into stable structures. The symmetric self-association between two identical mis-translated CFr sub-domains to generate an extremely stable structure parallels a mechanism for natural protein-fold evolution by modular recombination of protein sub-structures.
Gil Goobes, Rivka Goobes, Ora Schueler-Furman, David Baker, Patrick S Stayton, Gary P Drobny
Folding of the C-terminal bacterial binding domain in statherin upon adsorption onto hydroxyapatite crystals Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 103, pp. 16083-8, 2006, ISSN: 0027-8424.
@article{292,
title = {Folding of the C-terminal bacterial binding domain in statherin upon adsorption onto hydroxyapatite crystals},
author = { Gil Goobes and Rivka Goobes and Ora Schueler-Furman and David Baker and Patrick S Stayton and Gary P Drobny},
issn = {0027-8424},
year = {2006},
date = {2006-10-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {103},
pages = {16083-8},
abstract = {Statherin is an enamel pellicle protein that inhibits hydroxyapatite (HAP) nucleation and growth, lubricates the enamel surface, and is recognized by oral bacteria in periodontal diseases. We report here from solid-state NMR measurements that the proteintextquoterights C-terminal region folds into an alpha-helix upon adsorption to HAP crystals. This region contains the binding sites for bacterial fimbriae that mediate bacterial cell adhesion to the surface of the tooth. The helical segment is shown through long-range distance measurements to fold back onto the intermediate region (residues Y16-P28) defining the global fold of the protein. Statherin, previously shown to be unstructured in solution, undergoes conformation selection on its substrate mineral surface. This surface-induced folding of statherin can be related to its functionality in inhibiting HAP crystal growth and can explain how oral pathogens selectively recognize HAP-bound statherin.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Statherin is an enamel pellicle protein that inhibits hydroxyapatite (HAP) nucleation and growth, lubricates the enamel surface, and is recognized by oral bacteria in periodontal diseases. We report here from solid-state NMR measurements that the proteintextquoterights C-terminal region folds into an alpha-helix upon adsorption to HAP crystals. This region contains the binding sites for bacterial fimbriae that mediate bacterial cell adhesion to the surface of the tooth. The helical segment is shown through long-range distance measurements to fold back onto the intermediate region (residues Y16-P28) defining the global fold of the protein. Statherin, previously shown to be unstructured in solution, undergoes conformation selection on its substrate mineral surface. This surface-induced folding of statherin can be related to its functionality in inhibiting HAP crystal growth and can explain how oral pathogens selectively recognize HAP-bound statherin.
Matthew L Baker, Wen Jiang, William J Wedemeyer, Frazer J Rixon, David Baker, Wah Chiu
Ab initio modeling of the herpesvirus VP26 core domain assessed by CryoEM density Journal Article
In: PLoS computational biology, vol. 2, pp. e146, 2006, ISSN: 1553-7358.
@article{291,
title = {Ab initio modeling of the herpesvirus VP26 core domain assessed by CryoEM density},
author = { Matthew L Baker and Wen Jiang and William J Wedemeyer and Frazer J Rixon and David Baker and Wah Chiu},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/baker06B.pdf},
issn = {1553-7358},
year = {2006},
date = {2006-10-01},
journal = {PLoS computational biology},
volume = {2},
pages = {e146},
abstract = {Efforts in structural biology have targeted the systematic determination of all protein structures through experimental determination or modeling. In recent years, 3-D electron cryomicroscopy (cryoEM) has assumed an increasingly important role in determining the structures of these large macromolecular assemblies to intermediate resolutions (6-10 A). While these structures provide a snapshot of the assembly and its components in well-defined functional states, the resolution limits the ability to build accurate structural models. In contrast, sequence-based modeling techniques are capable of producing relatively robust structural models for isolated proteins or domains. In this work, we developed and applied a hybrid modeling approach, utilizing cryoEM density and ab initio modeling to produce a structural model for the core domain of a herpesvirus structural protein, VP26. Specifically, this method, first tested on simulated data, utilizes the cryoEM density map as a geometrical constraint in identifying the most native-like models from a gallery of models generated by ab initio modeling. The resulting model for the core domain of VP26, based on the 8.5-A resolution herpes simplex virus type 1 (HSV-1) capsid cryoEM structure and mutational data, exhibited a novel fold. Additionally, the core domain of VP26 appeared to have a complementary interface to the known upper-domain structure of VP5, its cognate binding partner. While this new model provides for a better understanding of the assembly and interactions of VP26 in HSV-1, the approach itself may have broader applications in modeling the components of large macromolecular assemblies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Efforts in structural biology have targeted the systematic determination of all protein structures through experimental determination or modeling. In recent years, 3-D electron cryomicroscopy (cryoEM) has assumed an increasingly important role in determining the structures of these large macromolecular assemblies to intermediate resolutions (6-10 A). While these structures provide a snapshot of the assembly and its components in well-defined functional states, the resolution limits the ability to build accurate structural models. In contrast, sequence-based modeling techniques are capable of producing relatively robust structural models for isolated proteins or domains. In this work, we developed and applied a hybrid modeling approach, utilizing cryoEM density and ab initio modeling to produce a structural model for the core domain of a herpesvirus structural protein, VP26. Specifically, this method, first tested on simulated data, utilizes the cryoEM density map as a geometrical constraint in identifying the most native-like models from a gallery of models generated by ab initio modeling. The resulting model for the core domain of VP26, based on the 8.5-A resolution herpes simplex virus type 1 (HSV-1) capsid cryoEM structure and mutational data, exhibited a novel fold. Additionally, the core domain of VP26 appeared to have a complementary interface to the known upper-domain structure of VP5, its cognate binding partner. While this new model provides for a better understanding of the assembly and interactions of VP26 in HSV-1, the approach itself may have broader applications in modeling the components of large macromolecular assemblies.
Lukasz A Joachimiak, Tanja Kortemme, Barry L Stoddard, David Baker
Computational design of a new hydrogen bond network and at least a 300-fold specificity switch at a protein-protein interface Journal Article
In: Journal of molecular biology, vol. 361, pp. 195-208, 2006, ISSN: 0022-2836.
@article{158,
title = {Computational design of a new hydrogen bond network and at least a 300-fold specificity switch at a protein-protein interface},
author = { Lukasz A Joachimiak and Tanja Kortemme and Barry L Stoddard and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/joachimiak06A.pdf},
issn = {0022-2836},
year = {2006},
date = {2006-08-01},
journal = {Journal of molecular biology},
volume = {361},
pages = {195-208},
abstract = {The redesign of protein-protein interactions is a stringent test of our understanding of molecular recognition and specificity. Previously we engineered a modest specificity switch into the colicin E7 DNase-Im7 immunity protein complex by identifying mutations that are disruptive in the native complex, but can be compensated by mutations on the interacting partner. Here we extend the approach by systematically sampling alternate rigid body orientations to optimize the interactions in a binding mode specific manner. Using this protocol we designed a de novo hydrogen bond network at the DNase-immunity protein interface and confirmed the design with X-ray crystallographic analysis. Subsequent design of the second shell of interactions guided by insights from the crystal structure on tightly bound water molecules, conformational strain, and packing defects yielded new binding partners that exhibited specificities of at least 300-fold between the cognate and the non-cognate complexes. This multi-step approach should be applicable to the design of polar protein-protein interactions and contribute to the re-engineering of regulatory networks mediated by protein-protein interactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The redesign of protein-protein interactions is a stringent test of our understanding of molecular recognition and specificity. Previously we engineered a modest specificity switch into the colicin E7 DNase-Im7 immunity protein complex by identifying mutations that are disruptive in the native complex, but can be compensated by mutations on the interacting partner. Here we extend the approach by systematically sampling alternate rigid body orientations to optimize the interactions in a binding mode specific manner. Using this protocol we designed a de novo hydrogen bond network at the DNase-immunity protein interface and confirmed the design with X-ray crystallographic analysis. Subsequent design of the second shell of interactions guided by insights from the crystal structure on tightly bound water molecules, conformational strain, and packing defects yielded new binding partners that exhibited specificities of at least 300-fold between the cognate and the non-cognate complexes. This multi-step approach should be applicable to the design of polar protein-protein interactions and contribute to the re-engineering of regulatory networks mediated by protein-protein interactions.
Justin Ashworth, James J Havranek, Carlos M Duarte, Django Sussman, Raymond J Monnat, Barry L Stoddard, David Baker
Computational redesign of endonuclease DNA binding and cleavage specificity Journal Article
In: Nature, vol. 441, pp. 656-9, 2006, ISSN: 1476-4687.
@article{152,
title = {Computational redesign of endonuclease DNA binding and cleavage specificity},
author = { Justin Ashworth and James J Havranek and Carlos M Duarte and Django Sussman and Raymond J Monnat and Barry L Stoddard and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/ashworth06A.pdf},
issn = {1476-4687},
year = {2006},
date = {2006-06-01},
journal = {Nature},
volume = {441},
pages = {656-9},
abstract = {The reprogramming of DNA-binding specificity is an important challenge for computational protein design that tests current understanding of protein-DNA recognition, and has considerable practical relevance for biotechnology and medicine. Here we describe the computational redesign of the cleavage specificity of the intron-encoded homing endonuclease I-MsoI using a physically realistic atomic-level forcefield. Using an in silico screen, we identified single base-pair substitutions predicted to disrupt binding by the wild-type enzyme, and then optimized the identities and conformations of clusters of amino acids around each of these unfavourable substitutions using Monte Carlo sampling. A redesigned enzyme that was predicted to display altered target site specificity, while maintaining wild-type binding affinity, was experimentally characterized. The redesigned enzyme binds and cleaves the redesigned recognition site approximately 10,000 times more effectively than does the wild-type enzyme, with a level of target discrimination comparable to the original endonuclease. Determination of the structure of the redesigned nuclease-recognition site complex by X-ray crystallography confirms the accuracy of the computationally predicted interface. These results suggest that computational protein design methods can have an important role in the creation of novel highly specific endonucleases for gene therapy and other applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The reprogramming of DNA-binding specificity is an important challenge for computational protein design that tests current understanding of protein-DNA recognition, and has considerable practical relevance for biotechnology and medicine. Here we describe the computational redesign of the cleavage specificity of the intron-encoded homing endonuclease I-MsoI using a physically realistic atomic-level forcefield. Using an in silico screen, we identified single base-pair substitutions predicted to disrupt binding by the wild-type enzyme, and then optimized the identities and conformations of clusters of amino acids around each of these unfavourable substitutions using Monte Carlo sampling. A redesigned enzyme that was predicted to display altered target site specificity, while maintaining wild-type binding affinity, was experimentally characterized. The redesigned enzyme binds and cleaves the redesigned recognition site approximately 10,000 times more effectively than does the wild-type enzyme, with a level of target discrimination comparable to the original endonuclease. Determination of the structure of the redesigned nuclease-recognition site complex by X-ray crystallography confirms the accuracy of the computationally predicted interface. These results suggest that computational protein design methods can have an important role in the creation of novel highly specific endonucleases for gene therapy and other applications.
Elizabeth R Sprague, Chu Wang, David Baker, Pamela J Bjorkman
Crystal structure of the HSV-1 Fc receptor bound to Fc reveals a mechanism for antibody bipolar bridging Journal Article
In: PLoS biology, vol. 4, pp. e148, 2006, ISSN: 1545-7885.
@article{295,
title = {Crystal structure of the HSV-1 Fc receptor bound to Fc reveals a mechanism for antibody bipolar bridging},
author = { Elizabeth R Sprague and Chu Wang and David Baker and Pamela J Bjorkman},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/sprague06A.pdf},
issn = {1545-7885},
year = {2006},
date = {2006-06-01},
journal = {PLoS biology},
volume = {4},
pages = {e148},
abstract = {Herpes simplex virus type-1 expresses a heterodimeric Fc receptor, gE-gI, on the surfaces of virions and infected cells that binds the Fc region of host immunoglobulin G and is implicated in the cell-to-cell spread of virus. gE-gI binds immunoglobulin G at the basic pH of the cell surface and releases it at the acidic pH of lysosomes, consistent with a role in facilitating the degradation of antiviral antibodies. Here we identify the C-terminal domain of the gE ectodomain (CgE) as the minimal Fc-binding domain and present a 1.78-angstroms CgE structure. A 5-angstroms gE-gI/Fc crystal structure, which was independently verified by a theoretical prediction method, reveals that CgE binds Fc at the C(H)2-C(H)3 interface, the binding site for several mammalian and bacterial Fc-binding proteins. The structure identifies interface histidines that may confer pH-dependent binding and regions of CgE implicated in cell-to-cell spread of virus. The ternary organization of the gE-gI/Fc complex is compatible with antibody bipolar bridging, which can interfere with the antiviral immune response.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Herpes simplex virus type-1 expresses a heterodimeric Fc receptor, gE-gI, on the surfaces of virions and infected cells that binds the Fc region of host immunoglobulin G and is implicated in the cell-to-cell spread of virus. gE-gI binds immunoglobulin G at the basic pH of the cell surface and releases it at the acidic pH of lysosomes, consistent with a role in facilitating the degradation of antiviral antibodies. Here we identify the C-terminal domain of the gE ectodomain (CgE) as the minimal Fc-binding domain and present a 1.78-angstroms CgE structure. A 5-angstroms gE-gI/Fc crystal structure, which was independently verified by a theoretical prediction method, reveals that CgE binds Fc at the C(H)2-C(H)3 interface, the binding site for several mammalian and bacterial Fc-binding proteins. The structure identifies interface histidines that may confer pH-dependent binding and regions of CgE implicated in cell-to-cell spread of virus. The ternary organization of the gE-gI/Fc complex is compatible with antibody bipolar bridging, which can interfere with the antiviral immune response.
Vladimir Yarov-Yarovoy, David Baker, William A Catterall
Voltage sensor conformations in the open and closed states in ROSETTA structural models of K(+) channels Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 103, pp. 7292-7, 2006, ISSN: 0027-8424.
@article{164,
title = {Voltage sensor conformations in the open and closed states in ROSETTA structural models of K(+) channels},
author = { Vladimir Yarov-Yarovoy and David Baker and William A Catterall},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/yarov-yarovoy06A.pdf},
issn = {0027-8424},
year = {2006},
date = {2006-05-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {103},
pages = {7292-7},
abstract = {Voltage-gated ion channels control generation and propagation of action potentials in excitable cells. Significant progress has been made in understanding structure and function of the voltage-gated ion channels, highlighted by the high-resolution open-state structure of the voltage-gated potassium channel, K(v)1.2. However, because the structure of the closed state is unknown, the gating mechanism remains controversial. We adapted the rosetta membrane method to model the structures of the K(v)1.2 and KvAP channels using homology, de novo, and domain assembly methods and selected the most plausible models using a limited number of experimental constraints. Our model of K(v)1.2 in the open state is very similar in overall topology to the x-ray structure of this channel. Modeling of KvAP in the open state suggests that orientation of the voltage-sensing domain relative to the pore-forming domain is considerably different from the orientation in the K(v)1.2 open state and that the magnitude of the vertical movement of S4 is significantly greater. Structural modeling of closed state of K(v)1.2 suggests gating movement that can be viewed as a sum of two previously suggested mechanisms: translation (2-4 A) plus rotation ( approximately 180 degrees ) of the S4 segment as proposed in the original "sliding helix" or "helical screw" models coupled with a rolling motion of the S1-S3 segments around S4, similar to recent "transporter" models of gating. We propose a unified mechanism of voltage-dependent gating for K(v)1.2 and KvAP in which this major conformational change moves the gating charge across the electric field in an analogous way for both channels.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Voltage-gated ion channels control generation and propagation of action potentials in excitable cells. Significant progress has been made in understanding structure and function of the voltage-gated ion channels, highlighted by the high-resolution open-state structure of the voltage-gated potassium channel, K(v)1.2. However, because the structure of the closed state is unknown, the gating mechanism remains controversial. We adapted the rosetta membrane method to model the structures of the K(v)1.2 and KvAP channels using homology, de novo, and domain assembly methods and selected the most plausible models using a limited number of experimental constraints. Our model of K(v)1.2 in the open state is very similar in overall topology to the x-ray structure of this channel. Modeling of KvAP in the open state suggests that orientation of the voltage-sensing domain relative to the pore-forming domain is considerably different from the orientation in the K(v)1.2 open state and that the magnitude of the vertical movement of S4 is significantly greater. Structural modeling of closed state of K(v)1.2 suggests gating movement that can be viewed as a sum of two previously suggested mechanisms: translation (2-4 A) plus rotation ( approximately 180 degrees ) of the S4 segment as proposed in the original "sliding helix" or "helical screw" models coupled with a rolling motion of the S1-S3 segments around S4, similar to recent "transporter" models of gating. We propose a unified mechanism of voltage-dependent gating for K(v)1.2 and KvAP in which this major conformational change moves the gating charge across the electric field in an analogous way for both channels.
Amy E Palmer, Marta Giacomello, Tanja Kortemme, S Andrew Hires, Varda Lev-Ram, David Baker, Roger Y Tsien
Ca2+ indicators based on computationally redesigned calmodulin-peptide pairs Journal Article
In: Chemistry & biology, vol. 13, pp. 521-30, 2006, ISSN: 1074-5521.
@article{293,
title = {Ca2+ indicators based on computationally redesigned calmodulin-peptide pairs},
author = { Amy E Palmer and Marta Giacomello and Tanja Kortemme and S Andrew Hires and Varda Lev-Ram and David Baker and Roger Y Tsien},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/palmer06A.pdf},
issn = {1074-5521},
year = {2006},
date = {2006-05-01},
journal = {Chemistry & biology},
volume = {13},
pages = {521-30},
abstract = {The binding interface of calmodulin and a calmodulin binding peptide were reengineered by computationally designing complementary bumps and holes. This redesign led to the development of sensitive and specific pairs of mutant proteins used to sense Ca(2+) in a second generation of genetically encoded Ca(2+) indicators (cameleons). These cameleons are no longer perturbed by large excesses of native calmodulin, and they display Ca(2+) sensitivities tuned over a 100-fold range (0.6-160 microM). Incorporation of circularly permuted Venus in place of Citrine results in a 3- to 5-fold increase in the dynamic range. These redesigned cameleons show significant improvements over previous versions in the ability to monitor Ca(2+) in the cytoplasm as well as distinct subcellular localizations, such as the plasma membrane of neurons and the mitochondria.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The binding interface of calmodulin and a calmodulin binding peptide were reengineered by computationally designing complementary bumps and holes. This redesign led to the development of sensitive and specific pairs of mutant proteins used to sense Ca(2+) in a second generation of genetically encoded Ca(2+) indicators (cameleons). These cameleons are no longer perturbed by large excesses of native calmodulin, and they display Ca(2+) sensitivities tuned over a 100-fold range (0.6-160 microM). Incorporation of circularly permuted Venus in place of Citrine results in a 3- to 5-fold increase in the dynamic range. These redesigned cameleons show significant improvements over previous versions in the ability to monitor Ca(2+) in the cytoplasm as well as distinct subcellular localizations, such as the plasma membrane of neurons and the mitochondria.
Neil Dobson, Gautam Dantas, David Baker, Gabriele Varani
High-resolution structural validation of the computational redesign of human U1A protein Journal Article
In: Structure, vol. 14, pp. 847-56, 2006, ISSN: 0969-2126.
@article{157,
title = {High-resolution structural validation of the computational redesign of human U1A protein},
author = { Neil Dobson and Gautam Dantas and David Baker and Gabriele Varani},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/dobson06A.pdf},
issn = {0969-2126},
year = {2006},
date = {2006-05-01},
journal = {Structure},
volume = {14},
pages = {847-56},
abstract = {Achieving atomic-level resolution in the computational design of a protein structure remains a challenging problem despite recent progress. Rigorous experimental tests are needed to improve protein design algorithms, yet studies of the structure and dynamics of computationally designed proteins are very few. The NMR structure and backbone dynamics of a redesigned protein of 96 amino acids are compared here with the design target, human U1A protein. We demonstrate that the redesigned protein reproduces the target structure to within the uncertainty of the NMR coordinates, even as 65 out of 96 amino acids were simultaneously changed by purely computational methods. The dynamics of the backbone of the redesigned protein also mirror those of human U1A, suggesting that the protein design algorithm captures the shape of the potential energy landscape in addition to the local energy minimum.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Achieving atomic-level resolution in the computational design of a protein structure remains a challenging problem despite recent progress. Rigorous experimental tests are needed to improve protein design algorithms, yet studies of the structure and dynamics of computationally designed proteins are very few. The NMR structure and backbone dynamics of a redesigned protein of 96 amino acids are compared here with the design target, human U1A protein. We demonstrate that the redesigned protein reproduces the target structure to within the uncertainty of the NMR coordinates, even as 65 out of 96 amino acids were simultaneously changed by purely computational methods. The dynamics of the backbone of the redesigned protein also mirror those of human U1A, suggesting that the protein design algorithm captures the shape of the potential energy landscape in addition to the local energy minimum.
Kira M S Misura, Dylan Chivian, Carol A Rohl, David E Kim, David Baker
Physically realistic homology models built with ROSETTA can be more accurate than their templates Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 103, pp. 5361-6, 2006, ISSN: 0027-8424.
@article{160,
title = {Physically realistic homology models built with ROSETTA can be more accurate than their templates},
author = { Kira M S Misura and Dylan Chivian and Carol A Rohl and David E Kim and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/misura06A.pdf},
issn = {0027-8424},
year = {2006},
date = {2006-04-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {103},
pages = {5361-6},
abstract = {We have developed a method that combines the ROSETTA de novo protein folding and refinement protocol with distance constraints derived from homologous structures to build homology models that are frequently more accurate than their templates. We test this method by building complete-chain models for a benchmark set of 22 proteins, each with 1 or 2 candidate templates, for a total of 39 test cases. We use structure-based and sequence-based alignments for each of the test cases. All atoms, including hydrogens, are represented explicitly. The resulting models contain approximately the same number of atomic overlaps as experimentally determined crystal structures and maintain good stereochemistry. The most accurate models can be identified by their energies, and in 22 of 39 cases a model that is more accurate than the template over aligned regions is one of the 10 lowest-energy models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have developed a method that combines the ROSETTA de novo protein folding and refinement protocol with distance constraints derived from homologous structures to build homology models that are frequently more accurate than their templates. We test this method by building complete-chain models for a benchmark set of 22 proteins, each with 1 or 2 candidate templates, for a total of 39 test cases. We use structure-based and sequence-based alignments for each of the test cases. All atoms, including hydrogens, are represented explicitly. The resulting models contain approximately the same number of atomic overlaps as experimentally determined crystal structures and maintain good stereochemistry. The most accurate models can be identified by their energies, and in 22 of 39 cases a model that is more accurate than the template over aligned regions is one of the 10 lowest-energy models.
Vanita D Sood, David Baker
Recapitulation and design of protein binding peptide structures and sequences Journal Article
In: Journal of molecular biology, vol. 357, pp. 917-27, 2006, ISSN: 0022-2836.
@article{162,
title = {Recapitulation and design of protein binding peptide structures and sequences},
author = { Vanita D Sood and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/sood06A.pdf},
issn = {0022-2836},
year = {2006},
date = {2006-03-01},
journal = {Journal of molecular biology},
volume = {357},
pages = {917-27},
abstract = {An important objective of computational protein design is the generation of high affinity peptide inhibitors of protein-peptide interactions, both as a precursor to the development of therapeutics aimed at disrupting disease causing complexes, and as a tool to aid investigators in understanding the role of specific complexes in the cell. We have developed a computational approach to increase the affinity of a protein-peptide complex by designing N or C-terminal extensions which interact with the protein outside the canonical peptide binding pocket. In a first in silico test, we show that by simultaneously optimizing the sequence and structure of three to nine residue peptide extensions starting from short (1-6 residue) peptide stubs in the binding pocket of a peptide binding protein, the approach can recover both the conformations and the sequences of known binding peptides. Comparison with phage display and other experimental data suggests that the peptide extension approach recapitulates naturally occurring peptide binding specificity better than fixed backbone design, and that it should be useful for predicting peptide binding specificities from crystal structures. We then experimentally test the approach by designing extensions for p53 and dystroglycan-based peptides predicted to bind with increased affinity to the Mdm2 oncoprotein and to dystrophin, respectively. The measured increases in affinity are modest, revealing some limitations of the method. Based on these in silico and experimental results, we discuss future applications of the approach to the prediction and design of protein-peptide interactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
An important objective of computational protein design is the generation of high affinity peptide inhibitors of protein-peptide interactions, both as a precursor to the development of therapeutics aimed at disrupting disease causing complexes, and as a tool to aid investigators in understanding the role of specific complexes in the cell. We have developed a computational approach to increase the affinity of a protein-peptide complex by designing N or C-terminal extensions which interact with the protein outside the canonical peptide binding pocket. In a first in silico test, we show that by simultaneously optimizing the sequence and structure of three to nine residue peptide extensions starting from short (1-6 residue) peptide stubs in the binding pocket of a peptide binding protein, the approach can recover both the conformations and the sequences of known binding peptides. Comparison with phage display and other experimental data suggests that the peptide extension approach recapitulates naturally occurring peptide binding specificity better than fixed backbone design, and that it should be useful for predicting peptide binding specificities from crystal structures. We then experimentally test the approach by designing extensions for p53 and dystroglycan-based peptides predicted to bind with increased affinity to the Mdm2 oncoprotein and to dystrophin, respectively. The measured increases in affinity are modest, revealing some limitations of the method. Based on these in silico and experimental results, we discuss future applications of the approach to the prediction and design of protein-peptide interactions.
David Baker
Prediction and design of macromolecular structures and interactions Journal Article
In: Philosophical transactions of the Royal Society of London, vol. 361, pp. 459-63, 2006, ISSN: 0962-8436.
@article{153,
title = {Prediction and design of macromolecular structures and interactions},
author = { David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/baker06A.pdf},
issn = {0962-8436},
year = {2006},
date = {2006-03-01},
journal = {Philosophical transactions of the Royal Society of London},
volume = {361},
pages = {459-63},
abstract = {In this article, I summarize recent work from my group directed towards developing an improved model of intra and intermolecular interactions and applying this improved model to the prediction and design of macromolecular structures and interactions. Prediction and design applications can be of great biological interest in their own right, and also provide very stringent and objective tests which drive the improvement of the model and increases in fundamental understanding. I emphasize the results from the prediction and design tests that suggest progress is being made in high-resolution modelling, and that there is hope for reliably and accurately computing structural biology.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this article, I summarize recent work from my group directed towards developing an improved model of intra and intermolecular interactions and applying this improved model to the prediction and design of macromolecular structures and interactions. Prediction and design applications can be of great biological interest in their own right, and also provide very stringent and objective tests which drive the improvement of the model and increases in fundamental understanding. I emphasize the results from the prediction and design tests that suggest progress is being made in high-resolution modelling, and that there is hope for reliably and accurately computing structural biology.
Alexandre V Morozov, Kiril Tsemekhman, David Baker
Electron density redistribution accounts for half the cooperativity of alpha helix formation Journal Article
In: The journal of physical chemistry. B, vol. 110, pp. 4503-5, 2006, ISSN: 1520-6106.
@article{161,
title = {Electron density redistribution accounts for half the cooperativity of alpha helix formation},
author = { Alexandre V Morozov and Kiril Tsemekhman and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/morozov06A.pdf},
issn = {1520-6106},
year = {2006},
date = {2006-03-01},
journal = {The journal of physical chemistry. B},
volume = {110},
pages = {4503-5},
abstract = {The energy of alpha helix formation is well known to be highly cooperative, but the origin and relative importance of the contributions to helical cooperativity have been unclear. Here we separate the energy of helix formation into short range and long range components by using two series of helical dimers of variable length. In one dimer series two monomeric helices interact by forming hydrogen bonds, while in the other they are coupled only through long range, primarily electrostatic interactions. Using Density Functional Theory, we find that approximately half of the cooperativity of helix formation is due to electrostatic interactions between residues, while the other half is due to nonadditive many-body effects brought about by redistribution of electron density with helix length.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The energy of alpha helix formation is well known to be highly cooperative, but the origin and relative importance of the contributions to helical cooperativity have been unclear. Here we separate the energy of helix formation into short range and long range components by using two series of helical dimers of variable length. In one dimer series two monomeric helices interact by forming hydrogen bonds, while in the other they are coupled only through long range, primarily electrostatic interactions. Using Density Functional Theory, we find that approximately half of the cooperativity of helix formation is due to electrostatic interactions between residues, while the other half is due to nonadditive many-body effects brought about by redistribution of electron density with helix length.
Michael J Thompson, Stuart A Sievers, John Karanicolas, Magdalena I Ivanova, David Baker, David Eisenberg
The 3D profile method for identifying fibril-forming segments of proteins Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 103, pp. 4074-8, 2006, ISSN: 0027-8424.
@article{163,
title = {The 3D profile method for identifying fibril-forming segments of proteins},
author = { Michael J Thompson and Stuart A Sievers and John Karanicolas and Magdalena I Ivanova and David Baker and David Eisenberg},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/thompson06A.pdf},
issn = {0027-8424},
year = {2006},
date = {2006-03-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {103},
pages = {4074-8},
abstract = {Based on the crystal structure of the cross-beta spine formed by the peptide NNQQNY, we have developed a computational approach for identifying those segments of amyloidogenic proteins that themselves can form amyloid-like fibrils. The approach builds on experiments showing that hexapeptides are sufficient for forming amyloid-like fibrils. Each six-residue peptide of a protein of interest is mapped onto an ensemble of templates, or 3D profile, generated from the crystal structure of the peptide NNQQNY by small displacements of one of the two intermeshed beta-sheets relative to the other. The energy of each mapping of a sequence to the profile is evaluated by using ROSETTADESIGN, and the lowest energy match for a given peptide to the template library is taken as the putative prediction. If the energy of the putative prediction is lower than a threshold value, a prediction of fibril formation is made. This method can reach an accuracy of approximately 80% with a P value of approximately 10(-12) when a conservative energy threshold is used to separate peptides that form fibrils from those that do not. We see enrichment for positive predictions in a set of fibril-forming segments of amyloid proteins, and we illustrate the method with applications to proteins of interest in amyloid research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Based on the crystal structure of the cross-beta spine formed by the peptide NNQQNY, we have developed a computational approach for identifying those segments of amyloidogenic proteins that themselves can form amyloid-like fibrils. The approach builds on experiments showing that hexapeptides are sufficient for forming amyloid-like fibrils. Each six-residue peptide of a protein of interest is mapped onto an ensemble of templates, or 3D profile, generated from the crystal structure of the peptide NNQQNY by small displacements of one of the two intermeshed beta-sheets relative to the other. The energy of each mapping of a sequence to the profile is evaluated by using ROSETTADESIGN, and the lowest energy match for a given peptide to the template library is taken as the putative prediction. If the energy of the putative prediction is lower than a threshold value, a prediction of fibril formation is made. This method can reach an accuracy of approximately 80% with a P value of approximately 10(-12) when a conservative energy threshold is used to separate peptides that form fibrils from those that do not. We see enrichment for positive predictions in a set of fibril-forming segments of amyloid proteins, and we illustrate the method with applications to proteins of interest in amyloid research.
Vladimir Yarov-Yarovoy, Jack Schonbrun, David Baker
Multipass membrane protein structure prediction using Rosetta Journal Article
In: Proteins, vol. 62, pp. 1010-25, 2006, ISSN: 1097-0134.
@article{165,
title = {Multipass membrane protein structure prediction using Rosetta},
author = { Vladimir Yarov-Yarovoy and Jack Schonbrun and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/yarov-yarovoy06B.pdf},
issn = {1097-0134},
year = {2006},
date = {2006-03-01},
journal = {Proteins},
volume = {62},
pages = {1010-25},
abstract = {We describe the adaptation of the Rosetta de novo structure prediction method for prediction of helical transmembrane protein structures. The membrane environment is modeled by embedding the protein chain into a model membrane represented by parallel planes defining hydrophobic, interface, and polar membrane layers for each energy evaluation. The optimal embedding is determined by maximizing the exposure of surface hydrophobic residues within the membrane and minimizing hydrophobic exposure outside of the membrane. Protein conformations are built up using the Rosetta fragment assembly method and evaluated using a new membrane-specific version of the Rosetta low-resolution energy function in which residue-residue and residue-environment interactions are functions of the membrane layer in addition to amino acid identity, distance, and density. We find that lower energy and more native-like structures are achieved by sequential addition of helices to a growing chain, which may mimic some aspects of helical protein biogenesis after translocation, rather than folding the whole chain simultaneously as in the Rosetta soluble protein prediction method. In tests on 12 membrane proteins for which the structure is known, between 51 and 145 residues were predicted with root-mean-square deviation <4 A from the native structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe the adaptation of the Rosetta de novo structure prediction method for prediction of helical transmembrane protein structures. The membrane environment is modeled by embedding the protein chain into a model membrane represented by parallel planes defining hydrophobic, interface, and polar membrane layers for each energy evaluation. The optimal embedding is determined by maximizing the exposure of surface hydrophobic residues within the membrane and minimizing hydrophobic exposure outside of the membrane. Protein conformations are built up using the Rosetta fragment assembly method and evaluated using a new membrane-specific version of the Rosetta low-resolution energy function in which residue-residue and residue-environment interactions are functions of the membrane layer in addition to amino acid identity, distance, and density. We find that lower energy and more native-like structures are achieved by sequential addition of helices to a growing chain, which may mimic some aspects of helical protein biogenesis after translocation, rather than folding the whole chain simultaneously as in the Rosetta soluble protein prediction method. In tests on 12 membrane proteins for which the structure is known, between 51 and 145 residues were predicted with root-mean-square deviation <4 A from the native structure.
Tracy Arakaki, Isolde Le Trong, Eric Phizicky, Erin Quartley, George Detitta, Joseph Luft, Angela Lauricella, Lori Anderson, Oleksandr Kalyuzhniy, Elizabeth Worthey, Peter J Myler, David Kim, David Baker, Wim G J Hol, Ethan A Merritt
Structure of Lmaj006129AAA, a hypothetical protein from Leishmania major Journal Article
In: Acta crystallographica. Section F, Structural biology and crystallization communications, vol. 62, pp. 175-9, 2006, ISSN: 1744-3091.
@article{575,
title = {Structure of Lmaj006129AAA, a hypothetical protein from Leishmania major},
author = { Tracy Arakaki and Isolde Le Trong and Eric Phizicky and Erin Quartley and George Detitta and Joseph Luft and Angela Lauricella and Lori Anderson and Oleksandr Kalyuzhniy and Elizabeth Worthey and Peter J Myler and David Kim and David Baker and Wim G J Hol and Ethan A Merritt},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/structureoflmaj006129aaa_Baker2006.pdf},
doi = {10.1107/S1744309106005902},
issn = {1744-3091},
year = {2006},
date = {2006-03-01},
journal = {Acta crystallographica. Section F, Structural biology and crystallization communications},
volume = {62},
pages = {175-9},
abstract = {The gene product of structural genomics target Lmaj006129 from Leishmania major codes for a 164-residue protein of unknown function. When SeMet expression of the full-length gene product failed, several truncation variants were created with the aid of Ginzu, a domain-prediction method. 11 truncations were selected for expression, purification and crystallization based upon secondary-structure elements and disorder. The structure of one of these variants, Lmaj006129AAH, was solved by multiple-wavelength anomalous diffraction (MAD) using ELVES, an automatic protein crystal structure-determination system. This model was then successfully used as a molecular-replacement probe for the parent full-length target, Lmaj006129AAA. The final structure of Lmaj006129AAA was refined to an R value of 0.185 (Rfree = 0.229) at 1.60 A resolution. Structure and sequence comparisons based on Lmaj006129AAA suggest that proteins belonging to Pfam sequence families PF04543 and PF01878 may share a common ligand-binding motif.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The gene product of structural genomics target Lmaj006129 from Leishmania major codes for a 164-residue protein of unknown function. When SeMet expression of the full-length gene product failed, several truncation variants were created with the aid of Ginzu, a domain-prediction method. 11 truncations were selected for expression, purification and crystallization based upon secondary-structure elements and disorder. The structure of one of these variants, Lmaj006129AAH, was solved by multiple-wavelength anomalous diffraction (MAD) using ELVES, an automatic protein crystal structure-determination system. This model was then successfully used as a molecular-replacement probe for the parent full-length target, Lmaj006129AAA. The final structure of Lmaj006129AAA was refined to an R value of 0.185 (Rfree = 0.229) at 1.60 A resolution. Structure and sequence comparisons based on Lmaj006129AAA suggest that proteins belonging to Pfam sequence families PF04543 and PF01878 may share a common ligand-binding motif.
Gang Song, Greg A Lazar, Tanja Kortemme, Motomu Shimaoka, John R Desjarlais, David Baker, Timothy A Springer
In: The Journal of biological chemistry, vol. 281, pp. 5042-9, 2006, ISSN: 0021-9258.
@article{294,
title = {Rational design of intercellular adhesion molecule-1 (ICAM-1) variants for antagonizing integrin lymphocyte function-associated antigen-1-dependent adhesion},
author = { Gang Song and Greg A Lazar and Tanja Kortemme and Motomu Shimaoka and John R Desjarlais and David Baker and Timothy A Springer},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/song06A.pdf},
issn = {0021-9258},
year = {2006},
date = {2006-02-01},
journal = {The Journal of biological chemistry},
volume = {281},
pages = {5042-9},
abstract = {The interaction between integrin lymphocyte function-associated antigen-1 (LFA-1) and its ligand intercellular adhesion molecule-1 (ICAM-1) is critical in immunological and inflammatory reactions but, like other adhesive interactions, is of low affinity. Here, multiple rational design methods were used to engineer ICAM-1 mutants with enhanced affinity for LFA-1. Five amino acid substitutions 1) enhance the hydrophobicity and packing of residues surrounding Glu-34 of ICAM-1, which coordinates to a Mg2+ in the LFA-1 I domain, and 2) alter associations at the edges of the binding interface. The affinity of the most improved ICAM-1 mutant for intermediate- and high-affinity LFA-1 I domains was increased by 19-fold and 22-fold, respectively, relative to wild type. Moreover, potency was similarly enhanced for inhibition of LFA-1-dependent ligand binding and cell adhesion. Thus, rational design can be used to engineer novel adhesion molecules with high monomeric affinity; furthermore, the ICAM-1 mutant holds promise for targeting LFA-1-ICAM-1 interaction for biological studies and therapeutic purposes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The interaction between integrin lymphocyte function-associated antigen-1 (LFA-1) and its ligand intercellular adhesion molecule-1 (ICAM-1) is critical in immunological and inflammatory reactions but, like other adhesive interactions, is of low affinity. Here, multiple rational design methods were used to engineer ICAM-1 mutants with enhanced affinity for LFA-1. Five amino acid substitutions 1) enhance the hydrophobicity and packing of residues surrounding Glu-34 of ICAM-1, which coordinates to a Mg2+ in the LFA-1 I domain, and 2) alter associations at the edges of the binding interface. The affinity of the most improved ICAM-1 mutant for intermediate- and high-affinity LFA-1 I domains was increased by 19-fold and 22-fold, respectively, relative to wild type. Moreover, potency was similarly enhanced for inhibition of LFA-1-dependent ligand binding and cell adhesion. Thus, rational design can be used to engineer novel adhesion molecules with high monomeric affinity; furthermore, the ICAM-1 mutant holds promise for targeting LFA-1-ICAM-1 interaction for biological studies and therapeutic purposes.
Dylan Chivian, David Baker
Homology modeling using parametric alignment ensemble generation with consensus and energy-based model selection Journal Article
In: Nucleic acids research, vol. 34, pp. e112, 2006, ISSN: 1362-4962.
@article{155,
title = {Homology modeling using parametric alignment ensemble generation with consensus and energy-based model selection},
author = { Dylan Chivian and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/08/chivian06A.pdf},
issn = {1362-4962},
year = {2006},
date = {2006-00-01},
journal = {Nucleic acids research},
volume = {34},
pages = {e112},
abstract = {The accuracy of a homology model based on the structure of a distant relative or other topologically equivalent protein is primarily limited by the quality of the alignment. Here we describe a systematic approach for sequence-to-structure alignment, called textquoterightK*Synctextquoteright, in which alignments are generated by dynamic programming using a scoring function that combines information on many protein features, including a novel measure of how obligate a sequence region is to the protein fold. By systematically varying the weights on the different features that contribute to the alignment score, we generate very large ensembles of diverse alignments, each optimal under a particular constellation of weights. We investigate a variety of approaches to select the best models from the ensemble, including consensus of the alignments, a hydrophobic burial measure, low- and high-resolution energy functions, and combinations of these evaluation methods. The effect on model quality and selection resulting from loop modeling and backbone optimization is also studied. The performance of the method on a benchmark set is reported and shows the approach to be effective at both generating and selecting accurate alignments. The method serves as the foundation of the homology modeling module in the Robetta server.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The accuracy of a homology model based on the structure of a distant relative or other topologically equivalent protein is primarily limited by the quality of the alignment. Here we describe a systematic approach for sequence-to-structure alignment, called textquoterightK*Synctextquoteright, in which alignments are generated by dynamic programming using a scoring function that combines information on many protein features, including a novel measure of how obligate a sequence region is to the protein fold. By systematically varying the weights on the different features that contribute to the alignment score, we generate very large ensembles of diverse alignments, each optimal under a particular constellation of weights. We investigate a variety of approaches to select the best models from the ensemble, including consensus of the alignments, a hydrophobic burial measure, low- and high-resolution energy functions, and combinations of these evaluation methods. The effect on model quality and selection resulting from loop modeling and backbone optimization is also studied. The performance of the method on a benchmark set is reported and shows the approach to be effective at both generating and selecting accurate alignments. The method serves as the foundation of the homology modeling module in the Robetta server.
2005
D Borden Lacy, Henry C Lin, Roman A Melnyk, Ora Schueler-Furman, Laura Reither, Kristina Cunningham, David Baker, R John Collier
A model of anthrax toxin lethal factor bound to protective antigen Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 102, pp. 16409-14, 2005, ISSN: 0027-8424.
@article{299,
title = {A model of anthrax toxin lethal factor bound to protective antigen},
author = { D Borden Lacy and Henry C Lin and Roman A Melnyk and Ora Schueler-Furman and Laura Reither and Kristina Cunningham and David Baker and R John Collier},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/lacy05A.pdf},
issn = {0027-8424},
year = {2005},
date = {2005-11-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {102},
pages = {16409-14},
abstract = {Anthrax toxin is made up of three proteins: the edema factor (EF), lethal factor (LF) enzymes, and the multifunctional protective antigen (PA). Proteolytically activated PA heptamerizes, binds the EF/LF enzymes, and forms a pore that allows for EF/LF passage into host cells. Using directed mutagenesis, we identified three LF-PA contact points defined by a specific disulfide crosslink and two pairs of complementary charge-reversal mutations. These contact points were consistent with the lowest energy LF-PA complex found by using Rosetta protein-protein docking. These results illustrate how biochemical and computational methods can be combined to produce reliable models of large complexes. The model shows that EF and LF bind through a highly electrostatic interface, with their flexible N-terminal region positioned at the entrance of the heptameric PA pore and thus poised to initiate translocation in an N- to C-terminal direction.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Anthrax toxin is made up of three proteins: the edema factor (EF), lethal factor (LF) enzymes, and the multifunctional protective antigen (PA). Proteolytically activated PA heptamerizes, binds the EF/LF enzymes, and forms a pore that allows for EF/LF passage into host cells. Using directed mutagenesis, we identified three LF-PA contact points defined by a specific disulfide crosslink and two pairs of complementary charge-reversal mutations. These contact points were consistent with the lowest energy LF-PA complex found by using Rosetta protein-protein docking. These results illustrate how biochemical and computational methods can be combined to produce reliable models of large complexes. The model shows that EF and LF bind through a highly electrostatic interface, with their flexible N-terminal region positioned at the entrance of the heptameric PA pore and thus poised to initiate translocation in an N- to C-terminal direction.
Ora Schueler-Furman, Chu Wang, Phil Bradley, Kira Misura, David Baker
Progress in modeling of protein structures and interactions Journal Article
In: Science, vol. 310, pp. 638-42, 2005, ISSN: 1095-9203.
@article{94,
title = {Progress in modeling of protein structures and interactions},
author = { Ora Schueler-Furman and Chu Wang and Phil Bradley and Kira Misura and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/schueler-furman05B.pdf},
issn = {1095-9203},
year = {2005},
date = {2005-10-01},
journal = {Science},
volume = {310},
pages = {638-42},
abstract = {The prediction of the structures and interactions of biological macromolecules at the atomic level and the design of new structures and interactions are critical tests of our understanding of the interatomic interactions that underlie molecular biology. Equally important, the capability to accurately predict and design macromolecular structures and interactions would streamline the interpretation of genome sequence information and allow the creation of macromolecules with new and useful functions. This review summarizes recent progress in modeling that suggests that we are entering an era in which high-resolution prediction and design will make increasingly important contributions to biology and medicine.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The prediction of the structures and interactions of biological macromolecules at the atomic level and the design of new structures and interactions are critical tests of our understanding of the interatomic interactions that underlie molecular biology. Equally important, the capability to accurately predict and design macromolecular structures and interactions would streamline the interpretation of genome sequence information and allow the creation of macromolecules with new and useful functions. This review summarizes recent progress in modeling that suggests that we are entering an era in which high-resolution prediction and design will make increasingly important contributions to biology and medicine.
Philip Bradley, Kira M S Misura, David Baker
Toward high-resolution de novo structure prediction for small proteins Journal Article
In: Science, vol. 309, pp. 1868-71, 2005, ISSN: 1095-9203.
@article{104,
title = {Toward high-resolution de novo structure prediction for small proteins},
author = { Philip Bradley and Kira M S Misura and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bradley05B.pdf},
issn = {1095-9203},
year = {2005},
date = {2005-09-01},
journal = {Science},
volume = {309},
pages = {1868-71},
abstract = {The prediction of protein structure from amino acid sequence is a grand challenge of computational molecular biology. By using a combination of improved low- and high-resolution conformational sampling methods, improved atomically detailed potential functions that capture the jigsaw puzzle-like packing of protein cores, and high-performance computing, high-resolution structure prediction (<1.5 angstroms) can be achieved for small protein domains (<85 residues). The primary bottleneck to consistent high-resolution prediction appears to be conformational sampling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The prediction of protein structure from amino acid sequence is a grand challenge of computational molecular biology. By using a combination of improved low- and high-resolution conformational sampling methods, improved atomically detailed potential functions that capture the jigsaw puzzle-like packing of protein cores, and high-performance computing, high-resolution structure prediction (<1.5 angstroms) can be achieved for small protein domains (<85 residues). The primary bottleneck to consistent high-resolution prediction appears to be conformational sampling.
Ora Schueler-Furman, Chu Wang, David Baker
In: Proteins, vol. 60, pp. 187-94, 2005, ISSN: 1097-0134.
@article{95,
title = {Progress in protein-protein docking: atomic resolution predictions in the CAPRI experiment using RosettaDock with an improved treatment of side-chain flexibility},
author = { Ora Schueler-Furman and Chu Wang and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/schueler-rurman05A.pdf},
issn = {1097-0134},
year = {2005},
date = {2005-08-01},
journal = {Proteins},
volume = {60},
pages = {187-94},
abstract = {RosettaDock uses real-space Monte Carlo minimization (MCM) on both rigid-body and side-chain degrees of freedom to identify the lowest free energy docked arrangement of 2 protein structures. An improved version of the method that uses gradient-based minimization for off-rotamer side-chain optimization and includes information from unbound structures was used to create predictions for Rounds 4 and 5 of CAPRI. First, large numbers of independent MCM trajectories were carried out and the lowest free energy docked configurations identified. Second, new trajectories were started from these lowest energy structures to thoroughly sample the surrounding conformation space, and the lowest energy configurations were submitted as predictions. For all cases in which there were no significant backbone conformational changes, a small number of very low-energy configurations were identified in the first, global search and subsequently found to be close to the center of the basin of attraction in the free energy landscape in the second, local search. Following the release of the experimental coordinates, it was found that the centers of these free energy minima were remarkably close to the native structures in not only the rigid-body orientation but also the detailed conformations of the side-chains. Out of 8 targets, the lowest energy models had interface root-mean-square deviations (RMSDs) less than 1.1 A from the correct structures for 6 targets, and interface RMSDs less than 0.4 A for 3 targets. The predictions were top submissions to CAPRI for Targets 11, 12, 14, 15, and 19. The close correspondence of the lowest free energy structures found in our searches to the experimental structures suggests that our free energy function is a reasonable representation of the physical chemistry, and that the real space search with full side-chain flexibility to some extent solves the protein-protein docking problem in the absence of significant backbone conformational changes. On the other hand, the approach fails when there are significant backbone conformational changes as the steric complementarity of the 2 proteins cannot be modeled without incorporating backbone flexibility, and this is the major goal of our current work.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
RosettaDock uses real-space Monte Carlo minimization (MCM) on both rigid-body and side-chain degrees of freedom to identify the lowest free energy docked arrangement of 2 protein structures. An improved version of the method that uses gradient-based minimization for off-rotamer side-chain optimization and includes information from unbound structures was used to create predictions for Rounds 4 and 5 of CAPRI. First, large numbers of independent MCM trajectories were carried out and the lowest free energy docked configurations identified. Second, new trajectories were started from these lowest energy structures to thoroughly sample the surrounding conformation space, and the lowest energy configurations were submitted as predictions. For all cases in which there were no significant backbone conformational changes, a small number of very low-energy configurations were identified in the first, global search and subsequently found to be close to the center of the basin of attraction in the free energy landscape in the second, local search. Following the release of the experimental coordinates, it was found that the centers of these free energy minima were remarkably close to the native structures in not only the rigid-body orientation but also the detailed conformations of the side-chains. Out of 8 targets, the lowest energy models had interface root-mean-square deviations (RMSDs) less than 1.1 A from the correct structures for 6 targets, and interface RMSDs less than 0.4 A for 3 targets. The predictions were top submissions to CAPRI for Targets 11, 12, 14, 15, and 19. The close correspondence of the lowest free energy structures found in our searches to the experimental structures suggests that our free energy function is a reasonable representation of the physical chemistry, and that the real space search with full side-chain flexibility to some extent solves the protein-protein docking problem in the absence of significant backbone conformational changes. On the other hand, the approach fails when there are significant backbone conformational changes as the steric complementarity of the 2 proteins cannot be modeled without incorporating backbone flexibility, and this is the major goal of our current work.
Aaron Korkegian, Margaret E Black, David Baker, Barry L Stoddard
Computational thermostabilization of an enzyme Journal Article
In: Science, vol. 308, pp. 857-60, 2005, ISSN: 1095-9203.
@article{298,
title = {Computational thermostabilization of an enzyme},
author = { Aaron Korkegian and Margaret E Black and David Baker and Barry L Stoddard},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/korkegian05A.pdf},
issn = {1095-9203},
year = {2005},
date = {2005-05-01},
journal = {Science},
volume = {308},
pages = {857-60},
abstract = {Thermostabilizing an enzyme while maintaining its activity for industrial or biomedical applications can be difficult with traditional selection methods. We describe a rapid computational approach that identified three mutations within a model enzyme that produced a 10 degrees C increase in apparent melting temperature T(m) and a 30-fold increase in half-life at 50 degrees C, with no reduction in catalytic efficiency. The effects of the mutations were synergistic, giving an increase in excess of the sum of their individual effects. The redesigned enzyme induced an increased, temperature-dependent bacterial growth rate under conditions that required its activity, thereby coupling molecular and metabolic engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Thermostabilizing an enzyme while maintaining its activity for industrial or biomedical applications can be difficult with traditional selection methods. We describe a rapid computational approach that identified three mutations within a model enzyme that produced a 10 degrees C increase in apparent melting temperature T(m) and a 30-fold increase in half-life at 50 degrees C, with no reduction in catalytic efficiency. The effects of the mutations were synergistic, giving an increase in excess of the sum of their individual effects. The redesigned enzyme induced an increased, temperature-dependent bacterial growth rate under conditions that required its activity, thereby coupling molecular and metabolic engineering.
Chu Wang, Ora Schueler-Furman, David Baker
Improved side-chain modeling for protein-protein docking Journal Article
In: Protein science, vol. 14, pp. 1328-39, 2005, ISSN: 0961-8368.
@article{93,
title = {Improved side-chain modeling for protein-protein docking},
author = { Chu Wang and Ora Schueler-Furman and David Baker},
issn = {0961-8368},
year = {2005},
date = {2005-05-01},
journal = {Protein science},
volume = {14},
pages = {1328-39},
abstract = {Success in high-resolution protein-protein docking requires accurate modeling of side-chain conformations at the interface. Most current methods either leave side chains fixed in the conformations observed in the unbound protein structures or allow the side chains to sample a set of discrete rotamer conformations. Here we describe a rapid and efficient method for sampling off-rotamer side-chain conformations by torsion space minimization during protein-protein docking starting from discrete rotamer libraries supplemented with side-chain conformations taken from the unbound structures, and show that the new method improves side-chain modeling and increases the energetic discrimination between good and bad models. Analysis of the distribution of side-chain interaction energies within and between the two protein partners shows that the new method leads to more native-like distributions of interaction energies and that the neglect of side-chain entropy produces a small but measurable increase in the number of residues whose interaction energy cannot compensate for the entropic cost of side-chain freezing at the interface. The power of the method is highlighted by a number of predictions of unprecedented accuracy in the recent CAPRI (Critical Assessment of PRedicted Interactions) blind test of protein-protein docking methods.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Success in high-resolution protein-protein docking requires accurate modeling of side-chain conformations at the interface. Most current methods either leave side chains fixed in the conformations observed in the unbound protein structures or allow the side chains to sample a set of discrete rotamer conformations. Here we describe a rapid and efficient method for sampling off-rotamer side-chain conformations by torsion space minimization during protein-protein docking starting from discrete rotamer libraries supplemented with side-chain conformations taken from the unbound structures, and show that the new method improves side-chain modeling and increases the energetic discrimination between good and bad models. Analysis of the distribution of side-chain interaction energies within and between the two protein partners shows that the new method leads to more native-like distributions of interaction energies and that the neglect of side-chain entropy produces a small but measurable increase in the number of residues whose interaction energy cannot compensate for the entropic cost of side-chain freezing at the interface. The power of the method is highlighted by a number of predictions of unprecedented accuracy in the recent CAPRI (Critical Assessment of PRedicted Interactions) blind test of protein-protein docking methods.
Kira M S Misura, David Baker
Progress and challenges in high-resolution refinement of protein structure models Journal Article
In: Proteins, vol. 59, pp. 15-29, 2005, ISSN: 1097-0134.
@article{98,
title = {Progress and challenges in high-resolution refinement of protein structure models},
author = { Kira M S Misura and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/misura05A.pdf},
issn = {1097-0134},
year = {2005},
date = {2005-04-01},
journal = {Proteins},
volume = {59},
pages = {15-29},
abstract = {Achieving atomic level accuracy in de novo structure prediction presents a formidable challenge even in the context of protein models with correct topologies. High-resolution refinement is a fundamental test of force field accuracy and sampling methodology, and its limited success in both comparative modeling and de novo prediction contexts highlights the limitations of current approaches. We constructed four tests to identify bottlenecks in our current approach and to guide progress in this challenging area. The first three tests showed that idealized native structures are stable under our refinement simulation conditions and that the refinement protocol can significantly decrease the root mean square deviation (RMSD) of perturbed native structures. In the fourth test we applied the refinement protocol to de novo models and showed that accurate models could be identified based on their energies, and in several cases many of the buried side chains adopted native-like conformations. We also showed that the differences in backbone and side-chain conformations between the refined de novo models and the native structures are largely localized to loop regions and regions where the native structure has unusual features such as rare rotamers or atypical hydrogen bonding between beta-strands. The refined de novo models typically have higher energies than refined idealized native structures, indicating that sampling of local backbone conformations and side-chain packing arrangements in a condensed state is a primary obstacle.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Achieving atomic level accuracy in de novo structure prediction presents a formidable challenge even in the context of protein models with correct topologies. High-resolution refinement is a fundamental test of force field accuracy and sampling methodology, and its limited success in both comparative modeling and de novo prediction contexts highlights the limitations of current approaches. We constructed four tests to identify bottlenecks in our current approach and to guide progress in this challenging area. The first three tests showed that idealized native structures are stable under our refinement simulation conditions and that the refinement protocol can significantly decrease the root mean square deviation (RMSD) of perturbed native structures. In the fourth test we applied the refinement protocol to de novo models and showed that accurate models could be identified based on their energies, and in several cases many of the buried side chains adopted native-like conformations. We also showed that the differences in backbone and side-chain conformations between the refined de novo models and the native structures are largely localized to loop regions and regions where the native structure has unusual features such as rare rotamers or atypical hydrogen bonding between beta-strands. The refined de novo models typically have higher energies than refined idealized native structures, indicating that sampling of local backbone conformations and side-chain packing arrangements in a condensed state is a primary obstacle.
Jens Meiler, David Baker
The fumarate sensor DcuS: progress in rapid protein fold elucidation by combining protein structure prediction methods with NMR spectroscopy Journal Article
In: Journal of magnetic resonance, vol. 173, pp. 310-6, 2005, ISSN: 1090-7807.
@article{99,
title = {The fumarate sensor DcuS: progress in rapid protein fold elucidation by combining protein structure prediction methods with NMR spectroscopy},
author = { Jens Meiler and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/meiler05A.pdf},
issn = {1090-7807},
year = {2005},
date = {2005-04-01},
journal = {Journal of magnetic resonance},
volume = {173},
pages = {310-6},
abstract = {We illustrate how moderate resolution protein structures can be rapidly obtained by interlinking computational prediction methodologies with un- or partially assigned NMR data. To facilitate the application of our recently described method of ranking and subsequent refining alternative structural models using unassigned NMR data [Proc. Natl. Acad. Sci. USA 100 (2003) 15404] for such "structural genomics"-type experiments it is combined with protein models from several prediction techniques, enhanced to utilize partial assignments, and applied on a protein with an unknown structure and fold. From the original NMR spectra obtained for the 140 residue fumarate sensor DcuS, 1100 1H, 13C, and 15N chemical shift signals, 3000 1H-1H NOESY cross peak intensities, and 209 backbone residual dipolar couplings were extracted and used to rank models produced by de novo structure prediction and comparative modeling methods. The ranking proceeds in two steps: first, an optimal assignment of the NMR peaks to atoms is found for each model independently, and second, the models are ranked based on the consistency between the NMR data and the model assuming these optimal assignments. The low-resolution model selected using this ranking procedure had the correct overall fold and a global backbone RMSD of 6.0 angstrom, and was subsequently refined to 3.7 angstrom RMSD. With the incorporation of a small number of NOE and residual dipolar coupling constraints available very early in the traditional spectral assignment process, a model with an RMSD of 2.8 angstrom could rapidly be built. The ability to generate moderate resolution models within days of NMR data collection should facilitate large scale NMR structure determination efforts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We illustrate how moderate resolution protein structures can be rapidly obtained by interlinking computational prediction methodologies with un- or partially assigned NMR data. To facilitate the application of our recently described method of ranking and subsequent refining alternative structural models using unassigned NMR data [Proc. Natl. Acad. Sci. USA 100 (2003) 15404] for such "structural genomics"-type experiments it is combined with protein models from several prediction techniques, enhanced to utilize partial assignments, and applied on a protein with an unknown structure and fold. From the original NMR spectra obtained for the 140 residue fumarate sensor DcuS, 1100 1H, 13C, and 15N chemical shift signals, 3000 1H-1H NOESY cross peak intensities, and 209 backbone residual dipolar couplings were extracted and used to rank models produced by de novo structure prediction and comparative modeling methods. The ranking proceeds in two steps: first, an optimal assignment of the NMR peaks to atoms is found for each model independently, and second, the models are ranked based on the consistency between the NMR data and the model assuming these optimal assignments. The low-resolution model selected using this ranking procedure had the correct overall fold and a global backbone RMSD of 6.0 angstrom, and was subsequently refined to 3.7 angstrom RMSD. With the incorporation of a small number of NOE and residual dipolar coupling constraints available very early in the traditional spectral assignment process, a model with an RMSD of 2.8 angstrom could rapidly be built. The ability to generate moderate resolution models within days of NMR data collection should facilitate large scale NMR structure determination efforts.
Lin Jiang, Brian Kuhlman, Tanja Kortemme, David Baker
A "solvated rotamer" approach to modeling water-mediated hydrogen bonds at protein-protein interfaces Journal Article
In: Proteins, vol. 58, pp. 893-904, 2005, ISSN: 1097-0134.
@article{101,
title = {A "solvated rotamer" approach to modeling water-mediated hydrogen bonds at protein-protein interfaces},
author = { Lin Jiang and Brian Kuhlman and Tanja Kortemme and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/jiang05A.pdf},
issn = {1097-0134},
year = {2005},
date = {2005-03-01},
journal = {Proteins},
volume = {58},
pages = {893-904},
abstract = {Water-mediated hydrogen bonds play critical roles at protein-protein and protein-nucleic acid interfaces, and the interactions formed by discrete water molecules cannot be captured using continuum solvent models. We describe a simple model for the energetics of water-mediated hydrogen bonds, and show that, together with knowledge of the positions of buried water molecules observed in X-ray crystal structures, the model improves the prediction of free-energy changes upon mutation at protein-protein interfaces, and the recovery of native amino acid sequences in protein interface design calculations. We then describe a "solvated rotamer" approach to efficiently predict the positions of water molecules, at protein-protein interfaces and in monomeric proteins, that is compatible with widely used rotamer-based side-chain packing and protein design algorithms. Finally, we examine the extent to which the predicted water molecules can be used to improve prediction of amino acid identities and protein-protein interface stability, and discuss avenues for overcoming current limitations of the approach.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Water-mediated hydrogen bonds play critical roles at protein-protein and protein-nucleic acid interfaces, and the interactions formed by discrete water molecules cannot be captured using continuum solvent models. We describe a simple model for the energetics of water-mediated hydrogen bonds, and show that, together with knowledge of the positions of buried water molecules observed in X-ray crystal structures, the model improves the prediction of free-energy changes upon mutation at protein-protein interfaces, and the recovery of native amino acid sequences in protein interface design calculations. We then describe a "solvated rotamer" approach to efficiently predict the positions of water molecules, at protein-protein interfaces and in monomeric proteins, that is compatible with widely used rotamer-based side-chain packing and protein design algorithms. Finally, we examine the extent to which the predicted water molecules can be used to improve prediction of amino acid identities and protein-protein interface stability, and discuss avenues for overcoming current limitations of the approach.
Christopher T Saunders, David Baker
Recapitulation of protein family divergence using flexible backbone protein design Journal Article
In: Journal of molecular biology, vol. 346, pp. 631-44, 2005, ISSN: 0022-2836.
@article{96,
title = {Recapitulation of protein family divergence using flexible backbone protein design},
author = { Christopher T Saunders and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/saundersa05A.pdf},
issn = {0022-2836},
year = {2005},
date = {2005-02-01},
journal = {Journal of molecular biology},
volume = {346},
pages = {631-44},
abstract = {We use flexible backbone protein design to explore the sequence and structure neighborhoods of naturally occurring proteins. The method samples sequence and structure space in the vicinity of a known sequence and structure by alternately optimizing the sequence for a fixed protein backbone using rotamer based sequence search, and optimizing the backbone for a fixed amino acid sequence using atomic-resolution structure prediction. We find that such a flexible backbone design method better recapitulates protein family sequence variation than sequence optimization on fixed backbones or randomly perturbed backbone ensembles for ten diverse protein structures. For the SH3 domain, the backbone structure variation in the family is also better recapitulated than in randomly perturbed backbones. The potential application of this method as a model of protein family evolution is highlighted by a concerted transition to the amino acid sequence in the structural core of one SH3 domain starting from the backbone coordinates of an homologous structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We use flexible backbone protein design to explore the sequence and structure neighborhoods of naturally occurring proteins. The method samples sequence and structure space in the vicinity of a known sequence and structure by alternately optimizing the sequence for a fixed protein backbone using rotamer based sequence search, and optimizing the backbone for a fixed amino acid sequence using atomic-resolution structure prediction. We find that such a flexible backbone design method better recapitulates protein family sequence variation than sequence optimization on fixed backbones or randomly perturbed backbone ensembles for ten diverse protein structures. For the SH3 domain, the backbone structure variation in the family is also better recapitulated than in randomly perturbed backbones. The potential application of this method as a model of protein family evolution is highlighted by a concerted transition to the amino acid sequence in the structural core of one SH3 domain starting from the backbone coordinates of an homologous structure.
David E Kim, Dylan Chivian, Lars Malmstr"om, David Baker
Automated prediction of domain boundaries in CASP6 targets using Ginzu and RosettaDOM Journal Article
In: Proteins, vol. 61 Suppl 7, pp. 193-200, 2005, ISSN: 1097-0134.
@article{100,
title = {Automated prediction of domain boundaries in CASP6 targets using Ginzu and RosettaDOM},
author = { David E Kim and Dylan Chivian and Lars Malmstr"om and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/kim05A.pdf},
issn = {1097-0134},
year = {2005},
date = {2005-00-01},
journal = {Proteins},
volume = {61 Suppl 7},
pages = {193-200},
abstract = {Domain boundary prediction is an important step in both experimental and computational protein structure characterization. We have developed two fully automated domain parsing methods: the first, Ginzu, which we have described previously, utilizes information from homologous sequences and structures, while the second, RosettaDOM, which has not been described previously, uses only information in the query sequence. Ginzu iteratively assigns domains by homology to structures and sequence families using successively less confident methods. RosettaDOM uses the Rosetta de novo structure prediction method to build three-dimensional models, and then applies Taylortextquoterights structure based domain assignment method to parse the models into domains. Domain boundaries observed repeatedly in the models are predicted to be domain boundaries for the protein. Interestingly, RosettaDOM produced quite good domain predictions for proteins of a size typically considered to be beyond the reach of de novo structure prediction methods. For remote fold recognition targets and new folds, both Ginzu and RosettaDOM produced promising results, and in some cases where one method failed to detect the correct domain boundary, it was correctly identified by the other method. We describe here the successes and failures using both methods, and address the possibility of incorporating both protocols into an improved hybrid method.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Domain boundary prediction is an important step in both experimental and computational protein structure characterization. We have developed two fully automated domain parsing methods: the first, Ginzu, which we have described previously, utilizes information from homologous sequences and structures, while the second, RosettaDOM, which has not been described previously, uses only information in the query sequence. Ginzu iteratively assigns domains by homology to structures and sequence families using successively less confident methods. RosettaDOM uses the Rosetta de novo structure prediction method to build three-dimensional models, and then applies Taylortextquoterights structure based domain assignment method to parse the models into domains. Domain boundaries observed repeatedly in the models are predicted to be domain boundaries for the protein. Interestingly, RosettaDOM produced quite good domain predictions for proteins of a size typically considered to be beyond the reach of de novo structure prediction methods. For remote fold recognition targets and new folds, both Ginzu and RosettaDOM produced promising results, and in some cases where one method failed to detect the correct domain boundary, it was correctly identified by the other method. We describe here the successes and failures using both methods, and address the possibility of incorporating both protocols into an improved hybrid method.
Osvaldo Gra~na, David Baker, Robert M MacCallum, Jens Meiler, Marco Punta, Burkhard Rost, Michael L Tress, Alfonso Valencia
CASP6 assessment of contact prediction Journal Article
In: Proteins, vol. 61 Suppl 7, pp. 214-24, 2005, ISSN: 1097-0134.
@article{297,
title = {CASP6 assessment of contact prediction},
author = { Osvaldo Gra~na and David Baker and Robert M MacCallum and Jens Meiler and Marco Punta and Burkhard Rost and Michael L Tress and Alfonso Valencia},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/grana05A.pdf},
issn = {1097-0134},
year = {2005},
date = {2005-00-01},
journal = {Proteins},
volume = {61 Suppl 7},
pages = {214-24},
abstract = {Here we present the evaluation results of the Critical Assessment of Protein Structure Prediction (CASP6) contact prediction category. Contact prediction was assessed with standard measures well known in the field and the performance of specialist groups was evaluated alongside groups that submitted models with 3D coordinates. The evaluation was mainly focused on long range contact predictions for the set of new fold targets, although we analyzed predictions for all targets. Three groups with similar levels of accuracy and coverage performed a little better than the others. Comparisons of the predictions of the three best methods with those of CASP5/CAFASP3 suggested some improvement, although there were not enough targets in the comparisons to make this statistically significant.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Here we present the evaluation results of the Critical Assessment of Protein Structure Prediction (CASP6) contact prediction category. Contact prediction was assessed with standard measures well known in the field and the performance of specialist groups was evaluated alongside groups that submitted models with 3D coordinates. The evaluation was mainly focused on long range contact predictions for the set of new fold targets, although we analyzed predictions for all targets. Three groups with similar levels of accuracy and coverage performed a little better than the others. Comparisons of the predictions of the three best methods with those of CASP5/CAFASP3 suggested some improvement, although there were not enough targets in the comparisons to make this statistically significant.
Philip Bradley, Lars Malmstr"om, Bin Qian, Jack Schonbrun, Dylan Chivian, David E Kim, Jens Meiler, Kira M S Misura, David Baker
Free modeling with Rosetta in CASP6 Journal Article
In: Proteins, vol. 61 Suppl 7, pp. 128-34, 2005, ISSN: 1097-0134.
@article{105,
title = {Free modeling with Rosetta in CASP6},
author = { Philip Bradley and Lars Malmstr"om and Bin Qian and Jack Schonbrun and Dylan Chivian and David E Kim and Jens Meiler and Kira M S Misura and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/bradley05A.pdf},
issn = {1097-0134},
year = {2005},
date = {2005-00-01},
journal = {Proteins},
volume = {61 Suppl 7},
pages = {128-34},
abstract = {We describe Rosetta predictions in the Sixth Community-Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP), focusing on the free modeling category. Methods developed since CASP5 are described, and their application to selected targets is discussed. Highlights include improved performance on larger proteins (100-200 residues) and the prediction of a 70-residue alpha-beta protein to near-atomic resolution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe Rosetta predictions in the Sixth Community-Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP), focusing on the free modeling category. Methods developed since CASP5 are described, and their application to selected targets is discussed. Highlights include improved performance on larger proteins (100-200 residues) and the prediction of a 70-residue alpha-beta protein to near-atomic resolution.
Gong Cheng, Bin Qian, Ram Samudrala, David Baker
In: Nucleic acids research, vol. 33, pp. 5861-7, 2005, ISSN: 1362-4962.
@article{103,
title = {Improvement in protein functional site prediction by distinguishing structural and functional constraints on protein family evolution using computational design},
author = { Gong Cheng and Bin Qian and Ram Samudrala and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/cheng05A.pdf},
issn = {1362-4962},
year = {2005},
date = {2005-00-01},
journal = {Nucleic acids research},
volume = {33},
pages = {5861-7},
abstract = {The prediction of functional sites in newly solved protein structures is a challenge for computational structural biology. Most methods for approaching this problem use evolutionary conservation as the primary indicator of the location of functional sites. However, sequence conservation reflects not only evolutionary selection at functional sites to maintain protein function, but also selection throughout the protein to maintain the stability of the folded state. To disentangle sequence conservation due to protein functional constraints from sequence conservation due to protein structural constraints, we use all atom computational protein design methodology to predict sequence profiles expected under solely structural constraints, and to compute the free energy difference between the naturally occurring amino acid and the lowest free energy amino acid at each position. We show that functional sites are more likely than non-functional sites to have computed sequence profiles which differ significantly from the naturally occurring sequence profiles and to have residues with sub-optimal free energies, and that incorporation of these two measures improves sequence based prediction of protein functional sites. The combined sequence and structure based functional site prediction method has been implemented in a publicly available web server.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The prediction of functional sites in newly solved protein structures is a challenge for computational structural biology. Most methods for approaching this problem use evolutionary conservation as the primary indicator of the location of functional sites. However, sequence conservation reflects not only evolutionary selection at functional sites to maintain protein function, but also selection throughout the protein to maintain the stability of the folded state. To disentangle sequence conservation due to protein functional constraints from sequence conservation due to protein structural constraints, we use all atom computational protein design methodology to predict sequence profiles expected under solely structural constraints, and to compute the free energy difference between the naturally occurring amino acid and the lowest free energy amino acid at each position. We show that functional sites are more likely than non-functional sites to have computed sequence profiles which differ significantly from the naturally occurring sequence profiles and to have residues with sub-optimal free energies, and that incorporation of these two measures improves sequence based prediction of protein functional sites. The combined sequence and structure based functional site prediction method has been implemented in a publicly available web server.
Dylan Chivian, David E Kim, Lars Malmstr"om, Jack Schonbrun, Carol A Rohl, David Baker
Prediction of CASP6 structures using automated Robetta protocols Journal Article
In: Proteins, vol. 61 Suppl 7, pp. 157-66, 2005, ISSN: 1097-0134.
@article{102,
title = {Prediction of CASP6 structures using automated Robetta protocols},
author = { Dylan Chivian and David E Kim and Lars Malmstr"om and Jack Schonbrun and Carol A Rohl and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/07/chivian05A.pdf},
issn = {1097-0134},
year = {2005},
date = {2005-00-01},
journal = {Proteins},
volume = {61 Suppl 7},
pages = {157-66},
abstract = {The Robetta server and revised automatic protocols were used to predict structures for CASP6 targets. Robetta is a publicly available protein structure prediction server (http://robetta.bakerlab.org/ that uses the Rosetta de novo and homology modeling structure prediction methods. We incorporated some of the lessons learned in the CASP5 experiment into the server prior to participating in CASP6. We additionally tested new ideas that were amenable to full-automation with an eye toward improving the server. We find that the Robetta server shows the greatest promise for the more challenging targets. The most significant finding from CASP5, that automated protocols can be roughly comparable in ability with the better human-intervention predictors, is repeated here in CASP6.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Robetta server and revised automatic protocols were used to predict structures for CASP6 targets. Robetta is a publicly available protein structure prediction server (http://robetta.bakerlab.org/ that uses the Rosetta de novo and homology modeling structure prediction methods. We incorporated some of the lessons learned in the CASP5 experiment into the server prior to participating in CASP6. We additionally tested new ideas that were amenable to full-automation with an eye toward improving the server. We find that the Robetta server shows the greatest promise for the more challenging targets. The most significant finding from CASP5, that automated protocols can be roughly comparable in ability with the better human-intervention predictors, is repeated here in CASP6.
Alexandre V Morozov, James J Havranek, David Baker, Eric D Siggia
Protein-DNA binding specificity predictions with structural models Journal Article
In: Nucleic acids research, vol. 33, pp. 5781-98, 2005, ISSN: 1362-4962.
@article{97,
title = {Protein-DNA binding specificity predictions with structural models},
author = { Alexandre V Morozov and James J Havranek and David Baker and Eric D Siggia},
issn = {1362-4962},
year = {2005},
date = {2005-00-01},
journal = {Nucleic acids research},
volume = {33},
pages = {5781-98},
abstract = {Protein-DNA interactions play a central role in transcriptional regulation and other biological processes. Investigating the mechanism of binding affinity and specificity in protein-DNA complexes is thus an important goal. Here we develop a simple physical energy function, which uses electrostatics, solvation, hydrogen bonds and atom-packing terms to model direct readout and sequence-specific DNA conformational energy to model indirect readout of DNA sequence by the bound protein. The predictive capability of the model is tested against another model based only on the knowledge of the consensus sequence and the number of contacts between amino acids and DNA bases. Both models are used to carry out predictions of protein-DNA binding affinities which are then compared with experimental measurements. The nearly additive nature of protein-DNA interaction energies in our model allows us to construct position-specific weight matrices by computing base pair probabilities independently for each position in the binding site. Our approach is less data intensive than knowledge-based models of protein-DNA interactions, and is not limited to any specific family of transcription factors. However, native structures of protein-DNA complexes or their close homologs are required as input to the model. Use of homology modeling can significantly increase the extent of our approach, making it a useful tool for studying regulatory pathways in many organisms and cell types.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-DNA interactions play a central role in transcriptional regulation and other biological processes. Investigating the mechanism of binding affinity and specificity in protein-DNA complexes is thus an important goal. Here we develop a simple physical energy function, which uses electrostatics, solvation, hydrogen bonds and atom-packing terms to model direct readout and sequence-specific DNA conformational energy to model indirect readout of DNA sequence by the bound protein. The predictive capability of the model is tested against another model based only on the knowledge of the consensus sequence and the number of contacts between amino acids and DNA bases. Both models are used to carry out predictions of protein-DNA binding affinities which are then compared with experimental measurements. The nearly additive nature of protein-DNA interaction energies in our model allows us to construct position-specific weight matrices by computing base pair probabilities independently for each position in the binding site. Our approach is less data intensive than knowledge-based models of protein-DNA interactions, and is not limited to any specific family of transcription factors. However, native structures of protein-DNA complexes or their close homologs are required as input to the model. Use of homology modeling can significantly increase the extent of our approach, making it a useful tool for studying regulatory pathways in many organisms and cell types.
2004
James J Havranek, Carlos M Duarte, David Baker
A simple physical model for the prediction and design of protein-DNA interactions Journal Article
In: Journal of molecular biology, vol. 344, pp. 59-70, 2004, ISSN: 0022-2836.
@article{168,
title = {A simple physical model for the prediction and design of protein-DNA interactions},
author = { James J Havranek and Carlos M Duarte and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/havranek04A.pdf},
issn = {0022-2836},
year = {2004},
date = {2004-11-01},
journal = {Journal of molecular biology},
volume = {344},
pages = {59-70},
abstract = {Protein-DNA interactions are crucial for many biological processes. Attempts to model these interactions have generally taken the form of amino acid-base recognition codes or purely sequence-based profile methods, which depend on the availability of extensive sequence and structural information for specific structural families, neglect side-chain conformational variability, and lack generality beyond the structural family used to train the model. Here, we take advantage of recent advances in rotamer-based protein design and the large number of structurally characterized protein-DNA complexes to develop and parameterize a simple physical model for protein-DNA interactions. The model shows considerable promise for redesigning amino acids at protein-DNA interfaces, as design calculations recover the amino acid residue identities and conformations at these interfaces with accuracies comparable to sequence recovery in globular proteins. The model shows promise also for predicting DNA-binding specificity for fixed protein sequences: native DNA sequences are selected correctly from pools of competing DNA substrates; however, incorporation of backbone movement will likely be required to improve performance in homology modeling applications. Interestingly, optimization of zinc finger protein amino acid sequences for high-affinity binding to specific DNA sequences results in proteins with little or no predicted specificity, suggesting that naturally occurring DNA-binding proteins are optimized for specificity rather than affinity. When combined with algorithms that optimize specificity directly, the simple computational model developed here should be useful for the engineering of proteins with novel DNA-binding specificities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-DNA interactions are crucial for many biological processes. Attempts to model these interactions have generally taken the form of amino acid-base recognition codes or purely sequence-based profile methods, which depend on the availability of extensive sequence and structural information for specific structural families, neglect side-chain conformational variability, and lack generality beyond the structural family used to train the model. Here, we take advantage of recent advances in rotamer-based protein design and the large number of structurally characterized protein-DNA complexes to develop and parameterize a simple physical model for protein-DNA interactions. The model shows considerable promise for redesigning amino acids at protein-DNA interfaces, as design calculations recover the amino acid residue identities and conformations at these interfaces with accuracies comparable to sequence recovery in globular proteins. The model shows promise also for predicting DNA-binding specificity for fixed protein sequences: native DNA sequences are selected correctly from pools of competing DNA substrates; however, incorporation of backbone movement will likely be required to improve performance in homology modeling applications. Interestingly, optimization of zinc finger protein amino acid sequences for high-affinity binding to specific DNA sequences results in proteins with little or no predicted specificity, suggesting that naturally occurring DNA-binding proteins are optimized for specificity rather than affinity. When combined with algorithms that optimize specificity directly, the simple computational model developed here should be useful for the engineering of proteins with novel DNA-binding specificities.
Bin Qian, Angel R Ortiz, David Baker
Improvement of comparative model accuracy by free-energy optimization along principal components of natural structural variation Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 101, pp. 15346-51, 2004, ISSN: 0027-8424.
@article{175,
title = {Improvement of comparative model accuracy by free-energy optimization along principal components of natural structural variation},
author = { Bin Qian and Angel R Ortiz and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/qian04A.pdf},
issn = {0027-8424},
year = {2004},
date = {2004-10-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {101},
pages = {15346-51},
abstract = {Accurate high-resolution refinement of protein structure models is a formidable challenge because of the delicate balance of forces in the native state, the difficulty in sampling the very large number of alternative tightly packed conformations, and the inaccuracies in current force fields. Indeed, energy-based refinement of comparative models generally leads to degradation rather than improvement in model quality, and, hence, most current comparative modeling procedures omit physically based refinement. However, despite their inaccuracies, current force fields do contain information that is orthogonal to the evolutionary information on which comparative models are based, and, hence, refinement might be able to improve comparative models if the space that is sampled is restricted sufficiently so that false attractors are avoided. Here, we use the principal components of the variation of backbone structures within a homologous family to define a small number of evolutionarily favored sampling directions and show that model quality can be improved by energy-based optimization along these directions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Accurate high-resolution refinement of protein structure models is a formidable challenge because of the delicate balance of forces in the native state, the difficulty in sampling the very large number of alternative tightly packed conformations, and the inaccuracies in current force fields. Indeed, energy-based refinement of comparative models generally leads to degradation rather than improvement in model quality, and, hence, most current comparative modeling procedures omit physically based refinement. However, despite their inaccuracies, current force fields do contain information that is orthogonal to the evolutionary information on which comparative models are based, and, hence, refinement might be able to improve comparative models if the space that is sampled is restricted sufficiently so that false attractors are avoided. Here, we use the principal components of the variation of backbone structures within a homologous family to define a small number of evolutionarily favored sampling directions and show that model quality can be improved by energy-based optimization along these directions.
Kira M S Misura, Alexandre V Morozov, David Baker
Analysis of anisotropic side-chain packing in proteins and application to high-resolution structure prediction Journal Article
In: Journal of molecular biology, vol. 342, pp. 651-64, 2004, ISSN: 0022-2836.
@article{173,
title = {Analysis of anisotropic side-chain packing in proteins and application to high-resolution structure prediction},
author = { Kira M S Misura and Alexandre V Morozov and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/misura04A.pdf},
issn = {0022-2836},
year = {2004},
date = {2004-09-01},
journal = {Journal of molecular biology},
volume = {342},
pages = {651-64},
abstract = {pi-pi, Cation-pi, and hydrophobic packing interactions contribute specificity to protein folding and stability to the native state. As a step towards developing improved models of these interactions in proteins, we compare the side-chain packing arrangements in native proteins to those found in compact decoys produced by the Rosetta de novo structure prediction method. We find enrichments in the native distributions for T-shaped and parallel offset arrangements of aromatic residue pairs, in parallel stacked arrangements of cation-aromatic pairs, in parallel stacked pairs involving proline residues, and in parallel offset arrangements for aliphatic residue pairs. We then investigate the extent to which the distinctive features of native packing can be explained using Lennard-Jones and electrostatics models. Finally, we derive orientation-dependent pi-pi, cation-pi and hydrophobic interaction potentials based on the differences between the native and compact decoy distributions and investigate their efficacy for high-resolution protein structure prediction. Surprisingly, the orientation-dependent potential derived from the packing arrangements of aliphatic side-chain pairs distinguishes the native structure from compact decoys better than the orientation-dependent potentials describing pi-pi and cation-pi interactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
pi-pi, Cation-pi, and hydrophobic packing interactions contribute specificity to protein folding and stability to the native state. As a step towards developing improved models of these interactions in proteins, we compare the side-chain packing arrangements in native proteins to those found in compact decoys produced by the Rosetta de novo structure prediction method. We find enrichments in the native distributions for T-shaped and parallel offset arrangements of aromatic residue pairs, in parallel stacked arrangements of cation-aromatic pairs, in parallel stacked pairs involving proline residues, and in parallel offset arrangements for aliphatic residue pairs. We then investigate the extent to which the distinctive features of native packing can be explained using Lennard-Jones and electrostatics models. Finally, we derive orientation-dependent pi-pi, cation-pi and hydrophobic interaction potentials based on the differences between the native and compact decoy distributions and investigate their efficacy for high-resolution protein structure prediction. Surprisingly, the orientation-dependent potential derived from the packing arrangements of aliphatic side-chain pairs distinguishes the native structure from compact decoys better than the orientation-dependent potentials describing pi-pi and cation-pi interactions.
David E Kim, Dylan Chivian, David Baker
Protein structure prediction and analysis using the Robetta server Journal Article
In: Nucleic acids research, vol. 32, pp. W526-31, 2004, ISSN: 1362-4962.
@article{169,
title = {Protein structure prediction and analysis using the Robetta server},
author = { David E Kim and Dylan Chivian and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kim04A.pdf},
issn = {1362-4962},
year = {2004},
date = {2004-07-01},
journal = {Nucleic acids research},
volume = {32},
pages = {W526-31},
abstract = {The Robetta server (http://robetta.bakerlab.org) provides automated tools for protein structure prediction and analysis. For structure prediction, sequences submitted to the server are parsed into putative domains and structural models are generated using either comparative modeling or de novo structure prediction methods. If a confident match to a protein of known structure is found using BLAST, PSI-BLAST, FFAS03 or 3D-Jury, it is used as a template for comparative modeling. If no match is found, structure predictions are made using the de novo Rosetta fragment insertion method. Experimental nuclear magnetic resonance (NMR) constraints data can also be submitted with a query sequence for RosettaNMR de novo structure determination. Other current capabilities include the prediction of the effects of mutations on protein-protein interactions using computational interface alanine scanning. The Rosetta protein design and protein-protein docking methodologies will soon be available through the server as well.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Robetta server (http://robetta.bakerlab.org) provides automated tools for protein structure prediction and analysis. For structure prediction, sequences submitted to the server are parsed into putative domains and structural models are generated using either comparative modeling or de novo structure prediction methods. If a confident match to a protein of known structure is found using BLAST, PSI-BLAST, FFAS03 or 3D-Jury, it is used as a template for comparative modeling. If no match is found, structure predictions are made using the de novo Rosetta fragment insertion method. Experimental nuclear magnetic resonance (NMR) constraints data can also be submitted with a query sequence for RosettaNMR de novo structure determination. Other current capabilities include the prediction of the effects of mutations on protein-protein interactions using computational interface alanine scanning. The Rosetta protein design and protein-protein docking methodologies will soon be available through the server as well.
Maximilian Schlosshauer, David Baker
Realistic protein-protein association rates from a simple diffusional model neglecting long-range interactions, free energy barriers, and landscape ruggedness Journal Article
In: Protein science, vol. 13, pp. 1660-9, 2004, ISSN: 0961-8368.
@article{179,
title = {Realistic protein-protein association rates from a simple diffusional model neglecting long-range interactions, free energy barriers, and landscape ruggedness},
author = { Maximilian Schlosshauer and David Baker},
issn = {0961-8368},
year = {2004},
date = {2004-06-01},
journal = {Protein science},
volume = {13},
pages = {1660-9},
abstract = {We develop a simple but rigorous model of protein-protein association kinetics based on diffusional association on free energy landscapes obtained by sampling configurations within and surrounding the native complex binding funnels. Guided by results obtained on exactly solvable model problems, we transform the problem of diffusion in a potential into free diffusion in the presence of an absorbing zone spanning the entrance to the binding funnel. The free diffusion problem is solved using a recently derived analytic expression for the rate of association of asymmetrically oriented molecules. Despite the required high steric specificity and the absence of long-range attractive interactions, the computed rates are typically on the order of 10(4)-10(6) M(-1) sec(-1), several orders of magnitude higher than rates obtained using a purely probabilistic model in which the association rate for free diffusion of uniformly reactive molecules is multiplied by the probability of a correct alignment of the two partners in a random collision. As the association rates of many protein-protein complexes are also in the 10(5)-10(6) M(-1) sec(-1) range, our results suggest that free energy barriers arising from desolvation and/or side-chain freezing during complex formation or increased ruggedness within the binding funnel, which are completely neglected in our simple diffusional model, do not contribute significantly to the dynamics of protein-protein association. The transparent physical interpretation of our approach that computes association rates directly from the size and geometry of protein-protein binding funnels makes it a useful complement to Brownian dynamics simulations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We develop a simple but rigorous model of protein-protein association kinetics based on diffusional association on free energy landscapes obtained by sampling configurations within and surrounding the native complex binding funnels. Guided by results obtained on exactly solvable model problems, we transform the problem of diffusion in a potential into free diffusion in the presence of an absorbing zone spanning the entrance to the binding funnel. The free diffusion problem is solved using a recently derived analytic expression for the rate of association of asymmetrically oriented molecules. Despite the required high steric specificity and the absence of long-range attractive interactions, the computed rates are typically on the order of 10(4)-10(6) M(-1) sec(-1), several orders of magnitude higher than rates obtained using a purely probabilistic model in which the association rate for free diffusion of uniformly reactive molecules is multiplied by the probability of a correct alignment of the two partners in a random collision. As the association rates of many protein-protein complexes are also in the 10(5)-10(6) M(-1) sec(-1) range, our results suggest that free energy barriers arising from desolvation and/or side-chain freezing during complex formation or increased ruggedness within the binding funnel, which are completely neglected in our simple diffusional model, do not contribute significantly to the dynamics of protein-protein association. The transparent physical interpretation of our approach that computes association rates directly from the size and geometry of protein-protein binding funnels makes it a useful complement to Brownian dynamics simulations.
Alexandre V Morozov, Tanja Kortemme, Kiril Tsemekhman, David Baker
Close agreement between the orientation dependence of hydrogen bonds observed in protein structures and quantum mechanical calculations Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 101, pp. 6946-51, 2004, ISSN: 0027-8424.
@article{174,
title = {Close agreement between the orientation dependence of hydrogen bonds observed in protein structures and quantum mechanical calculations},
author = { Alexandre V Morozov and Tanja Kortemme and Kiril Tsemekhman and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/morozov04A.pdf},
issn = {0027-8424},
year = {2004},
date = {2004-05-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {101},
pages = {6946-51},
abstract = {Hydrogen bonding is a key contributor to the exquisite specificity of the interactions within and between biological macromolecules, and hence accurate modeling of such interactions requires an accurate description of hydrogen bonding energetics. Here we investigate the orientation and distance dependence of hydrogen bonding energetics by combining two quite disparate but complementary approaches: quantum mechanical electronic structure calculations and protein structural analysis. We find a remarkable agreement between the energy landscapes obtained from the electronic structure calculations and the distributions of hydrogen bond geometries observed in protein structures. In contrast, molecular mechanics force fields commonly used for biomolecular simulations do not consistently exhibit close correspondence to either quantum mechanical calculations or experimentally observed hydrogen bonding geometries. These results suggest a route to improved energy functions for biological macromolecules that combines the generality of quantum mechanical electronic structure calculations with the accurate context dependence implicit in protein structural analysis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hydrogen bonding is a key contributor to the exquisite specificity of the interactions within and between biological macromolecules, and hence accurate modeling of such interactions requires an accurate description of hydrogen bonding energetics. Here we investigate the orientation and distance dependence of hydrogen bonding energetics by combining two quite disparate but complementary approaches: quantum mechanical electronic structure calculations and protein structural analysis. We find a remarkable agreement between the energy landscapes obtained from the electronic structure calculations and the distributions of hydrogen bond geometries observed in protein structures. In contrast, molecular mechanics force fields commonly used for biomolecular simulations do not consistently exhibit close correspondence to either quantum mechanical calculations or experimentally observed hydrogen bonding geometries. These results suggest a route to improved energy functions for biological macromolecules that combines the generality of quantum mechanical electronic structure calculations with the accurate context dependence implicit in protein structural analysis.
Carol A Rohl, Charlie E M Strauss, Dylan Chivian, David Baker
Modeling structurally variable regions in homologous proteins with rosetta Journal Article
In: Proteins, vol. 55, pp. 656-77, 2004, ISSN: 1097-0134.
@article{177,
title = {Modeling structurally variable regions in homologous proteins with rosetta},
author = { Carol A Rohl and Charlie E M Strauss and Dylan Chivian and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/rohl04A.pdf},
issn = {1097-0134},
year = {2004},
date = {2004-05-01},
journal = {Proteins},
volume = {55},
pages = {656-77},
abstract = {A major limitation of current comparative modeling methods is the accuracy with which regions that are structurally divergent from homologues of known structure can be modeled. Because structural differences between homologous proteins are responsible for variations in protein function and specificity, the ability to model these differences has important functional consequences. Although existing methods can provide reasonably accurate models of short loop regions, modeling longer structurally divergent regions is an unsolved problem. Here we describe a method based on the de novo structure prediction algorithm, Rosetta, for predicting conformations of structurally divergent regions in comparative models. Initial conformations for short segments are selected from the protein structure database, whereas longer segments are built up by using three- and nine-residue fragments drawn from the database and combined by using the Rosetta algorithm. A gap closure term in the potential in combination with modified Newtontextquoterights method for gradient descent minimization is used to ensure continuity of the peptide backbone. Conformations of variable regions are refined in the context of a fixed template structure using Monte Carlo minimization together with rapid repacking of side-chains to iteratively optimize backbone torsion angles and side-chain rotamers. For short loops, mean accuracies of 0.69, 1.45, and 3.62 A are obtained for 4, 8, and 12 residue loops, respectively. In addition, the method can provide reasonable models of conformations of longer protein segments: predicted conformations of 3A root-mean-square deviation or better were obtained for 5 of 10 examples of segments ranging from 13 to 34 residues. In combination with a sequence alignment algorithm, this method generates complete, ungapped models of protein structures, including regions both similar to and divergent from a homologous structure. This combined method was used to make predictions for 28 protein domains in the Critical Assessment of Protein Structure 4 (CASP 4) and 59 domains in CASP 5, where the method ranked highly among comparative modeling and fold recognition methods. Model accuracy in these blind predictions is dominated by alignment quality, but in the context of accurate alignments, long protein segments can be accurately modeled. Notably, the method correctly predicted the local structure of a 39-residue insertion into a TIM barrel in CASP 5 target T0186.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A major limitation of current comparative modeling methods is the accuracy with which regions that are structurally divergent from homologues of known structure can be modeled. Because structural differences between homologous proteins are responsible for variations in protein function and specificity, the ability to model these differences has important functional consequences. Although existing methods can provide reasonably accurate models of short loop regions, modeling longer structurally divergent regions is an unsolved problem. Here we describe a method based on the de novo structure prediction algorithm, Rosetta, for predicting conformations of structurally divergent regions in comparative models. Initial conformations for short segments are selected from the protein structure database, whereas longer segments are built up by using three- and nine-residue fragments drawn from the database and combined by using the Rosetta algorithm. A gap closure term in the potential in combination with modified Newtontextquoterights method for gradient descent minimization is used to ensure continuity of the peptide backbone. Conformations of variable regions are refined in the context of a fixed template structure using Monte Carlo minimization together with rapid repacking of side-chains to iteratively optimize backbone torsion angles and side-chain rotamers. For short loops, mean accuracies of 0.69, 1.45, and 3.62 A are obtained for 4, 8, and 12 residue loops, respectively. In addition, the method can provide reasonable models of conformations of longer protein segments: predicted conformations of 3A root-mean-square deviation or better were obtained for 5 of 10 examples of segments ranging from 13 to 34 residues. In combination with a sequence alignment algorithm, this method generates complete, ungapped models of protein structures, including regions both similar to and divergent from a homologous structure. This combined method was used to make predictions for 28 protein domains in the Critical Assessment of Protein Structure 4 (CASP 4) and 59 domains in CASP 5, where the method ranked highly among comparative modeling and fold recognition methods. Model accuracy in these blind predictions is dominated by alignment quality, but in the context of accurate alignments, long protein segments can be accurately modeled. Notably, the method correctly predicted the local structure of a 39-residue insertion into a TIM barrel in CASP 5 target T0186.
Alexander L Watters, David Baker
Searching for folded proteins in vitro and in silico Journal Article
In: European journal of biochemistry, vol. 271, pp. 1615-22, 2004, ISSN: 0014-2956.
@article{181,
title = {Searching for folded proteins in vitro and in silico},
author = { Alexander L Watters and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/watters04A.pdf},
issn = {0014-2956},
year = {2004},
date = {2004-05-01},
journal = {European journal of biochemistry},
volume = {271},
pages = {1615-22},
abstract = {Understanding the sequence determinants of protein structure, stability and folding is critical for understanding how natural proteins have evolved and how proteins can be engineered to perform novel functions. The complexity of the protein folding problem requires the ability to search large volumes of sequence space for proteins with specific structural or functional characteristics. Here we describe our efforts to identify novel proteins using a phage-display selection strategy from a textquoterightmini-exontextquoteright shuffling library generated from the yeast genome and from completely random sequence libraries, and compare the results to recent successes in generating novel proteins using in silico protein design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Understanding the sequence determinants of protein structure, stability and folding is critical for understanding how natural proteins have evolved and how proteins can be engineered to perform novel functions. The complexity of the protein folding problem requires the ability to search large volumes of sequence space for proteins with specific structural or functional characteristics. Here we describe our efforts to identify novel proteins using a phage-display selection strategy from a textquoterightmini-exontextquoteright shuffling library generated from the yeast genome and from completely random sequence libraries, and compare the results to recent successes in generating novel proteins using in silico protein design.
Michelle Scalley-Kim, David Baker
In: Journal of molecular biology, vol. 338, pp. 573-83, 2004, ISSN: 0022-2836.
@article{178,
title = {Characterization of the folding energy landscapes of computer generated proteins suggests high folding free energy barriers and cooperativity may be consequences of natural selection},
author = { Michelle Scalley-Kim and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/scalley-kim04A.pdf},
issn = {0022-2836},
year = {2004},
date = {2004-04-01},
journal = {Journal of molecular biology},
volume = {338},
pages = {573-83},
abstract = {To determine the extent to which protein folding rates and free energy landscapes have been shaped by natural selection, we have examined the folding kinetics of five proteins generated using computational design methods and, hence, never exposed to natural selection. Four of these proteins are complete computer-generated redesigns of naturally occurring structures and the fifth protein, called Top7, has a computer-generated fold not yet observed in nature. We find that three of the four redesigned proteins fold much faster than their naturally occurring counterparts. While natural selection thus does not appear to operate on protein folding rates, the majority of the designed proteins unfold considerably faster than their naturally occurring counterparts, suggesting possible selection for a high free energy barrier to unfolding. In contrast to almost all naturally occurring proteins of less than 100 residues but consistent with simple computational models, the folding energy landscape for Top7 appears to be quite complex, suggesting the smooth energy landscapes and highly cooperative folding transitions observed for small naturally occurring proteins may also reflect the workings of natural selection.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To determine the extent to which protein folding rates and free energy landscapes have been shaped by natural selection, we have examined the folding kinetics of five proteins generated using computational design methods and, hence, never exposed to natural selection. Four of these proteins are complete computer-generated redesigns of naturally occurring structures and the fifth protein, called Top7, has a computer-generated fold not yet observed in nature. We find that three of the four redesigned proteins fold much faster than their naturally occurring counterparts. While natural selection thus does not appear to operate on protein folding rates, the majority of the designed proteins unfold considerably faster than their naturally occurring counterparts, suggesting possible selection for a high free energy barrier to unfolding. In contrast to almost all naturally occurring proteins of less than 100 residues but consistent with simple computational models, the folding energy landscape for Top7 appears to be quite complex, suggesting the smooth energy landscapes and highly cooperative folding transitions observed for small naturally occurring proteins may also reflect the workings of natural selection.
Tanja Kortemme, Lukasz A Joachimiak, Alex N Bullock, Aaron D Schuler, Barry L Stoddard, David Baker
Computational redesign of protein-protein interaction specificity Journal Article
In: Nature structural & molecular biology, vol. 11, pp. 371-9, 2004, ISSN: 1545-9993.
@article{170,
title = {Computational redesign of protein-protein interaction specificity},
author = { Tanja Kortemme and Lukasz A Joachimiak and Alex N Bullock and Aaron D Schuler and Barry L Stoddard and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kortemme04A.pdf},
issn = {1545-9993},
year = {2004},
date = {2004-04-01},
journal = {Nature structural & molecular biology},
volume = {11},
pages = {371-9},
abstract = {We developed a textquoterightcomputational second-site suppressortextquoteright strategy to redesign specificity at a protein-protein interface and applied it to create new specifically interacting DNase-inhibitor protein pairs. We demonstrate that the designed switch in specificity holds in in vitro binding and functional assays. We also show that the designed interfaces are specific in the natural functional context in living cells, and present the first high-resolution X-ray crystallographic analysis of a computer-redesigned functional protein-protein interface with altered specificity. The approach should be applicable to the design of interacting protein pairs with novel specificities for delineating and re-engineering protein interaction networks in living cells.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We developed a textquoterightcomputational second-site suppressortextquoteright strategy to redesign specificity at a protein-protein interface and applied it to create new specifically interacting DNase-inhibitor protein pairs. We demonstrate that the designed switch in specificity holds in in vitro binding and functional assays. We also show that the designed interfaces are specific in the natural functional context in living cells, and present the first high-resolution X-ray crystallographic analysis of a computer-redesigned functional protein-protein interface with altered specificity. The approach should be applicable to the design of interacting protein pairs with novel specificities for delineating and re-engineering protein interaction networks in living cells.
Henrik G Svensson, William J Wedemeyer, Jennifer L Ekstrom, David R Callender, Tanja Kortemme, David E Kim, Ulf Sj"obring, David Baker
Contributions of amino acid side chains to the kinetics and thermodynamics of the bivalent binding of protein L to Ig kappa light chain Journal Article
In: Biochemistry, vol. 43, pp. 2445-57, 2004, ISSN: 0006-2960.
@article{180,
title = {Contributions of amino acid side chains to the kinetics and thermodynamics of the bivalent binding of protein L to Ig kappa light chain},
author = { Henrik G Svensson and William J Wedemeyer and Jennifer L Ekstrom and David R Callender and Tanja Kortemme and David E Kim and Ulf Sj"obring and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/svensson04A.pdf},
issn = {0006-2960},
year = {2004},
date = {2004-03-01},
journal = {Biochemistry},
volume = {43},
pages = {2445-57},
abstract = {Protein L is a bacterial surface protein with 4-5 immunoglobulin (Ig)-binding domains (B1-B5), each of which appears to have two binding sites for Ig, corresponding to the two edges of its beta-sheet. To verify these sites biochemically and to probe their relative contributions to the protein L-Ig kappa light chain (kappa) interaction, we compared the binding of PLW (the Y47W mutant of the B1 domain) to that of mutants designed to disrupt binding to sites 1 and 2, using gel filtration, BIAcore surface plasmon resonance, fluorescence titration, and solid-phase radioimmunoassays. Gel filtration experiments show that PLW binds kappa both in 1:1 complexes and multivalently, consistent with two binding sites. Covalent dimers of the A20C and V51C mutants of PLW were prepared to eliminate site 1 and site 2 binding, respectively; both the A20C and V51C dimers bind kappa in 1:1 complexes and multivalently, indicating that neither site 1 nor site 2 is solely responsible for kappa binding. The A20R mutant was designed computationally to eliminate site 1 binding while preserving site 2 binding; consistent with this design, the A20R mutant binds kappa in 1:1 complexes but not multivalently. To probe the contributions of amino acid side chains to binding, we prepared 75 point mutants spanning nearly every residue of PLW; BIAcore studies of these mutants revealed two binding-energy "hot spots" consistent with sites 1 and 2. These data indicate that PLW binds kappa at both sites with similar affinities (high nanomolar), with the strongest contributions to the binding energy from Tyr34 (site 2) and Tyr36 (site 1). Compared to other protein-protein complexes, the binding is insensitive to amino acid substitutions at these sites, consistent with the large number of main chain interactions relative to side chain interactions. The strong binding of protein L to Ig kappa light chains of various species may result from the ambidextrous binding of the B1-B5 domains and the unimportance of specific side chain interactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein L is a bacterial surface protein with 4-5 immunoglobulin (Ig)-binding domains (B1-B5), each of which appears to have two binding sites for Ig, corresponding to the two edges of its beta-sheet. To verify these sites biochemically and to probe their relative contributions to the protein L-Ig kappa light chain (kappa) interaction, we compared the binding of PLW (the Y47W mutant of the B1 domain) to that of mutants designed to disrupt binding to sites 1 and 2, using gel filtration, BIAcore surface plasmon resonance, fluorescence titration, and solid-phase radioimmunoassays. Gel filtration experiments show that PLW binds kappa both in 1:1 complexes and multivalently, consistent with two binding sites. Covalent dimers of the A20C and V51C mutants of PLW were prepared to eliminate site 1 and site 2 binding, respectively; both the A20C and V51C dimers bind kappa in 1:1 complexes and multivalently, indicating that neither site 1 nor site 2 is solely responsible for kappa binding. The A20R mutant was designed computationally to eliminate site 1 binding while preserving site 2 binding; consistent with this design, the A20R mutant binds kappa in 1:1 complexes but not multivalently. To probe the contributions of amino acid side chains to binding, we prepared 75 point mutants spanning nearly every residue of PLW; BIAcore studies of these mutants revealed two binding-energy "hot spots" consistent with sites 1 and 2. These data indicate that PLW binds kappa at both sites with similar affinities (high nanomolar), with the strongest contributions to the binding energy from Tyr34 (site 2) and Tyr36 (site 1). Compared to other protein-protein complexes, the binding is insensitive to amino acid substitutions at these sites, consistent with the large number of main chain interactions relative to side chain interactions. The strong binding of protein L to Ig kappa light chains of various species may result from the ambidextrous binding of the B1-B5 domains and the unimportance of specific side chain interactions.
Tanja Kortemme, David E Kim, David Baker
Computational alanine scanning of protein-protein interfaces Journal Article
In: Sciencetextquoterights STKE, vol. 2004, pp. pl2, 2004, ISSN: 1525-8882.
@article{300,
title = {Computational alanine scanning of protein-protein interfaces},
author = { Tanja Kortemme and David E Kim and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kortemme04B-1.pdf},
issn = {1525-8882},
year = {2004},
date = {2004-02-01},
journal = {Sciencetextquoterights STKE},
volume = {2004},
pages = {pl2},
abstract = {Protein-protein interactions are key components of all signal transduction processes, so methods to alter these interactions promise to become important tools in dissecting function of connectivities in these networks. We have developed a fast computational approach for the prediction of energetically important amino acid residues in protein-protein interfaces (available at http://robetta.bakerlab.org/alaninescan), which we, following Peter Kollman, have termed "computational alanine scanning." The input consists of a three-dimensional structure of a protein-protein complex; output is a list of "hot spots," or amino acid side chains that are predicted to significantly destabilize the interface when mutated to alanine, analogous to the results of experimental alanine-scanning mutagenesis. 79% of hot spots and 68% of neutral residues were correctly predicted in a test of 233 mutations in 19 protein-protein complexes. A single interface can be analyzed in minutes. The computational methodology has been validated by the successful design of protein interfaces with new specificity and activity, and has yielded new insights into the mechanisms of receptor specificity and promiscuity in biological systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-protein interactions are key components of all signal transduction processes, so methods to alter these interactions promise to become important tools in dissecting function of connectivities in these networks. We have developed a fast computational approach for the prediction of energetically important amino acid residues in protein-protein interfaces (available at http://robetta.bakerlab.org/alaninescan), which we, following Peter Kollman, have termed "computational alanine scanning." The input consists of a three-dimensional structure of a protein-protein complex; output is a list of "hot spots," or amino acid side chains that are predicted to significantly destabilize the interface when mutated to alanine, analogous to the results of experimental alanine-scanning mutagenesis. 79% of hot spots and 68% of neutral residues were correctly predicted in a test of 233 mutations in 19 protein-protein complexes. A single interface can be analyzed in minutes. The computational methodology has been validated by the successful design of protein interfaces with new specificity and activity, and has yielded new insights into the mechanisms of receptor specificity and promiscuity in biological systems.
Michael Kuhn, Jens Meiler, David Baker
Strand-loop-strand motifs: prediction of hairpins and diverging turns in proteins Journal Article
In: Proteins, vol. 54, pp. 282-8, 2004, ISSN: 1097-0134.
@article{172,
title = {Strand-loop-strand motifs: prediction of hairpins and diverging turns in proteins},
author = { Michael Kuhn and Jens Meiler and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kuhn04A.pdf},
issn = {1097-0134},
year = {2004},
date = {2004-02-01},
journal = {Proteins},
volume = {54},
pages = {282-8},
abstract = {Beta-sheet proteins have been particularly challenging for de novo structure prediction methods, which tend to pair adjacent beta-strands into beta-hairpins and produce overly local topologies. To remedy this problem and facilitate de novo prediction of beta-sheet protein structures, we have developed a neural network that classifies strand-loop-strand motifs by local hairpins and nonlocal diverging turns by using the amino acid sequence as input. The neural network is trained with a representative subset of the Protein Data Bank and achieves a prediction accuracy of 75.9 +/- 4.4% compared to a baseline prediction rate of 59.1%. Hairpins are predicted with an accuracy of 77.3 +/- 6.1%, diverging turns with an accuracy of 73.9 +/- 6.0%. Incorporation of the beta-hairpin/diverging turn classification into the ROSETTA de novo structure prediction method led to higher contact order models and somewhat improved tertiary structure predictions for a test set of 11 all-beta-proteins and 3 alphabeta-proteins. The beta-hairpin/diverging turn classification from amino acid sequences is available online for academic use (Meiler and Kuhn, 2003; www.jens-meiler.de/turnpred.html).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Beta-sheet proteins have been particularly challenging for de novo structure prediction methods, which tend to pair adjacent beta-strands into beta-hairpins and produce overly local topologies. To remedy this problem and facilitate de novo prediction of beta-sheet protein structures, we have developed a neural network that classifies strand-loop-strand motifs by local hairpins and nonlocal diverging turns by using the amino acid sequence as input. The neural network is trained with a representative subset of the Protein Data Bank and achieves a prediction accuracy of 75.9 +/- 4.4% compared to a baseline prediction rate of 59.1%. Hairpins are predicted with an accuracy of 77.3 +/- 6.1%, diverging turns with an accuracy of 73.9 +/- 6.0%. Incorporation of the beta-hairpin/diverging turn classification into the ROSETTA de novo structure prediction method led to higher contact order models and somewhat improved tertiary structure predictions for a test set of 11 all-beta-proteins and 3 alphabeta-proteins. The beta-hairpin/diverging turn classification from amino acid sequences is available online for academic use (Meiler and Kuhn, 2003; www.jens-meiler.de/turnpred.html).
Tanja Kortemme, David Baker
Computational design of protein-protein interactions Journal Article
In: Current opinion in chemical biology, vol. 8, pp. 91-7, 2004, ISSN: 1367-5931.
@article{171,
title = {Computational design of protein-protein interactions},
author = { Tanja Kortemme and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kortemme04A_0.pdf},
issn = {1367-5931},
year = {2004},
date = {2004-02-01},
journal = {Current opinion in chemical biology},
volume = {8},
pages = {91-7},
abstract = {Computational protein design strategies have been developed to reengineer protein-protein interfaces in an automated, generalizable fashion. In the past two years, these methods have been successfully applied to generate chimeric proteins and protein pairs with specificities different from naturally occurring protein-protein interactions. Although there are shortcomings in current approaches, both in the way conformational space is sampled and in the energy functions used to evaluate designed conformations, the successes suggest we are now entering an era in which computational methods can be used to modulate, reengineer and design protein-protein interaction networks in living cells.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computational protein design strategies have been developed to reengineer protein-protein interfaces in an automated, generalizable fashion. In the past two years, these methods have been successfully applied to generate chimeric proteins and protein pairs with specificities different from naturally occurring protein-protein interactions. Although there are shortcomings in current approaches, both in the way conformational space is sampled and in the energy functions used to evaluate designed conformations, the successes suggest we are now entering an era in which computational methods can be used to modulate, reengineer and design protein-protein interaction networks in living cells.
Brian Kuhlman, David Baker
Exploring folding free energy landscapes using computational protein design Journal Article
In: Current opinion in structural biology, vol. 14, pp. 89-95, 2004, ISSN: 0959-440X.
@article{574,
title = {Exploring folding free energy landscapes using computational protein design},
author = { Brian Kuhlman and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/exploringfoldingfreeenergy_Baker2004.pdf},
doi = {10.1016/j.sbi.2004.01.002},
issn = {0959-440X},
year = {2004},
date = {2004-02-01},
journal = {Current opinion in structural biology},
volume = {14},
pages = {89-95},
abstract = {Recent advances in computational protein design have allowed exciting new insights into the sequence dependence of protein folding free energy landscapes. Whereas most previous studies have examined the sequence dependence of protein stability and folding kinetics by characterizing naturally occurring proteins and variants of these proteins that contain a small number of mutations, it is now possible to generate and characterize computationally designed proteins that differ significantly from naturally occurring proteins in sequence and/or structure. These computer-generated proteins provide insights into the determinants of protein structure, stability and folding, and make it possible to disentangle the properties of proteins that are the consequence of natural selection from those that reflect the fundamental physical chemistry of polypeptide chains.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent advances in computational protein design have allowed exciting new insights into the sequence dependence of protein folding free energy landscapes. Whereas most previous studies have examined the sequence dependence of protein stability and folding kinetics by characterizing naturally occurring proteins and variants of these proteins that contain a small number of mutations, it is now possible to generate and characterize computationally designed proteins that differ significantly from naturally occurring proteins in sequence and/or structure. These computer-generated proteins provide insights into the determinants of protein structure, stability and folding, and make it possible to disentangle the properties of proteins that are the consequence of natural selection from those that reflect the fundamental physical chemistry of polypeptide chains.
Morozov AV, Misura KMS, Tsemekhman K, Baker D
Comparison of Quantum Mechanics and Molecular Mechanics Dimerization Energy Landscapes for Pairs of Ring-Containing Amino Acids in Proteins Journal Article
In: Journal of Physical Chemistry B, 2004.
@article{301,
title = {Comparison of Quantum Mechanics and Molecular Mechanics Dimerization Energy Landscapes for Pairs of Ring-Containing Amino Acids in Proteins},
author = { Morozov AV and Misura KMS and Tsemekhman K and Baker D},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/morozov04B.pdf},
doi = {10.1021/jp037711e},
year = {2004},
date = {2004-01-01},
journal = {Journal of Physical Chemistry B},
abstract = {A promising approach to developing improved potential functions for modeling macromolecular interactions consists of combining protein structural analysis, quantum mechanical calculations on small molecule models, and molecular mechanics potential decomposition. Here we apply this approach to the interactions of pairs of ring-containing amino acids in proteins. We find reasonable qualitative agreement between molecular mechanics and quantum chemistry calculations, both over one-dimensional projections of the binding free energy landscape for amino acid homodimers and over a set of homodimers and heterodimers from experimentally observed protein crystal structures. The molecular mechanics landscapes are a sum of charge-charge and Lennard-Jones contributions; short-range quantum mechanical effects such as charge transfer appear not to be significant in ring side chain interactions. We also find a reasonable degree of correlation between the molecular mechanics energy landscapes and the distributions of dimer geometries observed in protein structures, suggesting that the intrinsic dimer interaction energies do contribute to packing of side chains in proteins rather than being overwhelmed by the numerous interactions with other protein atoms and solvent. These results demonstrate that interactions involving aromatic residues and proline can be fairly well modeled using current molecular mechanics force fields, but there is still room for improvement, particularly for interactions involving proline and tyrosine.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A promising approach to developing improved potential functions for modeling macromolecular interactions consists of combining protein structural analysis, quantum mechanical calculations on small molecule models, and molecular mechanics potential decomposition. Here we apply this approach to the interactions of pairs of ring-containing amino acids in proteins. We find reasonable qualitative agreement between molecular mechanics and quantum chemistry calculations, both over one-dimensional projections of the binding free energy landscape for amino acid homodimers and over a set of homodimers and heterodimers from experimentally observed protein crystal structures. The molecular mechanics landscapes are a sum of charge-charge and Lennard-Jones contributions; short-range quantum mechanical effects such as charge transfer appear not to be significant in ring side chain interactions. We also find a reasonable degree of correlation between the molecular mechanics energy landscapes and the distributions of dimer geometries observed in protein structures, suggesting that the intrinsic dimer interaction energies do contribute to packing of side chains in proteins rather than being overwhelmed by the numerous interactions with other protein atoms and solvent. These results demonstrate that interactions involving aromatic residues and proline can be fairly well modeled using current molecular mechanics force fields, but there is still room for improvement, particularly for interactions involving proline and tyrosine.
Yu Chen, Tanja Kortemme, Tim Robertson, David Baker, Gabriele Varani
A new hydrogen-bonding potential for the design of protein-RNA interactions predicts specific contacts and discriminates decoys Journal Article
In: Nucleic acids research, vol. 32, pp. 5147-62, 2004, ISSN: 1362-4962.
@article{167,
title = {A new hydrogen-bonding potential for the design of protein-RNA interactions predicts specific contacts and discriminates decoys},
author = { Yu Chen and Tanja Kortemme and Tim Robertson and David Baker and Gabriele Varani},
issn = {1362-4962},
year = {2004},
date = {2004-00-01},
journal = {Nucleic acids research},
volume = {32},
pages = {5147-62},
abstract = {RNA-binding proteins play many essential roles in the regulation of gene expression in the cell. Despite the significant increase in the number of structures for RNA-protein complexes in the last few years, the molecular basis of specificity remains unclear even for the best-studied protein families. We have developed a distance and orientation-dependent hydrogen-bonding potential based on the statistical analysis of hydrogen-bonding geometries that are observed in high-resolution crystal structures of protein-DNA and protein-RNA complexes. We observe very strong geometrical preferences that reflect significant energetic constraints on the relative placement of hydrogen-bonding atom pairs at protein-nucleic acid interfaces. A scoring function based on the hydrogen-bonding potential discriminates native protein-RNA structures from incorrectly docked decoys with remarkable predictive power. By incorporating the new hydrogen-bonding potential into a physical model of protein-RNA interfaces with full atom representation, we were able to recover native amino acids at protein-RNA interfaces.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
RNA-binding proteins play many essential roles in the regulation of gene expression in the cell. Despite the significant increase in the number of structures for RNA-protein complexes in the last few years, the molecular basis of specificity remains unclear even for the best-studied protein families. We have developed a distance and orientation-dependent hydrogen-bonding potential based on the statistical analysis of hydrogen-bonding geometries that are observed in high-resolution crystal structures of protein-DNA and protein-RNA complexes. We observe very strong geometrical preferences that reflect significant energetic constraints on the relative placement of hydrogen-bonding atom pairs at protein-nucleic acid interfaces. A scoring function based on the hydrogen-bonding potential discriminates native protein-RNA structures from incorrectly docked decoys with remarkable predictive power. By incorporating the new hydrogen-bonding potential into a physical model of protein-RNA interfaces with full atom representation, we were able to recover native amino acids at protein-RNA interfaces.
Carol A Rohl, Charlie E M Strauss, Kira M S Misura, David Baker
Protein structure prediction using Rosetta. Journal Article
In: Methods in enzymology, vol. 383, pp. 66-93, 2004, ISSN: 0076-6879.
@article{176,
title = {Protein structure prediction using Rosetta.},
author = { Carol A Rohl and Charlie E M Strauss and Kira M S Misura and David Baker},
issn = {0076-6879},
year = {2004},
date = {2004-00-01},
journal = {Methods in enzymology},
volume = {383},
pages = {66-93},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2003
Jens Meiler, David Baker
Rapid protein fold determination using unassigned NMR data Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 100, pp. 15404-9, 2003, ISSN: 0027-8424.
@article{79,
title = {Rapid protein fold determination using unassigned NMR data},
author = { Jens Meiler and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/meiler03B.pdf},
issn = {0027-8424},
year = {2003},
date = {2003-12-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {100},
pages = {15404-9},
abstract = {Experimental structure determination by x-ray crystallography and NMR spectroscopy is slow and time-consuming compared with the rate at which new protein sequences are being identified. NMR spectroscopy has the advantage of rapidly providing the structurally relevant information in the form of unassigned chemical shifts (CSs), intensities of NOESY crosspeaks [nuclear Overhauser effects (NOEs)], and residual dipolar couplings (RDCs), but use of these data are limited by the time and effort needed to assign individual resonances to specific atoms. Here, we develop a method for generating low-resolution protein structures by using unassigned NMR data that relies on the de novo protein structure prediction algorithm, rosetta [Simons, K. T., Kooperberg, C., Huang, E. & Baker, D. (1997) J. Mol. Biol. 268, 209-225] and a Monte Carlo procedure that searches for the assignment of resonances to atoms that produces the best fit of the experimental NMR data to a candidate 3D structure. A large ensemble of models is generated from sequence information alone by using rosetta, an optimal assignment is identified for each model, and the models are then ranked based on their fit with the NMR data assuming the identified assignments. The method was tested on nine protein sequences between 56 and 140 amino acids and published CS, NOE, and RDC data. The procedure yielded models with rms deviations between 3 and 6 A, and, in four of the nine cases, the partial assignments obtained by the method could be used to refine the structures to high resolution (0.6-1.8 A) by repeated cycles of structure generation guided by the partial assignments, followed by reassignment using the newly generated models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Experimental structure determination by x-ray crystallography and NMR spectroscopy is slow and time-consuming compared with the rate at which new protein sequences are being identified. NMR spectroscopy has the advantage of rapidly providing the structurally relevant information in the form of unassigned chemical shifts (CSs), intensities of NOESY crosspeaks [nuclear Overhauser effects (NOEs)], and residual dipolar couplings (RDCs), but use of these data are limited by the time and effort needed to assign individual resonances to specific atoms. Here, we develop a method for generating low-resolution protein structures by using unassigned NMR data that relies on the de novo protein structure prediction algorithm, rosetta [Simons, K. T., Kooperberg, C., Huang, E. & Baker, D. (1997) J. Mol. Biol. 268, 209-225] and a Monte Carlo procedure that searches for the assignment of resonances to atoms that produces the best fit of the experimental NMR data to a candidate 3D structure. A large ensemble of models is generated from sequence information alone by using rosetta, an optimal assignment is identified for each model, and the models are then ranked based on their fit with the NMR data assuming the identified assignments. The method was tested on nine protein sequences between 56 and 140 amino acids and published CS, NOE, and RDC data. The procedure yielded models with rms deviations between 3 and 6 A, and, in four of the nine cases, the partial assignments obtained by the method could be used to refine the structures to high resolution (0.6-1.8 A) by repeated cycles of structure generation guided by the partial assignments, followed by reassignment using the newly generated models.
Tony R Hazbun, Lars Malmstr"om, Scott Anderson, Beth J Graczyk, Bethany Fox, Michael Riffle, Bryan A Sundin, J Derringer Aranda, W Hayes McDonald, Chun-Hwei Chiu, Brian E Snydsman, Phillip Bradley, Eric G D Muller, Stanley Fields, David Baker, John R Yates, Trisha N Davis
Assigning function to yeast proteins by integration of technologies Journal Article
In: Molecular cell, vol. 12, pp. 1353-65, 2003, ISSN: 1097-2765.
@article{314,
title = {Assigning function to yeast proteins by integration of technologies},
author = { Tony R Hazbun and Lars Malmstr"om and Scott Anderson and Beth J Graczyk and Bethany Fox and Michael Riffle and Bryan A Sundin and J Derringer Aranda and W Hayes McDonald and Chun-Hwei Chiu and Brian E Snydsman and Phillip Bradley and Eric G D Muller and Stanley Fields and David Baker and John R Yates and Trisha N Davis},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/hazbun03A.pdf},
issn = {1097-2765},
year = {2003},
date = {2003-12-01},
journal = {Molecular cell},
volume = {12},
pages = {1353-65},
abstract = {Interpreting genome sequences requires the functional analysis of thousands of predicted proteins, many of which are uncharacterized and without obvious homologs. To assess whether the roles of large sets of uncharacterized genes can be assigned by targeted application of a suite of technologies, we used four complementary protein-based methods to analyze a set of 100 uncharacterized but essential open reading frames (ORFs) of the yeast Saccharomyces cerevisiae. These proteins were subjected to affinity purification and mass spectrometry analysis to identify copurifying proteins, two-hybrid analysis to identify interacting proteins, fluorescence microscopy to localize the proteins, and structure prediction methodology to predict structural domains or identify remote homologies. Integration of the data assigned function to 48 ORFs using at least two of the Gene Ontology (GO) categories of biological process, molecular function, and cellular component; 77 ORFs were annotated by at least one method. This combination of technologies, coupled with annotation using GO, is a powerful approach to classifying genes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Interpreting genome sequences requires the functional analysis of thousands of predicted proteins, many of which are uncharacterized and without obvious homologs. To assess whether the roles of large sets of uncharacterized genes can be assigned by targeted application of a suite of technologies, we used four complementary protein-based methods to analyze a set of 100 uncharacterized but essential open reading frames (ORFs) of the yeast Saccharomyces cerevisiae. These proteins were subjected to affinity purification and mass spectrometry analysis to identify copurifying proteins, two-hybrid analysis to identify interacting proteins, fluorescence microscopy to localize the proteins, and structure prediction methodology to predict structural domains or identify remote homologies. Integration of the data assigned function to 48 ORFs using at least two of the Gene Ontology (GO) categories of biological process, molecular function, and cellular component; 77 ORFs were annotated by at least one method. This combination of technologies, coupled with annotation using GO, is a powerful approach to classifying genes.
Brian Kuhlman, Gautam Dantas, Gregory C Ireton, Gabriele Varani, Barry L Stoddard, David Baker
Design of a novel globular protein fold with atomic-level accuracy Journal Article
In: Science, vol. 302, pp. 1364-8, 2003, ISSN: 1095-9203.
@article{82,
title = {Design of a novel globular protein fold with atomic-level accuracy},
author = { Brian Kuhlman and Gautam Dantas and Gregory C Ireton and Gabriele Varani and Barry L Stoddard and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kuhlman03A.pdf},
issn = {1095-9203},
year = {2003},
date = {2003-11-01},
journal = {Science},
volume = {302},
pages = {1364-8},
abstract = {A major challenge of computational protein design is the creation of novel proteins with arbitrarily chosen three-dimensional structures. Here, we used a general computational strategy that iterates between sequence design and structure prediction to design a 93-residue alpha/beta protein called Top7 with a novel sequence and topology. Top7 was found experimentally to be folded and extremely stable, and the x-ray crystal structure of Top7 is similar (root mean square deviation equals 1.2 angstroms) to the design model. The ability to design a new protein fold makes possible the exploration of the large regions of the protein universe not yet observed in nature.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A major challenge of computational protein design is the creation of novel proteins with arbitrarily chosen three-dimensional structures. Here, we used a general computational strategy that iterates between sequence design and structure prediction to design a 93-residue alpha/beta protein called Top7 with a novel sequence and topology. Top7 was found experimentally to be folded and extremely stable, and the x-ray crystal structure of Top7 is similar (root mean square deviation equals 1.2 angstroms) to the design model. The ability to design a new protein fold makes possible the exploration of the large regions of the protein universe not yet observed in nature.
William J Wedemeyer, David Baker
Efficient minimization of angle-dependent potentials for polypeptides in internal coordinates Journal Article
In: Proteins, vol. 53, pp. 262-72, 2003, ISSN: 1097-0134.
@article{73,
title = {Efficient minimization of angle-dependent potentials for polypeptides in internal coordinates},
author = { William J Wedemeyer and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/wedemeyer03A.pdf},
issn = {1097-0134},
year = {2003},
date = {2003-11-01},
journal = {Proteins},
volume = {53},
pages = {262-72},
abstract = {Angular potentials play an important role in the refinement of protein structures through angle-dependent restraints (e.g., those determined by cross-correlated relaxations, residual dipolar couplings, and hydrogen bonds). Analytic derivatives of such angular potentials with respect to the dihedral angles of proteins would be useful for optimizing such restraints and other types of angular potentials (i.e., such as we are now introducing into protein structure prediction) but have not been described. In this article, analytic derivatives are calculated for four types of angular potentials and integrated with the efficient recursive derivative calculation methods of Go and coworkers. The formulas are implemented in publicly available software and illustrated by refining a low-resolution protein structure with idealized vector-angle, dipolar-coupling, and hydrogen-bond restraints. The method is now being used routinely to optimize hydrogen-bonding potentials in ROSETTA.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Angular potentials play an important role in the refinement of protein structures through angle-dependent restraints (e.g., those determined by cross-correlated relaxations, residual dipolar couplings, and hydrogen bonds). Analytic derivatives of such angular potentials with respect to the dihedral angles of proteins would be useful for optimizing such restraints and other types of angular potentials (i.e., such as we are now introducing into protein structure prediction) but have not been described. In this article, analytic derivatives are calculated for four types of angular potentials and integrated with the efficient recursive derivative calculation methods of Go and coworkers. The formulas are implemented in publicly available software and illustrated by refining a low-resolution protein structure with idealized vector-angle, dipolar-coupling, and hydrogen-bond restraints. The method is now being used routinely to optimize hydrogen-bonding potentials in ROSETTA.
Jens Meiler, David Baker
Coupled prediction of protein secondary and tertiary structure Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 100, pp. 12105-10, 2003, ISSN: 0027-8424.
@article{80,
title = {Coupled prediction of protein secondary and tertiary structure},
author = { Jens Meiler and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/meiler03A.pdf},
issn = {0027-8424},
year = {2003},
date = {2003-10-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {100},
pages = {12105-10},
abstract = {The strong coupling between secondary and tertiary structure formation in protein folding is neglected in most structure prediction methods. In this work we investigate the extent to which nonlocal interactions in predicted tertiary structures can be used to improve secondary structure prediction. The architecture of a neural network for secondary structure prediction that utilizes multiple sequence alignments was extended to accept low-resolution nonlocal tertiary structure information as an additional input. By using this modified network, together with tertiary structure information from native structures, the Q3-prediction accuracy is increased by 7-10% on average and by up to 35% in individual cases for independent test data. By using tertiary structure information from models generated with the ROSETTA de novo tertiary structure prediction method, the Q3-prediction accuracy is improved by 4-5% on average for small and medium-sized single-domain proteins. Analysis of proteins with particularly large improvements in secondary structure prediction using tertiary structure information provides insight into the feedback from tertiary to secondary structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The strong coupling between secondary and tertiary structure formation in protein folding is neglected in most structure prediction methods. In this work we investigate the extent to which nonlocal interactions in predicted tertiary structures can be used to improve secondary structure prediction. The architecture of a neural network for secondary structure prediction that utilizes multiple sequence alignments was extended to accept low-resolution nonlocal tertiary structure information as an additional input. By using this modified network, together with tertiary structure information from native structures, the Q3-prediction accuracy is increased by 7-10% on average and by up to 35% in individual cases for independent test data. By using tertiary structure information from models generated with the ROSETTA de novo tertiary structure prediction method, the Q3-prediction accuracy is improved by 4-5% on average for small and medium-sized single-domain proteins. Analysis of proteins with particularly large improvements in secondary structure prediction using tertiary structure information provides insight into the feedback from tertiary to secondary structure.
Jerry Tsai, Richard Bonneau, Alexandre V Morozov, Brian Kuhlman, Carol A Rohl, David Baker
An improved protein decoy set for testing energy functions for protein structure prediction Journal Article
In: Proteins, vol. 53, pp. 76-87, 2003, ISSN: 1097-0134.
@article{74,
title = {An improved protein decoy set for testing energy functions for protein structure prediction},
author = { Jerry Tsai and Richard Bonneau and Alexandre V Morozov and Brian Kuhlman and Carol A Rohl and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/Tsai03A.pdf},
issn = {1097-0134},
year = {2003},
date = {2003-10-01},
journal = {Proteins},
volume = {53},
pages = {76-87},
abstract = {We have improved the original Rosetta centroid/backbone decoy set by increasing the number of proteins and frequency of near native models and by building on sidechains and minimizing clashes. The new set consists of 1,400 model structures for 78 different and diverse protein targets and provides a challenging set for the testing and evaluation of scoring functions. We evaluated the extent to which a variety of all-atom energy functions could identify the native and close-to-native structures in the new decoy sets. Of various implicit solvent models, we found that a solvent-accessible surface area-based solvation provided the best enrichment and discrimination of close-to-native decoys. The combination of this solvation treatment with Lennard Jones terms and the original Rosetta energy provided better enrichment and discrimination than any of the individual terms. The results also highlight the differences in accuracy of NMR and X-ray crystal structures: a large energy gap was observed between native and non-native conformations for X-ray structures but not for NMR structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have improved the original Rosetta centroid/backbone decoy set by increasing the number of proteins and frequency of near native models and by building on sidechains and minimizing clashes. The new set consists of 1,400 model structures for 78 different and diverse protein targets and provides a challenging set for the testing and evaluation of scoring functions. We evaluated the extent to which a variety of all-atom energy functions could identify the native and close-to-native structures in the new decoy sets. Of various implicit solvent models, we found that a solvent-accessible surface area-based solvation provided the best enrichment and discrimination of close-to-native decoys. The combination of this solvation treatment with Lennard Jones terms and the original Rosetta energy provided better enrichment and discrimination than any of the individual terms. The results also highlight the differences in accuracy of NMR and X-ray crystal structures: a large energy gap was observed between native and non-native conformations for X-ray structures but not for NMR structures.
Ruslan I Sadreyev, David Baker, Nick V Grishin
Profile-profile comparisons by COMPASS predict intricate homologies between protein families Journal Article
In: Protein science, vol. 12, pp. 2262-72, 2003, ISSN: 0961-8368.
@article{316,
title = {Profile-profile comparisons by COMPASS predict intricate homologies between protein families},
author = { Ruslan I Sadreyev and David Baker and Nick V Grishin},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/sadreyev03A.pdf},
issn = {0961-8368},
year = {2003},
date = {2003-10-01},
journal = {Protein science},
volume = {12},
pages = {2262-72},
abstract = {Recently we proposed a novel method of alignment-alignment comparison, COMPASS (the tool for COmparison of Multiple Protein Alignments with Assessment of Statistical Significance). Here we present several examples of the relations between PFAM protein families that were detected by COMPASS and that lead to the predictions of presently unresolved protein structures. We discuss relatively straightforward COMPASS predictions that are new and interesting to us, and that would require a substantial time and effort to justify even for a skilled PSI-BLAST user. All of the presented COMPASS hits are independently confirmed by other methods, including the ab initio structure-prediction method ROSETTA. The tertiary structure predictions made by ROSETTA proved to be useful for improving sequence-derived alignments, because they are based on a reasonable folding of the polypeptide chain rather than on the information from sequence databases. The ability of COMPASS to predict new relations within the PFAM database indicates the high sensitivity of COMPASS searches and substantiates its potential value for the discovery of previously unknown similarities between protein families.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recently we proposed a novel method of alignment-alignment comparison, COMPASS (the tool for COmparison of Multiple Protein Alignments with Assessment of Statistical Significance). Here we present several examples of the relations between PFAM protein families that were detected by COMPASS and that lead to the predictions of presently unresolved protein structures. We discuss relatively straightforward COMPASS predictions that are new and interesting to us, and that would require a substantial time and effort to justify even for a skilled PSI-BLAST user. All of the presented COMPASS hits are independently confirmed by other methods, including the ab initio structure-prediction method ROSETTA. The tertiary structure predictions made by ROSETTA proved to be useful for improving sequence-derived alignments, because they are based on a reasonable folding of the polypeptide chain rather than on the information from sequence databases. The ability of COMPASS to predict new relations within the PFAM database indicates the high sensitivity of COMPASS searches and substantiates its potential value for the discovery of previously unknown similarities between protein families.
Gautam Dantas, Brian Kuhlman, David Callender, Michelle Wong, David Baker
A large scale test of computational protein design: folding and stability of nine completely redesigned globular proteins Journal Article
In: Journal of molecular biology, vol. 332, pp. 449-60, 2003, ISSN: 0022-2836.
@article{87,
title = {A large scale test of computational protein design: folding and stability of nine completely redesigned globular proteins},
author = { Gautam Dantas and Brian Kuhlman and David Callender and Michelle Wong and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/dantas03A.pdf},
issn = {0022-2836},
year = {2003},
date = {2003-09-01},
journal = {Journal of molecular biology},
volume = {332},
pages = {449-60},
abstract = {A previously developed computer program for protein design, RosettaDesign, was used to predict low free energy sequences for nine naturally occurring protein backbones. RosettaDesign had no knowledge of the naturally occurring sequences and on average 65% of the residues in the designed sequences differ from wild-type. Synthetic genes for ten completely redesigned proteins were generated, and the proteins were expressed, purified, and then characterized using circular dichroism, chemical and temperature denaturation and NMR experiments. Although high-resolution structures have not yet been determined, eight of these proteins appear to be folded and their circular dichroism spectra are similar to those of their wild-type counterparts. Six of the proteins have stabilities equal to or up to 7kcal/mol greater than their wild-type counterparts, and four of the proteins have NMR spectra consistent with a well-packed, rigid structure. These encouraging results indicate that the computational protein design methods can, with significant reliability, identify amino acid sequences compatible with a target protein backbone.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A previously developed computer program for protein design, RosettaDesign, was used to predict low free energy sequences for nine naturally occurring protein backbones. RosettaDesign had no knowledge of the naturally occurring sequences and on average 65% of the residues in the designed sequences differ from wild-type. Synthetic genes for ten completely redesigned proteins were generated, and the proteins were expressed, purified, and then characterized using circular dichroism, chemical and temperature denaturation and NMR experiments. Although high-resolution structures have not yet been determined, eight of these proteins appear to be folded and their circular dichroism spectra are similar to those of their wild-type counterparts. Six of the proteins have stabilities equal to or up to 7kcal/mol greater than their wild-type counterparts, and four of the proteins have NMR spectra consistent with a well-packed, rigid structure. These encouraging results indicate that the computational protein design methods can, with significant reliability, identify amino acid sequences compatible with a target protein backbone.
Dmitry N Ivankov, Sergiy O Garbuzynskiy, Eric Alm, Kevin W Plaxco, David Baker, Alexei V Finkelstein
Contact order revisited: influence of protein size on the folding rate Journal Article
In: Protein science, vol. 12, pp. 2057-62, 2003, ISSN: 0961-8368.
@article{84,
title = {Contact order revisited: influence of protein size on the folding rate},
author = { Dmitry N Ivankov and Sergiy O Garbuzynskiy and Eric Alm and Kevin W Plaxco and David Baker and Alexei V Finkelstein},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/ivankov03A.pdf},
issn = {0961-8368},
year = {2003},
date = {2003-09-01},
journal = {Protein science},
volume = {12},
pages = {2057-62},
abstract = {Guided by the recent success of empirical model predicting the folding rates of small two-state folding proteins from the relative contact order (CO) of their native structures, by a theoretical model of protein folding that predicts that logarithm of the folding rate decreases with the protein chain length L as L(2/3), and by the finding that the folding rates of multistate folding proteins strongly correlate with their sizes and have very bad correlation with CO, we reexamined the dependence of folding rate on CO and L in attempt to find a structural parameter that determines folding rates for the totality of proteins. We show that the Abs_CO = CO x L, is able to predict rather accurately folding rates for both two-state and multistate folding proteins, as well as short peptides, and that this Abs_CO scales with the protein chain length as L(0.70 +/- 0.07) for the totality of studied single-domain proteins and peptides.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Guided by the recent success of empirical model predicting the folding rates of small two-state folding proteins from the relative contact order (CO) of their native structures, by a theoretical model of protein folding that predicts that logarithm of the folding rate decreases with the protein chain length L as L(2/3), and by the finding that the folding rates of multistate folding proteins strongly correlate with their sizes and have very bad correlation with CO, we reexamined the dependence of folding rate on CO and L in attempt to find a structural parameter that determines folding rates for the totality of proteins. We show that the Abs_CO = CO x L, is able to predict rather accurately folding rates for both two-state and multistate folding proteins, as well as short peptides, and that this Abs_CO scales with the protein chain length as L(0.70 +/- 0.07) for the totality of studied single-domain proteins and peptides.
Martin J Boulanger, Alexander J Bankovich, Tanja Kortemme, David Baker, K Christopher Garcia
Convergent mechanisms for recognition of divergent cytokines by the shared signaling receptor gp130 Journal Article
In: Molecular cell, vol. 12, pp. 577-89, 2003, ISSN: 1097-2765.
@article{315,
title = {Convergent mechanisms for recognition of divergent cytokines by the shared signaling receptor gp130},
author = { Martin J Boulanger and Alexander J Bankovich and Tanja Kortemme and David Baker and K Christopher Garcia},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/boulanger03A.pdf},
issn = {1097-2765},
year = {2003},
date = {2003-09-01},
journal = {Molecular cell},
volume = {12},
pages = {577-89},
abstract = {Gp130 is a shared cell-surface signaling receptor for at least ten different hematopoietic cytokines, but the basis of its degenerate recognition properties is unknown. We have determined the crystal structure of human leukemia inhibitory factor (LIF) bound to the cytokine binding region (CHR) of gp130 at 2.5 A resolution. Strikingly, we find that the shared binding site on gp130 has an entirely rigid core, while the LIF binding interface diverges sharply in structure and chemistry from that of other gp130 ligands. Dissection of the LIF-gp130 interface, along with comparative studies of other gp130 cytokines, reveal that gp130 has evolved a "thermodynamic plasticity" that is relatively insensitive to ligand structure, to enable crossreactivity. These observations reveal a novel and alternative mechanism for degenerate recognition from that of structural plasticity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Gp130 is a shared cell-surface signaling receptor for at least ten different hematopoietic cytokines, but the basis of its degenerate recognition properties is unknown. We have determined the crystal structure of human leukemia inhibitory factor (LIF) bound to the cytokine binding region (CHR) of gp130 at 2.5 A resolution. Strikingly, we find that the shared binding site on gp130 has an entirely rigid core, while the LIF binding interface diverges sharply in structure and chemistry from that of other gp130 ligands. Dissection of the LIF-gp130 interface, along with comparative studies of other gp130 cytokines, reveal that gp130 has evolved a "thermodynamic plasticity" that is relatively insensitive to ligand structure, to enable crossreactivity. These observations reveal a novel and alternative mechanism for degenerate recognition from that of structural plasticity.
Lisa N Kinch, David Baker, Nick V Grishin
Deciphering a novel thioredoxin-like fold family Journal Article
In: Proteins, vol. 52, pp. 323-31, 2003, ISSN: 1097-0134.
@article{573,
title = {Deciphering a novel thioredoxin-like fold family},
author = { Lisa N Kinch and David Baker and Nick V Grishin},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/decipheringanovel_Baker2003.pdf},
doi = {10.1002/prot.10425},
issn = {1097-0134},
year = {2003},
date = {2003-08-01},
journal = {Proteins},
volume = {52},
pages = {323-31},
abstract = {Sequence--and structure-based searching strategies have proven useful in the identification of remote homologs and have facilitated both structural and functional predictions of many uncharacterized protein families. We implement these strategies to predict the structure of and to classify a previously uncharacterized cluster of orthologs (COG3019) in the thioredoxin-like fold superfamily. The results of each searching method indicate that thioltransferases are the closest structural family to COG3019. We substantiate this conclusion using the ab initio structure prediction method rosetta, which generates a thioredoxin-like fold similar to that of the glutaredoxin-like thioltransferase (NrdH) for a COG3019 target sequence. This structural model contains the thiol-redox functional motif CYS-X-X-CYS in close proximity to other absolutely conserved COG3019 residues, defining a novel thioredoxin-like active site that potentially binds metal ions. Finally, the rosetta-derived model structure assists us in assembling a global multiple-sequence alignment of COG3019 with two other thioredoxin-like fold families, the thioltransferases and the bacterial arsenate reductases (ArsC).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sequence–and structure-based searching strategies have proven useful in the identification of remote homologs and have facilitated both structural and functional predictions of many uncharacterized protein families. We implement these strategies to predict the structure of and to classify a previously uncharacterized cluster of orthologs (COG3019) in the thioredoxin-like fold superfamily. The results of each searching method indicate that thioltransferases are the closest structural family to COG3019. We substantiate this conclusion using the ab initio structure prediction method rosetta, which generates a thioredoxin-like fold similar to that of the glutaredoxin-like thioltransferase (NrdH) for a COG3019 target sequence. This structural model contains the thiol-redox functional motif CYS-X-X-CYS in close proximity to other absolutely conserved COG3019 residues, defining a novel thioredoxin-like active site that potentially binds metal ions. Finally, the rosetta-derived model structure assists us in assembling a global multiple-sequence alignment of COG3019 with two other thioredoxin-like fold families, the thioltransferases and the bacterial arsenate reductases (ArsC).
Ora Schueler-Furman, David Baker
Conserved residue clustering and protein structure prediction Journal Article
In: Proteins, vol. 52, pp. 225-35, 2003, ISSN: 1097-0134.
@article{75,
title = {Conserved residue clustering and protein structure prediction},
author = { Ora Schueler-Furman and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/schueler-furman03A.pdf},
issn = {1097-0134},
year = {2003},
date = {2003-08-01},
journal = {Proteins},
volume = {52},
pages = {225-35},
abstract = {Protein residues that are critical for structure and function are expected to be conserved throughout evolution. Here, we investigate the extent to which these conserved residues are clustered in three-dimensional protein structures. In 92% of the proteins in a data set of 79 proteins, the most conserved positions in multiple sequence alignments are significantly more clustered than randomly selected sets of positions. The comparison to random subsets is not necessarily appropriate, however, because the signal could be the result of differences in the amino acid composition of sets of conserved residues compared to random subsets (hydrophobic residues tend to be close together in the protein core), or differences in sequence separation of the residues in the different sets. In order to overcome these limits, we compare the degree of clustering of the conserved positions on the native structure and on alternative conformations generated by the de novo structure prediction method Rosetta. For 65% of the 79 proteins, the conserved residues are significantly more clustered in the native structure than in the alternative conformations, indicating that the clustering of conserved residues in protein structures goes beyond that expected purely from sequence locality and composition effects. The differences in the spatial distribution of conserved residues can be utilized in de novo protein structure prediction: We find that for 79% of the proteins, selection of the Rosetta generated conformations with the greatest clustering of the conserved residues significantly enriches the fraction of close-to-native structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein residues that are critical for structure and function are expected to be conserved throughout evolution. Here, we investigate the extent to which these conserved residues are clustered in three-dimensional protein structures. In 92% of the proteins in a data set of 79 proteins, the most conserved positions in multiple sequence alignments are significantly more clustered than randomly selected sets of positions. The comparison to random subsets is not necessarily appropriate, however, because the signal could be the result of differences in the amino acid composition of sets of conserved residues compared to random subsets (hydrophobic residues tend to be close together in the protein core), or differences in sequence separation of the residues in the different sets. In order to overcome these limits, we compare the degree of clustering of the conserved positions on the native structure and on alternative conformations generated by the de novo structure prediction method Rosetta. For 65% of the 79 proteins, the conserved residues are significantly more clustered in the native structure than in the alternative conformations, indicating that the clustering of conserved residues in protein structures goes beyond that expected purely from sequence locality and composition effects. The differences in the spatial distribution of conserved residues can be utilized in de novo protein structure prediction: We find that for 79% of the proteins, selection of the Rosetta generated conformations with the greatest clustering of the conserved residues significantly enriches the fraction of close-to-native structures.
Jeffrey J Gray, Stewart Moughon, Chu Wang, Ora Schueler-Furman, Brian Kuhlman, Carol A Rohl, David Baker
Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations Journal Article
In: Journal of molecular biology, vol. 331, pp. 281-99, 2003, ISSN: 0022-2836.
@article{85,
title = {Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations},
author = { Jeffrey J Gray and Stewart Moughon and Chu Wang and Ora Schueler-Furman and Brian Kuhlman and Carol A Rohl and David Baker},
issn = {0022-2836},
year = {2003},
date = {2003-08-01},
journal = {Journal of molecular biology},
volume = {331},
pages = {281-99},
abstract = {Protein-protein docking algorithms provide a means to elucidate structural details for presently unknown complexes. Here, we present and evaluate a new method to predict protein-protein complexes from the coordinates of the unbound monomer components. The method employs a low-resolution, rigid-body, Monte Carlo search followed by simultaneous optimization of backbone displacement and side-chain conformations using Monte Carlo minimization. Up to 10(5) independent simulations are carried out, and the resulting "decoys" are ranked using an energy function dominated by van der Waals interactions, an implicit solvation model, and an orientation-dependent hydrogen bonding potential. Top-ranking decoys are clustered to select the final predictions. Small-perturbation studies reveal the formation of binding funnels in 42 of 54 cases using coordinates derived from the bound complexes and in 32 of 54 cases using independently determined coordinates of one or both monomers. Experimental binding affinities correlate with the calculated score function and explain the predictive success or failure of many targets. Global searches using one or both unbound components predict at least 25% of the native residue-residue contacts in 28 of the 32 cases where binding funnels exist. The results suggest that the method may soon be useful for generating models of biologically important complexes from the structures of the isolated components, but they also highlight the challenges that must be met to achieve consistent and accurate prediction of protein-protein interactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-protein docking algorithms provide a means to elucidate structural details for presently unknown complexes. Here, we present and evaluate a new method to predict protein-protein complexes from the coordinates of the unbound monomer components. The method employs a low-resolution, rigid-body, Monte Carlo search followed by simultaneous optimization of backbone displacement and side-chain conformations using Monte Carlo minimization. Up to 10(5) independent simulations are carried out, and the resulting “decoys” are ranked using an energy function dominated by van der Waals interactions, an implicit solvation model, and an orientation-dependent hydrogen bonding potential. Top-ranking decoys are clustered to select the final predictions. Small-perturbation studies reveal the formation of binding funnels in 42 of 54 cases using coordinates derived from the bound complexes and in 32 of 54 cases using independently determined coordinates of one or both monomers. Experimental binding affinities correlate with the calculated score function and explain the predictive success or failure of many targets. Global searches using one or both unbound components predict at least 25% of the native residue-residue contacts in 28 of the 32 cases where binding funnels exist. The results suggest that the method may soon be useful for generating models of biologically important complexes from the structures of the isolated components, but they also highlight the challenges that must be met to achieve consistent and accurate prediction of protein-protein interactions.
Jeffrey J Gray, Stewart E Moughon, Tanja Kortemme, Ora Schueler-Furman, Kira M S Misura, Alexandre V Morozov, David Baker
Protein-protein docking predictions for the CAPRI experiment Journal Article
In: Proteins, vol. 52, pp. 118-22, 2003, ISSN: 1097-0134.
@article{86,
title = {Protein-protein docking predictions for the CAPRI experiment},
author = { Jeffrey J Gray and Stewart E Moughon and Tanja Kortemme and Ora Schueler-Furman and Kira M S Misura and Alexandre V Morozov and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/gray03B.pdf},
issn = {1097-0134},
year = {2003},
date = {2003-07-01},
journal = {Proteins},
volume = {52},
pages = {118-22},
abstract = {We predicted structures for all seven targets in the CAPRI experiment using a new method in development at the time of the challenge. The technique includes a low-resolution rigid body Monte Carlo search followed by high-resolution refinement with side-chain conformational changes and rigid body minimization. Decoys (approximately 10(6) per target) were discriminated using a scoring function including van der Waals and solvation interactions, hydrogen bonding, residue-residue pair statistics, and rotamer probabilities. Decoys were ranked, clustered, manually inspected, and selected. The top ranked model for target 6 predicted the experimental structure to 1.5 A RMSD and included 48 of 65 correct residue-residue contacts. Target 7 was predicted at 5.3 A RMSD with 22 of 37 correct residue-residue contacts using a homology model from a known complex structure. Using a preliminary version of the protocol in round 1, target 1 was predicted within 8.8 A although few contacts were correct. For targets 2 and 3, the interface locations and a small fraction of the contacts were correctly identified.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We predicted structures for all seven targets in the CAPRI experiment using a new method in development at the time of the challenge. The technique includes a low-resolution rigid body Monte Carlo search followed by high-resolution refinement with side-chain conformational changes and rigid body minimization. Decoys (approximately 10(6) per target) were discriminated using a scoring function including van der Waals and solvation interactions, hydrogen bonding, residue-residue pair statistics, and rotamer probabilities. Decoys were ranked, clustered, manually inspected, and selected. The top ranked model for target 6 predicted the experimental structure to 1.5 A RMSD and included 48 of 65 correct residue-residue contacts. Target 7 was predicted at 5.3 A RMSD with 22 of 37 correct residue-residue contacts using a homology model from a known complex structure. Using a preliminary version of the protocol in round 1, target 1 was predicted within 8.8 A although few contacts were correct. For targets 2 and 3, the interface locations and a small fraction of the contacts were correctly identified.
Oscar Millet, Anthony Mittermaier, David Baker, Lewis E Kay
The effects of mutations on motions of side-chains in protein L studied by 2H NMR dynamics and scalar couplings Journal Article
In: Journal of molecular biology, vol. 329, pp. 551-63, 2003, ISSN: 0022-2836.
@article{78,
title = {The effects of mutations on motions of side-chains in protein L studied by 2H NMR dynamics and scalar couplings},
author = { Oscar Millet and Anthony Mittermaier and David Baker and Lewis E Kay},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/millet03A.pdf},
issn = {0022-2836},
year = {2003},
date = {2003-06-01},
journal = {Journal of molecular biology},
volume = {329},
pages = {551-63},
abstract = {Recently developed 2H spin relaxation experiments are applied to study the dynamics of methyl-containing side-chains in the B1 domain of protein L and in a pair of point mutants of the domain, F22L and A20V. X-ray and NMR studies of the three variants of protein L studied here establish that their structures are very similar, despite the fact that the F22L mutant is 3.2kcal/mol less stable. Measurements of methyl 2H spin relaxation rates, which probe dynamics on a picosecond-nanosecond time scale, and three-bond 3J(Cgamma-CO), 3J(Cgamma-N) and 3J(Calpha-Cdelta) scalar coupling constants, which are sensitive to motion spanning a wide range of time-scales, reveal changes in the magnitude of side-chain dynamics in response to mutation. Observed differences in the time-scale of motions between the variants have been related to changes in energetic barriers. Of interest, several of the residues with different motional properties across the variants are far from the site of mutation, suggesting the presence of long-range interactions within the protein that can be probed through studies of dynamics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recently developed 2H spin relaxation experiments are applied to study the dynamics of methyl-containing side-chains in the B1 domain of protein L and in a pair of point mutants of the domain, F22L and A20V. X-ray and NMR studies of the three variants of protein L studied here establish that their structures are very similar, despite the fact that the F22L mutant is 3.2kcal/mol less stable. Measurements of methyl 2H spin relaxation rates, which probe dynamics on a picosecond-nanosecond time scale, and three-bond 3J(Cgamma-CO), 3J(Cgamma-N) and 3J(Calpha-Cdelta) scalar coupling constants, which are sensitive to motion spanning a wide range of time-scales, reveal changes in the magnitude of side-chain dynamics in response to mutation. Observed differences in the time-scale of motions between the variants have been related to changes in energetic barriers. Of interest, several of the residues with different motional properties across the variants are far from the site of mutation, suggesting the presence of long-range interactions within the protein that can be probed through studies of dynamics.
Qian Yi, Ponni Rajagopal, Rachel E Klevit, David Baker
Structural and kinetic characterization of the simplified SH3 domain FP1 Journal Article
In: Protein science, vol. 12, pp. 776-83, 2003, ISSN: 0961-8368.
@article{72,
title = {Structural and kinetic characterization of the simplified SH3 domain FP1},
author = { Qian Yi and Ponni Rajagopal and Rachel E Klevit and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/yi03A.pdf},
issn = {0961-8368},
year = {2003},
date = {2003-04-01},
journal = {Protein science},
volume = {12},
pages = {776-83},
abstract = {The simplified SH3 domain sequence, FP1, obtained in phage display selection experiments has an amino acid composition that is 95% Ile, Lys, Glu, Ala, Gly. Here we use NMR to investigate the tertiary structure of FP1. We find that the overall topology of FP1 resembles that of the src SH3 domain, the hydrogen-deuterium exchange and chemical shift perturbation profiles are similar to those of naturally occurring SH3 domains, and the (15)N relaxation rates are in the range of naturally occurring small proteins. Guided by the structure, we further simplify the FP1 sequence and compare the effects on folding kinetics of point mutations in FP1 and the wild-type src SH3 domain. The results suggest that the folding transition state of FP1 is similar to but somewhat less polarized than that of the wild-type src SH3 domain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The simplified SH3 domain sequence, FP1, obtained in phage display selection experiments has an amino acid composition that is 95% Ile, Lys, Glu, Ala, Gly. Here we use NMR to investigate the tertiary structure of FP1. We find that the overall topology of FP1 resembles that of the src SH3 domain, the hydrogen-deuterium exchange and chemical shift perturbation profiles are similar to those of naturally occurring SH3 domains, and the (15)N relaxation rates are in the range of naturally occurring small proteins. Guided by the structure, we further simplify the FP1 sequence and compare the effects on folding kinetics of point mutations in FP1 and the wild-type src SH3 domain. The results suggest that the folding transition state of FP1 is similar to but somewhat less polarized than that of the wild-type src SH3 domain.
Benjamin J McFarland, Tanja Kortemme, Shuyuarn F Yu, David Baker, Roland K Strong
Symmetry recognizing asymmetry: analysis of the interactions between the C-type lectin-like immunoreceptor NKG2D and MHC class I-like ligands Journal Article
In: Structure, vol. 11, pp. 411-22, 2003, ISSN: 0969-2126.
@article{81,
title = {Symmetry recognizing asymmetry: analysis of the interactions between the C-type lectin-like immunoreceptor NKG2D and MHC class I-like ligands},
author = { Benjamin J McFarland and Tanja Kortemme and Shuyuarn F Yu and David Baker and Roland K Strong},
issn = {0969-2126},
year = {2003},
date = {2003-04-01},
journal = {Structure},
volume = {11},
pages = {411-22},
abstract = {Engagement of diverse protein ligands (MIC-A/B, ULBP, Rae-1, or H60) by NKG2D immunoreceptors mediates elimination of tumorigenic or virally infected cells by natural killer and T cells. Three previous NKG2D-ligand complex structures show the homodimeric receptor interacting with the monomeric ligands in similar 2:1 complexes, with an equivalent surface on each NKG2D monomer binding intimately to a total of six distinct ligand surfaces. Here, the crystal structure of free human NKG2D and in silico and in vitro alanine-scanning mutagenesis analyses of the complex interfaces indicate that NKG2D recognition degeneracy is not explained by a classical induced-fit mechanism. Rather, the divergent ligands appear to utilize different strategies to interact with structurally conserved elements of the consensus NKG2D binding site.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Engagement of diverse protein ligands (MIC-A/B, ULBP, Rae-1, or H60) by NKG2D immunoreceptors mediates elimination of tumorigenic or virally infected cells by natural killer and T cells. Three previous NKG2D-ligand complex structures show the homodimeric receptor interacting with the monomeric ligands in similar 2:1 complexes, with an equivalent surface on each NKG2D monomer binding intimately to a total of six distinct ligand surfaces. Here, the crystal structure of free human NKG2D and in silico and in vitro alanine-scanning mutagenesis analyses of the complex interfaces indicate that NKG2D recognition degeneracy is not explained by a classical induced-fit mechanism. Rather, the divergent ligands appear to utilize different strategies to interact with structurally conserved elements of the consensus NKG2D binding site.
Tanja Kortemme, Alexandre V Morozov, David Baker
An orientation-dependent hydrogen bonding potential improves prediction of specificity and structure for proteins and protein-protein complexes Journal Article
In: Journal of molecular biology, vol. 326, pp. 1239-59, 2003, ISSN: 0022-2836.
@article{83,
title = {An orientation-dependent hydrogen bonding potential improves prediction of specificity and structure for proteins and protein-protein complexes},
author = { Tanja Kortemme and Alexandre V Morozov and David Baker},
issn = {0022-2836},
year = {2003},
date = {2003-02-01},
journal = {Journal of molecular biology},
volume = {326},
pages = {1239-59},
abstract = {Hydrogen bonding is a key contributor to the specificity of intramolecular and intermolecular interactions in biological systems. Here, we develop an orientation-dependent hydrogen bonding potential based on the geometric characteristics of hydrogen bonds in high-resolution protein crystal structures, and evaluate it using four tests related to the prediction and design of protein structures and protein-protein complexes. The new potential is superior to the widely used Coulomb model of hydrogen bonding in prediction of the sequences of proteins and protein-protein interfaces from their structures, and improves discrimination of correctly docked protein-protein complexes from large sets of alternative structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hydrogen bonding is a key contributor to the specificity of intramolecular and intermolecular interactions in biological systems. Here, we develop an orientation-dependent hydrogen bonding potential based on the geometric characteristics of hydrogen bonds in high-resolution protein crystal structures, and evaluate it using four tests related to the prediction and design of protein structures and protein-protein complexes. The new potential is superior to the widely used Coulomb model of hydrogen bonding in prediction of the sequences of proteins and protein-protein interfaces from their structures, and improves discrimination of correctly docked protein-protein complexes from large sets of alternative structures.
Michelle Scalley-Kim, Philippe Minard, David Baker
Low free energy cost of very long loop insertions in proteins Journal Article
In: Protein science, vol. 12, pp. 197-206, 2003, ISSN: 0961-8368.
@article{76,
title = {Low free energy cost of very long loop insertions in proteins},
author = { Michelle Scalley-Kim and Philippe Minard and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/scalley-kim03A.pdf},
issn = {0961-8368},
year = {2003},
date = {2003-02-01},
journal = {Protein science},
volume = {12},
pages = {197-206},
abstract = {Long insertions into a loop of a folded host protein are expected to have destabilizing effects because of the entropic cost associated with loop closure unless the inserted sequence adopts a folded structure with amino- and carboxy-termini in close proximity. A loop entropy reduction screen based on this concept was used in an attempt to retrieve folded sequences from random sequence libraries. A library of long random sequences was inserted into a loop of the SH2 domain, displayed on the surface of M13 phage, and the inserted sequences that did not disrupt SH2 function were retrieved by panning using beads coated with a phosphotyrosine containing SH2 peptide ligand. Two sequences of a library of 2 x 10(8) sequences were isolated after multiple rounds of panning, and were found to have recovery levels similar to the wild-type SH2 domain and to be relatively intolerant to further mutation in PCR mutagenesis experiments. Surprisingly, although these inserted sequences exhibited little nonrandom structure, they do not significantly destabilize the host SH2 domain. Additional insertion variants recovered at lower levels in the panning experiments were also found to have a minimal effect on the stability and peptide-binding function of the SH2 domain. The additional level of selection present in the panning experiments is likely to involve in vivo folding and assembly, as there was a rough correlation between recovery levels in the phage-panning experiments and protein solubility. The finding that loop insertions of 60-80 amino acids have minimal effects on SH2 domain stability suggests that the free energy cost of inserting long loops may be considerably less than polymer theory estimates based on the entropic cost of loop closure, and, hence, that loop insertion may have provided an evolutionary route to multidomain protein structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Long insertions into a loop of a folded host protein are expected to have destabilizing effects because of the entropic cost associated with loop closure unless the inserted sequence adopts a folded structure with amino- and carboxy-termini in close proximity. A loop entropy reduction screen based on this concept was used in an attempt to retrieve folded sequences from random sequence libraries. A library of long random sequences was inserted into a loop of the SH2 domain, displayed on the surface of M13 phage, and the inserted sequences that did not disrupt SH2 function were retrieved by panning using beads coated with a phosphotyrosine containing SH2 peptide ligand. Two sequences of a library of 2 x 10(8) sequences were isolated after multiple rounds of panning, and were found to have recovery levels similar to the wild-type SH2 domain and to be relatively intolerant to further mutation in PCR mutagenesis experiments. Surprisingly, although these inserted sequences exhibited little nonrandom structure, they do not significantly destabilize the host SH2 domain. Additional insertion variants recovered at lower levels in the panning experiments were also found to have a minimal effect on the stability and peptide-binding function of the SH2 domain. The additional level of selection present in the panning experiments is likely to involve in vivo folding and assembly, as there was a rough correlation between recovery levels in the phage-panning experiments and protein solubility. The finding that loop insertions of 60-80 amino acids have minimal effects on SH2 domain stability suggests that the free energy cost of inserting long loops may be considerably less than polymer theory estimates based on the entropic cost of loop closure, and, hence, that loop insertion may have provided an evolutionary route to multidomain protein structures.
A Morozov, T Kortemme, David Baker
Evaluation of Models of Electrostatic Interactions in Proteins Journal Article
In: Journal of Physical Chemistry B, vol. 107, pp. 2075-2090, 2003.
@article{77,
title = {Evaluation of Models of Electrostatic Interactions in Proteins},
author = { A Morozov and T Kortemme and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/morozov03A.pdf
http://pubs.acs.org/doi/pdf/10.1021/jp0267555},
year = {2003},
date = {2003-02-01},
journal = {Journal of Physical Chemistry B},
volume = {107},
pages = {2075-2090},
chapter = {2075},
abstract = {The conformations of proteins and protein-protein complexes observed in nature must be low in free energy relative to alternative (not observed) conformations, and it is plausible (but not absolutely necessary) that the electrostatic free energies of experimentally observed conformations are also low relative to other conformations. Starting from this assumption, we evaluate alternative models of electrostatic interactions in proteins by comparing the electrostatic free energies of native, nativelike, and non-native structures. We observe that the total electrostatic free energy computed using the Poisson-Boltzmann (PB) equation or the generalized Born (GB) model exhibits free energy gaps that are comparable to, or smaller than, the free energy gaps resulting from Coulomb interactions alone. Detailed characterization of the contributions of different atom types to the total electrostatic free energy showed that, although for most atoms unfavorable solvation energies associated with atom burial are more than compensated by attractive Coulomb interactions, Coulomb interactions do not become more favorable with burial for certain backbone atom types, suggesting inaccuracies in the treatment of backbone electrostatics. Sizable free energy gaps are obtained using simple distance-dependent dielectric models, suggesting their usefulness in approximating the attenuation of long range Coulomb interactions by induced polarization effects. Hydrogen bonding interactions appear to be better modeled with an explicitly orientation-dependent hydrogen bonding potential than with any of the purely electrostatic models of hydrogen bonds, as there are larger free energy gaps with the former. Finally, a combined electrostatics-hydrogen bonding potential is developed that appears to better capture the free energy differences between native, nativelike, and non-native proteins and protein-protein complexes than electrostatic or hydrogen bonding models alone.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The conformations of proteins and protein-protein complexes observed in nature must be low in free energy relative to alternative (not observed) conformations, and it is plausible (but not absolutely necessary) that the electrostatic free energies of experimentally observed conformations are also low relative to other conformations. Starting from this assumption, we evaluate alternative models of electrostatic interactions in proteins by comparing the electrostatic free energies of native, nativelike, and non-native structures. We observe that the total electrostatic free energy computed using the Poisson-Boltzmann (PB) equation or the generalized Born (GB) model exhibits free energy gaps that are comparable to, or smaller than, the free energy gaps resulting from Coulomb interactions alone. Detailed characterization of the contributions of different atom types to the total electrostatic free energy showed that, although for most atoms unfavorable solvation energies associated with atom burial are more than compensated by attractive Coulomb interactions, Coulomb interactions do not become more favorable with burial for certain backbone atom types, suggesting inaccuracies in the treatment of backbone electrostatics. Sizable free energy gaps are obtained using simple distance-dependent dielectric models, suggesting their usefulness in approximating the attenuation of long range Coulomb interactions by induced polarization effects. Hydrogen bonding interactions appear to be better modeled with an explicitly orientation-dependent hydrogen bonding potential than with any of the purely electrostatic models of hydrogen bonds, as there are larger free energy gaps with the former. Finally, a combined electrostatics-hydrogen bonding potential is developed that appears to better capture the free energy differences between native, nativelike, and non-native proteins and protein-protein complexes than electrostatic or hydrogen bonding models alone.
Dylan Chivian, Timothy Robertson, Richard Bonneau, David Baker
Ab initio methods Journal Article
In: Methods of biochemical analysis, vol. 44, pp. 547-57, 2003, ISSN: 0076-6941.
@article{89,
title = {Ab initio methods},
author = { Dylan Chivian and Timothy Robertson and Richard Bonneau and David Baker},
issn = {0076-6941},
year = {2003},
date = {2003-00-01},
journal = {Methods of biochemical analysis},
volume = {44},
pages = {547-57},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dylan Chivian, David E Kim, Lars Malmstr"om, Philip Bradley, Timothy Robertson, Paul Murphy, Charles E M Strauss, Richard Bonneau, Carol A Rohl, David Baker
Automated prediction of CASP-5 structures using the Robetta server Journal Article
In: Proteins, vol. 53 Suppl 6, pp. 524-33, 2003, ISSN: 1097-0134.
@article{88,
title = {Automated prediction of CASP-5 structures using the Robetta server},
author = { Dylan Chivian and David E Kim and Lars Malmstr"om and Philip Bradley and Timothy Robertson and Paul Murphy and Charles E M Strauss and Richard Bonneau and Carol A Rohl and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/chivian03A.pdf},
issn = {1097-0134},
year = {2003},
date = {2003-00-01},
journal = {Proteins},
volume = {53 Suppl 6},
pages = {524-33},
abstract = {Robetta is a fully automated protein structure prediction server that uses the Rosetta fragment-insertion method. It combines template-based and de novo structure prediction methods in an attempt to produce high quality models that cover every residue of a submitted sequence. The first step in the procedure is the automatic detection of the locations of domains and selection of the appropriate modeling protocol for each domain. For domains matched to a homolog with an experimentally characterized structure by PSI-BLAST or Pcons2, Robetta uses a new alignment method, called K*Sync, to align the query sequence onto the parent structure. It then models the variable regions by allowing them to explore conformational space with fragments in fashion similar to the de novo protocol, but in the context of the template. When no structural homolog is available, domains are modeled with the Rosetta de novo protocol, which allows the full length of the domain to explore conformational space via fragment-insertion, producing a large decoy ensemble from which the final models are selected. The Robetta server produced quite reasonable predictions for targets in the recent CASP-5 and CAFASP-3 experiments, some of which were at the level of the best human predictions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Robetta is a fully automated protein structure prediction server that uses the Rosetta fragment-insertion method. It combines template-based and de novo structure prediction methods in an attempt to produce high quality models that cover every residue of a submitted sequence. The first step in the procedure is the automatic detection of the locations of domains and selection of the appropriate modeling protocol for each domain. For domains matched to a homolog with an experimentally characterized structure by PSI-BLAST or Pcons2, Robetta uses a new alignment method, called K*Sync, to align the query sequence onto the parent structure. It then models the variable regions by allowing them to explore conformational space with fragments in fashion similar to the de novo protocol, but in the context of the template. When no structural homolog is available, domains are modeled with the Rosetta de novo protocol, which allows the full length of the domain to explore conformational space via fragment-insertion, producing a large decoy ensemble from which the final models are selected. The Robetta server produced quite reasonable predictions for targets in the recent CASP-5 and CAFASP-3 experiments, some of which were at the level of the best human predictions.
Philip Bradley, Dylan Chivian, Jens Meiler, Kira M S Misura, Carol A Rohl, William R Schief, William J Wedemeyer, Ora Schueler-Furman, Paul Murphy, Jack Schonbrun, Charles E M Strauss, David Baker
Rosetta predictions in CASP5: successes, failures, and prospects for complete automation Journal Article
In: Proteins, vol. 53 Suppl 6, pp. 457-68, 2003, ISSN: 1097-0134.
@article{90,
title = {Rosetta predictions in CASP5: successes, failures, and prospects for complete automation},
author = { Philip Bradley and Dylan Chivian and Jens Meiler and Kira M S Misura and Carol A Rohl and William R Schief and William J Wedemeyer and Ora Schueler-Furman and Paul Murphy and Jack Schonbrun and Charles E M Strauss and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bradley03A.pdf},
issn = {1097-0134},
year = {2003},
date = {2003-00-01},
journal = {Proteins},
volume = {53 Suppl 6},
pages = {457-68},
abstract = {We describe predictions of the structures of CASP5 targets using Rosetta. The Rosetta fragment insertion protocol was used to generate models for entire target domains without detectable sequence similarity to a protein of known structure and to build long loop insertions (and N-and C-terminal extensions) in cases where a structural template was available. Encouraging results were obtained both for the de novo predictions and for the long loop insertions; we describe here the successes as well as the failures in the context of current efforts to improve the Rosetta method. In particular, de novo predictions failed for large proteins that were incorrectly parsed into domains and for topologically complex (high contact order) proteins with swapping of segments between domains. However, for the remaining targets, at least one of the five submitted models had a long fragment with significant similarity to the native structure. A fully automated version of the CASP5 protocol produced results that were comparable to the human-assisted predictions for most of the targets, suggesting that automated genomic-scale, de novo protein structure prediction may soon be worthwhile. For the three targets where the human-assisted predictions were significantly closer to the native structure, we identify the steps that remain to be automated.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe predictions of the structures of CASP5 targets using Rosetta. The Rosetta fragment insertion protocol was used to generate models for entire target domains without detectable sequence similarity to a protein of known structure and to build long loop insertions (and N-and C-terminal extensions) in cases where a structural template was available. Encouraging results were obtained both for the de novo predictions and for the long loop insertions; we describe here the successes as well as the failures in the context of current efforts to improve the Rosetta method. In particular, de novo predictions failed for large proteins that were incorrectly parsed into domains and for topologically complex (high contact order) proteins with swapping of segments between domains. However, for the remaining targets, at least one of the five submitted models had a long fragment with significant similarity to the native structure. A fully automated version of the CASP5 protocol produced results that were comparable to the human-assisted predictions for most of the targets, suggesting that automated genomic-scale, de novo protein structure prediction may soon be worthwhile. For the three targets where the human-assisted predictions were significantly closer to the native structure, we identify the steps that remain to be automated.
2002
Sehat Nauli, Brian Kuhlman, Isolde Le Trong, Ronald E Stenkamp, David Teller, David Baker
Crystal structures and increased stabilization of the protein G variants with switched folding pathways NuG1 and NuG2 Journal Article
In: Protein science, vol. 11, pp. 2924-31, 2002, ISSN: 0961-8368.
@article{189,
title = {Crystal structures and increased stabilization of the protein G variants with switched folding pathways NuG1 and NuG2},
author = { Sehat Nauli and Brian Kuhlman and Isolde Le Trong and Ronald E Stenkamp and David Teller and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/nauli02A.pdf},
issn = {0961-8368},
year = {2002},
date = {2002-12-01},
journal = {Protein science},
volume = {11},
pages = {2924-31},
abstract = {We recently described two protein G variants (NuG1 and NuG2) with redesigned first hairpins that were almost twice as stable, folded 100-fold faster, and had a switched folding mechanism relative to the wild-type protein. To test the structural accuracy of our design algorithm and to provide insights to the dramatic changes in the kinetics and thermodynamics of folding, we have now determined the crystal structures of NuG1 and NuG2 to 1.8 A and 1.85 A, respectively. We find that they adopt hairpin structures that are closer to the computational models than to wild-type protein G; the RMSD of the NuG1 hairpin to the design model and the wild-type structure are 1.7 A and 5.1 A, respectively. The crystallographic B factor in the redesigned first hairpin of NuG1 is systematically higher than the second hairpin, suggesting that the redesigned region is somewhat less rigid. A second round of structure-based design yielded new variants of NuG1 and NuG2, which are further stabilized by 0.5 kcal/mole and 0.9 kcal/mole.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We recently described two protein G variants (NuG1 and NuG2) with redesigned first hairpins that were almost twice as stable, folded 100-fold faster, and had a switched folding mechanism relative to the wild-type protein. To test the structural accuracy of our design algorithm and to provide insights to the dramatic changes in the kinetics and thermodynamics of folding, we have now determined the crystal structures of NuG1 and NuG2 to 1.8 A and 1.85 A, respectively. We find that they adopt hairpin structures that are closer to the computational models than to wild-type protein G; the RMSD of the NuG1 hairpin to the design model and the wild-type structure are 1.7 A and 5.1 A, respectively. The crystallographic B factor in the redesigned first hairpin of NuG1 is systematically higher than the second hairpin, suggesting that the redesigned region is somewhat less rigid. A second round of structure-based design yielded new variants of NuG1 and NuG2, which are further stabilized by 0.5 kcal/mole and 0.9 kcal/mole.
Tanja Kortemme, David Baker
A simple physical model for binding energy hot spots in protein-protein complexes Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 99, pp. 14116-21, 2002, ISSN: 0027-8424.
@article{186,
title = {A simple physical model for binding energy hot spots in protein-protein complexes},
author = { Tanja Kortemme and David Baker},
issn = {0027-8424},
year = {2002},
date = {2002-10-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {99},
pages = {14116-21},
abstract = {Protein-protein recognition plays a central role in most biological processes. Although the structures of many protein-protein complexes have been solved in molecular detail, general rules describing affinity and selectivity of protein-protein interactions do not accurately account for the extremely diverse nature of the interfaces. We investigate the extent to which a simple physical model can account for the wide range of experimentally measured free energy changes brought about by alanine mutation at protein-protein interfaces. The model successfully predicts the results of alanine scanning experiments on globular proteins (743 mutations) and 19 protein-protein interfaces (233 mutations) with average unsigned errors of 0.81 kcal/mol and 1.06 kcal/mol, respectively. The results test our understanding of the dominant contributions to the free energy of protein-protein interactions, can guide experiments aimed at the design of protein interaction inhibitors, and provide a stepping-stone to important applications such as interface redesign.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein-protein recognition plays a central role in most biological processes. Although the structures of many protein-protein complexes have been solved in molecular detail, general rules describing affinity and selectivity of protein-protein interactions do not accurately account for the extremely diverse nature of the interfaces. We investigate the extent to which a simple physical model can account for the wide range of experimentally measured free energy changes brought about by alanine mutation at protein-protein interfaces. The model successfully predicts the results of alanine scanning experiments on globular proteins (743 mutations) and 19 protein-protein interfaces (233 mutations) with average unsigned errors of 0.81 kcal/mol and 1.06 kcal/mol, respectively. The results test our understanding of the dominant contributions to the free energy of protein-protein interactions, can guide experiments aimed at the design of protein interaction inhibitors, and provide a stepping-stone to important applications such as interface redesign.
Brett S Chevalier, Tanja Kortemme, Meggen S Chadsey, David Baker, Raymond J Monnat, Barry L Stoddard
Design, activity, and structure of a highly specific artificial endonuclease Journal Article
In: Molecular cell, vol. 10, pp. 895-905, 2002, ISSN: 1097-2765.
@article{185,
title = {Design, activity, and structure of a highly specific artificial endonuclease},
author = { Brett S Chevalier and Tanja Kortemme and Meggen S Chadsey and David Baker and Raymond J Monnat and Barry L Stoddard},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/chevalier02A.pdf},
issn = {1097-2765},
year = {2002},
date = {2002-10-01},
journal = {Molecular cell},
volume = {10},
pages = {895-905},
abstract = {We have generated an artificial highly specific endonuclease by fusing domains of homing endonucleases I-DmoI and I-CreI and creating a new 1400 A(2) protein interface between these domains. Protein engineering was accomplished by combining computational redesign and an in vivo protein-folding screen. The resulting enzyme, E-DreI (Engineered I-DmoI/I-CreI), binds a long chimeric DNA target site with nanomolar affinity, cleaving it precisely at a rate equivalent to its natural parents. The structure of an E-DreI/DNA complex demonstrates the accuracy of the protein interface redesign algorithm and reveals how catalytic function is maintained during the creation of the new endonuclease. These results indicate that it may be possible to generate novel highly specific DNA binding proteins from homing endonucleases.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have generated an artificial highly specific endonuclease by fusing domains of homing endonucleases I-DmoI and I-CreI and creating a new 1400 A(2) protein interface between these domains. Protein engineering was accomplished by combining computational redesign and an in vivo protein-folding screen. The resulting enzyme, E-DreI (Engineered I-DmoI/I-CreI), binds a long chimeric DNA target site with nanomolar affinity, cleaving it precisely at a rate equivalent to its natural parents. The structure of an E-DreI/DNA complex demonstrates the accuracy of the protein interface redesign algorithm and reveals how catalytic function is maintained during the creation of the new endonuclease. These results indicate that it may be possible to generate novel highly specific DNA binding proteins from homing endonucleases.
Richard Bonneau, Charlie E M Strauss, Carol A Rohl, Dylan Chivian, Phillip Bradley, Lars Malmstr"om, Tim Robertson, David Baker
De novo prediction of three-dimensional structures for major protein families Journal Article
In: Journal of molecular biology, vol. 322, pp. 65-78, 2002, ISSN: 0022-2836.
@article{184,
title = {De novo prediction of three-dimensional structures for major protein families},
author = { Richard Bonneau and Charlie E M Strauss and Carol A Rohl and Dylan Chivian and Phillip Bradley and Lars Malmstr"om and Tim Robertson and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bonneau02B.pdf},
issn = {0022-2836},
year = {2002},
date = {2002-09-01},
journal = {Journal of molecular biology},
volume = {322},
pages = {65-78},
abstract = {We use the Rosetta de novo structure prediction method to produce three-dimensional structure models for all Pfam-A sequence families with average length under 150 residues and no link to any protein of known structure. To estimate the reliability of the predictions, the method was calibrated on 131 proteins of known structure. For approximately 60% of the proteins one of the top five models was correctly predicted for 50 or more residues, and for approximately 35%, the correct SCOP superfamily was identified in a structure-based search of the Protein Data Bank using one of the models. This performance is consistent with results from the fourth critical assessment of structure prediction (CASP4). Correct and incorrect predictions could be partially distinguished using a confidence function based on a combination of simulation convergence, protein length and the similarity of a given structure prediction to known protein structures. While the limited accuracy and reliability of the method precludes definitive conclusions, the Pfam models provide the only tertiary structure information available for the 12% of publicly available sequences represented by these large protein families.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We use the Rosetta de novo structure prediction method to produce three-dimensional structure models for all Pfam-A sequence families with average length under 150 residues and no link to any protein of known structure. To estimate the reliability of the predictions, the method was calibrated on 131 proteins of known structure. For approximately 60% of the proteins one of the top five models was correctly predicted for 50 or more residues, and for approximately 35%, the correct SCOP superfamily was identified in a structure-based search of the Protein Data Bank using one of the models. This performance is consistent with results from the fourth critical assessment of structure prediction (CASP4). Correct and incorrect predictions could be partially distinguished using a confidence function based on a combination of simulation convergence, protein length and the similarity of a given structure prediction to known protein structures. While the limited accuracy and reliability of the method precludes definitive conclusions, the Pfam models provide the only tertiary structure information available for the 12% of publicly available sequences represented by these large protein families.
Christopher T Saunders, David Baker
Evaluation of structural and evolutionary contributions to deleterious mutation prediction Journal Article
In: Journal of molecular biology, vol. 322, pp. 891-901, 2002, ISSN: 0022-2836.
@article{233,
title = {Evaluation of structural and evolutionary contributions to deleterious mutation prediction},
author = { Christopher T Saunders and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/saunders02A.pdf},
issn = {0022-2836},
year = {2002},
date = {2002-09-01},
journal = {Journal of molecular biology},
volume = {322},
pages = {891-901},
abstract = {Methods for automated prediction of deleterious protein mutations have utilized both structural and evolutionary information but the relative contribution of these two factors remains unclear. To address this, we have used a variety of structural and evolutionary features to create simple deleterious mutation models that have been tested on both experimental mutagenesis and human allele data. We find that the most accurate predictions are obtained using a solvent-accessibility term, the C(beta) density, and a score derived from homologous sequences, SIFT. A classification tree using these two features has a cross-validated prediction error of 20.5% on an experimental mutagenesis test set when the prior probability for deleterious and neutral cases is equal, whereas this prediction error is 28.8% and 22.2% using either the C(beta) density or SIFT alone. The improvement imparted by structure increases when fewer homologs are available: when restricted to three homologs the prediction error improves from 26.9% using SIFT alone to 22.4% using SIFT and the C(beta) density, or 24.8% using SIFT and a noisy C(beta) density term approximating the inaccuracy of ab initio structures modeled by the Rosetta method. We conclude that methods for deleterious mutation prediction should include structural information when fewer than five to ten homologs are available, and that ab initio predicted structures may soon be useful in such cases when high-resolution structures are unavailable.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Methods for automated prediction of deleterious protein mutations have utilized both structural and evolutionary information but the relative contribution of these two factors remains unclear. To address this, we have used a variety of structural and evolutionary features to create simple deleterious mutation models that have been tested on both experimental mutagenesis and human allele data. We find that the most accurate predictions are obtained using a solvent-accessibility term, the C(beta) density, and a score derived from homologous sequences, SIFT. A classification tree using these two features has a cross-validated prediction error of 20.5% on an experimental mutagenesis test set when the prior probability for deleterious and neutral cases is equal, whereas this prediction error is 28.8% and 22.2% using either the C(beta) density or SIFT alone. The improvement imparted by structure increases when fewer homologs are available: when restricted to three homologs the prediction error improves from 26.9% using SIFT alone to 22.4% using SIFT and the C(beta) density, or 24.8% using SIFT and a noisy C(beta) density term approximating the inaccuracy of ab initio structures modeled by the Rosetta method. We conclude that methods for deleterious mutation prediction should include structural information when fewer than five to ten homologs are available, and that ab initio predicted structures may soon be useful in such cases when high-resolution structures are unavailable.
Eric Alm, Alexandre V Morozov, Tanja Kortemme, David Baker
Simple physical models connect theory and experiment in protein folding kinetics Journal Article
In: Journal of molecular biology, vol. 322, pp. 463-76, 2002, ISSN: 0022-2836.
@article{182,
title = {Simple physical models connect theory and experiment in protein folding kinetics},
author = { Eric Alm and Alexandre V Morozov and Tanja Kortemme and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/alm02A.pdf},
issn = {0022-2836},
year = {2002},
date = {2002-09-01},
journal = {Journal of molecular biology},
volume = {322},
pages = {463-76},
abstract = {Our understanding of the principles underlying the protein-folding problem can be tested by developing and characterizing simple models that make predictions which can be compared to experimental data. Here we extend our earlier model of folding free energy landscapes, in which each residue is considered to be either folded as in the native state or completely disordered, by investigating the role of additional factors representing hydrogen bonding and backbone torsion strain, and by using a hybrid between the master equation approach and the simple transition state theory to evaluate kinetics near the free energy barrier in greater detail. Model calculations of folding phi-values are compared to experimental data for 19 proteins, and for more than half of these, experimental data are reproduced with correlation coefficients between r=0.41 and 0.88; calculations of transition state free energy barriers correlate with rates measured for 37 single domain proteins (r=0.69). The model provides insight into the contribution of alternative-folding pathways, the validity of quasi-equilibrium treatments of the folding landscape, and the magnitude of the Arrhenius prefactor for protein folding. Finally, we discuss the limitations of simple native-state-based models, and as a more general test of such models, provide predictions of folding rates and mechanisms for a comprehensive set of over 400 small protein domains of known structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Our understanding of the principles underlying the protein-folding problem can be tested by developing and characterizing simple models that make predictions which can be compared to experimental data. Here we extend our earlier model of folding free energy landscapes, in which each residue is considered to be either folded as in the native state or completely disordered, by investigating the role of additional factors representing hydrogen bonding and backbone torsion strain, and by using a hybrid between the master equation approach and the simple transition state theory to evaluate kinetics near the free energy barrier in greater detail. Model calculations of folding phi-values are compared to experimental data for 19 proteins, and for more than half of these, experimental data are reproduced with correlation coefficients between r=0.41 and 0.88; calculations of transition state free energy barriers correlate with rates measured for 37 single domain proteins (r=0.69). The model provides insight into the contribution of alternative-folding pathways, the validity of quasi-equilibrium treatments of the folding landscape, and the magnitude of the Arrhenius prefactor for protein folding. Finally, we discuss the limitations of simple native-state-based models, and as a more general test of such models, provide predictions of folding rates and mechanisms for a comprehensive set of over 400 small protein domains of known structure.
Richard Bonneau, Ingo Ruczinski, Jerry Tsai, David Baker
Contact order and ab initio protein structure prediction Journal Article
In: Protein science, vol. 11, pp. 1937-44, 2002, ISSN: 0961-8368.
@article{183,
title = {Contact order and ab initio protein structure prediction},
author = { Richard Bonneau and Ingo Ruczinski and Jerry Tsai and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bonneau02A.pdf},
issn = {0961-8368},
year = {2002},
date = {2002-08-01},
journal = {Protein science},
volume = {11},
pages = {1937-44},
abstract = {Although much of the motivation for experimental studies of protein folding is to obtain insights for improving protein structure prediction, there has been relatively little connection between experimental protein folding studies and computational structural prediction work in recent years. In the present study, we show that the relationship between protein folding rates and the contact order (CO) of the native structure has implications for ab initio protein structure prediction. Rosetta ab initio folding simulations produce a dearth of high CO structures and an excess of low CO structures, as expected if the computer simulations mimic to some extent the actual folding process. Consistent with this, the majority of failures in ab initio prediction in the CASP4 (critical assessment of structure prediction) experiment involved high CO structures likely to fold much more slowly than the lower CO structures for which reasonable predictions were made. This bias against high CO structures can be partially alleviated by performing large numbers of additional simulations, selecting out the higher CO structures, and eliminating the very low CO structures; this leads to a modest improvement in prediction quality. More significant improvements in predictions for proteins with complex topologies may be possible following significant increases in high-performance computing power, which will be required for thoroughly sampling high CO conformations (high CO proteins can take six orders of magnitude longer to fold than low CO proteins). Importantly for such a strategy, simulations performed for high CO structures converge much less strongly than those for low CO structures, and hence, lack of simulation convergence can indicate the need for improved sampling of high CO conformations. The parallels between Rosetta simulations and folding in vivo may extend to misfolding: The very low CO structures that accumulate in Rosetta simulations consist primarily of local up-down beta-sheets that may resemble precursors to amyloid formation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Although much of the motivation for experimental studies of protein folding is to obtain insights for improving protein structure prediction, there has been relatively little connection between experimental protein folding studies and computational structural prediction work in recent years. In the present study, we show that the relationship between protein folding rates and the contact order (CO) of the native structure has implications for ab initio protein structure prediction. Rosetta ab initio folding simulations produce a dearth of high CO structures and an excess of low CO structures, as expected if the computer simulations mimic to some extent the actual folding process. Consistent with this, the majority of failures in ab initio prediction in the CASP4 (critical assessment of structure prediction) experiment involved high CO structures likely to fold much more slowly than the lower CO structures for which reasonable predictions were made. This bias against high CO structures can be partially alleviated by performing large numbers of additional simulations, selecting out the higher CO structures, and eliminating the very low CO structures; this leads to a modest improvement in prediction quality. More significant improvements in predictions for proteins with complex topologies may be possible following significant increases in high-performance computing power, which will be required for thoroughly sampling high CO conformations (high CO proteins can take six orders of magnitude longer to fold than low CO proteins). Importantly for such a strategy, simulations performed for high CO structures converge much less strongly than those for low CO structures, and hence, lack of simulation convergence can indicate the need for improved sampling of high CO conformations. The parallels between Rosetta simulations and folding in vivo may extend to misfolding: The very low CO structures that accumulate in Rosetta simulations consist primarily of local up-down beta-sheets that may resemble precursors to amyloid formation.
Ingo Ruczinski, Charles Kooperberg, Richard Bonneau, David Baker
Distributions of beta sheets in proteins with application to structure prediction Journal Article
In: Proteins, vol. 48, pp. 85-97, 2002, ISSN: 1097-0134.
@article{191,
title = {Distributions of beta sheets in proteins with application to structure prediction},
author = { Ingo Ruczinski and Charles Kooperberg and Richard Bonneau and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/ruczinski02A.pdf},
issn = {1097-0134},
year = {2002},
date = {2002-07-01},
journal = {Proteins},
volume = {48},
pages = {85-97},
abstract = {We recently developed the Rosetta algorithm for ab initio protein structure prediction, which generates protein structures from fragment libraries using simulated annealing. The scoring function in this algorithm favors the assembly of strands into sheets. However, it does not discriminate between different sheet motifs. After generating many structures using Rosetta, we found that the folding algorithm predominantly generates very local structures. We surveyed the distribution of beta-sheet motifs with two edge strands (open sheets) in a large set of non-homologous proteins. We investigated how much of that distribution can be accounted for by rules previously published in the literature, and developed a filter and a scoring method that enables us to improve protein structure prediction for beta-sheet proteins. Proteins 2002;48:85-97.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We recently developed the Rosetta algorithm for ab initio protein structure prediction, which generates protein structures from fragment libraries using simulated annealing. The scoring function in this algorithm favors the assembly of strands into sheets. However, it does not discriminate between different sheet motifs. After generating many structures using Rosetta, we found that the folding algorithm predominantly generates very local structures. We surveyed the distribution of beta-sheet motifs with two edge strands (open sheets) in a large set of non-homologous proteins. We investigated how much of that distribution can be accounted for by rules previously published in the literature, and developed a filter and a scoring method that enables us to improve protein structure prediction for beta-sheet proteins. Proteins 2002;48:85-97.
Jack Schonbrun, William J Wedemeyer, David Baker
Protein structure prediction in 2002. Journal Article
In: Current opinion in structural biology, vol. 12, pp. 348-54, 2002, ISSN: 0959-440X.
@article{234,
title = {Protein structure prediction in 2002.},
author = { Jack Schonbrun and William J Wedemeyer and David Baker},
issn = {0959-440X},
year = {2002},
date = {2002-06-01},
journal = {Current opinion in structural biology},
volume = {12},
pages = {348-54},
abstract = {Central issues concerning protein structure prediction have been highlighted by the recently published summary of the fourth community-wide protein structure prediction experiment (CASP4). Although sequence/structure alignment remains the bottleneck in comparative modeling, there has been substantial progress in fully automated remote homolog detection and in de novo structure prediction. Significant further progress will probably require improvements in high-resolution modeling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Central issues concerning protein structure prediction have been highlighted by the recently published summary of the fourth community-wide protein structure prediction experiment (CASP4). Although sequence/structure alignment remains the bottleneck in comparative modeling, there has been substantial progress in fully automated remote homolog detection and in de novo structure prediction. Significant further progress will probably require improvements in high-resolution modeling.
Bryan A Krantz, Alok K Srivastava, Sehat Nauli, David Baker, Robert T Sauer, Tobin R Sosnick
Understanding protein hydrogen bond formation with kinetic H/D amide isotope effects Journal Article
In: Nature structural biology, vol. 9, pp. 458-63, 2002, ISSN: 1072-8368.
@article{187,
title = {Understanding protein hydrogen bond formation with kinetic H/D amide isotope effects},
author = { Bryan A Krantz and Alok K Srivastava and Sehat Nauli and David Baker and Robert T Sauer and Tobin R Sosnick},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/krantz02A.pdf},
issn = {1072-8368},
year = {2002},
date = {2002-06-01},
journal = {Nature structural biology},
volume = {9},
pages = {458-63},
abstract = {Through the development of a procedure to measure when hydrogen bonds form under two-state folding conditions, alpha-helices have been determined to form proportionally to denaturant-sensitive surface area buried in the transition state. Previous experiments assessing H/D isotope effects are applied to various model proteins, including lambda and Arc repressor variants, a coiled coil domain, cytochrome c, colicin immunity protein 7, proteins L and G, acylphosphatase, chymotrypsin inhibitor II and a Src SH3 domain. The change in free energy accompanied by backbone deuteration is highly correlated to secondary structure composition when hydrogen bonds are divided into two classes. The number of helical hydrogen bonds correlates with an average equilibrium isotope effect of 8.6 +/- 0.9 cal x mol(-1) x site(-1). However, beta-sheet and long-range hydrogen bonds have little isotope effect. The kinetic isotope effects support our hypothesis that, for helical proteins, hydrophobic association cannot be separated from helix formation in the transition state. Therefore, folding models that describe an incremental build-up of structure in which hydrophobic burial and hydrogen bond formation occur commensurately are more consistent with the data than are models that posit the extensive formation of one quantity before the other.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Through the development of a procedure to measure when hydrogen bonds form under two-state folding conditions, alpha-helices have been determined to form proportionally to denaturant-sensitive surface area buried in the transition state. Previous experiments assessing H/D isotope effects are applied to various model proteins, including lambda and Arc repressor variants, a coiled coil domain, cytochrome c, colicin immunity protein 7, proteins L and G, acylphosphatase, chymotrypsin inhibitor II and a Src SH3 domain. The change in free energy accompanied by backbone deuteration is highly correlated to secondary structure composition when hydrogen bonds are divided into two classes. The number of helical hydrogen bonds correlates with an average equilibrium isotope effect of 8.6 +/- 0.9 cal x mol(-1) x site(-1). However, beta-sheet and long-range hydrogen bonds have little isotope effect. The kinetic isotope effects support our hypothesis that, for helical proteins, hydrophobic association cannot be separated from helix formation in the transition state. Therefore, folding models that describe an incremental build-up of structure in which hydrophobic burial and hydrogen bond formation occur commensurately are more consistent with the data than are models that posit the extensive formation of one quantity before the other.
Carol A Rohl, David Baker
De novo determination of protein backbone structure from residual dipolar couplings using Rosetta Journal Article
In: Journal of the American Chemical Society, vol. 124, pp. 2723-9, 2002, ISSN: 0002-7863.
@article{190,
title = {De novo determination of protein backbone structure from residual dipolar couplings using Rosetta},
author = { Carol A Rohl and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/rohl02A.pdf},
issn = {0002-7863},
year = {2002},
date = {2002-03-01},
journal = {Journal of the American Chemical Society},
volume = {124},
pages = {2723-9},
abstract = {As genome-sequencing projects rapidly increase the database of protein sequences, the gap between known sequences and known structures continues to grow exponentially, increasing the demand to accelerate structure determination methods. Residual dipolar couplings (RDCs) are an attractive source of experimental restraints for NMR structure determination, particularly rapid, high-throughput methods, because they yield both local and long-range orientational information and can be easily measured and assigned once the backbone resonances of a protein have been assigned. While very extensive RDC data sets have been used to determine the structure of ubiquitin, it is unclear to what extent such methods will generalize to larger proteins with less complete data sets. Here we incorporate experimental RDC restraints into Rosetta, an ab initio structure prediction method, and demonstrate that the combined algorithm provides a general method for de novo determination of a variety of protein folds from RDC data. Backbone structures for multiple proteins up to approximately 125 residues in length and spanning a range of topological complexities are rapidly and reproducibly generated using data sets that are insufficient in isolation to uniquely determine the protein fold de novo, although ambiguities and errors are observed for proteins with symmetry about an axis of the alignment tensor. The models generated are not high-resolution structures completely defined by experimental data but are sufficiently accurate to accelerate traditional high-resolution NMR structure determination and provide structure-based functional insights.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
As genome-sequencing projects rapidly increase the database of protein sequences, the gap between known sequences and known structures continues to grow exponentially, increasing the demand to accelerate structure determination methods. Residual dipolar couplings (RDCs) are an attractive source of experimental restraints for NMR structure determination, particularly rapid, high-throughput methods, because they yield both local and long-range orientational information and can be easily measured and assigned once the backbone resonances of a protein have been assigned. While very extensive RDC data sets have been used to determine the structure of ubiquitin, it is unclear to what extent such methods will generalize to larger proteins with less complete data sets. Here we incorporate experimental RDC restraints into Rosetta, an ab initio structure prediction method, and demonstrate that the combined algorithm provides a general method for de novo determination of a variety of protein folds from RDC data. Backbone structures for multiple proteins up to approximately 125 residues in length and spanning a range of topological complexities are rapidly and reproducibly generated using data sets that are insufficient in isolation to uniquely determine the protein fold de novo, although ambiguities and errors are observed for proteins with symmetry about an axis of the alignment tensor. The models generated are not high-resolution structures completely defined by experimental data but are sufficiently accurate to accelerate traditional high-resolution NMR structure determination and provide structure-based functional insights.
Stefan M Larson, Ingo Ruczinski, Alan R Davidson, David Baker, Kevin W Plaxco
Residues participating in the protein folding nucleus do not exhibit preferential evolutionary conservation Journal Article
In: Journal of molecular biology, vol. 316, pp. 225-33, 2002, ISSN: 0022-2836.
@article{188,
title = {Residues participating in the protein folding nucleus do not exhibit preferential evolutionary conservation},
author = { Stefan M Larson and Ingo Ruczinski and Alan R Davidson and David Baker and Kevin W Plaxco},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/larson02A.pdf},
issn = {0022-2836},
year = {2002},
date = {2002-02-01},
journal = {Journal of molecular biology},
volume = {316},
pages = {225-33},
abstract = {To what extent does natural selection act to optimize the details of protein folding kinetics? In an effort to address this question, the relationship between an amino acidtextquoterights evolutionary conservation and its role in protein folding kinetics has been investigated intensively. Despite this effort, no consensus has been reached regarding the degree to which residues involved in native-like transition state structure (the folding nucleus) are conserved. Here we report the results of an exhaustive, systematic study of sequence conservation among residues known to participate in the experimentally (Phi-value) defined folding nuclei of all of the appropriately characterized proteins reported to date. We observe no significant evidence that these residues exhibit any anomalous sequence conservation. We do observe, however, a significant bias in the existing kinetic data: the mean sequence conservation of the residues that have been the subject of kinetic characterization is greater than the mean sequence conservation of all residues in 13 of 14 proteins studied. This systematic experimental bias gives rise to the previous observation that the median conservation of residues reported to participate in the folding nucleus is greater than the median conservation of all of the residues in a protein. When this bias is corrected (by comparing, for example, the conservation of residues known to participate in the folding nucleus with that of other, kinetically characterized residues) the previously reported preferential conservation is effectively eliminated. In contrast to well-established theoretical expectations, both poorly and highly conserved residues are apparently equally likely to participate in the protein-folding nucleus.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To what extent does natural selection act to optimize the details of protein folding kinetics? In an effort to address this question, the relationship between an amino acidtextquoterights evolutionary conservation and its role in protein folding kinetics has been investigated intensively. Despite this effort, no consensus has been reached regarding the degree to which residues involved in native-like transition state structure (the folding nucleus) are conserved. Here we report the results of an exhaustive, systematic study of sequence conservation among residues known to participate in the experimentally (Phi-value) defined folding nuclei of all of the appropriately characterized proteins reported to date. We observe no significant evidence that these residues exhibit any anomalous sequence conservation. We do observe, however, a significant bias in the existing kinetic data: the mean sequence conservation of the residues that have been the subject of kinetic characterization is greater than the mean sequence conservation of all residues in 13 of 14 proteins studied. This systematic experimental bias gives rise to the previous observation that the median conservation of residues reported to participate in the folding nucleus is greater than the median conservation of all of the residues in a protein. When this bias is corrected (by comparing, for example, the conservation of residues known to participate in the folding nucleus with that of other, kinetically characterized residues) the previously reported preferential conservation is effectively eliminated. In contrast to well-established theoretical expectations, both poorly and highly conserved residues are apparently equally likely to participate in the protein-folding nucleus.
Brian Kuhlman, Jason W OtextquoterightNeill, David E Kim, Kam Y J Zhang, David Baker
Accurate computer-based design of a new backbone conformation in the second turn of protein L Journal Article
In: Journal of molecular biology, vol. 315, pp. 471-7, 2002, ISSN: 0022-2836.
@article{318,
title = {Accurate computer-based design of a new backbone conformation in the second turn of protein L},
author = { Brian Kuhlman and Jason W OtextquoterightNeill and David E Kim and Kam Y J Zhang and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kuhlman02A.pdf},
issn = {0022-2836},
year = {2002},
date = {2002-01-01},
journal = {Journal of molecular biology},
volume = {315},
pages = {471-7},
abstract = {The rational design of loops and turns is a key step towards creating proteins with new functions. We used a computational design procedure to create new backbone conformations in the second turn of protein L. The Protein Data Bank was searched for alternative turn conformations, and sequences optimal for these turns in the context of protein L were identified using a Monte Carlo search procedure and an energy function that favors close packing. Two variants containing 12 and 14 mutations were found to be as stable as wild-type protein L. The crystal structure of one of the variants has been solved at a resolution of 1.9 A, and the backbone conformation in the second turn is remarkably close to that of the in silico model (1.1 A RMSD) while it differs significantly from that of wild-type protein L (the turn residues are displaced by an average of 7.2 A). The folding rates of the redesigned proteins are greater than that of the wild-type protein and in contrast to wild-type protein L the second beta-turn appears to be formed at the rate limiting step in folding.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The rational design of loops and turns is a key step towards creating proteins with new functions. We used a computational design procedure to create new backbone conformations in the second turn of protein L. The Protein Data Bank was searched for alternative turn conformations, and sequences optimal for these turns in the context of protein L were identified using a Monte Carlo search procedure and an energy function that favors close packing. Two variants containing 12 and 14 mutations were found to be as stable as wild-type protein L. The crystal structure of one of the variants has been solved at a resolution of 1.9 A, and the backbone conformation in the second turn is remarkably close to that of the in silico model (1.1 A RMSD) while it differs significantly from that of wild-type protein L (the turn residues are displaced by an average of 7.2 A). The folding rates of the redesigned proteins are greater than that of the wild-type protein and in contrast to wild-type protein L the second beta-turn appears to be formed at the rate limiting step in folding.
Maximilian Schlosshauer, David Baker
A general expression for bimolecular association rates with orientational constraints Journal Article
In: Physical Chemistry B, 2002.
@article{319,
title = {A general expression for bimolecular association rates with orientational constraints},
author = { Maximilian Schlosshauer and David Baker},
year = {2002},
date = {2002-00-01},
journal = {Physical Chemistry B},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2001
J W ONeill, David E Kim, K Johnsen, David Baker, K Y Zhang
Single-site mutations induce 3D domain swapping in the B1 domain of protein L from Peptostreptococcus magnus Journal Article
In: Structure, vol. 9, pp. 1017-27, 2001, ISSN: 0969-2126.
@article{57,
title = {Single-site mutations induce 3D domain swapping in the B1 domain of protein L from Peptostreptococcus magnus},
author = { J W ONeill and David E Kim and K Johnsen and David Baker and K Y Zhang},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/oneill01A.pdf},
issn = {0969-2126},
year = {2001},
date = {2001-11-01},
journal = {Structure},
volume = {9},
pages = {1017-27},
abstract = {BACKGROUND: Thermodynamic and kinetic studies of the Protein L B1 domain (Ppl) suggest a folding pathway in which, during the folding transition, the first beta hairpin is formed while the second beta hairpin and the alpha helix are largely unstructured. The same mutations in the two beta turns have opposite effects on the folding and unfolding rates. Three of the four residues composing the second beta turn in Ppl have consecutive positive phi angles, indicating strain in the second beta turn. RESULTS: We have determined the crystal structures of the beta turn mutants G55A, K54G, and G15A, as well as a core mutant, V49A, in order to investigate how backbone strain affects the overall structure of Ppl. Perturbation of the hydrophobic interactions at the closed interface by the V49A mutation triggered the domain swapping of the C-terminal beta strand that relieved the strain in the second beta turn. Interestingly, the asymmetric unit of V49A contains two monomers and one domain-swapped dimer. The G55A mutation escalated the strain in the second beta turn, and this increased strain shifted the equilibrium toward the domain-swapped dimer. The K54G structure revealed that the increased stability is due to the reduction of strain in the second beta turn, while the G15A structure showed that increased strain alone is insufficient to trigger domain swapping. CONCLUSIONS: Domain swapping in Ppl is determined by the balance of two opposing components of the free energy. One is the strain in the second beta turn that favors the dimer, and the other is the entropic cost of dimer formation that favors the monomer. A single-site mutation can disrupt this balance and trigger domain swapping.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Thermodynamic and kinetic studies of the Protein L B1 domain (Ppl) suggest a folding pathway in which, during the folding transition, the first beta hairpin is formed while the second beta hairpin and the alpha helix are largely unstructured. The same mutations in the two beta turns have opposite effects on the folding and unfolding rates. Three of the four residues composing the second beta turn in Ppl have consecutive positive phi angles, indicating strain in the second beta turn. RESULTS: We have determined the crystal structures of the beta turn mutants G55A, K54G, and G15A, as well as a core mutant, V49A, in order to investigate how backbone strain affects the overall structure of Ppl. Perturbation of the hydrophobic interactions at the closed interface by the V49A mutation triggered the domain swapping of the C-terminal beta strand that relieved the strain in the second beta turn. Interestingly, the asymmetric unit of V49A contains two monomers and one domain-swapped dimer. The G55A mutation escalated the strain in the second beta turn, and this increased strain shifted the equilibrium toward the domain-swapped dimer. The K54G structure revealed that the increased stability is due to the reduction of strain in the second beta turn, while the G15A structure showed that increased strain alone is insufficient to trigger domain swapping. CONCLUSIONS: Domain swapping in Ppl is determined by the balance of two opposing components of the free energy. One is the strain in the second beta turn that favors the dimer, and the other is the entropic cost of dimer formation that favors the monomer. A single-site mutation can disrupt this balance and trigger domain swapping.
David Baker, A Sali
Protein structure prediction and structural genomics. Journal Article
In: Science (New York, N.Y.), vol. 294, pp. 93-6, 2001, ISSN: 0036-8075.
@article{71,
title = {Protein structure prediction and structural genomics.},
author = { David Baker and A Sali},
issn = {0036-8075},
year = {2001},
date = {2001-10-01},
journal = {Science (New York, N.Y.)},
volume = {294},
pages = {93-6},
abstract = {Genome sequencing projects are producing linear amino acid sequences, but full understanding of the biological role of these proteins will require knowledge of their structure and function. Although experimental structure determination methods are providing high-resolution structure information about a subset of the proteins, computational structure prediction methods will provide valuable information for the large fraction of sequences whose structures will not be determined experimentally. The first class of protein structure prediction methods, including threading and comparative modeling, rely on detectable similarity spanning most of the modeled sequence and at least one known structure. The second class of methods, de novo or ab initio methods, predict the structure from sequence alone, without relying on similarity at the fold level between the modeled sequence and any of the known structures. In this Viewpoint, we begin by describing the essential features of the methods, the accuracy of the models, and their application to the prediction and understanding of protein function, both for single proteins and on the scale of whole genomes. We then discuss the important role that protein structure prediction methods play in the growing worldwide effort in structural genomics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Genome sequencing projects are producing linear amino acid sequences, but full understanding of the biological role of these proteins will require knowledge of their structure and function. Although experimental structure determination methods are providing high-resolution structure information about a subset of the proteins, computational structure prediction methods will provide valuable information for the large fraction of sequences whose structures will not be determined experimentally. The first class of protein structure prediction methods, including threading and comparative modeling, rely on detectable similarity spanning most of the modeled sequence and at least one known structure. The second class of methods, de novo or ab initio methods, predict the structure from sequence alone, without relying on similarity at the fold level between the modeled sequence and any of the known structures. In this Viewpoint, we begin by describing the essential features of the methods, the accuracy of the models, and their application to the prediction and understanding of protein function, both for single proteins and on the scale of whole genomes. We then discuss the important role that protein structure prediction methods play in the growing worldwide effort in structural genomics.
M R Lee, J Tsai, David Baker, P A Kollman
Molecular dynamics in the endgame of protein structure prediction Journal Article
In: Journal of molecular biology, vol. 313, pp. 417-30, 2001, ISSN: 0022-2836.
@article{62,
title = {Molecular dynamics in the endgame of protein structure prediction},
author = { M R Lee and J Tsai and David Baker and P A Kollman},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/lee01B.pdf},
issn = {0022-2836},
year = {2001},
date = {2001-10-01},
journal = {Journal of molecular biology},
volume = {313},
pages = {417-30},
abstract = {In order adequately to sample conformational space, methods for protein structure prediction make necessary simplifications that also prevent them from being as accurate as desired. Thus, the idea of feeding them, hierarchically, into a more accurate method that samples less effectively was introduced a decade ago but has not met with more than limited success in a few isolated instances. Ideally, the final stages should be able to identify the native state, show a good correlation with native similarity in order to add value to the selection process, and refine the structures even further. In this work, we explore the possibility of using state-of-the-art explicit solvent molecular dynamics and implicit solvent free energy calculations to accomplish all three of those objectives on 12 small, single-domain proteins, four each of alpha, beta and mixed topologies. We find that this approach is very successful in ranking the native and also enhances the structure selection of predictions generated from the Rosetta method.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In order adequately to sample conformational space, methods for protein structure prediction make necessary simplifications that also prevent them from being as accurate as desired. Thus, the idea of feeding them, hierarchically, into a more accurate method that samples less effectively was introduced a decade ago but has not met with more than limited success in a few isolated instances. Ideally, the final stages should be able to identify the native state, show a good correlation with native similarity in order to add value to the selection process, and refine the structures even further. In this work, we explore the possibility of using state-of-the-art explicit solvent molecular dynamics and implicit solvent free energy calculations to accomplish all three of those objectives on 12 small, single-domain proteins, four each of alpha, beta and mixed topologies. We find that this approach is very successful in ranking the native and also enhances the structure selection of predictions generated from the Rosetta method.
B Kuhlman, J W ONeill, David E Kim, K Y Zhang, David Baker
Conversion of monomeric protein L to an obligate dimer by computational protein design Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 98, pp. 10687-91, 2001, ISSN: 0027-8424.
@article{63,
title = {Conversion of monomeric protein L to an obligate dimer by computational protein design},
author = { B Kuhlman and J W ONeill and David E Kim and K Y Zhang and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kuhlman01A.pdf},
issn = {0027-8424},
year = {2001},
date = {2001-09-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {98},
pages = {10687-91},
abstract = {Protein L consists of a single alpha-helix packed on a four-stranded beta-sheet formed by two symmetrically opposed beta-hairpins. We use a computer-based protein design procedure to stabilize a domain-swapped dimer of protein L in which the second beta-turn straightens and the C-terminal strand inserts into the beta-sheet of the partner. The designed obligate dimer contains three mutations (A52V, N53P, and G55A) and has a dissociation constant of approximately 700 pM, which is comparable to the dissociation constant of many naturally occurring protein dimers. The structure of the dimer has been determined by x-ray crystallography and is close to the in silico model.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Protein L consists of a single alpha-helix packed on a four-stranded beta-sheet formed by two symmetrically opposed beta-hairpins. We use a computer-based protein design procedure to stabilize a domain-swapped dimer of protein L in which the second beta-turn straightens and the C-terminal strand inserts into the beta-sheet of the partner. The designed obligate dimer contains three mutations (A52V, N53P, and G55A) and has a dissociation constant of approximately 700 pM, which is comparable to the dissociation constant of many naturally occurring protein dimers. The structure of the dimer has been determined by x-ray crystallography and is close to the in silico model.
S Nauli, B Kuhlman, David Baker
Computer-based redesign of a protein folding pathway. Journal Article
In: Nature structural biology, vol. 8, pp. 602-5, 2001, ISSN: 1072-8368.
@article{59,
title = {Computer-based redesign of a protein folding pathway.},
author = { S Nauli and B Kuhlman and David Baker},
issn = {1072-8368},
year = {2001},
date = {2001-07-01},
journal = {Nature structural biology},
volume = {8},
pages = {602-5},
abstract = {A fundamental test of our current understanding of protein folding is to rationally redesign protein folding pathways. We use a computer-based design strategy to switch the folding pathway of protein G, which normally involves formation of the second, but not the first, beta-turn at the rate limiting step in folding. Backbone conformations and amino acid sequences that maximize the interaction density in the first beta-hairpin were identified, and two variants containing 11 amino acid replacements were found to be approximately 4 kcal mol-1 more stable than wild type protein G. Kinetic studies show that the redesigned proteins fold approximately 100 x faster than wild type protein and that the first beta-turn is formed and the second disrupted at the rate limiting step in folding.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A fundamental test of our current understanding of protein folding is to rationally redesign protein folding pathways. We use a computer-based design strategy to switch the folding pathway of protein G, which normally involves formation of the second, but not the first, beta-turn at the rate limiting step in folding. Backbone conformations and amino acid sequences that maximize the interaction density in the first beta-hairpin were identified, and two variants containing 11 amino acid replacements were found to be approximately 4 kcal mol-1 more stable than wild type protein G. Kinetic studies show that the redesigned proteins fold approximately 100 x faster than wild type protein and that the first beta-turn is formed and the second disrupted at the rate limiting step in folding.
R Bonneau, J Tsai, I Ruczinski, David Baker
Functional inferences from blind ab initio protein structure predictions Journal Article
In: Journal of structural biology, vol. 134, pp. 186-90, 2001, ISSN: 1047-8477.
@article{67,
title = {Functional inferences from blind ab initio protein structure predictions},
author = { R Bonneau and J Tsai and I Ruczinski and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bonneau01B.pdf},
issn = {1047-8477},
year = {2001},
date = {2001-05-01},
journal = {Journal of structural biology},
volume = {134},
pages = {186-90},
abstract = {Ab initio protein structure prediction methods have improved dramatically in the past several years. Because these methods require only the sequence of the protein of interest, they are potentially applicable to the open reading frames in the many organisms whose sequences have been and will be determined. Ab initio methods cannot currently produce models of high enough resolution for use in rational drug design, but there is an exciting potential for using the methods for functional annotation of protein sequences on a genomic scale. Here we illustrate how functional insights can be obtained from low-resolution predicted structures using examples from blind ab initio structure predictions from the third and fourth critical assessment of structure prediction (CASP3, CASP4) experiments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ab initio protein structure prediction methods have improved dramatically in the past several years. Because these methods require only the sequence of the protein of interest, they are potentially applicable to the open reading frames in the many organisms whose sequences have been and will be determined. Ab initio methods cannot currently produce models of high enough resolution for use in rational drug design, but there is an exciting potential for using the methods for functional annotation of protein sequences on a genomic scale. Here we illustrate how functional insights can be obtained from low-resolution predicted structures using examples from blind ab initio structure predictions from the third and fourth critical assessment of structure prediction (CASP3, CASP4) experiments.
K M Kim, E C Yi, David Baker, K Y Zhang
In: Acta crystallographica. Section D, vol. 57, pp. 759-62, 2001, ISSN: 0907-4449.
@article{64,
title = {Post-translational modification of the N-terminal His tag interferes with the crystallization of the wild-type and mutant SH3 domains from chicken src tyrosine kinase},
author = { K M Kim and E C Yi and David Baker and K Y Zhang},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kim01A.pdf},
issn = {0907-4449},
year = {2001},
date = {2001-05-01},
journal = {Acta crystallographica. Section D},
volume = {57},
pages = {759-62},
abstract = {Structural studies of the wild type and mutants of the src SH3 domain were initiated to elucidate the correlation of the native-state topology with protein thermostability and folding kinetics. An extra mass of 178 Da arising from the post-translational modification at the N-terminal His tag was observed. The spontaneous alpha-N-6 gluconoylation at the amino group of the His-tagged SH3 domain contributed to the observed extra mass. The partial modification of the N-terminal His-tag produced heterogeneity, both in size and in charge, in the Escherichia coli expressed SH3 domain. The removal of the His tag from the SH3 domain was essential for the crystallization of both wild-type and mutant src SH3. Both the wild type and the W43I mutant were crystallized by hanging-drop vapor diffusion and are in the hexagonal space group P6(5)22 with one molecule in the asymmetric unit. Data sets were collected to 1.8 and 1.95 A resolution for the the wild type and the W43I mutant, respectively.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Structural studies of the wild type and mutants of the src SH3 domain were initiated to elucidate the correlation of the native-state topology with protein thermostability and folding kinetics. An extra mass of 178 Da arising from the post-translational modification at the N-terminal His tag was observed. The spontaneous alpha-N-6 gluconoylation at the amino group of the His-tagged SH3 domain contributed to the observed extra mass. The partial modification of the N-terminal His-tag produced heterogeneity, both in size and in charge, in the Escherichia coli expressed SH3 domain. The removal of the His tag from the SH3 domain was essential for the crystallization of both wild-type and mutant src SH3. Both the wild type and the W43I mutant were crystallized by hanging-drop vapor diffusion and are in the hexagonal space group P6(5)22 with one molecule in the asymmetric unit. Data sets were collected to 1.8 and 1.95 A resolution for the the wild type and the W43I mutant, respectively.
R Bonneau, C E Strauss, David Baker
Improving the performance of Rosetta using multiple sequence alignment information and global measures of hydrophobic core formation Journal Article
In: Proteins, vol. 43, pp. 1-11, 2001, ISSN: 0887-3585.
@article{70,
title = {Improving the performance of Rosetta using multiple sequence alignment information and global measures of hydrophobic core formation},
author = { R Bonneau and C E Strauss and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bonneau01A.pdf},
issn = {0887-3585},
year = {2001},
date = {2001-04-01},
journal = {Proteins},
volume = {43},
pages = {1-11},
abstract = {This study explores the use of multiple sequence alignment (MSA) information and global measures of hydrophobic core formation for improving the Rosetta ab initio protein structure prediction method. The most effective use of the MSA information is achieved by carrying out independent folding simulations for a subset of the homologous sequences in the MSA and then identifying the free energy minima common to all folded sequences via simultaneous clustering of the independent folding runs. Global measures of hydrophobic core formation, using ellipsoidal rather than spherical representations of the hydrophobic core, are found to be useful in removing non-native conformations before cluster analysis. Through this combination of MSA information and global measures of protein core formation, we significantly increase the performance of Rosetta on a challenging test set. Proteins 2001;43:1-11.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study explores the use of multiple sequence alignment (MSA) information and global measures of hydrophobic core formation for improving the Rosetta ab initio protein structure prediction method. The most effective use of the MSA information is achieved by carrying out independent folding simulations for a subset of the homologous sequences in the MSA and then identifying the free energy minima common to all folded sequences via simultaneous clustering of the independent folding runs. Global measures of hydrophobic core formation, using ellipsoidal rather than spherical representations of the hydrophobic core, are found to be useful in removing non-native conformations before cluster analysis. Through this combination of MSA information and global measures of protein core formation, we significantly increase the performance of Rosetta on a challenging test set. Proteins 2001;43:1-11.
J W OtextquoterightNeill, David E Kim, David Baker, K Y Zhang
Structures of the B1 domain of protein L from Peptostreptococcus magnus with a tyrosine to tryptophan substitution. Journal Article
In: Acta crystallographica. Section D, Biological crystallography, vol. 57, pp. 480-7, 2001, ISSN: 0907-4449.
@article{58,
title = {Structures of the B1 domain of protein L from Peptostreptococcus magnus with a tyrosine to tryptophan substitution.},
author = { J W OtextquoterightNeill and David E Kim and David Baker and K Y Zhang},
issn = {0907-4449},
year = {2001},
date = {2001-04-01},
journal = {Acta crystallographica. Section D, Biological crystallography},
volume = {57},
pages = {480-7},
abstract = {The three-dimensional structure of a tryptophan-containing variant of the IgG-binding B1 domain of protein L has been solved in two crystal forms to 1.7 and 1.8 A resolution. In one of the crystal forms, the entire N-terminal histidine-tag region was immobilized through the coordination of zinc ions and its structural conformation along with the zinc coordination scheme were determined. However, the ordering of the histidine tag by zinc does not affect the overall structure of the rest of the protein. Structural comparisons of the tryptophan-containing variant with an NMR-derived wild-type structure, which contains a tyrosine at position 47, reveals a common fold, although the overall backbone root-mean-square difference is 1.5 A. The Y47W substitution only caused local rearrangement of several side chains, the most prominent of which is the rotation of the Tyr34 side chain, resulting in a 6 A displacement of its hydroxyl group. A small methyl-sized cavity bounded by beta-strands 1, 2 and 4 and the alpha-helix was found in the structures of the Y47W-substituted protein L B1 domain. This cavity may be created as the result of subsequent side-chain rearrangements caused by the Y47W substitution. These high-resolution structures of the tryptophan-containing variant provide a reference frame for the analysis of thermodynamic and kinetic data derived from a series of mutational studies of the protein L B1 domain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The three-dimensional structure of a tryptophan-containing variant of the IgG-binding B1 domain of protein L has been solved in two crystal forms to 1.7 and 1.8 A resolution. In one of the crystal forms, the entire N-terminal histidine-tag region was immobilized through the coordination of zinc ions and its structural conformation along with the zinc coordination scheme were determined. However, the ordering of the histidine tag by zinc does not affect the overall structure of the rest of the protein. Structural comparisons of the tryptophan-containing variant with an NMR-derived wild-type structure, which contains a tyrosine at position 47, reveals a common fold, although the overall backbone root-mean-square difference is 1.5 A. The Y47W substitution only caused local rearrangement of several side chains, the most prominent of which is the rotation of the Tyr34 side chain, resulting in a 6 A displacement of its hydroxyl group. A small methyl-sized cavity bounded by beta-strands 1, 2 and 4 and the alpha-helix was found in the structures of the Y47W-substituted protein L B1 domain. This cavity may be created as the result of subsequent side-chain rearrangements caused by the Y47W substitution. These high-resolution structures of the tryptophan-containing variant provide a reference frame for the analysis of thermodynamic and kinetic data derived from a series of mutational studies of the protein L B1 domain.
K T Simons, C Strauss, David Baker
Prospects for ab initio protein structural genomics Journal Article
In: Journal of molecular biology, vol. 306, pp. 1191-9, 2001, ISSN: 0022-2836.
@article{56,
title = {Prospects for ab initio protein structural genomics},
author = { K T Simons and C Strauss and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/simons01A.pdf},
issn = {0022-2836},
year = {2001},
date = {2001-03-01},
journal = {Journal of molecular biology},
volume = {306},
pages = {1191-9},
abstract = {We present the results of a large-scale testing of the ROSETTA method for ab initio protein structure prediction. Models were generated for two independently generated lists of small proteins (up to 150 amino acid residues), and the results were evaluated using traditional rmsd based measures and a novel measure based on the structure-based comparison of the models to the structures in the PDB using DALI. For 111 of 136 all alpha and alpha/beta proteins 50 to 150 residues in length, the method produced at least one model within 7 A rmsd of the native structure in 1000 attempts. For 60 of these proteins, the closest structure match in the PDB to at least one of the ten most frequently generated conformations was found to be structurally related (four standard deviations above background) to the native protein. These results suggest that ab initio structure prediction approaches may soon be useful for generating low resolution models and identifying distantly related proteins with similar structures and perhaps functions for these classes of proteins on the genome scale.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present the results of a large-scale testing of the ROSETTA method for ab initio protein structure prediction. Models were generated for two independently generated lists of small proteins (up to 150 amino acid residues), and the results were evaluated using traditional rmsd based measures and a novel measure based on the structure-based comparison of the models to the structures in the PDB using DALI. For 111 of 136 all alpha and alpha/beta proteins 50 to 150 residues in length, the method produced at least one model within 7 A rmsd of the native structure in 1000 attempts. For 60 of these proteins, the closest structure match in the PDB to at least one of the ten most frequently generated conformations was found to be structurally related (four standard deviations above background) to the native protein. These results suggest that ab initio structure prediction approaches may soon be useful for generating low resolution models and identifying distantly related proteins with similar structures and perhaps functions for these classes of proteins on the genome scale.
V P Grantcharova, David Baker
Circularization changes the folding transition state of the src SH3 domain Journal Article
In: Journal of molecular biology, vol. 306, pp. 555-63, 2001, ISSN: 0022-2836.
@article{65,
title = {Circularization changes the folding transition state of the src SH3 domain},
author = { V P Grantcharova and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/grantcharova01A.pdf},
issn = {0022-2836},
year = {2001},
date = {2001-02-01},
journal = {Journal of molecular biology},
volume = {306},
pages = {555-63},
abstract = {Native state topology has been implicated as a major determinant of protein-folding mechanisms. Here, we test experimentally the robustness of the src SH3-domain folding transition state to changes in topology by covalently constraining regions of the protein with disulfide crosslinks and then performing kinetic analysis on point mutations in the context of these modified proteins. Circularization (crosslinking the N and C termini) of the src SH3 domain makes the protein topologically symmetric and causes delocalization of structure in the transition state ensemble suggesting a change in the folding mechanism. In contrast, crosslinking a single structural element (the distal beta-hairpin) which is an essential part of the transition state, results in a protein that folds 30 times faster, but does not change the distribution of structure in the transition state. As the transition states of distantly related SH3 domains were previously found to be very similar, we conclude that the free energy landscape of this protein family contains deep features which are relatively insensitive to sequence variations but can be altered by changes in topology.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Native state topology has been implicated as a major determinant of protein-folding mechanisms. Here, we test experimentally the robustness of the src SH3-domain folding transition state to changes in topology by covalently constraining regions of the protein with disulfide crosslinks and then performing kinetic analysis on point mutations in the context of these modified proteins. Circularization (crosslinking the N and C termini) of the src SH3 domain makes the protein topologically symmetric and causes delocalization of structure in the transition state ensemble suggesting a change in the folding mechanism. In contrast, crosslinking a single structural element (the distal beta-hairpin) which is an essential part of the transition state, results in a protein that folds 30 times faster, but does not change the distribution of structure in the transition state. As the transition states of distantly related SH3 domains were previously found to be very similar, we conclude that the free energy landscape of this protein family contains deep features which are relatively insensitive to sequence variations but can be altered by changes in topology.
M R Lee, David Baker, P A Kollman
2.1 and 1.8 A average C(alpha) RMSD structure predictions on two small proteins, HP-36 and s15 Journal Article
In: Journal of the American Chemical Society, vol. 123, pp. 1040-6, 2001, ISSN: 0002-7863.
@article{61,
title = {2.1 and 1.8 A average C(alpha) RMSD structure predictions on two small proteins, HP-36 and s15},
author = { M R Lee and David Baker and P A Kollman},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/lee01A.pdf},
issn = {0002-7863},
year = {2001},
date = {2001-02-01},
journal = {Journal of the American Chemical Society},
volume = {123},
pages = {1040-6},
abstract = {On two different small proteins, the 36-mer villin headpiece domain (HP-36) and the 65-mer structured region of ribosomal protein (S15), several model predictions from the ab initio approach Rosetta were subjected to molecular dynamics simulations for refinement. After clustering the resulting trajectories into conformational families, the average molecular mechanics--Poisson Boltzmann/surface area (MM-PBSA) free energies and alpha carbon (C(alpha)) RMSDs were then calculated for each family. Those conformational families with the lowest average free energies also contained the best C(alpha) RMSD structures (1.4 A for S15 and HP-36 core) and the lowest average C(alpha) RMSDs (1.8 A for S15, 2.1 A for HP-36 core). For comparison, control simulations starting with the two experimental structures were very stable, each consisting of a single conformational family, with an average C(alpha) RMSD of 1.3 A for S15 and 1.2 A for HP-36 core (1.9 A over all residues). In addition, the average free energiestextquoteright ranks (Spearman rank, r(s)) correlate well with the average C(alpha) RMSDs (r(s) = 0.77 for HP-36, r(s) = 0.83 for S15). Molecular dynamics simulations combined with the MM--PBSA free energy function provide a potentially powerful tool for the protein structure prediction community in allowing for both high-resolution structural refinement and accurate ranking of model predictions. With all of the information that genomics is now providing, this methodology may allow for advances in going from sequence to structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
On two different small proteins, the 36-mer villin headpiece domain (HP-36) and the 65-mer structured region of ribosomal protein (S15), several model predictions from the ab initio approach Rosetta were subjected to molecular dynamics simulations for refinement. After clustering the resulting trajectories into conformational families, the average molecular mechanics–Poisson Boltzmann/surface area (MM-PBSA) free energies and alpha carbon (C(alpha)) RMSDs were then calculated for each family. Those conformational families with the lowest average free energies also contained the best C(alpha) RMSD structures (1.4 A for S15 and HP-36 core) and the lowest average C(alpha) RMSDs (1.8 A for S15, 2.1 A for HP-36 core). For comparison, control simulations starting with the two experimental structures were very stable, each consisting of a single conformational family, with an average C(alpha) RMSD of 1.3 A for S15 and 1.2 A for HP-36 core (1.9 A over all residues). In addition, the average free energiestextquoteright ranks (Spearman rank, r(s)) correlate well with the average C(alpha) RMSDs (r(s) = 0.77 for HP-36, r(s) = 0.83 for S15). Molecular dynamics simulations combined with the MM–PBSA free energy function provide a potentially powerful tool for the protein structure prediction community in allowing for both high-resolution structural refinement and accurate ranking of model predictions. With all of the information that genomics is now providing, this methodology may allow for advances in going from sequence to structure.
V Grantcharova, E J Alm, David Baker, A L Horwich
Mechanisms of protein folding. Journal Article
In: Current opinion in structural biology, vol. 11, pp. 70-82, 2001, ISSN: 0959-440X.
@article{66,
title = {Mechanisms of protein folding.},
author = { V Grantcharova and E J Alm and David Baker and A L Horwich},
issn = {0959-440X},
year = {2001},
date = {2001-02-01},
journal = {Current opinion in structural biology},
volume = {11},
pages = {70-82},
abstract = {The strong correlation between protein folding rates and the contact order suggests that folding rates are largely determined by the topology of the native structure. However, for a given topology, there may be several possible low free energy paths to the native state and the path that is chosen (the lowest free energy path) may depend on differences in interaction energies and local free energies of ordering in different parts of the structure. For larger proteins whose folding is assisted by chaperones, such as the Escherichia coli chaperonin GroEL, advances have been made in understanding both the aspects of an unfolded protein that GroEL recognizes and the mode of binding to the chaperonin. The possibility that GroEL can remove non-native proteins from kinetic traps by unfolding them either during polypeptide binding to the chaperonin or during the subsequent ATP-dependent formation of folding-active complexes with the co-chaperonin GroES has also been explored.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The strong correlation between protein folding rates and the contact order suggests that folding rates are largely determined by the topology of the native structure. However, for a given topology, there may be several possible low free energy paths to the native state and the path that is chosen (the lowest free energy path) may depend on differences in interaction energies and local free energies of ordering in different parts of the structure. For larger proteins whose folding is assisted by chaperones, such as the Escherichia coli chaperonin GroEL, advances have been made in understanding both the aspects of an unfolded protein that GroEL recognizes and the mode of binding to the chaperonin. The possibility that GroEL can remove non-native proteins from kinetic traps by unfolding them either during polypeptide binding to the chaperonin or during the subsequent ATP-dependent formation of folding-active complexes with the co-chaperonin GroES has also been explored.
P Minard, M Scalley-Kim, A Watters, David Baker
A "loop entropy reduction" phage-display selection for folded amino acid sequences Journal Article
In: Protein science, vol. 10, pp. 129-34, 2001, ISSN: 0961-8368.
@article{60,
title = {A "loop entropy reduction" phage-display selection for folded amino acid sequences},
author = { P Minard and M Scalley-Kim and A Watters and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/minard01A.pdf},
issn = {0961-8368},
year = {2001},
date = {2001-01-01},
journal = {Protein science},
volume = {10},
pages = {129-34},
abstract = {As a step toward selecting folded proteins from libraries of randomized sequences, we have designed a textquoterightloop entropy reductiontextquoteright-based phage-display method. The basic premise is that insertion of a long disordered sequence into a loop of a host protein will substantially destabilize the host because of the entropic cost of closing a loop in a disordered chain. If the inserted sequence spontaneously folds into a stable structure with the N and C termini close in space, however, this entropic cost is diminished. The host protein function can, therefore, be used to select folded inserted sequences without relying on specific properties of the inserted sequence. This principle is tested using the IgG binding domain of protein L and the lck SH2 domain as host proteins. The results indicate that the loop entropy reduction screen is capable of discriminating folded from unfolded sequences when the proper host protein and insertion point are chosen.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
As a step toward selecting folded proteins from libraries of randomized sequences, we have designed a textquoterightloop entropy reductiontextquoteright-based phage-display method. The basic premise is that insertion of a long disordered sequence into a loop of a host protein will substantially destabilize the host because of the entropic cost of closing a loop in a disordered chain. If the inserted sequence spontaneously folds into a stable structure with the N and C termini close in space, however, this entropic cost is diminished. The host protein function can, therefore, be used to select folded inserted sequences without relying on specific properties of the inserted sequence. This principle is tested using the IgG binding domain of protein L and the lck SH2 domain as host proteins. The results indicate that the loop entropy reduction screen is capable of discriminating folded from unfolded sequences when the proper host protein and insertion point are chosen.
R Bonneau, David Baker
Ab initio protein structure prediction: progress and prospects. Journal Article
In: Annual review of biophysics and biomolecular structure, vol. 30, pp. 173-89, 2001, ISSN: 1056-8700.
@article{69,
title = {Ab initio protein structure prediction: progress and prospects.},
author = { R Bonneau and David Baker},
issn = {1056-8700},
year = {2001},
date = {2001-00-01},
journal = {Annual review of biophysics and biomolecular structure},
volume = {30},
pages = {173-89},
abstract = {Considerable recent progress has been made in the field of ab initio protein structure prediction, as witnessed by the third Critical Assessment of Structure Prediction (CASP3). In spite of this progress, much work remains, for the field has yet to produce consistently reliable ab initio structure prediction protocols. In this work, we review the features of current ab initio protocols in an attempt to highlight the foundations of recent progress in the field and suggest promising directions for future work.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Considerable recent progress has been made in the field of ab initio protein structure prediction, as witnessed by the third Critical Assessment of Structure Prediction (CASP3). In spite of this progress, much work remains, for the field has yet to produce consistently reliable ab initio structure prediction protocols. In this work, we review the features of current ab initio protocols in an attempt to highlight the foundations of recent progress in the field and suggest promising directions for future work.
R Bonneau, J Tsai, I Ruczinski, D Chivian, C Rohl, C E Strauss, David Baker
Rosetta in CASP4: progress in ab initio protein structure prediction Journal Article
In: Proteins, vol. Suppl 5, pp. 119-26, 2001, ISSN: 0887-3585.
@article{68,
title = {Rosetta in CASP4: progress in ab initio protein structure prediction},
author = { R Bonneau and J Tsai and I Ruczinski and D Chivian and C Rohl and C E Strauss and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bonneau01C.pdf},
issn = {0887-3585},
year = {2001},
date = {2001-00-01},
journal = {Proteins},
volume = {Suppl 5},
pages = {119-26},
abstract = {Rosetta ab initio protein structure predictions in CASP4 were considerably more consistent and more accurate than previous ab initio structure predictions. Large segments were correctly predicted (>50 residues superimposed within an RMSD of 6.5 A) for 16 of the 21 domains under 300 residues for which models were submitted. Models with the global fold largely correct were produced for several targets with new folds, and for several difficult fold recognition targets, the Rosetta models were more accurate than those produced with traditional fold recognition models. These promising results suggest that Rosetta may soon be able to contribute to the interpretation of genome sequence information.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rosetta ab initio protein structure predictions in CASP4 were considerably more consistent and more accurate than previous ab initio structure predictions. Large segments were correctly predicted (>50 residues superimposed within an RMSD of 6.5 A) for 16 of the 21 domains under 300 residues for which models were submitted. Models with the global fold largely correct were produced for several targets with new folds, and for several difficult fold recognition targets, the Rosetta models were more accurate than those produced with traditional fold recognition models. These promising results suggest that Rosetta may soon be able to contribute to the interpretation of genome sequence information.
2000
P M Bowers, C E Strauss, David Baker
De novo protein structure determination using sparse NMR data. Journal Article
In: Journal of biomolecular NMR, vol. 18, pp. 311-8, 2000, ISSN: 0925-2738.
@article{193,
title = {De novo protein structure determination using sparse NMR data.},
author = { P M Bowers and C E Strauss and David Baker},
issn = {0925-2738},
year = {2000},
date = {2000-12-01},
journal = {Journal of biomolecular NMR},
volume = {18},
pages = {311-8},
abstract = {We describe a method for generating moderate to high-resolution protein structures using limited NMR data combined with the ab initio protein structure prediction method Rosetta. Peptide fragments are selected from proteins of known structure based on sequence similarity and consistency with chemical shift and NOE data. Models are built from these fragments by minimizing an energy function that favors hydrophobic burial, strand pairing, and satisfaction of NOE constraints. Models generated using this procedure with approximately 1 NOE constraint per residue are in some cases closer to the corresponding X-ray structures than the published NMR solution structures. The method requires only the sparse constraints available during initial stages of NMR structure determination, and thus holds promise for increasing the speed with which protein solution structures can be determined.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a method for generating moderate to high-resolution protein structures using limited NMR data combined with the ab initio protein structure prediction method Rosetta. Peptide fragments are selected from proteins of known structure based on sequence similarity and consistency with chemical shift and NOE data. Models are built from these fragments by minimizing an energy function that favors hydrophobic burial, strand pairing, and satisfaction of NOE constraints. Models generated using this procedure with approximately 1 NOE constraint per residue are in some cases closer to the corresponding X-ray structures than the published NMR solution structures. The method requires only the sparse constraints available during initial stages of NMR structure determination, and thus holds promise for increasing the speed with which protein solution structures can be determined.
K W Plaxco, K T Simons, I Ruczinski, D Baker
Topology, stability, sequence, and length: defining the determinants of two-state protein folding kinetics Journal Article
In: Biochemistry, vol. 39, pp. 11177-83, 2000, ISSN: 0006-2960.
@article{320,
title = {Topology, stability, sequence, and length: defining the determinants of two-state protein folding kinetics},
author = { K W Plaxco and K T Simons and I Ruczinski and D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/plaxco00b.pdf},
issn = {0006-2960},
year = {2000},
date = {2000-09-01},
journal = {Biochemistry},
volume = {39},
pages = {11177-83},
abstract = {The fastest simple, single domain proteins fold a million times more rapidly than the slowest. Ultimately this broad kinetic spectrum is determined by the amino acid sequences that define these proteins, suggesting that the mechanisms that underlie folding may be almost as complex as the sequences that encode them. Here, however, we summarize recent experimental results which suggest that (1) despite a vast diversity of structures and functions, there are fundamental similarities in the folding mechanisms of single domain proteins and (2) rather than being highly sensitive to the finest details of sequence, their folding kinetics are determined primarily by the large-scale, redundant features of sequence that determine a proteintextquoterights gross structural properties. That folding kinetics can be predicted using simple, empirical, structure-based rules suggests that the fundamental physics underlying folding may be quite straightforward and that a general and quantitative theory of protein folding rates and mechanisms (as opposed to unfolding rates and thus protein stability) may be near on the horizon.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The fastest simple, single domain proteins fold a million times more rapidly than the slowest. Ultimately this broad kinetic spectrum is determined by the amino acid sequences that define these proteins, suggesting that the mechanisms that underlie folding may be almost as complex as the sequences that encode them. Here, however, we summarize recent experimental results which suggest that (1) despite a vast diversity of structures and functions, there are fundamental similarities in the folding mechanisms of single domain proteins and (2) rather than being highly sensitive to the finest details of sequence, their folding kinetics are determined primarily by the large-scale, redundant features of sequence that determine a proteintextquoterights gross structural properties. That folding kinetics can be predicted using simple, empirical, structure-based rules suggests that the fundamental physics underlying folding may be quite straightforward and that a general and quantitative theory of protein folding rates and mechanisms (as opposed to unfolding rates and thus protein stability) may be near on the horizon.
B Kuhlman, David Baker
Native protein sequences are close to optimal for their structures Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 97, pp. 10383-8, 2000, ISSN: 0027-8424.
@article{198,
title = {Native protein sequences are close to optimal for their structures},
author = { B Kuhlman and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kuhlman00A.pdf},
issn = {0027-8424},
year = {2000},
date = {2000-09-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {97},
pages = {10383-8},
abstract = {How large is the volume of sequence space that is compatible with a given protein structure? Starting from random sequences, low free energy sequences were generated for 108 protein backbone structures by using a Monte Carlo optimization procedure and a free energy function based primarily on Lennard-Jones packing interactions and the Lazaridis-Karplus implicit solvation model. Remarkably, in the designed sequences 51% of the core residues and 27% of all residues were identical to the amino acids in the corresponding positions in the native sequences. The lowest free energy sequences obtained for ensembles of native-like backbone structures were also similar to the native sequence. Furthermore, both the individual residue frequencies and the covariances between pairs of positions observed in the very large SH3 domain family were recapitulated in core sequences designed for SH3 domain structures. Taken together, these results suggest that the volume of sequence space optimal for a protein structure is surprisingly restricted to a region around the native sequence.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
How large is the volume of sequence space that is compatible with a given protein structure? Starting from random sequences, low free energy sequences were generated for 108 protein backbone structures by using a Monte Carlo optimization procedure and a free energy function based primarily on Lennard-Jones packing interactions and the Lazaridis-Karplus implicit solvation model. Remarkably, in the designed sequences 51% of the core residues and 27% of all residues were identical to the amino acids in the corresponding positions in the native sequences. The lowest free energy sequences obtained for ensembles of native-like backbone structures were also similar to the native sequence. Furthermore, both the individual residue frequencies and the covariances between pairs of positions observed in the very large SH3 domain family were recapitulated in core sequences designed for SH3 domain structures. Taken together, these results suggest that the volume of sequence space optimal for a protein structure is surprisingly restricted to a region around the native sequence.
C Bystroff, V Thorsson, David Baker
HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins Journal Article
In: Journal of molecular biology, vol. 301, pp. 173-90, 2000, ISSN: 0022-2836.
@article{194,
title = {HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins},
author = { C Bystroff and V Thorsson and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bystroff00A.pdf},
issn = {0022-2836},
year = {2000},
date = {2000-08-01},
journal = {Journal of molecular biology},
volume = {301},
pages = {173-90},
abstract = {We describe a hidden Markov model, HMMSTR, for general protein sequence based on the I-sites library of sequence-structure motifs. Unlike the linear hidden Markov models used to model individual protein families, HMMSTR has a highly branched topology and captures recurrent local features of protein sequences and structures that transcend protein family boundaries. The model extends the I-sites library by describing the adjacencies of different sequence-structure motifs as observed in the protein database and, by representing overlapping motifs in a much more compact form, achieves a great reduction in parameters. The HMM attributes a considerably higher probability to coding sequence than does an equivalent dipeptide model, predicts secondary structure with an accuracy of 74.3 %, backbone torsion angles better than any previously reported method and the structural context of beta strands and turns with an accuracy that should be useful for tertiary structure prediction.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a hidden Markov model, HMMSTR, for general protein sequence based on the I-sites library of sequence-structure motifs. Unlike the linear hidden Markov models used to model individual protein families, HMMSTR has a highly branched topology and captures recurrent local features of protein sequences and structures that transcend protein family boundaries. The model extends the I-sites library by describing the adjacencies of different sequence-structure motifs as observed in the protein database and, by representing overlapping motifs in a much more compact form, achieves a great reduction in parameters. The HMM attributes a considerably higher probability to coding sequence than does an equivalent dipeptide model, predicts secondary structure with an accuracy of 74.3 %, backbone torsion angles better than any previously reported method and the structural context of beta strands and turns with an accuracy that should be useful for tertiary structure prediction.
E L McCallister, E Alm, David Baker
Critical role of beta-hairpin formation in protein G folding Journal Article
In: Nature structural biology, vol. 7, pp. 669-73, 2000, ISSN: 1072-8368.
@article{199,
title = {Critical role of beta-hairpin formation in protein G folding},
author = { E L McCallister and E Alm and David Baker},
issn = {1072-8368},
year = {2000},
date = {2000-08-01},
journal = {Nature structural biology},
volume = {7},
pages = {669-73},
abstract = {Comparison of the folding mechanisms of proteins with similar structures but very different sequences can provide fundamental insights into the determinants of protein folding mechanisms. Despite very little sequence similarity, the approximately 60 residue IgG binding domains of protein G and protein L both consist of a single helix packed against a four-stranded sheet formed by two symmetrically disposed beta-hairpins. We demonstrate that, as in the case of protein L, one of the two beta-turns of protein G is formed and the other disrupted in the folding transition state. Unlike protein L, however, in protein G it is the second beta-turn that is formed in the folding transition state ensemble. Substitution of an Asp residue by Ala in protein G that eliminates an i,i+2 side chain-main chain hydrogen bond in the second beta-turn slows the folding rate approximately 20-fold but has virtually no effect on the unfolding rate. Taken together with previous results, these findings suggest that the presence of an intact beta-turn in the folding transition state is a consequence of the overall topology of protein L and protein G, but the particular hairpin that is formed is determined by the detailed interatomic interactions that determine the free energies of formation of the isolated beta-hairpins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Comparison of the folding mechanisms of proteins with similar structures but very different sequences can provide fundamental insights into the determinants of protein folding mechanisms. Despite very little sequence similarity, the approximately 60 residue IgG binding domains of protein G and protein L both consist of a single helix packed against a four-stranded sheet formed by two symmetrically disposed beta-hairpins. We demonstrate that, as in the case of protein L, one of the two beta-turns of protein G is formed and the other disrupted in the folding transition state. Unlike protein L, however, in protein G it is the second beta-turn that is formed in the folding transition state ensemble. Substitution of an Asp residue by Ala in protein G that eliminates an i,i+2 side chain-main chain hydrogen bond in the second beta-turn slows the folding rate approximately 20-fold but has virtually no effect on the unfolding rate. Taken together with previous results, these findings suggest that the presence of an intact beta-turn in the folding transition state is a consequence of the overall topology of protein L and protein G, but the particular hairpin that is formed is determined by the detailed interatomic interactions that determine the free energies of formation of the isolated beta-hairpins.
Q Yi, M L Scalley-Kim, E J Alm, David Baker
NMR characterization of residual structure in the denatured state of protein L Journal Article
In: Journal of molecular biology, vol. 299, pp. 1341-51, 2000, ISSN: 0022-2836.
@article{202,
title = {NMR characterization of residual structure in the denatured state of protein L},
author = { Q Yi and M L Scalley-Kim and E J Alm and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/yia00A.pdf},
issn = {0022-2836},
year = {2000},
date = {2000-06-01},
journal = {Journal of molecular biology},
volume = {299},
pages = {1341-51},
abstract = {Triple-resonance NMR experiments were used to assign the (13)C(alpha), (13)C(beta), (15)N and NH resonances for all the residues in the denatured state of a destabilized protein L variant in 2 M guanidine. The chemical shifts of most resonances were very close to their random coil values. Significant deviations were observed for G22, L38 and K39; increasing the denaturant concentration shifted the chemical shifts of these residues towards theory random coil values. Medium-range nuclear Overhauser enhancements were detected in segments corresponding to the turn between the first two strands, the end of the second strand through the turn between the second strand and the helix, and the turn between the helix and the third strand in 3D H(1), N(15)-HSQC-NOESY-HSQC experiments on perdeuterated samples. Longer-range interactions were probed by measuring the paramagnetic relaxation enhancement produced by nitroxide spin labels introduced via cysteine residues at five sites around the molecule. Damped oscillations in the magnitude of the paramagnetic relaxation enhancement as a function of distance along the sequence suggested native-like chain reversals in the same three turn regions. The more extensive interactions within the region corresponding to the first beta-turn than in the region corresponding to the second beta-turn suggests that the asymmetry in the folding reaction evident in previous studies of the protein L folding transition state is already established in the denatured state.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Triple-resonance NMR experiments were used to assign the (13)C(alpha), (13)C(beta), (15)N and NH resonances for all the residues in the denatured state of a destabilized protein L variant in 2 M guanidine. The chemical shifts of most resonances were very close to their random coil values. Significant deviations were observed for G22, L38 and K39; increasing the denaturant concentration shifted the chemical shifts of these residues towards theory random coil values. Medium-range nuclear Overhauser enhancements were detected in segments corresponding to the turn between the first two strands, the end of the second strand through the turn between the second strand and the helix, and the turn between the helix and the third strand in 3D H(1), N(15)-HSQC-NOESY-HSQC experiments on perdeuterated samples. Longer-range interactions were probed by measuring the paramagnetic relaxation enhancement produced by nitroxide spin labels introduced via cysteine residues at five sites around the molecule. Damped oscillations in the magnitude of the paramagnetic relaxation enhancement as a function of distance along the sequence suggested native-like chain reversals in the same three turn regions. The more extensive interactions within the region corresponding to the first beta-turn than in the region corresponding to the second beta-turn suggests that the asymmetry in the folding reaction evident in previous studies of the protein L folding transition state is already established in the denatured state.
V P Grantcharova, D S Riddle, David Baker
Long-range order in the src SH3 folding transition state Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 97, pp. 7084-9, 2000, ISSN: 0027-8424.
@article{195,
title = {Long-range order in the src SH3 folding transition state},
author = { V P Grantcharova and D S Riddle and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/grantcharova00A.pdf},
issn = {0027-8424},
year = {2000},
date = {2000-06-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {97},
pages = {7084-9},
abstract = {One of the outstanding questions in protein folding concerns the degree of heterogeneity in the folding transition state ensemble: does a protein fold via a large multitude of diverse "pathways," or are the elements of native structure assembled in a well defined order? Herein, we build on previous point mutagenesis studies of the src SH3 by directly investigating the association of structural elements and the loss of backbone conformational entropy during folding. Double-mutant analysis of polar residues in the distal beta-hairpin and the diverging turn indicates that the hydrogen bond network between these elements is largely formed in the folding transition state. A 10-glycine insertion in the n-src loop (which connects the distal hairpin and the diverging turn) and a disulfide crosslink at the base of the distal beta-hairpin exclusively affect the folding rate, showing that these structural elements are nearly as ordered in the folding transition state as in the native state. In contrast, crosslinking the base of the RT loop or the N and C termini dramatically slows down the unfolding rate, suggesting that dissociation of the termini and opening of the RT loop precede the rate-limiting step in unfolding. Taken together, these results suggest that essentially all conformations in the folding transition state ensemble have the central three-stranded beta-sheet formed, indicating that, for the src homology 3 domain, there is a discrete order to structure assembly during folding.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
One of the outstanding questions in protein folding concerns the degree of heterogeneity in the folding transition state ensemble: does a protein fold via a large multitude of diverse "pathways," or are the elements of native structure assembled in a well defined order? Herein, we build on previous point mutagenesis studies of the src SH3 by directly investigating the association of structural elements and the loss of backbone conformational entropy during folding. Double-mutant analysis of polar residues in the distal beta-hairpin and the diverging turn indicates that the hydrogen bond network between these elements is largely formed in the folding transition state. A 10-glycine insertion in the n-src loop (which connects the distal hairpin and the diverging turn) and a disulfide crosslink at the base of the distal beta-hairpin exclusively affect the folding rate, showing that these structural elements are nearly as ordered in the folding transition state as in the native state. In contrast, crosslinking the base of the RT loop or the N and C termini dramatically slows down the unfolding rate, suggesting that dissociation of the termini and opening of the RT loop precede the rate-limiting step in unfolding. Taken together, these results suggest that essentially all conformations in the folding transition state ensemble have the central three-stranded beta-sheet formed, indicating that, for the src homology 3 domain, there is a discrete order to structure assembly during folding.
David Baker
A surprising simplicity to protein folding Journal Article
In: Nature, vol. 405, pp. 39-42, 2000, ISSN: 0028-0836.
@article{192,
title = {A surprising simplicity to protein folding},
author = { David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/baker00A.pdf},
issn = {0028-0836},
year = {2000},
date = {2000-05-01},
journal = {Nature},
volume = {405},
pages = {39-42},
abstract = {The polypeptide chains that make up proteins have thousands of atoms and hence millions of possible inter-atomic interactions. It might be supposed that the resulting complexity would make prediction of protein structure and protein-folding mechanisms nearly impossible. But the fundamental physics underlying folding may be much simpler than this complexity would lead us to expect folding rates and mechanisms appear to be largely determined by the topology of the native (folded) state, and new methods have shown great promise in predicting protein-folding mechanisms and the three-dimensional structures of proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The polypeptide chains that make up proteins have thousands of atoms and hence millions of possible inter-atomic interactions. It might be supposed that the resulting complexity would make prediction of protein structure and protein-folding mechanisms nearly impossible. But the fundamental physics underlying folding may be much simpler than this complexity would lead us to expect folding rates and mechanisms appear to be largely determined by the topology of the native (folded) state, and new methods have shown great promise in predicting protein-folding mechanisms and the three-dimensional structures of proteins.
David E Kim, C Fisher, David Baker
A breakdown of symmetry in the folding transition state of protein L Journal Article
In: Journal of molecular biology, vol. 298, pp. 971-84, 2000, ISSN: 0022-2836.
@article{196,
title = {A breakdown of symmetry in the folding transition state of protein L},
author = { David E Kim and C Fisher and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kim00A.pdf},
issn = {0022-2836},
year = {2000},
date = {2000-05-01},
journal = {Journal of molecular biology},
volume = {298},
pages = {971-84},
abstract = {The 62 residue IgG binding domain of protein L consists of a central alpha-helix packed on a four-stranded beta-sheet formed by N and C-terminal beta-hairpins. The overall topology of the protein is quite symmetric: the beta-hairpins have similar lengths and make very similar interactions with the central helix. Characterization of the effects of 70 point mutations distributed throughout the protein on the kinetics of folding and unfolding reveals that this symmetry is completely broken during folding; the first beta-hairpin is largely structured while the second beta-hairpin and helix are largely disrupted in the folding transition state ensemble. The results are not consistent with a "hydrophobic core first" picture of protein folding; the first beta-hairpin appears to be at least as ordered at the rate limiting step in folding as the hydrophobic core.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The 62 residue IgG binding domain of protein L consists of a central alpha-helix packed on a four-stranded beta-sheet formed by N and C-terminal beta-hairpins. The overall topology of the protein is quite symmetric: the beta-hairpins have similar lengths and make very similar interactions with the central helix. Characterization of the effects of 70 point mutations distributed throughout the protein on the kinetics of folding and unfolding reveals that this symmetry is completely broken during folding; the first beta-hairpin is largely structured while the second beta-hairpin and helix are largely disrupted in the folding transition state ensemble. The results are not consistent with a "hydrophobic core first" picture of protein folding; the first beta-hairpin appears to be at least as ordered at the rate limiting step in folding as the hydrophobic core.
K W Plaxco, S Larson, I Ruczinski, D S Riddle, E C Thayer, B Buchwitz, A R Davidson, David Baker
Evolutionary conservation in protein folding kinetics Journal Article
In: Journal of molecular biology, vol. 298, pp. 303-12, 2000, ISSN: 0022-2836.
@article{200,
title = {Evolutionary conservation in protein folding kinetics},
author = { K W Plaxco and S Larson and I Ruczinski and D S Riddle and E C Thayer and B Buchwitz and A R Davidson and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/plaxco00a.pdf},
issn = {0022-2836},
year = {2000},
date = {2000-04-01},
journal = {Journal of molecular biology},
volume = {298},
pages = {303-12},
abstract = {The sequence and structural conservation of folding transition states have been predicted on theoretical grounds. Using homologous sequence alignments of proteins previously characterized via coupled mutagenesis/kinetics studies, we tested these predictions experimentally. Only one of the six appropriately characterized proteins exhibits a statistically significant correlation between residuestextquoteright roles in transition state structure and their evolutionary conservation. However, a significant correlation is observed between the contributions of individual sequence positions to the transition state structure across a set of homologous proteins. Thus the structure of the folding transition state ensemble appears to be more highly conserved than the specific interactions that stabilize it.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The sequence and structural conservation of folding transition states have been predicted on theoretical grounds. Using homologous sequence alignments of proteins previously characterized via coupled mutagenesis/kinetics studies, we tested these predictions experimentally. Only one of the six appropriately characterized proteins exhibits a statistically significant correlation between residuestextquoteright roles in transition state structure and their evolutionary conservation. However, a significant correlation is observed between the contributions of individual sequence positions to the transition state structure across a set of homologous proteins. Thus the structure of the folding transition state ensemble appears to be more highly conserved than the specific interactions that stabilize it.
K Johnsen, J W OtextquoterightNeill, D E Kim, D Baker, K Y Zhang
Crystallization and preliminary X-ray diffraction studies of mutants of B1 IgG-binding domain of protein L from Peptostreptococcus magnus Journal Article
In: Acta crystallographica. Section D, vol. 56, pp. 506-8, 2000, ISSN: 0907-4449.
@article{321,
title = {Crystallization and preliminary X-ray diffraction studies of mutants of B1 IgG-binding domain of protein L from Peptostreptococcus magnus},
author = { K Johnsen and J W OtextquoterightNeill and D E Kim and D Baker and K Y Zhang},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/johnsen00A.pdf},
issn = {0907-4449},
year = {2000},
date = {2000-04-01},
journal = {Acta crystallographica. Section D},
volume = {56},
pages = {506-8},
abstract = {The small 62-residue IgG-binding domain B1 of protein L from Peptostreptococcus magnus (Ppl-B1) has proven to be a simple system for the study of the thermodynamics and kinetics of protein folding. X-ray diffraction studies have been initiated in order to determine how the thermostability, folding and unfolding rates of a series of point mutations spanning Ppl-B1 correlate with the high-resolution structures. To this end, a tryptophan-containing variant of Ppl-B1 (herein known as wild type) and two mutants, Lys61Ala and Val49Ala, have been crystallized. Full data sets have been collected for the wild type and the Lys61Ala and Val49Ala mutants to resolutions of 1. 7, 2.3 and 1.8 A, respectively. Interestingly, all three crystallize using different precipitants and in different space groups. This may be a consequence of the relatively large effects of single-site mutations on surface-charge distribution or structural conformation, which might affect crystal contact sites.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The small 62-residue IgG-binding domain B1 of protein L from Peptostreptococcus magnus (Ppl-B1) has proven to be a simple system for the study of the thermodynamics and kinetics of protein folding. X-ray diffraction studies have been initiated in order to determine how the thermostability, folding and unfolding rates of a series of point mutations spanning Ppl-B1 correlate with the high-resolution structures. To this end, a tryptophan-containing variant of Ppl-B1 (herein known as wild type) and two mutants, Lys61Ala and Val49Ala, have been crystallized. Full data sets have been collected for the wild type and the Lys61Ala and Val49Ala mutants to resolutions of 1. 7, 2.3 and 1.8 A, respectively. Interestingly, all three crystallize using different precipitants and in different space groups. This may be a consequence of the relatively large effects of single-site mutations on surface-charge distribution or structural conformation, which might affect crystal contact sites.
E C Thayer, C Bystroff, David Baker
Detection of protein coding sequences using a mixture model for local protein amino acid sequence Journal Article
In: Journal of computational biology : a journal of computational molecular cell biology, vol. 7, pp. 317-27, 2000, ISSN: 1066-5277.
@article{201,
title = {Detection of protein coding sequences using a mixture model for local protein amino acid sequence},
author = { E C Thayer and C Bystroff and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/thayer00A.pdf},
issn = {1066-5277},
year = {2000},
date = {2000-02-01},
journal = {Journal of computational biology : a journal of computational molecular cell biology},
volume = {7},
pages = {317-27},
abstract = {Locating protein coding regions in genomic DNA is a critical step in accessing the information generated by large scale sequencing projects. Current methods for gene detection depend on statistical measures of content differences between coding and noncoding DNA in addition to the recognition of promoters, splice sites, and other regulatory sites. Here we explore the potential value of recurrent amino acid sequence patterns 3-19 amino acids in length as a content statistic for use in gene finding approaches. A finite mixture model incorporating these patterns can partially discriminate protein sequences which have no (detectable) known homologs from randomized versions of these sequences, and from short (< or = 50 amino acids) non-coding segments extracted from the S. cerevisiea genome. The mixture model derived scores for a collection of human exons were not correlated with the GENSCAN scores, suggesting that the addition of our protein pattern recognition module to current gene recognition programs may improve their performance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Locating protein coding regions in genomic DNA is a critical step in accessing the information generated by large scale sequencing projects. Current methods for gene detection depend on statistical measures of content differences between coding and noncoding DNA in addition to the recognition of promoters, splice sites, and other regulatory sites. Here we explore the potential value of recurrent amino acid sequence patterns 3-19 amino acids in length as a content statistic for use in gene finding approaches. A finite mixture model incorporating these patterns can partially discriminate protein sequences which have no (detectable) known homologs from randomized versions of these sequences, and from short (< or = 50 amino acids) non-coding segments extracted from the S. cerevisiea genome. The mixture model derived scores for a collection of human exons were not correlated with the GENSCAN scores, suggesting that the addition of our protein pattern recognition module to current gene recognition programs may improve their performance.
1999
H Gu, N Doshi, David E Kim, K T Simons, J V Santiago, S Nauli, David Baker
Robustness of protein folding kinetics to surface hydrophobic substitutions Journal Article
In: Protein science, vol. 8, pp. 2734-41, 1999, ISSN: 0961-8368.
@article{46,
title = {Robustness of protein folding kinetics to surface hydrophobic substitutions},
author = { H Gu and N Doshi and David E Kim and K T Simons and J V Santiago and S Nauli and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/gu99A.pdf},
issn = {0961-8368},
year = {1999},
date = {1999-12-01},
journal = {Protein science},
volume = {8},
pages = {2734-41},
abstract = {We use both combinatorial and site-directed mutagenesis to explore the consequences of surface hydrophobic substitutions for the folding of two small single domain proteins, the src SH3 domain, and the IgG binding domain of Peptostreptococcal protein L. We find that in almost every case, destabilizing surface hydrophobic substitutions have much larger effects on the rate of unfolding than on the rate of folding, suggesting that nonnative hydrophobic interactions do not significantly interfere with the rate of core assembly.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We use both combinatorial and site-directed mutagenesis to explore the consequences of surface hydrophobic substitutions for the folding of two small single domain proteins, the src SH3 domain, and the IgG binding domain of Peptostreptococcal protein L. We find that in almost every case, destabilizing surface hydrophobic substitutions have much larger effects on the rate of unfolding than on the rate of folding, suggesting that nonnative hydrophobic interactions do not significantly interfere with the rate of core assembly.
M L Scalley, S Nauli, S T Gladwin, David Baker
Structural transitions in the protein L denatured state ensemble Journal Article
In: Biochemistry, vol. 38, pp. 15927-35, 1999, ISSN: 0006-2960.
@article{42,
title = {Structural transitions in the protein L denatured state ensemble},
author = { M L Scalley and S Nauli and S T Gladwin and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/scalley99A.pdf},
issn = {0006-2960},
year = {1999},
date = {1999-11-01},
journal = {Biochemistry},
volume = {38},
pages = {15927-35},
abstract = {We use a broad array of biophysical methods to probe the extent of structure and time scale of structural transitions in the protein L denatured state ensemble. Measurement of amide proton exchange protection during the first several milliseconds following initiation of refolding in 0.4 M sodium sulfate revealed weak protection in the first beta-hairpin and helix. A tryptophan residue was introduced into the first beta-hairpin to probe the extent of structure formation in this part of the protein; the intrinsic fluorescence of this tryptophan was found to deviate from that expected given its local sequence context in 2-3 M guanidine, suggesting some partial ordering of this region in the unfolded state ensemble. To further probe this partial ordering, dansyl groups were introduced via cysteine residues at three sites in the protein. It was found that fluorescence energy transfer from the introduced tryptophan to the dansyl groups decreased dramatically upon unfolding. Stopped-flow fluorescence studies showed that the recovery of dansyl fluorescence upon refolding occurred on a submillisecond time scale. To probe the interactions responsible for the residual structure observed in the denatured state ensemble, the conformation of a peptide corresponding to the first beta-hairpin and helix of protein L was studied using circular dichroism spectroscopy and compared to that of full-length protein L and previously characterized peptides corresponding to the isolated helix and second beta-hairpin.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We use a broad array of biophysical methods to probe the extent of structure and time scale of structural transitions in the protein L denatured state ensemble. Measurement of amide proton exchange protection during the first several milliseconds following initiation of refolding in 0.4 M sodium sulfate revealed weak protection in the first beta-hairpin and helix. A tryptophan residue was introduced into the first beta-hairpin to probe the extent of structure formation in this part of the protein; the intrinsic fluorescence of this tryptophan was found to deviate from that expected given its local sequence context in 2-3 M guanidine, suggesting some partial ordering of this region in the unfolded state ensemble. To further probe this partial ordering, dansyl groups were introduced via cysteine residues at three sites in the protein. It was found that fluorescence energy transfer from the introduced tryptophan to the dansyl groups decreased dramatically upon unfolding. Stopped-flow fluorescence studies showed that the recovery of dansyl fluorescence upon refolding occurred on a submillisecond time scale. To probe the interactions responsible for the residual structure observed in the denatured state ensemble, the conformation of a peptide corresponding to the first beta-hairpin and helix of protein L was studied using circular dichroism spectroscopy and compared to that of full-length protein L and previously characterized peptides corresponding to the isolated helix and second beta-hairpin.
D S Riddle, V P Grantcharova, J V Santiago, E Alm, I Ruczinski, David Baker
Experiment and theory highlight role of native state topology in SH3 folding Journal Article
In: Nature structural biology, vol. 6, pp. 1016-24, 1999, ISSN: 1072-8368.
@article{43,
title = {Experiment and theory highlight role of native state topology in SH3 folding},
author = { D S Riddle and V P Grantcharova and J V Santiago and E Alm and I Ruczinski and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/riddle99A.pdf},
issn = {1072-8368},
year = {1999},
date = {1999-11-01},
journal = {Nature structural biology},
volume = {6},
pages = {1016-24},
abstract = {We use a combination of experiments, computer simulations and simple model calculations to characterize, first, the folding transition state ensemble of the src SH3 domain, and second, the features of the protein that determine its folding mechanism. Kinetic analysis of mutations at 52 of the 57 residues in the src SH3 domain revealed that the transition state ensemble is even more polarized than suspected earlier: no single alanine substitution in the N-terminal 15 residues or the C-terminal 9 residues has more than a two-fold effect on the folding rate, while such substitutions at 15 sites in the central three-stranded beta-sheet cause significant decreases in the folding rate. Molecular dynamics (MD) unfolding simulations and ab initio folding simulations on the src SH3 domain exhibit a hierarchy of folding similar to that observed in the experiments. The similarity in folding mechanism of different SH3 domains and the similar hierarchy of structure formation observed in the experiments and the simulations can be largely accounted for by a simple native state topology-based model of protein folding energy landscapes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We use a combination of experiments, computer simulations and simple model calculations to characterize, first, the folding transition state ensemble of the src SH3 domain, and second, the features of the protein that determine its folding mechanism. Kinetic analysis of mutations at 52 of the 57 residues in the src SH3 domain revealed that the transition state ensemble is even more polarized than suspected earlier: no single alanine substitution in the N-terminal 15 residues or the C-terminal 9 residues has more than a two-fold effect on the folding rate, while such substitutions at 15 sites in the central three-stranded beta-sheet cause significant decreases in the folding rate. Molecular dynamics (MD) unfolding simulations and ab initio folding simulations on the src SH3 domain exhibit a hierarchy of folding similar to that observed in the experiments. The similarity in folding mechanism of different SH3 domains and the similar hierarchy of structure formation observed in the experiments and the simulations can be largely accounted for by a simple native state topology-based model of protein folding energy landscapes.
E Alm, David Baker
Prediction of protein-folding mechanisms from free-energy landscapes derived from native structures Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 96, pp. 11305-10, 1999, ISSN: 0027-8424.
@article{48,
title = {Prediction of protein-folding mechanisms from free-energy landscapes derived from native structures},
author = { E Alm and David Baker},
issn = {0027-8424},
year = {1999},
date = {1999-09-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {96},
pages = {11305-10},
abstract = {Guided by recent experimental results suggesting that protein-folding rates and mechanisms are determined largely by native-state topology, we develop a simple model for protein folding free-energy landscapes based on native-state structures. The configurations considered by the model contain one or two contiguous stretches of residues ordered as in the native structure with all other residues completely disordered; the free energy of each configuration is the difference between the entropic cost of ordering the residues, which depends on the total number of residues ordered and the length of the loop between the two ordered segments, and the favorable attractive interactions, which are taken to be proportional to the total surface area buried by the ordered residues in the native structure. Folding kinetics are modeled by allowing only one residue to become ordered/disordered at a time, and a rigorous and exact method is used to identify free-energy maxima on the lowest free-energy paths connecting the fully disordered and fully ordered configurations. The distribution of structure in these free-energy maxima, which comprise the transition-state ensemble in the model, are reasonably consistent with experimental data on the folding transition state for five of seven proteins studied. Thus, the model appears to capture, at least in part, the basic physics underlying protein folding and the aspects of native-state topology that determine protein-folding mechanisms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Guided by recent experimental results suggesting that protein-folding rates and mechanisms are determined largely by native-state topology, we develop a simple model for protein folding free-energy landscapes based on native-state structures. The configurations considered by the model contain one or two contiguous stretches of residues ordered as in the native structure with all other residues completely disordered; the free energy of each configuration is the difference between the entropic cost of ordering the residues, which depends on the total number of residues ordered and the length of the loop between the two ordered segments, and the favorable attractive interactions, which are taken to be proportional to the total surface area buried by the ordered residues in the native structure. Folding kinetics are modeled by allowing only one residue to become ordered/disordered at a time, and a rigorous and exact method is used to identify free-energy maxima on the lowest free-energy paths connecting the fully disordered and fully ordered configurations. The distribution of structure in these free-energy maxima, which comprise the transition-state ensemble in the model, are reasonably consistent with experimental data on the folding transition state for five of seven proteins studied. Thus, the model appears to capture, at least in part, the basic physics underlying protein folding and the aspects of native-state topology that determine protein-folding mechanisms.
J Tsai, M Levitt, David Baker
Hierarchy of structure loss in MD simulations of src SH3 domain unfolding Journal Article
In: Journal of molecular biology, vol. 291, pp. 215-25, 1999, ISSN: 0022-2836.
@article{39,
title = {Hierarchy of structure loss in MD simulations of src SH3 domain unfolding},
author = { J Tsai and M Levitt and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/tsai99A.pdf},
issn = {0022-2836},
year = {1999},
date = {1999-08-01},
journal = {Journal of molecular biology},
volume = {291},
pages = {215-25},
abstract = {To complement experimental studies of the src SH3 domain folding, we studied 30 independent, high-temperature, molecular dynamics simulations of src SH3 domain unfolding. These trajectories were observed to differ widely from each other. Thus, rather than analyzing individual trajectories, we sought to identify the recurrent features of the high-temperature unfolding process. The conformations from all simulations were combined and then divided into groups based on the number of native contacts. Average occupancies of each side-chain hydrophobic contact and hydrogen bond in the protein were then determined. In the symmetric funnel limit, the occupancies of all contacts should decrease in concert with the loss in total number of native contacts. If there is a lack of symmetry or hierarchy to the unfolding process, the occupancies of some contacts should decrease more slowly, and others more rapidly. Despite the heterogeneity of the individual trajectories, the ensemble averaging revealed an order to the unfolding process: contacts between the N and C-terminal strands are the first to disappear, whereas contacts within the distal beta-hairpin and a hydrogen-bonding network involving the distal loop beta-turn and the diverging turn persist well after the majority of the native contacts are lost. This hierarchy of events resembles but is somewhat less pronounced than that observed in our experimental studies of the folding of src SH3 domain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To complement experimental studies of the src SH3 domain folding, we studied 30 independent, high-temperature, molecular dynamics simulations of src SH3 domain unfolding. These trajectories were observed to differ widely from each other. Thus, rather than analyzing individual trajectories, we sought to identify the recurrent features of the high-temperature unfolding process. The conformations from all simulations were combined and then divided into groups based on the number of native contacts. Average occupancies of each side-chain hydrophobic contact and hydrogen bond in the protein were then determined. In the symmetric funnel limit, the occupancies of all contacts should decrease in concert with the loss in total number of native contacts. If there is a lack of symmetry or hierarchy to the unfolding process, the occupancies of some contacts should decrease more slowly, and others more rapidly. Despite the heterogeneity of the individual trajectories, the ensemble averaging revealed an order to the unfolding process: contacts between the N and C-terminal strands are the first to disappear, whereas contacts within the distal beta-hairpin and a hydrogen-bonding network involving the distal loop beta-turn and the diverging turn persist well after the majority of the native contacts are lost. This hierarchy of events resembles but is somewhat less pronounced than that observed in our experimental studies of the folding of src SH3 domain.
David Baker, WF DeGrado
Engineering and design Journal Article
In: Current opinion in structural biology, vol. 9, pp. 485-6, 1999, ISSN: 1879-033X.
@article{47,
title = {Engineering and design},
author = { David Baker and WF DeGrado},
issn = {1879-033X},
year = {1999},
date = {1999-08-01},
journal = {Current opinion in structural biology},
volume = {9},
pages = {485-6},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
K W Plaxco, I S Millett, D J Segel, S Doniach, David Baker
Chain collapse can occur concomitantly with the rate-limiting step in protein folding Journal Article
In: Nature structural biology, vol. 6, pp. 554-6, 1999, ISSN: 1072-8368.
@article{44,
title = {Chain collapse can occur concomitantly with the rate-limiting step in protein folding},
author = { K W Plaxco and I S Millett and D J Segel and S Doniach and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/plaxco99A.pdf},
issn = {1072-8368},
year = {1999},
date = {1999-06-01},
journal = {Nature structural biology},
volume = {6},
pages = {554-6},
abstract = {We have directly characterized the extent of chain collapse early in the folding of protein L using time-resolved small angle X-ray scattering. We find that, immediately after the initiation of refolding, the protein exhibits dimensions indistinguishable from those observed under highly denaturing, equilibrium conditions and that this expanded initial state collapses with the same rate as that of the overall folding reaction. The observation that chain compaction need not significantly precede the rate-limiting step of folding demonstrates that rapid chain collapse is not an obligatory feature of protein folding reactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have directly characterized the extent of chain collapse early in the folding of protein L using time-resolved small angle X-ray scattering. We find that, immediately after the initiation of refolding, the protein exhibits dimensions indistinguishable from those observed under highly denaturing, equilibrium conditions and that this expanded initial state collapses with the same rate as that of the overall folding reaction. The observation that chain compaction need not significantly precede the rate-limiting step of folding demonstrates that rapid chain collapse is not an obligatory feature of protein folding reactions.
E Alm, David Baker
Matching theory and experiment in protein folding. Journal Article
In: Current opinion in structural biology, vol. 9, pp. 189-96, 1999, ISSN: 0959-440X.
@article{49,
title = {Matching theory and experiment in protein folding.},
author = { E Alm and David Baker},
issn = {0959-440X},
year = {1999},
date = {1999-04-01},
journal = {Current opinion in structural biology},
volume = {9},
pages = {189-96},
abstract = {There has been considerable progress made over the past year in linking experimental and theoretical approaches to protein folding. Recent results from several independent lines of investigation suggest that protein folding mechanisms and landscapes are largely determined by the topology of the native state and are relatively insensitive to details of the interatomic interactions. This dependence on low-resolution structural features, rather than high-resolution detail, suggests that it should be possible to describe the fundamental physics of the folding process using relatively low-resolution models. Recent experiments have set benchmarks for testing new models and progress has been made in developing theoretical models for interpreting and predicting experimental results.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
There has been considerable progress made over the past year in linking experimental and theoretical approaches to protein folding. Recent results from several independent lines of investigation suggest that protein folding mechanisms and landscapes are largely determined by the topology of the native state and are relatively insensitive to details of the interatomic interactions. This dependence on low-resolution structural features, rather than high-resolution detail, suggests that it should be possible to describe the fundamental physics of the folding process using relatively low-resolution models. Recent experiments have set benchmarks for testing new models and progress has been made in developing theoretical models for interpreting and predicting experimental results.
K T Simons, I Ruczinski, C Kooperberg, B A Fox, C Bystroff, D Baker
Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins Journal Article
In: Proteins, vol. 34, pp. 82-95, 1999, ISSN: 0887-3585.
@article{322,
title = {Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins},
author = { K T Simons and I Ruczinski and C Kooperberg and B A Fox and C Bystroff and D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/simons98A.pdf},
issn = {0887-3585},
year = {1999},
date = {1999-01-01},
journal = {Proteins},
volume = {34},
pages = {82-95},
abstract = {We describe the development of a scoring function based on the decomposition P(structure/sequence) proportional to P(sequence/structure) *P(structure), which outperforms previous scoring functions in correctly identifying native-like protein structures in large ensembles of compact decoys. The first term captures sequence-dependent features of protein structures, such as the burial of hydrophobic residues in the core, the second term, universal sequence-independent features, such as the assembly of beta-strands into beta-sheets. The efficacies of a wide variety of sequence-dependent and sequence-independent features of protein structures for recognizing native-like structures were systematically evaluated using ensembles of approximately 30,000 compact conformations with fixed secondary structure for each of 17 small protein domains. The best results were obtained using a core scoring function with P(sequence/structure) parameterized similarly to our previous work (Simons et al., J Mol Biol 1997;268:209-225] and P(structure) focused on secondary structure packing preferences; while several additional features had some discriminatory power on their own, they did not provide any additional discriminatory power when combined with the core scoring function. Our results, on both the training set and the independent decoy set of Park and Levitt (J Mol Biol 1996;258:367-392), suggest that this scoring function should contribute to the prediction of tertiary structure from knowledge of sequence and secondary structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe the development of a scoring function based on the decomposition P(structure/sequence) proportional to P(sequence/structure) *P(structure), which outperforms previous scoring functions in correctly identifying native-like protein structures in large ensembles of compact decoys. The first term captures sequence-dependent features of protein structures, such as the burial of hydrophobic residues in the core, the second term, universal sequence-independent features, such as the assembly of beta-strands into beta-sheets. The efficacies of a wide variety of sequence-dependent and sequence-independent features of protein structures for recognizing native-like structures were systematically evaluated using ensembles of approximately 30,000 compact conformations with fixed secondary structure for each of 17 small protein domains. The best results were obtained using a core scoring function with P(sequence/structure) parameterized similarly to our previous work (Simons et al., J Mol Biol 1997;268:209-225] and P(structure) focused on secondary structure packing preferences; while several additional features had some discriminatory power on their own, they did not provide any additional discriminatory power when combined with the core scoring function. Our results, on both the training set and the independent decoy set of Park and Levitt (J Mol Biol 1996;258:367-392), suggest that this scoring function should contribute to the prediction of tertiary structure from knowledge of sequence and secondary structure.
K T Simons, R Bonneau, I Ruczinski, David Baker
Ab initio protein structure prediction of CASP III targets using ROSETTA Journal Article
In: Proteins, vol. Suppl 3, pp. 171-6, 1999, ISSN: 0887-3585.
@article{41,
title = {Ab initio protein structure prediction of CASP III targets using ROSETTA},
author = { K T Simons and R Bonneau and I Ruczinski and David Baker},
issn = {0887-3585},
year = {1999},
date = {1999-00-01},
journal = {Proteins},
volume = {Suppl 3},
pages = {171-6},
abstract = {To generate structures consistent with both the local and nonlocal interactions responsible for protein stability, 3 and 9 residue fragments of known structures with local sequences similar to the target sequence were assembled into complete tertiary structures using a Monte Carlo simulated annealing procedure (Simons et al., J Mol Biol 1997; 268:209-225). The scoring function used in the simulated annealing procedure consists of sequence-dependent terms representing hydrophobic burial and specific pair interactions such as electrostatics and disulfide bonding and sequence-independent terms representing hard sphere packing, alpha-helix and beta-strand packing, and the collection of beta-strands in beta-sheets (Simons et al., Proteins 1999;34:82-95). For each of 21 small, ab initio targets, 1,200 final structures were constructed, each the result of 100,000 attempted fragment substitutions. The five structures submitted for the CASP III experiment were chosen from the approximately 25 structures with the lowest scores in the broadest minima (assessed through the number of structural neighbors; Shortle et al., Proc Natl Acad Sci USA 1998;95:1158-1162). The results were encouraging: highlights of the predictions include a 99-residue segment for MarA with an rmsd of 6.4 A to the native structure, a 95-residue (full length) prediction for the EH2 domain of EPS15 with an rmsd of 6.0 A, a 75-residue segment of DNAB helicase with an rmsd of 4.7 A, and a 67-residue segment of ribosomal protein L30 with an rmsd of 3.8 A. These results suggest that ab initio methods may soon become useful for low-resolution structure prediction for proteins that lack a close homologue of known structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To generate structures consistent with both the local and nonlocal interactions responsible for protein stability, 3 and 9 residue fragments of known structures with local sequences similar to the target sequence were assembled into complete tertiary structures using a Monte Carlo simulated annealing procedure (Simons et al., J Mol Biol 1997; 268:209-225). The scoring function used in the simulated annealing procedure consists of sequence-dependent terms representing hydrophobic burial and specific pair interactions such as electrostatics and disulfide bonding and sequence-independent terms representing hard sphere packing, alpha-helix and beta-strand packing, and the collection of beta-strands in beta-sheets (Simons et al., Proteins 1999;34:82-95). For each of 21 small, ab initio targets, 1,200 final structures were constructed, each the result of 100,000 attempted fragment substitutions. The five structures submitted for the CASP III experiment were chosen from the approximately 25 structures with the lowest scores in the broadest minima (assessed through the number of structural neighbors; Shortle et al., Proc Natl Acad Sci USA 1998;95:1158-1162). The results were encouraging: highlights of the predictions include a 99-residue segment for MarA with an rmsd of 6.4 A to the native structure, a 95-residue (full length) prediction for the EH2 domain of EPS15 with an rmsd of 6.0 A, a 75-residue segment of DNAB helicase with an rmsd of 4.7 A, and a 67-residue segment of ribosomal protein L30 with an rmsd of 3.8 A. These results suggest that ab initio methods may soon become useful for low-resolution structure prediction for proteins that lack a close homologue of known structure.
1998
David E Kim, Q Yi, S T Gladwin, J M Goldberg, David Baker
The single helix in protein L is largely disrupted at the rate-limiting step in folding Journal Article
In: Journal of molecular biology, vol. 284, pp. 807-15, 1998, ISSN: 0022-2836.
@article{209,
title = {The single helix in protein L is largely disrupted at the rate-limiting step in folding},
author = { David E Kim and Q Yi and S T Gladwin and J M Goldberg and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kim98A_0.pdf},
issn = {0022-2836},
year = {1998},
date = {1998-12-01},
journal = {Journal of molecular biology},
volume = {284},
pages = {807-15},
abstract = {To investigate the role of helix formation in the folding of protein L, a 62 residue alpha/beta protein, we studied the consequences of both single and multiple mutations in the helix on the kinetics of folding. A triple mutant with 11 additional carbon atoms in core residues in the amino-terminal portion of the helix folded substantially faster than wild type, suggesting that hydrophobic association with residues elsewhere in the protein occurs at the rate-limiting step in folding. However, helix-destabilizing mutations had little effect on the rate of folding; in particular, a triple glycine substitution on the solvent-exposed side of the helix increased the unfolding rate 56-fold while reducing the folding rate less than threefold. Thus, in contrast to the predictions of models of folding involving the coalescence of well-formed secondary structure elements, the single helix in protein L appears to be largely disrupted at the rate-limiting step in folding and unfolding.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To investigate the role of helix formation in the folding of protein L, a 62 residue alpha/beta protein, we studied the consequences of both single and multiple mutations in the helix on the kinetics of folding. A triple mutant with 11 additional carbon atoms in core residues in the amino-terminal portion of the helix folded substantially faster than wild type, suggesting that hydrophobic association with residues elsewhere in the protein occurs at the rate-limiting step in folding. However, helix-destabilizing mutations had little effect on the rate of folding; in particular, a triple glycine substitution on the solvent-exposed side of the helix increased the unfolding rate 56-fold while reducing the folding rate less than threefold. Thus, in contrast to the predictions of models of folding involving the coalescence of well-formed secondary structure elements, the single helix in protein L appears to be largely disrupted at the rate-limiting step in folding and unfolding.
David Baker
Metastable states and folding free energy barriers Journal Article
In: Nature Structural Biology, vol. 5, pp. 1021-4, 1998, ISSN: 1072-8368.
@article{203,
title = {Metastable states and folding free energy barriers},
author = { David Baker},
issn = {1072-8368},
year = {1998},
date = {1998-12-01},
urldate = {1998-12-01},
journal = {Nature Structural Biology},
volume = {5},
pages = {1021-4},
abstract = {https://www.nature.com/articles/nsb1298_1021},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
https://www.nature.com/articles/nsb1298_1021
K W Plaxco, David Baker
Limited internal friction in the rate-limiting step of a two-state protein folding reaction Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 95, pp. 13591-6, 1998, ISSN: 0027-8424.
@article{211,
title = {Limited internal friction in the rate-limiting step of a two-state protein folding reaction},
author = { K W Plaxco and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/plaxco98A.pdf},
issn = {0027-8424},
year = {1998},
date = {1998-11-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {95},
pages = {13591-6},
abstract = {Small, single-domain proteins typically fold via a compact transition-state ensemble in a process well fitted by a simple, two-state model. To characterize the rate-limiting conformational changes that underlie two-state folding, we have investigated experimentally the effects of changing solvent viscosity on the refolding of the IgG binding domain of protein L. In conjunction with numerical simulations, our results indicate that the rate-limiting conformational changes of the folding of this domain are strongly coupled to solvent viscosity and lack any significant "internal friction" arising from intrachain collisions. When compared with the previously determined solvent viscosity dependencies of other, more restricted conformational changes, our results suggest that the rate-limiting folding transition involves conformational fluctuations that displace considerable amounts of solvent. Reconciling evidence that the folding transition state ensemble is comprised of highly collapsed species with these and similar, previously reported results should provide a significant constraint for theoretical models of the folding process.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Small, single-domain proteins typically fold via a compact transition-state ensemble in a process well fitted by a simple, two-state model. To characterize the rate-limiting conformational changes that underlie two-state folding, we have investigated experimentally the effects of changing solvent viscosity on the refolding of the IgG binding domain of protein L. In conjunction with numerical simulations, our results indicate that the rate-limiting conformational changes of the folding of this domain are strongly coupled to solvent viscosity and lack any significant "internal friction" arising from intrachain collisions. When compared with the previously determined solvent viscosity dependencies of other, more restricted conformational changes, our results suggest that the rate-limiting folding transition involves conformational fluctuations that displace considerable amounts of solvent. Reconciling evidence that the folding transition state ensemble is comprised of highly collapsed species with these and similar, previously reported results should provide a significant constraint for theoretical models of the folding process.
D Shortle, K T Simons, David Baker
Clustering of low-energy conformations near the native structures of small proteins Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 95, pp. 11158-62, 1998, ISSN: 0027-8424.
@article{213,
title = {Clustering of low-energy conformations near the native structures of small proteins},
author = { D Shortle and K T Simons and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/shortle98A.pdf},
issn = {0027-8424},
year = {1998},
date = {1998-09-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {95},
pages = {11158-62},
abstract = {Recent experimental studies of the denatured state and theoretical analyses of the folding landscape suggest that there are a large multiplicity of low-energy, partially folded conformations near the native state. In this report, we describe a strategy for predicting protein structure based on the working hypothesis that there are a greater number of low-energy conformations surrounding the correct fold than there are surrounding low-energy incorrect folds. To test this idea, 12 ensembles of 500 to 1,000 low-energy structures for 10 small proteins were analyzed by calculating the rms deviation of the Calpha coordinates between each conformation and every other conformation in the ensemble. In all 12 cases, the conformation with the greatest number of conformations within 4-A rms deviation was closer to the native structure than were the majority of conformations in the ensemble, and in most cases it was among the closest 1 to 5%. These results suggest that, to fold efficiently and retain robustness to changes in amino acid sequence, proteins may have evolved a native structure situated within a broad basin of low-energy conformations, a feature which could facilitate the prediction of protein structure at low resolution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent experimental studies of the denatured state and theoretical analyses of the folding landscape suggest that there are a large multiplicity of low-energy, partially folded conformations near the native state. In this report, we describe a strategy for predicting protein structure based on the working hypothesis that there are a greater number of low-energy conformations surrounding the correct fold than there are surrounding low-energy incorrect folds. To test this idea, 12 ensembles of 500 to 1,000 low-energy structures for 10 small proteins were analyzed by calculating the rms deviation of the Calpha coordinates between each conformation and every other conformation in the ensemble. In all 12 cases, the conformation with the greatest number of conformations within 4-A rms deviation was closer to the native structure than were the majority of conformations in the ensemble, and in most cases it was among the closest 1 to 5%. These results suggest that, to fold efficiently and retain robustness to changes in amino acid sequence, proteins may have evolved a native structure situated within a broad basin of low-energy conformations, a feature which could facilitate the prediction of protein structure at low resolution.
C Bystroff, D Baker
Prediction of local structure in proteins using a library of sequence-structure motifs Journal Article
In: Journal of molecular biology, vol. 281, pp. 565-77, 1998, ISSN: 0022-2836.
@article{311,
title = {Prediction of local structure in proteins using a library of sequence-structure motifs},
author = { C Bystroff and D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bystroff98A.pdf},
issn = {0022-2836},
year = {1998},
date = {1998-08-01},
journal = {Journal of molecular biology},
volume = {281},
pages = {565-77},
abstract = {We describe a new method for local protein structure prediction based on a library of short sequence pattern that correlate strongly with protein three-dimensional structural elements. The library was generated using an automated method for finding correlations between protein sequence and local structure, and contains most previously described local sequence-structure correlations as well as new relationships, including a diverging type-II beta-turn, a frayed helix, and a proline-terminated helix. The query sequence is scanned for segments 7 to 19 residues in length that strongly match one of the 82 patterns in the library. Matching segments are assigned the three-dimensional structure characteristic of the corresponding sequence pattern, and backbone torsion angles for the entire query sequence are then predicted by piecing together mutually compatible segment predictions. In predictions of local structure in a test set of 55 proteins, about 50% of all residues, and 76% of residues covered by high-confidence predictions, were found in eight-residue segments within 1.4 A of their true structures. The predictions are complementary to traditional secondary structure predictions because they are considerably more specific in turn regions, and may contribute to ab initio tertiary structure prediction and fold recognition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a new method for local protein structure prediction based on a library of short sequence pattern that correlate strongly with protein three-dimensional structural elements. The library was generated using an automated method for finding correlations between protein sequence and local structure, and contains most previously described local sequence-structure correlations as well as new relationships, including a diverging type-II beta-turn, a frayed helix, and a proline-terminated helix. The query sequence is scanned for segments 7 to 19 residues in length that strongly match one of the 82 patterns in the library. Matching segments are assigned the three-dimensional structure characteristic of the corresponding sequence pattern, and backbone torsion angles for the entire query sequence are then predicted by piecing together mutually compatible segment predictions. In predictions of local structure in a test set of 55 proteins, about 50% of all residues, and 76% of residues covered by high-confidence predictions, were found in eight-residue segments within 1.4 A of their true structures. The predictions are complementary to traditional secondary structure predictions because they are considerably more specific in turn regions, and may contribute to ab initio tertiary structure prediction and fold recognition.
V P Grantcharova, D S Riddle, J V Santiago, David Baker
Important role of hydrogen bonds in the structurally polarized transition state for folding of the src SH3 domain Journal Article
In: Nature structural biology, vol. 5, pp. 714-20, 1998, ISSN: 1072-8368.
@article{204,
title = {Important role of hydrogen bonds in the structurally polarized transition state for folding of the src SH3 domain},
author = { V P Grantcharova and D S Riddle and J V Santiago and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/grantcharova98A.pdf},
issn = {1072-8368},
year = {1998},
date = {1998-08-01},
journal = {Nature structural biology},
volume = {5},
pages = {714-20},
abstract = {Experimental and theoretical studies on the folding of small proteins such as the chymotrypsin inhibitor 2 (CI-2) and the P22 Arc repressor suggest that the folding transition state is an expanded version of the native state with most interactions partially formed. Here we report that this picture does not hold generally: a hydrogen bond network involving two beta-turns and an adjacent hydrophobic cluster appear to be formed in the folding transition state of the src SH3 domain, while the remainder of the polypeptide chain is largely unstructured. Comparison with data on other small proteins suggests that this structural polarization is a consequence of the topology of the SH3 domain fold. The non-uniform distribution of structure in the folding transition state provides a challenging test for computational models of the folding process.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Experimental and theoretical studies on the folding of small proteins such as the chymotrypsin inhibitor 2 (CI-2) and the P22 Arc repressor suggest that the folding transition state is an expanded version of the native state with most interactions partially formed. Here we report that this picture does not hold generally: a hydrogen bond network involving two beta-turns and an adjacent hydrophobic cluster appear to be formed in the folding transition state of the src SH3 domain, while the remainder of the polypeptide chain is largely unstructured. Comparison with data on other small proteins suggests that this structural polarization is a consequence of the topology of the SH3 domain fold. The non-uniform distribution of structure in the folding transition state provides a challenging test for computational models of the folding process.
D E Kim, H Gu, D Baker
The sequences of small proteins are not extensively optimized for rapid folding by natural selection Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 95, pp. 4982-6, 1998, ISSN: 0027-8424.
@article{312,
title = {The sequences of small proteins are not extensively optimized for rapid folding by natural selection},
author = { D E Kim and H Gu and D Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kim98A.pdf},
issn = {0027-8424},
year = {1998},
date = {1998-04-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {95},
pages = {4982-6},
abstract = {The thermodynamic stabilities of small protein domains are clearly subject to natural selection, but it is less clear whether the rapid folding rates typically observed for such proteins are consequences of direct evolutionary optimization or reflect intrinsic physical properties of the polypeptide chain. This issue can be investigated by comparing the folding rates of laboratory-generated protein sequences to those of naturally occurring sequences provided that the method by which the sequences are generated has no kinetic bias. Herein we report the folding thermodynamics and kinetics of 12 heavily mutated variants of the small IgG binding domain of protein L retrieved from high-complexity combinatorial libraries by using a phage-display selection for proper folding that does not discriminate between rapidly and slowly folding proteins. Although the stabilities of all variants were decreased, many of the variants fold faster than wild type. Taken together with similar results for the src homology 3 domain, this observation suggests that the sequences of small proteins have not been extensively optimized for rapid folding; instead, rapid folding appears to be a consequence of selection for stability.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The thermodynamic stabilities of small protein domains are clearly subject to natural selection, but it is less clear whether the rapid folding rates typically observed for such proteins are consequences of direct evolutionary optimization or reflect intrinsic physical properties of the polypeptide chain. This issue can be investigated by comparing the folding rates of laboratory-generated protein sequences to those of naturally occurring sequences provided that the method by which the sequences are generated has no kinetic bias. Herein we report the folding thermodynamics and kinetics of 12 heavily mutated variants of the small IgG binding domain of protein L retrieved from high-complexity combinatorial libraries by using a phage-display selection for proper folding that does not discriminate between rapidly and slowly folding proteins. Although the stabilities of all variants were decreased, many of the variants fold faster than wild type. Taken together with similar results for the src homology 3 domain, this observation suggests that the sequences of small proteins have not been extensively optimized for rapid folding; instead, rapid folding appears to be a consequence of selection for stability.
J A Rank, David Baker
Contributions of solvent-solvent hydrogen bonding and van der Waals interactions to the attraction between methane molecules in water Journal Article
In: Biophysical chemistry, vol. 71, pp. 199-204, 1998, ISSN: 0301-4622.
@article{210,
title = {Contributions of solvent-solvent hydrogen bonding and van der Waals interactions to the attraction between methane molecules in water},
author = { J A Rank and David Baker},
issn = {0301-4622},
year = {1998},
date = {1998-04-01},
journal = {Biophysical chemistry},
volume = {71},
pages = {199-204},
abstract = {The contribution of solvent-solvent hydrogen bonding and van der Waals interactions to the attraction between methane molecules in water was investigated by comparing the potential of mean force (PMF) between two methane molecules in TIP4P water to those in a series of related liquids in which the solvent-solvent interactions were progressively turned off while keeping the solvent-solute interactions unchanged. The magnitude of the attraction between methanes was not significantly changed when the hydrogen bonding interaction between solvent molecules was eliminated and the solvent was maintained in the liquid state by increasing either the pressure or the magnitude of the solvent-solvent van der Waals interaction. However, when solvent-solvent excluded volume interactions were eliminated, the methane molecules interacted no more strongly than in the gas phase. The results are consistent with the idea that the primary contribution of hydrogen bonding to the hydrophobic interaction is to keep water molecules in a liquid state; at constant density, packing interactions rather than hydrogen bonding appear to be critical as suggested by scaled particle theories of solvation. The overall shape of the PMF was, however, changed in the absence of hydrogen bonding, pointing to an influence of hydrogen bonding on the detailed form of the interactions between nonpolar solutes in water. The effects of correlations between the configurations sampled during the Monte Carlo procedure used in the free energy calculations on the estimation of errors was also characterized.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The contribution of solvent-solvent hydrogen bonding and van der Waals interactions to the attraction between methane molecules in water was investigated by comparing the potential of mean force (PMF) between two methane molecules in TIP4P water to those in a series of related liquids in which the solvent-solvent interactions were progressively turned off while keeping the solvent-solute interactions unchanged. The magnitude of the attraction between methanes was not significantly changed when the hydrogen bonding interaction between solvent molecules was eliminated and the solvent was maintained in the liquid state by increasing either the pressure or the magnitude of the solvent-solvent van der Waals interaction. However, when solvent-solvent excluded volume interactions were eliminated, the methane molecules interacted no more strongly than in the gas phase. The results are consistent with the idea that the primary contribution of hydrogen bonding to the hydrophobic interaction is to keep water molecules in a liquid state; at constant density, packing interactions rather than hydrogen bonding appear to be critical as suggested by scaled particle theories of solvation. The overall shape of the PMF was, however, changed in the absence of hydrogen bonding, pointing to an influence of hydrogen bonding on the detailed form of the interactions between nonpolar solutes in water. The effects of correlations between the configurations sampled during the Monte Carlo procedure used in the free energy calculations on the estimation of errors was also characterized.
K W Plaxco, K T Simons, David Baker
Contact order, transition state placement and the refolding rates of single domain proteins Journal Article
In: Journal of molecular biology, vol. 277, pp. 985-94, 1998, ISSN: 0022-2836.
@article{207,
title = {Contact order, transition state placement and the refolding rates of single domain proteins},
author = { K W Plaxco and K T Simons and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/plaxco98B.pdf},
issn = {0022-2836},
year = {1998},
date = {1998-04-01},
journal = {Journal of molecular biology},
volume = {277},
pages = {985-94},
abstract = {Theoretical studies have suggested relationships between the size, stability and topology of a protein fold and the rate and mechanisms by which it is achieved. The recent characterization of the refolding of a number of simple, single domain proteins has provided a means of testing these assertions. Our investigations have revealed statistically significant correlations between the average sequence separation between contacting residues in the native state and the rate and transition state placement of folding for a non-homologous set of simple, single domain proteins. These indicate that proteins featuring primarily sequence-local contacts tend to fold more rapidly and exhibit less compact folding transition states than those characterized by more non-local interactions. No significant relationship is apparent between protein length and folding rates, but a weak correlation is observed between length and the fraction of solvent-exposed surface area buried in the transition state. Anticipated strong relationships between equilibrium folding free energy and folding kinetics, or between chemical denaturant and temperature dependence-derived measures of transition state placement, are not apparent. The observed correlations are consistent with a model of protein folding in which the size and stability of the polypeptide segments organized in the transition state are largely independent of protein length, but are related to the topological complexity of the native state. The correlation between topological complexity and folding rates may reflect chain entropy contributions to the folding barrier.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Theoretical studies have suggested relationships between the size, stability and topology of a protein fold and the rate and mechanisms by which it is achieved. The recent characterization of the refolding of a number of simple, single domain proteins has provided a means of testing these assertions. Our investigations have revealed statistically significant correlations between the average sequence separation between contacting residues in the native state and the rate and transition state placement of folding for a non-homologous set of simple, single domain proteins. These indicate that proteins featuring primarily sequence-local contacts tend to fold more rapidly and exhibit less compact folding transition states than those characterized by more non-local interactions. No significant relationship is apparent between protein length and folding rates, but a weak correlation is observed between length and the fraction of solvent-exposed surface area buried in the transition state. Anticipated strong relationships between equilibrium folding free energy and folding kinetics, or between chemical denaturant and temperature dependence-derived measures of transition state placement, are not apparent. The observed correlations are consistent with a model of protein folding in which the size and stability of the polypeptide segments organized in the transition state are largely independent of protein length, but are related to the topological complexity of the native state. The correlation between topological complexity and folding rates may reflect chain entropy contributions to the folding barrier.
K W Plaxco, D S Riddle, V Grantcharova, David Baker
Simplified proteins: minimalist solutions to the protein folding problem Journal Article
In: Current opinion in structural biology, vol. 8, pp. 80-5, 1998, ISSN: 0959-440X.
@article{208,
title = {Simplified proteins: minimalist solutions to the protein folding problem},
author = { K W Plaxco and D S Riddle and V Grantcharova and David Baker},
issn = {0959-440X},
year = {1998},
date = {1998-02-01},
journal = {Current opinion in structural biology},
volume = {8},
pages = {80-5},
abstract = {Recent research has suggested that stable, native proteins may be encoded by simple sequences of fewer than the full set of 20 proteogenic amino acids. Studies of the ability of simple amino acid sequences to encode stable, topologically complex, native conformations and to fold to these conformations in a biologically relevant time frame have provided insights into the sequence determinants of protein structure and folding kinetics. They may also have important implications for protein design and for theories of the origins of protein synthesis itself.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent research has suggested that stable, native proteins may be encoded by simple sequences of fewer than the full set of 20 proteogenic amino acids. Studies of the ability of simple amino acid sequences to encode stable, topologically complex, native conformations and to fold to these conformations in a biologically relevant time frame have provided insights into the sequence determinants of protein structure and folding kinetics. They may also have important implications for protein design and for theories of the origins of protein synthesis itself.
Q Yi, C Bystroff, P Rajagopal, R E Klevit, David Baker
Prediction and structural characterization of an independently folding substructure in the src SH3 domain Journal Article
In: Journal of molecular biology, vol. 283, pp. 293-300, 1998, ISSN: 0022-2836.
@article{212,
title = {Prediction and structural characterization of an independently folding substructure in the src SH3 domain},
author = { Q Yi and C Bystroff and P Rajagopal and R E Klevit and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/yi98A.pdf},
issn = {0022-2836},
year = {1998},
date = {1998-00-01},
journal = {Journal of molecular biology},
volume = {283},
pages = {293-300},
abstract = {Previous studies of the conformations of peptides spanning the length of the alpha-spectrin SH3 domain suggested that SH3 domains lack independently folding substructures. Using a local structure prediction method based on the I-sites library of sequence-structure motifs, we identified a seven residue peptide in the src SH3 domain predicted to adopt a native-like structure, a type II beta-turn bridging unpaired beta-strands, that was not contained intact in any of the SH3 domain peptides studied earlier. NMR characterization confirmed that the isolated peptide, FKKGERL, adopts a structure similar to that adopted in the native protein: the NOE and 3JNHalpha coupling constant patterns were indicative of a type II beta-turn, and NOEs between the Phe and the Leu side-chains suggest that they are juxtaposed as in the prediction and the native structure. These results support the idea that high-confidence I-sites predictions identify protein segments that are likely to form native-like structures early in folding.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Previous studies of the conformations of peptides spanning the length of the alpha-spectrin SH3 domain suggested that SH3 domains lack independently folding substructures. Using a local structure prediction method based on the I-sites library of sequence-structure motifs, we identified a seven residue peptide in the src SH3 domain predicted to adopt a native-like structure, a type II beta-turn bridging unpaired beta-strands, that was not contained intact in any of the SH3 domain peptides studied earlier. NMR characterization confirmed that the isolated peptide, FKKGERL, adopts a structure similar to that adopted in the native protein: the NOE and 3JNHalpha coupling constant patterns were indicative of a type II beta-turn, and NOEs between the Phe and the Leu side-chains suggest that they are juxtaposed as in the prediction and the native structure. These results support the idea that high-confidence I-sites predictions identify protein segments that are likely to form native-like structures early in folding.
1997
V P Grantcharova, David Baker
Folding dynamics of the src SH3 domain Journal Article
In: Biochemistry, vol. 36, pp. 15685-92, 1997, ISSN: 0006-2960.
@article{32,
title = {Folding dynamics of the src SH3 domain},
author = { V P Grantcharova and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/grantcharova97A.pdf},
issn = {0006-2960},
year = {1997},
date = {1997-12-01},
journal = {Biochemistry},
volume = {36},
pages = {15685-92},
abstract = {The thermodynamics and kinetics of folding of the chicken src SH3 domain were characterized using equilibrium and stopped-flow fluorescence, circular dichroism (CD), and nuclear magnetic resonance (NMR) hydrogen exchange experiments. As found for other SH3 domains, guanidinium chloride (GdmCl) denaturation melts followed by both fluorescence and circular dichroism were nearly superimposable, indicating the concerted formation of secondary and tertiary structure. Kinetic studies confirmed the two-state character of the folding reaction. Except for a very slow refolding phase due to proline isomerization, both folding and unfolding traces fit well to single exponentials over a wide range of GdmCl concentrations, and no burst phase in amplitude was observed during the dead time of the stopped-flow instrument. The entropy, enthalpy, and heat capacity changes upon unfolding were determined by global fitting of temperature melts at varying GdmCl concentrations (0.4-3.7 M). Estimates of the free energy of unfolding, DeltaGUH2O, from guanidine denaturation, thermal denaturation, and kinetic experiments were in good agreement. To complement these data on the global characteristics of src SH3 folding, individual hydrogen-deuterium (HD) exchange rates were measured for approximately half of the backbone amides in 0 and 0.7 M GdmCl. The calculated free energies of the opening reaction leading to exchange (DeltaGHD) indicated that unfolding is highly cooperative--slowly exchanging protons were distributed throughout the core of the protein. The slowly exchanging protons exhibited DeltaGHD values higher than the global DeltaGUH2O by approximately 1 kcal/mol, suggesting that the denatured state might be somewhat compact under native conditions. Comparison of the src SH3 with homologous SH3 domains as well as with other small well-characterized beta-sheet proteins provides insights into the determinants of folding kinetics and protein stability.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The thermodynamics and kinetics of folding of the chicken src SH3 domain were characterized using equilibrium and stopped-flow fluorescence, circular dichroism (CD), and nuclear magnetic resonance (NMR) hydrogen exchange experiments. As found for other SH3 domains, guanidinium chloride (GdmCl) denaturation melts followed by both fluorescence and circular dichroism were nearly superimposable, indicating the concerted formation of secondary and tertiary structure. Kinetic studies confirmed the two-state character of the folding reaction. Except for a very slow refolding phase due to proline isomerization, both folding and unfolding traces fit well to single exponentials over a wide range of GdmCl concentrations, and no burst phase in amplitude was observed during the dead time of the stopped-flow instrument. The entropy, enthalpy, and heat capacity changes upon unfolding were determined by global fitting of temperature melts at varying GdmCl concentrations (0.4-3.7 M). Estimates of the free energy of unfolding, DeltaGUH2O, from guanidine denaturation, thermal denaturation, and kinetic experiments were in good agreement. To complement these data on the global characteristics of src SH3 folding, individual hydrogen-deuterium (HD) exchange rates were measured for approximately half of the backbone amides in 0 and 0.7 M GdmCl. The calculated free energies of the opening reaction leading to exchange (DeltaGHD) indicated that unfolding is highly cooperative–slowly exchanging protons were distributed throughout the core of the protein. The slowly exchanging protons exhibited DeltaGHD values higher than the global DeltaGUH2O by approximately 1 kcal/mol, suggesting that the denatured state might be somewhat compact under native conditions. Comparison of the src SH3 with homologous SH3 domains as well as with other small well-characterized beta-sheet proteins provides insights into the determinants of folding kinetics and protein stability.
H Gu, David E Kim, David Baker
Contrasting roles for symmetrically disposed beta-turns in the folding of a small protein Journal Article
In: Journal of molecular biology, vol. 274, pp. 588-96, 1997, ISSN: 0022-2836.
@article{33,
title = {Contrasting roles for symmetrically disposed beta-turns in the folding of a small protein},
author = { H Gu and David E Kim and David Baker},
issn = {0022-2836},
year = {1997},
date = {1997-12-01},
journal = {Journal of molecular biology},
volume = {274},
pages = {588-96},
abstract = {To investigate the role of turns in protein folding, we have characterized the effects of combinatorial and site-directed mutations in the two beta-turns of peptostreptococcal protein L on folding thermodynamics and kinetics. Sequences of folded variants recovered from combinatorial libraries using a phase display selection method were considerably more variable in the second turn than in the first turn. These combinatorial mutants as well as strategically placed point mutants in the two turns had a similar range of thermodynamic stabilities, but strikingly different folding kinetics. A glycine to alanine substitution in the second beta-turn increased the rate of unfolding more than tenfold but had little effect on the rate of folding, while mutation of a symmetrically disposed glycine residue in the first turn had little effect on unfolding but slowed the rate of folding nearly tenfold. These results demonstrate that the role of beta-turns in protein folding is strongly context-dependent, and suggests that the first turn is formed and the second turn disrupted in the folding transition state.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To investigate the role of turns in protein folding, we have characterized the effects of combinatorial and site-directed mutations in the two beta-turns of peptostreptococcal protein L on folding thermodynamics and kinetics. Sequences of folded variants recovered from combinatorial libraries using a phase display selection method were considerably more variable in the second turn than in the first turn. These combinatorial mutants as well as strategically placed point mutants in the two turns had a similar range of thermodynamic stabilities, but strikingly different folding kinetics. A glycine to alanine substitution in the second beta-turn increased the rate of unfolding more than tenfold but had little effect on the rate of folding, while mutation of a symmetrically disposed glycine residue in the first turn had little effect on unfolding but slowed the rate of folding nearly tenfold. These results demonstrate that the role of beta-turns in protein folding is strongly context-dependent, and suggests that the first turn is formed and the second turn disrupted in the folding transition state.
R Doyle, K Simons, H Qian, David Baker
Local interactions and the optimization of protein folding Journal Article
In: Proteins, vol. 29, pp. 282-91, 1997, ISSN: 0887-3585.
@article{31,
title = {Local interactions and the optimization of protein folding},
author = { R Doyle and K Simons and H Qian and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/doyle97A.pdf},
issn = {0887-3585},
year = {1997},
date = {1997-11-01},
journal = {Proteins},
volume = {29},
pages = {282-91},
abstract = {The role of local interactions in protein folding has recently been the subject of some controversy. Here we investigate an extension of Zwanzigtextquoterights simple and general model of folding in which local and nonlocal interactions are represented by functions of single and multiple conformational degrees of freedom, respectively. The kinetics and thermodynamics of folding are studied for a series of energy functions in which the energy of the native structure is fixed, but the relative contributions of local and nonlocal interactions to this energy are varied over a broad range. For funnel shaped energy landscapes, we find that 1) the rate of folding increases, but the stability of the folded state decreases, as the contribution of local interactions to the energy of the native structure increases, and 2) the amount of native structure in the unfolded state and the transition state vary considerably with the local interaction strength. Simple exponential kinetics and a well-defined free energy barrier separating folded and unfolded states are observed when nonlocal interactions make an appreciable contribution to the energy of the native structure; in such cases a transition state theory type approximation yields reasonably accurate estimates of the folding rate. Bumps in the folding funnel near the native state, which could result from desolvation effects, side chain freezing, or the breaking of nonnative contacts, significantly alter the dependence of the folding rate on the local interaction strength: the rate of folding decreases when the local interaction strength is increased beyond a certain point. A survey of the distribution of strong contacts in the protein structure database suggests that evolutionary optimization has involved both kinetics and thermodynamics: strong contacts are enriched at both very short and very long sequence separations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The role of local interactions in protein folding has recently been the subject of some controversy. Here we investigate an extension of Zwanzigtextquoterights simple and general model of folding in which local and nonlocal interactions are represented by functions of single and multiple conformational degrees of freedom, respectively. The kinetics and thermodynamics of folding are studied for a series of energy functions in which the energy of the native structure is fixed, but the relative contributions of local and nonlocal interactions to this energy are varied over a broad range. For funnel shaped energy landscapes, we find that 1) the rate of folding increases, but the stability of the folded state decreases, as the contribution of local interactions to the energy of the native structure increases, and 2) the amount of native structure in the unfolded state and the transition state vary considerably with the local interaction strength. Simple exponential kinetics and a well-defined free energy barrier separating folded and unfolded states are observed when nonlocal interactions make an appreciable contribution to the energy of the native structure; in such cases a transition state theory type approximation yields reasonably accurate estimates of the folding rate. Bumps in the folding funnel near the native state, which could result from desolvation effects, side chain freezing, or the breaking of nonnative contacts, significantly alter the dependence of the folding rate on the local interaction strength: the rate of folding decreases when the local interaction strength is increased beyond a certain point. A survey of the distribution of strong contacts in the protein structure database suggests that evolutionary optimization has involved both kinetics and thermodynamics: strong contacts are enriched at both very short and very long sequence separations.
D S Riddle, J V Santiago, S T Bray-Hall, N Doshi, V P Grantcharova, Q Yi, David Baker
Functional rapidly folding proteins from simplified amino acid sequences Journal Article
In: Nature structural biology, vol. 4, pp. 805-9, 1997, ISSN: 1072-8368.
@article{26,
title = {Functional rapidly folding proteins from simplified amino acid sequences},
author = { D S Riddle and J V Santiago and S T Bray-Hall and N Doshi and V P Grantcharova and Q Yi and David Baker},
issn = {1072-8368},
year = {1997},
date = {1997-10-01},
journal = {Nature structural biology},
volume = {4},
pages = {805-9},
abstract = {Early protein synthesis is thought to have involved a reduced amino acid alphabet. What is the minimum number of amino acids that would have been needed to encode complex protein folds similar to those found in nature today? Here we show that a small beta-sheet protein, the SH3 domain, can be largely encoded by a five letter amino acid alphabet but not by a three letter alphabet. Furthermore, despite the dramatic changes in sequence, the folding rates of the reduced alphabet proteins are very close to that of the naturally occurring SH3 domain. This finding suggests that despite the vast size of the search space, the rapid folding of biological sequences to their native states is not the result of extensive evolutionary optimization. Instead, the results support the idea that the interactions which stabilize the native state induce a funnel shape to the free energy landscape sufficient to guide the folding polypeptide chain to the proper structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Early protein synthesis is thought to have involved a reduced amino acid alphabet. What is the minimum number of amino acids that would have been needed to encode complex protein folds similar to those found in nature today? Here we show that a small beta-sheet protein, the SH3 domain, can be largely encoded by a five letter amino acid alphabet but not by a three letter alphabet. Furthermore, despite the dramatic changes in sequence, the folding rates of the reduced alphabet proteins are very close to that of the naturally occurring SH3 domain. This finding suggests that despite the vast size of the search space, the rapid folding of biological sequences to their native states is not the result of extensive evolutionary optimization. Instead, the results support the idea that the interactions which stabilize the native state induce a funnel shape to the free energy landscape sufficient to guide the folding polypeptide chain to the proper structure.
M L Scalley, David Baker
Protein folding kinetics exhibit an Arrhenius temperature dependence when corrected for the temperature dependence of protein stability Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 94, pp. 10636-40, 1997, ISSN: 0027-8424.
@article{29,
title = {Protein folding kinetics exhibit an Arrhenius temperature dependence when corrected for the temperature dependence of protein stability},
author = { M L Scalley and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/scalley97A.pdf},
issn = {0027-8424},
year = {1997},
date = {1997-09-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {94},
pages = {10636-40},
abstract = {The anomalous temperature dependence of protein folding has received considerable attention. Here we show that the temperature dependence of the folding of protein L becomes extremely simple when the effects of temperature on protein stability are corrected for; the logarithm of the folding rate is a linear function of 1/T on constant stability contours in the temperature-denaturant plane. This convincingly demonstrates that the anomalous temperature dependence of folding derives from the temperature dependence of the interactions that stabilize proteins, rather than from the super Arrhenius temperature dependence predicted for the configurational diffusion constant on a rough energy landscape. However, because of the limited temperature range accessible to experiment, the results do not rule out models with higher order temperature dependences. The significance of the slope of the stability-corrected Arrhenius plots is discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The anomalous temperature dependence of protein folding has received considerable attention. Here we show that the temperature dependence of the folding of protein L becomes extremely simple when the effects of temperature on protein stability are corrected for; the logarithm of the folding rate is a linear function of 1/T on constant stability contours in the temperature-denaturant plane. This convincingly demonstrates that the anomalous temperature dependence of folding derives from the temperature dependence of the interactions that stabilize proteins, rather than from the super Arrhenius temperature dependence predicted for the configurational diffusion constant on a rough energy landscape. However, because of the limited temperature range accessible to experiment, the results do not rule out models with higher order temperature dependences. The significance of the slope of the stability-corrected Arrhenius plots is discussed.
K F Han, C Bystroff, David Baker
Three-dimensional structures and contexts associated with recurrent amino acid sequence patterns Journal Article
In: Protein science, vol. 6, pp. 1587-90, 1997, ISSN: 0961-8368.
@article{36,
title = {Three-dimensional structures and contexts associated with recurrent amino acid sequence patterns},
author = { K F Han and C Bystroff and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/han97A.pdf},
issn = {0961-8368},
year = {1997},
date = {1997-07-01},
journal = {Protein science},
volume = {6},
pages = {1587-90},
abstract = {We have used cluster analysis to identify recurring sequence patterns that transcend protein family boundaries. A subset of these patterns occur predominantly in a single type of local structure in proteins. Here we characterize the three-dimensional structures and contexts in which these sequence patterns occur, with particular attention to the interactions responsible for their structural selectivity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have used cluster analysis to identify recurring sequence patterns that transcend protein family boundaries. A subset of these patterns occur predominantly in a single type of local structure in proteins. Here we characterize the three-dimensional structures and contexts in which these sequence patterns occur, with particular attention to the interactions responsible for their structural selectivity.
K T Simons, C Kooperberg, E Huang, David Baker
Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions Journal Article
In: Journal of molecular biology, vol. 268, pp. 209-25, 1997, ISSN: 0022-2836.
@article{28,
title = {Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions},
author = { K T Simons and C Kooperberg and E Huang and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/simons97A.pdf},
issn = {0022-2836},
year = {1997},
date = {1997-04-01},
journal = {Journal of molecular biology},
volume = {268},
pages = {209-25},
abstract = {We explore the ability of a simple simulated annealing procedure to assemble native-like structures from fragments of unrelated protein structures with similar local sequences using Bayesian scoring functions. Environment and residue pair specific contributions to the scoring functions appear as the first two terms in a series expansion for the residue probability distributions in the protein database; the decoupling of the distance and environment dependencies of the distributions resolves the major problems with current database-derived scoring functions noted by Thomas and Dill. The simulated annealing procedure rapidly and frequently generates native-like structures for small helical proteins and better than random structures for small beta sheet containing proteins. Most of the simulated structures have native-like solvent accessibility and secondary structure patterns, and thus ensembles of these structures provide a particularly challenging set of decoys for evaluating scoring functions. We investigate the effects of multiple sequence information and different types of conformational constraints on the overall performance of the method, and the ability of a variety of recently developed scoring functions to recognize the native-like conformations in the ensembles of simulated structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We explore the ability of a simple simulated annealing procedure to assemble native-like structures from fragments of unrelated protein structures with similar local sequences using Bayesian scoring functions. Environment and residue pair specific contributions to the scoring functions appear as the first two terms in a series expansion for the residue probability distributions in the protein database; the decoupling of the distance and environment dependencies of the distributions resolves the major problems with current database-derived scoring functions noted by Thomas and Dill. The simulated annealing procedure rapidly and frequently generates native-like structures for small helical proteins and better than random structures for small beta sheet containing proteins. Most of the simulated structures have native-like solvent accessibility and secondary structure patterns, and thus ensembles of these structures provide a particularly challenging set of decoys for evaluating scoring functions. We investigate the effects of multiple sequence information and different types of conformational constraints on the overall performance of the method, and the ability of a variety of recently developed scoring functions to recognize the native-like conformations in the ensembles of simulated structures.
M L Scalley, Q Yi, H Gu, A McCormack, J R Yates, David Baker
Kinetics of folding of the IgG binding domain of peptostreptococcal protein L. Journal Article
In: Biochemistry, vol. 36, pp. 3373-82, 1997, ISSN: 0006-2960.
@article{34,
title = {Kinetics of folding of the IgG binding domain of peptostreptococcal protein L.},
author = { M L Scalley and Q Yi and H Gu and A McCormack and J R Yates and David Baker},
issn = {0006-2960},
year = {1997},
date = {1997-03-01},
journal = {Biochemistry},
volume = {36},
pages = {3373-82},
abstract = {The kinetics of folding of a tryptophan containing mutant of the IgG binding domain of protein L were characterized using stopped-flow circular dichroism, stopped-flow fluorescence, and HD exchange coupled with high-resolution mass spectrometry. Both the thermodynamics and kinetics of folding fit well to a simple two-state model: (1) Guanidine induced equilibrium denaturation transitions measured by fluorescence and circular dichroism were virtually superimposable. (2) The kinetics of folding/unfolding were single exponential under all conditions examined, and the rate constants obtained using all probes were similar. (3) Mass spectra from pulsed HD exchange refolding experiments showed that a species with very little protection from exchange is converted to a fully protected species (the native state) at a rate very similar to that of the overall change in tryptophan fluorescence; no intervening partially protected species were observed. (4) Rate constants (in H2O) and m values for folding and unfolding determined by fitting observed relaxation rates obtained over a broad range of denaturant concentrations to a two-state model were consistent with the equilibrium parameters deltaG and m: -RT ln(k(u)/k(f))/deltaG(U)H2O = 1.02; (m(u) + m(f))/m = 1.08. In contrast to results with a number of other proteins, there was no deviation from linearity in plots of ln k(obs) versus guanidine at low guanidine concentrations, both in the presence and absence of 0.4 M Na2SO4, suggesting that significantly stabilized intermediates do not accumulate during folding. Although all of the change in fluorescence signal during folding in phosphate buffer was accounted for by the simple exponential describing the overall folding reaction, fluorescence-quenching experiments using sodium iodide revealed a small reduction in the extent of quenching of the protein within the first two milliseconds after initiation of refolding in low concentrations of guanidine, suggesting a partial collapse of the unfolded chain may occur under these conditions. Comparison with results on the structurally and functionally similar IgG binding domain of streptococcal protein G show intriguing differences in the folding of the two proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The kinetics of folding of a tryptophan containing mutant of the IgG binding domain of protein L were characterized using stopped-flow circular dichroism, stopped-flow fluorescence, and HD exchange coupled with high-resolution mass spectrometry. Both the thermodynamics and kinetics of folding fit well to a simple two-state model: (1) Guanidine induced equilibrium denaturation transitions measured by fluorescence and circular dichroism were virtually superimposable. (2) The kinetics of folding/unfolding were single exponential under all conditions examined, and the rate constants obtained using all probes were similar. (3) Mass spectra from pulsed HD exchange refolding experiments showed that a species with very little protection from exchange is converted to a fully protected species (the native state) at a rate very similar to that of the overall change in tryptophan fluorescence; no intervening partially protected species were observed. (4) Rate constants (in H2O) and m values for folding and unfolding determined by fitting observed relaxation rates obtained over a broad range of denaturant concentrations to a two-state model were consistent with the equilibrium parameters deltaG and m: -RT ln(k(u)/k(f))/deltaG(U)H2O = 1.02; (m(u) + m(f))/m = 1.08. In contrast to results with a number of other proteins, there was no deviation from linearity in plots of ln k(obs) versus guanidine at low guanidine concentrations, both in the presence and absence of 0.4 M Na2SO4, suggesting that significantly stabilized intermediates do not accumulate during folding. Although all of the change in fluorescence signal during folding in phosphate buffer was accounted for by the simple exponential describing the overall folding reaction, fluorescence-quenching experiments using sodium iodide revealed a small reduction in the extent of quenching of the protein within the first two milliseconds after initiation of refolding in low concentrations of guanidine, suggesting a partial collapse of the unfolded chain may occur under these conditions. Comparison with results on the structurally and functionally similar IgG binding domain of streptococcal protein G show intriguing differences in the folding of the two proteins.
J A Rank, David Baker
A desolvation barrier to hydrophobic cluster formation may contribute to the rate-limiting step in protein folding Journal Article
In: Protein science, vol. 6, pp. 347-54, 1997, ISSN: 0961-8368.
@article{35,
title = {A desolvation barrier to hydrophobic cluster formation may contribute to the rate-limiting step in protein folding},
author = { J A Rank and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/rank97A.pdf},
issn = {0961-8368},
year = {1997},
date = {1997-02-01},
journal = {Protein science},
volume = {6},
pages = {347-54},
abstract = {To gain insight into the free energy changes accompanying protein hydrophobic core formation, we have used computer simulations to study the formation of small clusters of nonpolar solutes in water. A barrier to association is observed at the largest solute separation that does not allow substantial solvent penetration. The barrier reflects an effective increase in the size of the cavity occupied by the expanded but water-excluding cluster relative to both the close-packed cluster and the fully solvated separated solutes; a similar effect may contribute to the barrier to protein folding/unfolding. Importantly for the simulation of protein folding without explicit solvent, we find that the interactions between nonpolar solutes of varying size and number can be approximated by a linear function of the molecular surface, but not the solvent-accessible surface of the solutes. Comparison of the free energy of cluster formation to that of dimer formation suggests that the assumption of pair additivity implicit in current protein database derived potentials may be in error.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To gain insight into the free energy changes accompanying protein hydrophobic core formation, we have used computer simulations to study the formation of small clusters of nonpolar solutes in water. A barrier to association is observed at the largest solute separation that does not allow substantial solvent penetration. The barrier reflects an effective increase in the size of the cavity occupied by the expanded but water-excluding cluster relative to both the close-packed cluster and the fully solvated separated solutes; a similar effect may contribute to the barrier to protein folding/unfolding. Importantly for the simulation of protein folding without explicit solvent, we find that the interactions between nonpolar solutes of varying size and number can be approximated by a linear function of the molecular surface, but not the solvent-accessible surface of the solutes. Comparison of the free energy of cluster formation to that of dimer formation suggests that the assumption of pair additivity implicit in current protein database derived potentials may be in error.
C Bystroff, David Baker
Blind predictions of local protein structure in CASP2 targets using the I-sites library Journal Article
In: Proteins, vol. Suppl 1, pp. 167-71, 1997, ISSN: 0887-3585.
@article{30,
title = {Blind predictions of local protein structure in CASP2 targets using the I-sites library},
author = { C Bystroff and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bystroff97A.pdf},
issn = {0887-3585},
year = {1997},
date = {1997-00-01},
journal = {Proteins},
volume = {Suppl 1},
pages = {167-71},
abstract = {Blind predictions of the local structure of nine CASP2 targets were made using the I-sites library of short sequence--structure motifs, revealing strengths and weaknesses in this new knowledge-based method. Many turns between secondary structural elements were accurately predicted. Estimates of the confidence of prediction correlated well with the accuracy over the whole set. Bias toward structures used to develop the library was minimal, probably because of the extensive use of cross-validation. However, helix positions were better predicted by the PHD program. The method is likely to be sensitive to the quality of the sequence alignment. A general measure for evaluating local structure predictions is suggested.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Blind predictions of the local structure of nine CASP2 targets were made using the I-sites library of short sequence–structure motifs, revealing strengths and weaknesses in this new knowledge-based method. Many turns between secondary structural elements were accurately predicted. Estimates of the confidence of prediction correlated well with the accuracy over the whole set. Bias toward structures used to develop the library was minimal, probably because of the extensive use of cross-validation. However, helix positions were better predicted by the PHD program. The method is likely to be sensitive to the quality of the sequence alignment. A general measure for evaluating local structure predictions is suggested.
Q Yi, M L Scalley, K T Simons, S T Gladwin, David Baker
Characterization of the free energy spectrum of peptostreptococcal protein L Journal Article
In: Folding & design, vol. 2, pp. 271-80, 1997, ISSN: 1359-0278.
@article{27,
title = {Characterization of the free energy spectrum of peptostreptococcal protein L},
author = { Q Yi and M L Scalley and K T Simons and S T Gladwin and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/yi97A.pdf},
issn = {1359-0278},
year = {1997},
date = {1997-00-01},
journal = {Folding & design},
volume = {2},
pages = {271-80},
abstract = {BACKGROUND: Native state hydrogen/deuterium exchange studies on cytochrome c and RNase H revealed the presence of excited states with partially formed native structure. We set out to determine whether such excited states are populated for a very small and simple protein, the IgG-binding domain of peptostreptococcal protein L. RESULTS: Hydrogen/deuterium exchange data on protein L in 0-1.2 M guanidine fit well to a simple model in which the only contributions to exchange are denaturant-independent local fluctuations and global unfolding. A substantial discrepancy emerged between unfolding free energy estimates from hydrogen/deuterium exchange and linear extrapolation of earlier guanidine denaturation experiments. A better determined estimate of the free energy of unfolding obtained by global analysis of a series of thermal denaturation experiments in the presence of 0-3 M guanidine was in good agreement with the estimate from hydrogen/deuterium exchange. CONCLUSIONS: For protein L under native conditions, there do not appear to be partially folded states with free energies intermediate between that of the folded and unfolded states. The linear extrapolation method significantly underestimates the free energy of folding of protein L due to deviations from linearity in the dependence of the free energy on the denaturant concentration.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Native state hydrogen/deuterium exchange studies on cytochrome c and RNase H revealed the presence of excited states with partially formed native structure. We set out to determine whether such excited states are populated for a very small and simple protein, the IgG-binding domain of peptostreptococcal protein L. RESULTS: Hydrogen/deuterium exchange data on protein L in 0-1.2 M guanidine fit well to a simple model in which the only contributions to exchange are denaturant-independent local fluctuations and global unfolding. A substantial discrepancy emerged between unfolding free energy estimates from hydrogen/deuterium exchange and linear extrapolation of earlier guanidine denaturation experiments. A better determined estimate of the free energy of unfolding obtained by global analysis of a series of thermal denaturation experiments in the presence of 0-3 M guanidine was in good agreement with the estimate from hydrogen/deuterium exchange. CONCLUSIONS: For protein L under native conditions, there do not appear to be partially folded states with free energies intermediate between that of the folded and unfolded states. The linear extrapolation method significantly underestimates the free energy of folding of protein L due to deviations from linearity in the dependence of the free energy on the denaturant concentration.
1996
C Bystroff, K T Simons, K F Han, David Baker
Local sequence-structure correlations in proteins Journal Article
In: Current opinion in biotechnology, vol. 7, pp. 417-21, 1996, ISSN: 0958-1669.
@article{214,
title = {Local sequence-structure correlations in proteins},
author = { C Bystroff and K T Simons and K F Han and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bystroff96A.pdf},
issn = {0958-1669},
year = {1996},
date = {1996-08-01},
journal = {Current opinion in biotechnology},
volume = {7},
pages = {417-21},
abstract = {Considerable progress has been made in understanding the relationship between local amino acid sequence and local protein structure. Recent highlights include numerous studies of the structures adopted by short peptides, new approaches to correlating sequence patterns with structure patterns, and folding simulations using simple potentials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Considerable progress has been made in understanding the relationship between local amino acid sequence and local protein structure. Recent highlights include numerous studies of the structures adopted by short peptides, new approaches to correlating sequence patterns with structure patterns, and folding simulations using simple potentials.
K F Han, David Baker
Global properties of the mapping between local amino acid sequence and local structure in proteins Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 93, pp. 5814-8, 1996, ISSN: 0027-8424.
@article{215,
title = {Global properties of the mapping between local amino acid sequence and local structure in proteins},
author = { K F Han and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/han96A.pdf},
issn = {0027-8424},
year = {1996},
date = {1996-06-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {93},
pages = {5814-8},
abstract = {Local protein structure prediction efforts have consistently failed to exceed approximately 70% accuracy. We characterize the degeneracy of the mapping from local sequence to local structure responsible for this failure by investigating the extent to which similar sequence segments found in different proteins adopt similar three-dimensional structures. Sequence segments 3-15 residues in length from 154 different protein families are partitioned into neighborhoods containing segments with similar sequences using cluster analysis. The consistency of the sequence-to-structure mapping is assessed by comparing the local structures adopted by sequence segments in the same neighborhood in proteins of known structure. In the 154 families, 45% and 28% of the positions occur in neighborhoods in which one and two local structures predominate, respectively. The sequence patterns that characterize the neighborhoods in the first class probably include virtually all of the short sequence motifs in proteins that consistently occur in a particular local structure. These patterns, many of which occur in transitions between secondary structural elements, are an interesting combination of previously studied and novel motifs. The identification of sequence patterns that consistently occur in one or a small number of local structures in proteins should contribute to the prediction of protein structure from sequence.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Local protein structure prediction efforts have consistently failed to exceed approximately 70% accuracy. We characterize the degeneracy of the mapping from local sequence to local structure responsible for this failure by investigating the extent to which similar sequence segments found in different proteins adopt similar three-dimensional structures. Sequence segments 3-15 residues in length from 154 different protein families are partitioned into neighborhoods containing segments with similar sequences using cluster analysis. The consistency of the sequence-to-structure mapping is assessed by comparing the local structures adopted by sequence segments in the same neighborhood in proteins of known structure. In the 154 families, 45% and 28% of the positions occur in neighborhoods in which one and two local structures predominate, respectively. The sequence patterns that characterize the neighborhoods in the first class probably include virtually all of the short sequence motifs in proteins that consistently occur in a particular local structure. These patterns, many of which occur in transitions between secondary structural elements, are an interesting combination of previously studied and novel motifs. The identification of sequence patterns that consistently occur in one or a small number of local structures in proteins should contribute to the prediction of protein structure from sequence.
Q Yi, David Baker
Direct evidence for a two-state protein unfolding transition from hydrogen-deuterium exchange, mass spectrometry, and NMR Journal Article
In: Protein science, vol. 5, pp. 1060-6, 1996, ISSN: 0961-8368.
@article{24,
title = {Direct evidence for a two-state protein unfolding transition from hydrogen-deuterium exchange, mass spectrometry, and NMR},
author = { Q Yi and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/yi96A.pdf},
issn = {0961-8368},
year = {1996},
date = {1996-06-01},
journal = {Protein science},
volume = {5},
pages = {1060-6},
abstract = {We use mass spectrometry in conjunction with hydrogen-deuterium exchange and NMR to characterize the conformational dynamics of the 62-residue IgG binding domain of protein L under conditions in which the native state is marginally stable. Mass spectra of protein L after short incubations in D2O reveal the presence of two distinct populations containing different numbers of protected protons. NMR experiments indicate that protons in the hydrophobic core are protected in one population, whereas all protons are exchanged for deuterons in the other. As the exchange period is increased, molecules are transferred from the former population to the latter. The absence of molecules with a subset of the core protons protected suggests that exchange occurs in part via a highly concerted transition to an excited state in which all protons exchange rapidly with deuterons. A steady increase in the molecular weight of the population with protected protons, and variation in the exchange rates of the individual protected protons indicates the presence of an additional exchange mechanism. A simple model in which exchange results from rapid (> 10(5)/s) local fluctuations around the native state superimposed upon transitions to an unfolded excited state at approximately 0.06/s is supported by qualitative agreement between the observed mass spectra and the mass spectra simulated according to the model using NMR-derived estimates of the proton exchange rates.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We use mass spectrometry in conjunction with hydrogen-deuterium exchange and NMR to characterize the conformational dynamics of the 62-residue IgG binding domain of protein L under conditions in which the native state is marginally stable. Mass spectra of protein L after short incubations in D2O reveal the presence of two distinct populations containing different numbers of protected protons. NMR experiments indicate that protons in the hydrophobic core are protected in one population, whereas all protons are exchanged for deuterons in the other. As the exchange period is increased, molecules are transferred from the former population to the latter. The absence of molecules with a subset of the core protons protected suggests that exchange occurs in part via a highly concerted transition to an excited state in which all protons exchange rapidly with deuterons. A steady increase in the molecular weight of the population with protected protons, and variation in the exchange rates of the individual protected protons indicates the presence of an additional exchange mechanism. A simple model in which exchange results from rapid (> 10(5)/s) local fluctuations around the native state superimposed upon transitions to an unfolded excited state at approximately 0.06/s is supported by qualitative agreement between the observed mass spectra and the mass spectra simulated according to the model using NMR-derived estimates of the proton exchange rates.
1995
K F Han, David Baker
Recurring local sequence motifs in proteins Journal Article
In: Journal of molecular biology, vol. 251, pp. 176-87, 1995, ISSN: 0022-2836.
@article{22,
title = {Recurring local sequence motifs in proteins},
author = { K F Han and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/han95A.pdf},
issn = {0022-2836},
year = {1995},
date = {1995-08-01},
journal = {Journal of molecular biology},
volume = {251},
pages = {176-87},
abstract = {We describe a completely automated approach to identifying local sequence motifs that transcend protein family boundaries. Cluster analysis is used to identify recurring patterns of variation at single positions and in short segments of contiguous positions in multiple sequence alignments for a non-redundant set of protein families. Parallel experiments on simulated data sets constructed with the overall residue frequencies of proteins but not the inter-residue correlations show that naturally occurring protein sequences are significantly more clustered than the corresponding random sequences for window lengths ranging from one to 13 contiguous positions. The patterns of variation at single positions are not in general surprising: chemically similar amino acids tend to be grouped together. More interesting patterns emerge as the window length increases. The patterns of variation for longer window lengths are in part recognizable patterns of hydrophobic and hydrophilic residues, and in part less obvious combinations. A particularly interesting class of patterns features highly conserved glycine residues. The patterns provide a means to abstract the information contained in multiple sequence alignments and may be useful for comparison of distantly related sequences or sequence families and for protein structure prediction.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a completely automated approach to identifying local sequence motifs that transcend protein family boundaries. Cluster analysis is used to identify recurring patterns of variation at single positions and in short segments of contiguous positions in multiple sequence alignments for a non-redundant set of protein families. Parallel experiments on simulated data sets constructed with the overall residue frequencies of proteins but not the inter-residue correlations show that naturally occurring protein sequences are significantly more clustered than the corresponding random sequences for window lengths ranging from one to 13 contiguous positions. The patterns of variation at single positions are not in general surprising: chemically similar amino acids tend to be grouped together. More interesting patterns emerge as the window length increases. The patterns of variation for longer window lengths are in part recognizable patterns of hydrophobic and hydrophilic residues, and in part less obvious combinations. A particularly interesting class of patterns features highly conserved glycine residues. The patterns provide a means to abstract the information contained in multiple sequence alignments and may be useful for comparison of distantly related sequences or sequence families and for protein structure prediction.
H Gu, Q Yi, S T Bray, D S Riddle, A K Shiau, David Baker
A phage display system for studying the sequence determinants of protein folding Journal Article
In: Protein science, vol. 4, pp. 1108-17, 1995, ISSN: 0961-8368.
@article{216,
title = {A phage display system for studying the sequence determinants of protein folding},
author = { H Gu and Q Yi and S T Bray and D S Riddle and A K Shiau and David Baker},
issn = {0961-8368},
year = {1995},
date = {1995-06-01},
journal = {Protein science},
volume = {4},
pages = {1108-17},
abstract = {We have developed a phage display system that provides a means to select variants of the IgG binding domain of peptostreptococcal protein L that fold from large combinatorial libraries. The premise underlying the selection scheme is that binding of protein L to IgG requires that the protein be properly folded. Using a combination of molecular biological and biophysical methods, we show that this assumption is valid. First, the phage selection procedure strongly selects against a point mutation in protein L that disrupts folding but is not in the IgG binding interface. Second, variants recovered from a library in which the first third of protein L was randomized are properly folded. The degree of sequence variation in the selected population is striking: the variants have as many as nine substitutions in the 14 residues that were mutagenized. The approach provides a selection for "foldedness" that is potentially applicable to any small binding protein.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have developed a phage display system that provides a means to select variants of the IgG binding domain of peptostreptococcal protein L that fold from large combinatorial libraries. The premise underlying the selection scheme is that binding of protein L to IgG requires that the protein be properly folded. Using a combination of molecular biological and biophysical methods, we show that this assumption is valid. First, the phage selection procedure strongly selects against a point mutation in protein L that disrupts folding but is not in the IgG binding interface. Second, variants recovered from a library in which the first third of protein L was randomized are properly folded. The degree of sequence variation in the selected population is striking: the variants have as many as nine substitutions in the 14 residues that were mutagenized. The approach provides a selection for “foldedness” that is potentially applicable to any small binding protein.
1994
D Baker, D A Agard
Influenza hemagglutinin: kinetic control of protein function. Journal Article
In: Structure (London, England : 1993), vol. 2, pp. 907-10, 1994, ISSN: 0969-2126.
@article{572,
title = {Influenza hemagglutinin: kinetic control of protein function.},
author = { D Baker and D A Agard},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/influenzahemagglutinin_Baker1994.pdf},
issn = {0969-2126},
year = {1994},
date = {1994-10-01},
journal = {Structure (London, England : 1993)},
volume = {2},
pages = {907-10},
abstract = {In response to decreased pH, influenza hemagglutinin changes to a more stable conformation. Such changes, which can be controlled thermodynamically or kinetically, are the method by which many biological textquoterightswitchestextquoteright are thrown.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In response to decreased pH, influenza hemagglutinin changes to a more stable conformation. Such changes, which can be controlled thermodynamically or kinetically, are the method by which many biological textquoterightswitchestextquoteright are thrown.
D Baker, D A Agard
Kinetics versus thermodynamics in protein folding. Journal Article
In: Biochemistry, vol. 33, pp. 7505-9, 1994, ISSN: 0006-2960.
@article{571,
title = {Kinetics versus thermodynamics in protein folding.},
author = { D Baker and D A Agard},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/kineticsversusthermodynamics_Baker1994.pdf},
issn = {0006-2960},
year = {1994},
date = {1994-06-01},
journal = {Biochemistry},
volume = {33},
pages = {7505-9},
abstract = {Until quite recently it has been generally believed that the observed tertiary structure of a protein is controlled by thermodynamic and not kinetic processes. In this essay we review several recent results which call into question the universality of the thermodynamic hypothesis and discuss their implications for the understanding of protein folding.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Until quite recently it has been generally believed that the observed tertiary structure of a protein is controlled by thermodynamic and not kinetic processes. In this essay we review several recent results which call into question the universality of the thermodynamic hypothesis and discuss their implications for the understanding of protein folding.
1993
D Baker, A K Shiau, D A Agard
The role of pro regions in protein folding. Journal Article
In: Current Opinion in Cell Biology, vol. 5, pp. 966-70, 1993, ISSN: 0955-0674.
@article{570,
title = {The role of pro regions in protein folding.},
author = { D Baker and A K Shiau and D A Agard},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/theroleofproregions_Baker1993.pdf},
issn = {0955-0674},
year = {1993},
date = {1993-12-01},
journal = {Current Opinion in Cell Biology},
volume = {5},
pages = {966-70},
abstract = {In vivo, many proteases are synthesized as larger precursors. During the maturation process, the catalytically active protease domain is released from the larger polypeptide or pro-enzyme by one or more proteolytic processing steps. In several well studied cases, amino-terminal pro regions have been shown to play a fundamental role in the folding of the associated protease domains. The mechanism by which pro regions facilitate folding appears to be significantly different from that used by the molecular chaperones. Recent results suggest that the pro region assisted folding mechanism may be used by a wide variety of proteases, and perhaps even by non-proteases.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In vivo, many proteases are synthesized as larger precursors. During the maturation process, the catalytically active protease domain is released from the larger polypeptide or pro-enzyme by one or more proteolytic processing steps. In several well studied cases, amino-terminal pro regions have been shown to play a fundamental role in the folding of the associated protease domains. The mechanism by which pro regions facilitate folding appears to be significantly different from that used by the molecular chaperones. Recent results suggest that the pro region assisted folding mechanism may be used by a wide variety of proteases, and perhaps even by non-proteases.
C Bystroff, D Baker, R J Fletterick, D A Agard
PRISM: application to the solution of two protein structures Journal Article
In: Acta crystallographica. Section D, vol. 49, pp. 440-8, 1993, ISSN: 0907-4449.
@article{326,
title = {PRISM: application to the solution of two protein structures},
author = { C Bystroff and D Baker and R J Fletterick and D A Agard},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/bystroff93A.pdf},
issn = {0907-4449},
year = {1993},
date = {1993-09-01},
journal = {Acta crystallographica. Section D},
volume = {49},
pages = {440-8},
abstract = {The previous paper described a phase-refinement strategy for protein crystallography which exploited the information that proteins consist of connected linear chains of atoms. Here the method is applied to a molecular-replacement problem, the structure of the protease inhibitor ecotin bound to trypsin, and a single isomorphous replacement problem, the structure of the N-terminal domain of apolipoprotein E. The starting phases for the ecotin-trypsin complex were based on a partial model (trypsin) containing 61% of the atoms in the complex. Iterative skeletonization gave better results than either solvent flattening or twofold non-crystallographic symmetry averaging as measured by the reduction in the free R factor [Br"unger (1992). Nature (London), 355, 472-474]. Protection of the trypsin density during the course of the refinement greatly improved the performance of both skeletonizing and solvent flattening. In the case of apolipoprotein E, previous attempts using solvent flattening had failed to improve the SIR phases to the point of obtaining an interpretable map. The combination of iterative skeletonization and solvent flattening decreased the phase error with respect to the final refined structure, significantly more than solvent flattening alone. The final maps generated by the skeletonization procedure for both the ecotin-trypsin complex and apolipoprotein E were readily interpretable.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The previous paper described a phase-refinement strategy for protein crystallography which exploited the information that proteins consist of connected linear chains of atoms. Here the method is applied to a molecular-replacement problem, the structure of the protease inhibitor ecotin bound to trypsin, and a single isomorphous replacement problem, the structure of the N-terminal domain of apolipoprotein E. The starting phases for the ecotin-trypsin complex were based on a partial model (trypsin) containing 61% of the atoms in the complex. Iterative skeletonization gave better results than either solvent flattening or twofold non-crystallographic symmetry averaging as measured by the reduction in the free R factor [Br"unger (1992). Nature (London), 355, 472-474]. Protection of the trypsin density during the course of the refinement greatly improved the performance of both skeletonizing and solvent flattening. In the case of apolipoprotein E, previous attempts using solvent flattening had failed to improve the SIR phases to the point of obtaining an interpretable map. The combination of iterative skeletonization and solvent flattening decreased the phase error with respect to the final refined structure, significantly more than solvent flattening alone. The final maps generated by the skeletonization procedure for both the ecotin-trypsin complex and apolipoprotein E were readily interpretable.
D Baker, C Bystroff, R J Fletterick, D A Agard
PRISM: topologically constrained phased refinement for macromolecular crystallography Journal Article
In: Acta crystallographica. Section D, vol. 49, pp. 429-39, 1993, ISSN: 0907-4449.
@article{323,
title = {PRISM: topologically constrained phased refinement for macromolecular crystallography},
author = { D Baker and C Bystroff and R J Fletterick and D A Agard},
issn = {0907-4449},
year = {1993},
date = {1993-09-01},
journal = {Acta crystallographica. Section D},
volume = {49},
pages = {429-39},
abstract = {We describe the further development of phase refinement by iterative skeletonization (PRISM), a recently introduced phase-refinement strategy [Wilson & Agard (1993). Acta Cryst. A49, 97-104] which makes use of the information that proteins consist of connected linear chains of atoms. An initial electron-density map is generated with inaccurate phases derived from a partial structure or from isomorphous replacement. A linear connected skeleton is then constructed from the map using a modified version of Greertextquoterights algorithm [Greer (1985). Methods Enzymol. 115, 206-226] and a new map is created from the skeleton. This textquoterightskeletonizedtextquoteright map is Fourier transformed to obtained new phases, which are combined with any starting-phase information and the experimental structure-factor amplitudes to produce a new map. The procedure is iterated until convergence is reached. In this paper significant improvements to the method are described as is a challenging molecular-replacement test case in which initial phases are calculated from a model containing only one third of the atoms of the intact protein. Application of the skeletonization procedure yields an easily interpretable map. In contrast, application of solvent flattening does not significantly improve the starting map. The iterative skeletonization procedure performs well in the presence of random noise and missing data, but requires Fourier data to at least 3.0 A. The constraints of linearity and connectedness prove strong enough to restore not only missing phase information, but also missing amplitudes. This enables the use of a powerful statistical test, analogous to the textquoterightfree R factortextquoteright of conventional refinement [Br"unger (1992). Nature (London), 355, 472-474], for optimizing the performance of the skeletonization procedure. In the accompanying paper, we describe the application of the method to the solution of the structure of the protease inhibitor ecotin bound to trypsin and to a single isomorphous replacement problem.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe the further development of phase refinement by iterative skeletonization (PRISM), a recently introduced phase-refinement strategy [Wilson & Agard (1993). Acta Cryst. A49, 97-104] which makes use of the information that proteins consist of connected linear chains of atoms. An initial electron-density map is generated with inaccurate phases derived from a partial structure or from isomorphous replacement. A linear connected skeleton is then constructed from the map using a modified version of Greertextquoterights algorithm [Greer (1985). Methods Enzymol. 115, 206-226] and a new map is created from the skeleton. This textquoterightskeletonizedtextquoteright map is Fourier transformed to obtained new phases, which are combined with any starting-phase information and the experimental structure-factor amplitudes to produce a new map. The procedure is iterated until convergence is reached. In this paper significant improvements to the method are described as is a challenging molecular-replacement test case in which initial phases are calculated from a model containing only one third of the atoms of the intact protein. Application of the skeletonization procedure yields an easily interpretable map. In contrast, application of solvent flattening does not significantly improve the starting map. The iterative skeletonization procedure performs well in the presence of random noise and missing data, but requires Fourier data to at least 3.0 A. The constraints of linearity and connectedness prove strong enough to restore not only missing phase information, but also missing amplitudes. This enables the use of a powerful statistical test, analogous to the textquoterightfree R factortextquoteright of conventional refinement [Br”unger (1992). Nature (London), 355, 472-474], for optimizing the performance of the skeletonization procedure. In the accompanying paper, we describe the application of the method to the solution of the structure of the protease inhibitor ecotin bound to trypsin and to a single isomorphous replacement problem.
H Ruohola-Baker, E Grell, T B Chou, D Baker, L Y Jan, Y N Jan
Spatially localized rhomboid is required for establishment of the dorsal-ventral axis in Drosophila oogenesis Journal Article
In: Cell, vol. 73, pp. 953-65, 1993, ISSN: 0092-8674.
@article{327,
title = {Spatially localized rhomboid is required for establishment of the dorsal-ventral axis in Drosophila oogenesis},
author = { H Ruohola-Baker and E Grell and T B Chou and D Baker and L Y Jan and Y N Jan},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/ruohola-baker93A-1.pdf},
issn = {0092-8674},
year = {1993},
date = {1993-06-01},
journal = {Cell},
volume = {73},
pages = {953-65},
abstract = {The establishment of dorsal-ventral asymmetry of the Drosophila embryo requires a group of genes that act maternally. None of the previously identified dorsal-ventral axis genes are known to produce asymmetrically localized gene products during oogenesis. We show that rhomboid (rho), a novel member of this group, encodes a protein that is localized on the apical surface of the dorsal-anterior follicle cells surrounding the oocyte. Loss of rho function causes ventralization of the eggshell and the embryo, whereas ectopic expression leads to dorsalization of both structures. Thus, spatially restricted rho is necessary and sufficient for dorsal-ventral axis formation. We propose, based on these observations and double mutant experiments, that the spatially restricted rho protein leads to selective activation of the epidermal growth factor receptor in the dorsal follicle cells and subsequently the specification of the dorsal follicle cells.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The establishment of dorsal-ventral asymmetry of the Drosophila embryo requires a group of genes that act maternally. None of the previously identified dorsal-ventral axis genes are known to produce asymmetrically localized gene products during oogenesis. We show that rhomboid (rho), a novel member of this group, encodes a protein that is localized on the apical surface of the dorsal-anterior follicle cells surrounding the oocyte. Loss of rho function causes ventralization of the eggshell and the embryo, whereas ectopic expression leads to dorsalization of both structures. Thus, spatially restricted rho is necessary and sufficient for dorsal-ventral axis formation. We propose, based on these observations and double mutant experiments, that the spatially restricted rho protein leads to selective activation of the epidermal growth factor receptor in the dorsal follicle cells and subsequently the specification of the dorsal follicle cells.
D Baker, A E Krukowski, D A Agard
Uniqueness and the ab initio phase problem in macromolecular crystallography Journal Article
In: Acta crystallographica. Section D, vol. 49, pp. 186-92, 1993, ISSN: 0907-4449.
@article{325,
title = {Uniqueness and the ab initio phase problem in macromolecular crystallography},
author = { D Baker and A E Krukowski and D A Agard},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/baker93C.pdf},
issn = {0907-4449},
year = {1993},
date = {1993-01-01},
journal = {Acta crystallographica. Section D},
volume = {49},
pages = {186-92},
abstract = {The crystallographic phase problem is indeterminate in the absence of additional chemical information. A successful ab initio approach to the macromolecular phase problem must employ sufficient chemical constraints to limit the solutions to a manageably small number. Here we show that commonly employed chemical constraints - positivity, atomicity and a solvent boundary - leave the phase problem greatly underdetermined for Fourier data sets of moderate (2.5-3.0 A) resolution. Entropy maximization is also beset by multiple false solutions: electron-density maps are readily generated which satisfy the same Fourier amplitude constraints but have higher entropies than the true solution. We conclude that a successful ab initio approach must make use of high-resolution Fourier data and/or stronger chemical constraints. One such constraint is the connectivity of the macromolecule. We describe a rapid algorithm for measuring the connectivity of a map, and show its utility in reducing the multiplicity of solutions to the phase problem.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The crystallographic phase problem is indeterminate in the absence of additional chemical information. A successful ab initio approach to the macromolecular phase problem must employ sufficient chemical constraints to limit the solutions to a manageably small number. Here we show that commonly employed chemical constraints – positivity, atomicity and a solvent boundary – leave the phase problem greatly underdetermined for Fourier data sets of moderate (2.5-3.0 A) resolution. Entropy maximization is also beset by multiple false solutions: electron-density maps are readily generated which satisfy the same Fourier amplitude constraints but have higher entropies than the true solution. We conclude that a successful ab initio approach must make use of high-resolution Fourier data and/or stronger chemical constraints. One such constraint is the connectivity of the macromolecule. We describe a rapid algorithm for measuring the connectivity of a map, and show its utility in reducing the multiplicity of solutions to the phase problem.
Baker D, Chan HS, Dill KA
Coordinate-Space Formulation of Polymer Lattice Cluster Theory Journal Article
In: Journal of Chemical Physics, 1993.
@article{324,
title = {Coordinate-Space Formulation of Polymer Lattice Cluster Theory},
author = { Baker D and Chan HS and Dill KA},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/baker93B.pdf},
year = {1993},
date = {1993-01-01},
journal = {Journal of Chemical Physics},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
1992
D Baker, J L Silen, D A Agard
Protease pro region required for folding is a potent inhibitor of the mature enzyme Journal Article
In: Proteins, vol. 12, pp. 339-44, 1992, ISSN: 0887-3585.
@article{328,
title = {Protease pro region required for folding is a potent inhibitor of the mature enzyme},
author = { D Baker and J L Silen and D A Agard},
issn = {0887-3585},
year = {1992},
date = {1992-04-01},
journal = {Proteins},
volume = {12},
pages = {339-44},
abstract = {alpha-Lytic protease, an extracellular bacterial serine protease, is synthesized with a large pro region that is required in vivo for the proper folding of the protease domain. To allow detailed mechanistic study, we have reconstituted pro region-dependent folding in vitro. The pro region promotes folding of the protease domain in the absence of other protein factors or exogenous energy sources. Surprisingly, we find that the pro region is a high affinity inhibitor of the mature protease. The pro region also inhibits the closely related Streptomyces griseus protease B, but not the more distantly related, yet structurally similar protease, elastase. Based on these data, we suggest a mechanism in which pro region binding reduces the free energy of a late folding transition state having native-like structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
alpha-Lytic protease, an extracellular bacterial serine protease, is synthesized with a large pro region that is required in vivo for the proper folding of the protease domain. To allow detailed mechanistic study, we have reconstituted pro region-dependent folding in vitro. The pro region promotes folding of the protease domain in the absence of other protein factors or exogenous energy sources. Surprisingly, we find that the pro region is a high affinity inhibitor of the mature protease. The pro region also inhibits the closely related Streptomyces griseus protease B, but not the more distantly related, yet structurally similar protease, elastase. Based on these data, we suggest a mechanism in which pro region binding reduces the free energy of a late folding transition state having native-like structure.
D Baker, J L Sohl, D A Agard
A protein-folding reaction under kinetic control Journal Article
In: Nature, vol. 356, pp. 263-5, 1992, ISSN: 0028-0836.
@article{329,
title = {A protein-folding reaction under kinetic control},
author = { D Baker and J L Sohl and D A Agard},
issn = {0028-0836},
year = {1992},
date = {1992-03-01},
journal = {Nature},
volume = {356},
pages = {263-5},
abstract = {Synthesis of alpha-lytic protease is as a precursor containing a 166 amino-acid pro region transiently required for the correct folding of the protease domain. By omitting the pro region in an in vitro refolding reaction we trapped an inactive, but folding competent state (I) having an expanded radius yet native-like secondary structure. The I state is stable for weeks at physiological pH in the absence of denaturant, but rapidly folds to the active, native state on addition of the pro region as a separate polypeptide chain. The mechanism of action of the pro region is distinct from that of the chaperonins: rather than reducing the rate of off-pathway reactions, the pro region accelerates the rate-limiting step on the folding pathway by more than 10(7). Because both the I and native states are stable under identical conditions with no detectable interconversion, the folding of alpha-lytic protease must be under kinetic and not thermodynamic control.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Synthesis of alpha-lytic protease is as a precursor containing a 166 amino-acid pro region transiently required for the correct folding of the protease domain. By omitting the pro region in an in vitro refolding reaction we trapped an inactive, but folding competent state (I) having an expanded radius yet native-like secondary structure. The I state is stable for weeks at physiological pH in the absence of denaturant, but rapidly folds to the active, native state on addition of the pro region as a separate polypeptide chain. The mechanism of action of the pro region is distinct from that of the chaperonins: rather than reducing the rate of off-pathway reactions, the pro region accelerates the rate-limiting step on the folding pathway by more than 10(7). Because both the I and native states are stable under identical conditions with no detectable interconversion, the folding of alpha-lytic protease must be under kinetic and not thermodynamic control.
1991
H Ruohola, K A Bremer, D Baker, J R Swedlow, L Y Jan, Y N Jan
Role of neurogenic genes in establishment of follicle cell fate and oocyte polarity during oogenesis in Drosophila. Journal Article
In: Cell, vol. 66, pp. 433-49, 1991, ISSN: 0092-8674.
@article{330,
title = {Role of neurogenic genes in establishment of follicle cell fate and oocyte polarity during oogenesis in Drosophila.},
author = { H Ruohola and K A Bremer and D Baker and J R Swedlow and L Y Jan and Y N Jan},
issn = {0092-8674},
year = {1991},
date = {1991-08-01},
journal = {Cell},
volume = {66},
pages = {433-49},
abstract = {Oogenesis in Drosophila involves specification of both germ cells and the surrounding somatic follicle cells, as well as the determination of oocyte polarity. We found that two neurogenic genes, Notch and Delta, are required in oogenesis. These genes encode membrane proteins with epidermal growth factor repeats and are essential in the decision of an embryonic ectodermal cell to take on the fate of neuroblast or epidermoblast. In oogenesis, mutation in either gene leads to an excess of posterior follicle cells, a cell fate change reminiscent of the hyperplasia of neuroblasts seen in neurogenic mutant embryos. Furthermore, the Notch mutation in somatic cells causes mislocalization of bicoid in the oocyte. These results suggest that the neurogenic genes Notch and Delta are involved in both follicle cell development and the establishment of anterior-posterior polarity in the oocyte.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Oogenesis in Drosophila involves specification of both germ cells and the surrounding somatic follicle cells, as well as the determination of oocyte polarity. We found that two neurogenic genes, Notch and Delta, are required in oogenesis. These genes encode membrane proteins with epidermal growth factor repeats and are essential in the decision of an embryonic ectodermal cell to take on the fate of neuroblast or epidermoblast. In oogenesis, mutation in either gene leads to an excess of posterior follicle cells, a cell fate change reminiscent of the hyperplasia of neuroblasts seen in neurogenic mutant embryos. Furthermore, the Notch mutation in somatic cells causes mislocalization of bicoid in the oocyte. These results suggest that the neurogenic genes Notch and Delta are involved in both follicle cell development and the establishment of anterior-posterior polarity in the oocyte.
1990
D Baker, L Wuestehube, R Schekman, D Botstein, N Segev
GTP-binding Ypt1 protein and Ca2+ function independently in a cell-free protein transport reaction Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 87, pp. 355-9, 1990, ISSN: 0027-8424.
@article{331,
title = {GTP-binding Ypt1 protein and Ca2+ function independently in a cell-free protein transport reaction},
author = { D Baker and L Wuestehube and R Schekman and D Botstein and N Segev},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/baker90A.pdf},
issn = {0027-8424},
year = {1990},
date = {1990-01-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {87},
pages = {355-9},
abstract = {The 21-kDa GTP-binding Ypt1 protein (Ypt1p) is required for protein transport from the endoplasmic reticulum to the Golgi complex in yeast extracts. Ypt1 antibodies block transport; this inhibition is alleviated by competition with excess purified Ypt1p produced in bacteria. Furthermore, extracts of cells carrying the mutation ypt1-1 are defective in transport, but transport is restored if a cytosolic fraction from wild-type cells is provided. The in vitro transport reaction also requires physiological levels of Ca2+. However, Ypt1p functions independently of Ca2+. First, buffering the free Ca2+ at concentrations ranging from 1 nM to 10 microM does not relieve inhibition by Ypt1 antibodies. Second, consumption of a Ca2+-requiring intermediate that accumulates in Ca2+-deficient incubations is not inhibited by anti-Ypt1 antibodies, although completion of transport requires ATP and an N-ethylmaleimide-sensitive factor. Thus, Ypt1p and Ca2+ are required at distinct steps.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The 21-kDa GTP-binding Ypt1 protein (Ypt1p) is required for protein transport from the endoplasmic reticulum to the Golgi complex in yeast extracts. Ypt1 antibodies block transport; this inhibition is alleviated by competition with excess purified Ypt1p produced in bacteria. Furthermore, extracts of cells carrying the mutation ypt1-1 are defective in transport, but transport is restored if a cytosolic fraction from wild-type cells is provided. The in vitro transport reaction also requires physiological levels of Ca2+. However, Ypt1p functions independently of Ca2+. First, buffering the free Ca2+ at concentrations ranging from 1 nM to 10 microM does not relieve inhibition by Ypt1 antibodies. Second, consumption of a Ca2+-requiring intermediate that accumulates in Ca2+-deficient incubations is not inhibited by anti-Ypt1 antibodies, although completion of transport requires ATP and an N-ethylmaleimide-sensitive factor. Thus, Ypt1p and Ca2+ are required at distinct steps.
1989
D Baker, R Schekman
Reconstitution of protein transport using broken yeast spheroplasts Journal Article
In: Methods in Cell Biology, vol. 31, pp. 127-41, 1989, ISSN: 0091-679X.
@article{569,
title = {Reconstitution of protein transport using broken yeast spheroplasts},
author = { D Baker and R Schekman},
issn = {0091-679X},
year = {1989},
date = {1989-00-01},
journal = {Methods in Cell Biology},
volume = {31},
pages = {127-41},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
1988
D Baker, L Hicke, M Rexach, M Schleyer, R Schekman
Reconstitution of SEC gene product-dependent intercompartmental protein transport Journal Article
In: Cell, vol. 54, pp. 335-44, 1988, ISSN: 0092-8674.
@article{332,
title = {Reconstitution of SEC gene product-dependent intercompartmental protein transport},
author = { D Baker and L Hicke and M Rexach and M Schleyer and R Schekman},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/baker88.pdf},
issn = {0092-8674},
year = {1988},
date = {1988-07-01},
journal = {Cell},
volume = {54},
pages = {335-44},
abstract = {Transport of alpha-factor precursor from the endoplasmic reticulum to the Golgi apparatus has been reconstituted in gently lysed yeast spheroplasts. Transport is measured through the coupled addition of outer-chain carbohydrate to [35S]methionine-labeled alpha-factor precursor translocated into the endoplasmic reticulum of broken spheroplasts. The reaction is absolutely dependent on ATP, stimulated 6-fold by cytosol, and occurs between physically separable sealed compartments. Transport is inhibited by the guanine nucleotide analog GTP gamma S. sec23 mutant cells have a temperature-sensitive defect in endoplasmic reticulum-to-Golgi transport in vivo. This defect has been reproduced in vitro using sec23 membranes and cytosol. Transport at 30 degrees C with sec23 membranes requires addition of cytosol containing the SEC23 (wild-type) gene product. This demonstrates that an in vitro inter-organelle transport reaction depends on a factor required for transport in vivo. Complementation of sec mutations in vitro provides a functional assay for the purification of individual intercompartmental transport factors.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Transport of alpha-factor precursor from the endoplasmic reticulum to the Golgi apparatus has been reconstituted in gently lysed yeast spheroplasts. Transport is measured through the coupled addition of outer-chain carbohydrate to [35S]methionine-labeled alpha-factor precursor translocated into the endoplasmic reticulum of broken spheroplasts. The reaction is absolutely dependent on ATP, stimulated 6-fold by cytosol, and occurs between physically separable sealed compartments. Transport is inhibited by the guanine nucleotide analog GTP gamma S. sec23 mutant cells have a temperature-sensitive defect in endoplasmic reticulum-to-Golgi transport in vivo. This defect has been reproduced in vitro using sec23 membranes and cytosol. Transport at 30 degrees C with sec23 membranes requires addition of cytosol containing the SEC23 (wild-type) gene product. This demonstrates that an in vitro inter-organelle transport reaction depends on a factor required for transport in vivo. Complementation of sec mutations in vitro provides a functional assay for the purification of individual intercompartmental transport factors.
G S Payne, D Baker, E van Tuinen, R Schekman
Protein transport to the vacuole and receptor-mediated endocytosis by clathrin heavy chain-deficient yeast Journal Article
In: The Journal of cell biology, vol. 106, pp. 1453-61, 1988, ISSN: 0021-9525.
@article{333,
title = {Protein transport to the vacuole and receptor-mediated endocytosis by clathrin heavy chain-deficient yeast},
author = { G S Payne and D Baker and E van Tuinen and R Schekman},
url = {https://www.bakerlab.org/wp-content/uploads/2016/06/payne88A.pdf},
issn = {0021-9525},
year = {1988},
date = {1988-05-01},
journal = {The Journal of cell biology},
volume = {106},
pages = {1453-61},
abstract = {Clathrin heavy chain-deficient mutants (chcl) of Saccharomyces cerevisiae are viable but exhibit compromised growth rates. To investigate the role of clathrin in intercompartmental protein transport, two pathways have been monitored in chcl cells: transport of newly synthesized vacuolar proteins to the vacuole and receptor-mediated uptake of mating pheromone. Newly synthesized precursors of the vacuolar protease carboxypeptidase Y (CPY) were converted to mature CPY with similar kinetics in mutant and wild-type cells. chcl cells did not aberrantly secrete CPY and immunolocalization techniques revealed most of the CPY in chcl cells within morphologically identifiable vacuolar structures. Receptor-mediated internalization of the mating pheromone alpha-factor occurred in chcl cells at 36-50% wild-type levels. The mutant cells were fully competent to respond to pheromone-induced cell-cycle arrest. These results argue that in yeast, clathrin may not play an essential role either in vacuolar protein sorting and delivery or in receptor-mediated endocytosis of alpha-factor. Alternative mechanisms ordinarily may execute these pathways, or be activated in clathrin-deficient cells.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Clathrin heavy chain-deficient mutants (chcl) of Saccharomyces cerevisiae are viable but exhibit compromised growth rates. To investigate the role of clathrin in intercompartmental protein transport, two pathways have been monitored in chcl cells: transport of newly synthesized vacuolar proteins to the vacuole and receptor-mediated uptake of mating pheromone. Newly synthesized precursors of the vacuolar protease carboxypeptidase Y (CPY) were converted to mature CPY with similar kinetics in mutant and wild-type cells. chcl cells did not aberrantly secrete CPY and immunolocalization techniques revealed most of the CPY in chcl cells within morphologically identifiable vacuolar structures. Receptor-mediated internalization of the mating pheromone alpha-factor occurred in chcl cells at 36-50% wild-type levels. The mutant cells were fully competent to respond to pheromone-induced cell-cycle arrest. These results argue that in yeast, clathrin may not play an essential role either in vacuolar protein sorting and delivery or in receptor-mediated endocytosis of alpha-factor. Alternative mechanisms ordinarily may execute these pathways, or be activated in clathrin-deficient cells.