Preprints
Available on bioRxiv.
Publications
1.
Gyu Rie Lee Justas Dauparas, Robert Pecoraro; Baker, David
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.
2.
Yang, Wei; Hicks, Derrick R; Ghosh, Agnidipta; Schwartze, Tristin A; Conventry, Brian; Goreshnik, Inna; Allen, Aza; Halabiya, Samer F; Kim, Chan Johng; Hinck, Cynthia S; Lee, David S; Bera, Asim K; Li, Zhe; Wang, Yujia; Schlichthaerle, Thomas; Cao, Longxing; Huang, Buwei; Garrett, Sarah; Gerben, Stacey R; Rettie, Stephen; Heine, Piper; Murray, Analisa; Edman, Natasha; Carter, Lauren; Stewart, Lance; Almo, Steven C; Hinck, Andrew P; Baker, David
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.
3.
Glögl, Matthias; Krishnakumar, Aditya; Ragotte, Robert J.; Goreshnik, Inna; Coventry, Brian; Bera, Asim K.; Kang, Alex; Joyce, Emily; Ahn, Green; Huang, Buwei; Yang, Wei; Chen, Wei; Sanchez, Mariana Garcia; Koepnick, Brian; Baker, David
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.
4.
Huang, Buwei; Abedi, Mohamad; Ahn, Green; Coventry, Brian; Sappington, Isaac; Tang, Cong; Wang, Rong; Schlichthaerle, Thomas; Zhang, Jason Z.; Wang, Yujia; Goreshnik, Inna; Chiu, Ching Wen; Chazin-Gray, Adam; Chan, Sidney; Gerben, Stacey; Murray, Analisa; Wang, Shunzhi; O’Neill, Jason; Yi, Li; Yeh, Ronald; Misquith, Ayesha; Wolf, Anitra; Tomasovic, Luke M.; Piraner, Dan I.; Gonzalez, Maria J. Duran; Bennett, Nathaniel R.; Venkatesh, Preetham; Ahlrichs, Maggie; Dobbins, Craig; Yang, Wei; Wang, Xinru; Sahtoe, Danny D.; Vafeados, Dionne; Mout, Rubul; Shivaei, Shirin; Cao, Longxing; Carter, Lauren; Stewart, Lance; Spangler, Jamie B.; Roybal, Kole T.; Greisen, Per Jr; Li, Xiaochun; Bernardes, Gonçalo J. L.; Bertozzi, Carolyn R.; Baker, David
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.
5.
Huang, Buwei; Coventry, Brian; Borowska, Marta T.; Arhontoulis, Dimitrios C.; Exposit, Marc; Abedi, Mohamad; Jude, Kevin M.; Halabiya, Samer F.; Allen, Aza; Cordray, Cami; Goreshnik, Inna; Ahlrichs, Maggie; Chan, Sidney; Tunggal, Hillary; DeWitt, Michelle; Hyams, Nathaniel; Carter, Lauren; Stewart, Lance; Fuller, Deborah H.; Mei, Ying; Garcia, K. Christopher; Baker, David
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.
6.
Sun, Ke; Li, Sicong; Zheng, Bowen; Zhu, Yanlei; Wang, Tongyue; Liang, Mingfu; Yao, Yue; Zhang, Kairan; Zhang, Jizhong; Li, Hongyong; Han, Dongyang; Zheng, Jishen; Coventry, Brian; Cao, Longxing; Baker, David; Liu, Lei; Lu, Peilong
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.
7.
An, Linna; Said, Meerit; Tran, Long; Majumder, Sagardip; Goreshnik, Inna; Lee, Gyu Rie; Juergens, David; Dauparas, Justas; Anishchenko, Ivan; Coventry, Brian; Bera, Asim K.; Kang, Alex; Levine, Paul M.; Alvarez, Valentina; Pillai, Arvind; Norn, Christoffer; Feldman, David; Zorine, Dmitri; Hicks, Derrick R.; Li, Xinting; Sanchez, Mariana Garcia; Vafeados, Dionne K.; Salveson, Patrick J.; Vorobieva, Anastassia A.; Baker, David
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.
8.
Berger, Stephanie; Seeger, Franziska; Yu, Ta-Yi; Aydin, Merve; Yang, Huilin; Rosenblum, Daniel; Guenin-Macé, Laure; Glassman, Caleb; Arguinchona, Lauren; Sniezek, Catherine; Blackstone, Alyssa; Carter, Lauren; Ravichandran, Rashmi; Ahlrichs, Maggie; Murphy, Michael; Pultz, Ingrid Swanson; Kang, Alex; Bera, Asim K.; Stewart, Lance; Garcia, K. Christopher; Naik, Shruti; Spangler, Jamie B.; Beigel, Florian; Siebeck, Matthias; Gropp, Roswitha; Baker, David
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.
9.
Jiang, Hanlun; Jude, Kevin M.; Wu, Kejia; Fallas, Jorge; Ueda, George; Brunette, T. J.; Hicks, Derrick R.; Pyles, Harley; Yang, Aerin; Carter, Lauren; Lamb, Mila; Li, Xinting; Levine, Paul M.; Stewart, Lance; Garcia, K. Christopher; 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.
10.
Sahtoe, Danny D.; Andrzejewska, Ewa A.; Han, Hannah L.; Rennella, Enrico; Schneider, Matthias M.; Meisl, Georg; Ahlrichs, Maggie; Decarreau, Justin; Nguyen, Hannah; Kang, Alex; Levine, Paul; Lamb, Mila; Li, Xinting; Bera, Asim K.; Kay, Lewis E.; Knowles, Tuomas P. J.; Baker, David
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.
11.
Mateos, Diego Lopez; Murray, Adam M.; Nguyen, Hai M.; Venkatesh, Preetham; Koepnick, Brian; Baker, David; Wulff, Heike; Yarov-Yarovoy, Vladimir
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.
12.
Torres, Susana Vázquez; Leung, Philip J Y; Venkatesh, Preetham; Lutz, Isaac D; Hink, Fabian; Huynh, Huu-Hien; Becker, Jessica; Yeh, Andy Hsien-Wei; Juergens, David; Bennett, Nathaniel R; Hoofnagle, Andrew N; Huang, Eric; MacCoss, Michael J; Expòsit, Marc; Lee, Gyu Rie; Bera, Asim K; Kang, Alex; Cruz, Joshmyn De La; Levine, Paul M; Li, Xinting; Lamb, Mila; Gerben, Stacey R; Murray, Analisa; Heine, Piper; Korkmaz, Elif Nihal; Nivala, Jeff; Stewart, Lance; Watson, Joseph L; Rogers, Joseph M; Baker, David
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.
13.
Olshefsky, Audrey; Benasutti, Halli; Sylvestre, Meilyn; Butterfield, Gabriel L; Rocklin, Gabriel J; Richardson, Christian; Hicks, Derrick R; Lajoie, Marc J; Song, Kefan; Leaf, Elizabeth; Treichel, Catherine; Decarreau, Justin; Ke, Sharon; Kher, Gargi; Carter, Lauren; Chamberlain, Jeffrey S; Baker, David; King, Neil P; Pun, Suzie H
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.
14.
Hicks DR An L, Zorine 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.
15.
Watson, Joseph L.; Juergens, David; Bennett, Nathaniel R.; Trippe, Brian L.; Yim, Jason; Eisenach, Helen E.; Ahern, Woody; Borst, Andrew J.; Ragotte, Robert J.; Milles, Lukas F.; Wicky, Basile I. M.; Hanikel, Nikita; Pellock, Samuel J.; Courbet, Alexis; Sheffler, William; Wang, Jue; Venkatesh, Preetham; Sappington, Isaac; Torres, Susana Vázquez; Lauko, Anna; De Bortoli, Valentin; Mathieu, Emile; Ovchinnikov, Sergey; Barzilay, Regina; Jaakkola, Tommi S.; DiMaio, Frank; Baek, Minkyung; 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.
16.
Bennett, Nathaniel R.; Coventry, Brian; Goreshnik, Inna; Huang, Buwei; Allen, Aza; Vafeados, Dionne; Peng, Ying Po; Dauparas, Justas; Baek, Minkyung; Stewart, Lance; DiMaio, Frank; De Munck, Steven; Savvides, Savvas N.; 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.
17.
Danny D. Sahtoe Enrico Rennella, David Baker; Kay, Lewis E.
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.
18.
Kim, David E.; Jensen, Davin R.; Feldman, David; Tischer, Doug; Saleem, Ayesha; Chow, Cameron M.; Li, Xinting; Carter, Lauren; Milles, Lukas; Nguyen, Hannah; Kang, Alex; Bera, Asim K.; Peterson, Francis C.; Volkman, Brian F.; Ovchinnikov, Sergey; 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.
19.
Gerben, Stacey R; Borst, Andrew J; Hicks, Derrick R; Moczygemba, Isabelle; Feldman, David; Coventry, Brian; Yang, Wei; Bera, Asim K.; Miranda, Marcos; Kang, Alex; Nguyen, Hannah; 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.
20.
Agarwal, Dilip Kumar; Hunt, Andrew C.; Shekhawat, Gajendra S.; Carter, Lauren; Chan, Sidney; Wu, Kejia; Cao, Longxing; Baker, David; Lorenzo-Redondo, Ramon; Ozer, Egon A.; Simons, Lacy M.; Hultquist, Judd F.; Jewett, Michael C.; 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.
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.
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.
COLLABORATOR LED
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2024
FROM THE LAB
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.
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.
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.
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.
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.
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.
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.
COLLABORATOR LED
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.
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.
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.
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.
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.
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.
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.
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.
2022
FROM THE LAB
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.
COLLABORATOR LED
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.
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.
2021
FROM THE LAB
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.
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.
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.
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Sorry, no publications matched your criteria.
2020
FROM THE LAB
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.
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.
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.
COLLABORATOR LED
Sorry, no publications matched your criteria.
2019
FROM THE LAB
Sorry, no publications matched your criteria.
COLLABORATOR LED
Sorry, no publications matched your criteria.
2018
FROM THE LAB
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
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.
2017-1988
ALL PAPERS
2017
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.
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.
2015
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.
2013
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.
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.
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.
2011
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.