Publications
Preprints available on bioRxiv.
2024
FROM THE LAB
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] },
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}
}
Sidney Lyayuga Lisanza, Jacob Merle Gershon, Samuel W. K. Tipps, Jeremiah Nelson Sims, Lucas Arnoldt, Samuel J. Hendel, Miriam K. Simma, Ge Liu, Muna Yase, Hongwei Wu, Claire D. Tharp, Xinting Li, Alex Kang, Evans Brackenbrough, Asim K. Bera, Stacey Gerben, Bruce J. Wittmann, Andrew C. McShan, David Baker
Multistate and functional protein design using RoseTTAFold sequence space diffusion Journal Article
In: Nature Biotechnology, 2024.
@article{Lisanza2024,
title = {Multistate and functional protein design using RoseTTAFold sequence space diffusion},
author = {Sidney Lyayuga Lisanza and Jacob Merle Gershon and Samuel W. K. Tipps and Jeremiah Nelson Sims and Lucas Arnoldt and Samuel J. Hendel and Miriam K. Simma and Ge Liu and Muna Yase and Hongwei Wu and Claire D. Tharp and Xinting Li and Alex Kang and Evans Brackenbrough and Asim K. Bera and Stacey Gerben and Bruce J. Wittmann and Andrew C. McShan and David Baker},
url = {https://www.nature.com/articles/s41587-024-02395-w, Nature Biotechnology [Open Access]},
doi = {10.1038/s41587-024-02395-w},
year = {2024},
date = {2024-09-25},
urldate = {2024-09-25},
journal = {Nature Biotechnology},
publisher = {Springer Science and Business Media LLC},
abstract = {Protein denoising diffusion probabilistic models are used for the de novo generation of protein backbones but are limited in their ability to guide generation of proteins with sequence-specific attributes and functional properties. To overcome this limitation, we developed ProteinGenerator (PG), a sequence space diffusion model based on RoseTTAFold that simultaneously generates protein sequences and structures. Beginning from a noised sequence representation, PG generates sequence and structure pairs by iterative denoising, guided by desired sequence and structural protein attributes. We designed thermostable proteins with varying amino acid compositions and internal sequence repeats and cage bioactive peptides, such as melittin. By averaging sequence logits between diffusion trajectories with distinct structural constraints, we designed multistate parent–child protein triples in which the same sequence folds to different supersecondary structures when intact in the parent versus split into two child domains. PG design trajectories can be guided by experimental sequence–activity data, providing a general approach for integrated computational and experimental optimization of protein function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ian R. Humphreys, Jing Zhang, Minkyung Baek, Yaxi Wang, Aditya Krishnakumar, Jimin Pei, Ivan Anishchenko, Catherine A. Tower, Blake A. Jackson, Thulasi Warrier, Deborah T. Hung, S. Brook Peterson, Joseph D. Mougous, Qian Cong, David Baker
Protein interactions in human pathogens revealed through deep learning Journal Article
In: Nature Microbiology, 2024, ISSN: 2058-5276.
@article{Humphreys2024,
title = {Protein interactions in human pathogens revealed through deep learning},
author = {Ian R. Humphreys and Jing Zhang and Minkyung Baek and Yaxi Wang and Aditya Krishnakumar and Jimin Pei and Ivan Anishchenko and Catherine A. Tower and Blake A. Jackson and Thulasi Warrier and Deborah T. Hung and S. Brook Peterson and Joseph D. Mougous and Qian Cong and David Baker},
url = {https://www.nature.com/articles/s41564-024-01791-x, Nature Microbiology [Open Access]},
doi = {10.1038/s41564-024-01791-x},
issn = {2058-5276},
year = {2024},
date = {2024-09-18},
urldate = {2024-09-18},
journal = {Nature Microbiology},
publisher = {Springer Science and Business Media LLC},
abstract = {Identification of bacterial protein–protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lite, a rapid deep learning model that leverages residue–residue coevolution and protein structure prediction to systematically identify and structurally characterize protein–protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1,923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer-membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Adam P. Moyer, Theresa A. Ramelot, Mariano Curti, Margaret A. Eastman, Alex Kang, Asim K. Bera, Roberto Tejero, Patrick J. Salveson, Carles Curutchet, Elisabet Romero, Gaetano T. Montelione, David Baker
Enumerative Discovery of Noncanonical Polypeptide Secondary Structures Journal Article
In: Journal of the American Chemical Society, 2024.
@article{Moyer2024,
title = {Enumerative Discovery of Noncanonical Polypeptide Secondary Structures},
author = {Adam P. Moyer and Theresa A. Ramelot and Mariano Curti and Margaret A. Eastman and Alex Kang and Asim K. Bera and Roberto Tejero and Patrick J. Salveson and Carles Curutchet and Elisabet Romero and Gaetano T. Montelione and David Baker},
url = {https://pubs.acs.org/doi/full/10.1021/jacs.4c04991, LACS [Open Access]},
doi = {10.1021/jacs.4c04991},
year = {2024},
date = {2024-09-18},
urldate = {2024-09-18},
journal = {Journal of the American Chemical Society},
publisher = {American Chemical Society (ACS)},
abstract = {Energetically favorable local interactions can overcome the entropic cost of chain ordering and cause otherwise flexible polymers to adopt regularly repeating backbone conformations. A prominent example is the α helix present in many protein structures, which is stabilized by i, i + 4 hydrogen bonds between backbone peptide units. With the increased chemical diversity offered by unnatural amino acids and backbones, it has been possible to identify regularly repeating structures not present in proteins, but to date, there has been no systematic approach for identifying new polymers likely to have such structures despite their considerable potential for molecular engineering. Here we describe a systematic approach to search through dipeptide combinations of 130 chemically diverse amino acids to identify those predicted to populate unique low-energy states. We characterize ten newly identified dipeptide repeating structures using circular dichroism spectroscopy and comparison with calculated spectra. NMR and X-ray crystallographic structures of two of these dipeptide-repeat polymers are similar to the computational models. Our approach is readily generalizable to identify low-energy repeating structures for a wide variety of polymers, and our ordered dipeptide repeats provide new building blocks for molecular engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Arvind Pillai, Abbas Idris, Annika Philomin, Connor Weidle, Rebecca Skotheim, Philip J. Y. Leung, Adam Broerman, Cullen Demakis, Andrew J. Borst, Florian Praetorius, David Baker
De novo design of allosterically switchable protein assemblies Journal Article
In: Nature, 2024.
@article{Pillai2024,
title = {De novo design of allosterically switchable protein assemblies},
author = {Arvind Pillai and Abbas Idris and Annika Philomin and Connor Weidle and Rebecca Skotheim and Philip J. Y. Leung and Adam Broerman and Cullen Demakis and Andrew J. Borst and Florian Praetorius and David Baker},
url = {https://www.nature.com/articles/s41586-024-07813-2, Nature [Open Access]},
doi = {10.1038/s41586-024-07813-2},
year = {2024},
date = {2024-08-14},
urldate = {2024-08-14},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {Allosteric modulation of protein function, wherein the binding of an effector to a protein triggers conformational changes at distant functional sites, plays a central part in the control of metabolism and cell signalling. There has been considerable interest in designing allosteric systems, both to gain insight into the mechanisms underlying such ‘action at a distance’ modulation and to create synthetic proteins whose functions can be regulated by effectors. However, emulating the subtle conformational changes distributed across many residues, characteristic of natural allosteric proteins, is a significant challenge. Here, inspired by the classic Monod–Wyman–Changeux model of cooperativity, we investigate the de novo design of allostery through rigid-body coupling of peptide-switchable hinge modules to protein interfaces that direct the formation of alternative oligomeric states. We find that this approach can be used to generate a wide variety of allosterically switchable systems, including cyclic rings that incorporate or eject subunits in response to peptide binding and dihedral cages that undergo effector-induced disassembly. Size-exclusion chromatography, mass photometry and electron microscopy reveal that these designed allosteric protein assemblies closely resemble the design models in both the presence and absence of peptide effectors and can have ligand-binding cooperativity comparable to classic natural systems such as haemoglobin. Our results indicate that allostery can arise from global coupling of the energetics of protein substructures without optimized side-chain–side-chain allosteric communication pathways and provide a roadmap for generating allosterically triggerable delivery systems, protein nanomachines and cellular feedback control circuitry.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Samuel Berhanu, Sagardip Majumder, Thomas Müntener, James Whitehouse, Carolin Berner, Asim K. Bera, Alex Kang, Binyong Liang, Nasir Khan, Banumathi Sankaran, Lukas K. Tamm, David J. Brockwell, Sebastian Hiller, Sheena E. Radford, David Baker, Anastassia A. Vorobieva
Sculpting conducting nanopore size and shape through de novo protein design Journal Article
In: Science, 2024.
@article{Berhanu2024,
title = {Sculpting conducting nanopore size and shape through de novo protein design},
author = {Samuel Berhanu and Sagardip Majumder and Thomas Müntener and James Whitehouse and Carolin Berner and Asim K. Bera and Alex Kang and Binyong Liang and Nasir Khan and Banumathi Sankaran and Lukas K. Tamm and David J. Brockwell and Sebastian Hiller and Sheena E. Radford and David Baker and Anastassia A. Vorobieva},
url = {https://www.science.org/doi/10.1126/science.adn3796, Science},
doi = {10.1126/science.adn3796},
year = {2024},
date = {2024-07-19},
urldate = {2024-07-19},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {Transmembrane β-barrels have considerable potential for a broad range of sensing applications. Current engineering approaches for nanopore sensors are limited to naturally occurring channels, which provide suboptimal starting points. By contrast, de novo protein design can in principle create an unlimited number of new nanopores with any desired properties. Here we describe a general approach to designing transmembrane β-barrel pores with different diameters and pore geometries. Nuclear magnetic resonance and crystallographic characterization show that the designs are stably folded with structures resembling those of the design models. The designs have distinct conductances that correlate with their pore diameter, ranging from 110 picosiemens (~0.5 nanometer pore diameter) to 430 picosiemens (~1.1 nanometer pore diameter). Our approach opens the door to the custom design of transmembrane nanopores for sensing and sequencing applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Natasha I. Edman, Ashish Phal, Rachel L. Redler, Thomas Schlichthaerle, Sanjay R. Srivatsan, Devon Duron Ehnes, Ali Etemadi, Seong J. An, Andrew Favor, Zhe Li, Florian Praetorius, Max Gordon, Thomas Vincent, Silvia Marchiano, Leslie Blakely, Chuwei Lin, Wei Yang, Brian Coventry, Derrick R. Hicks, Longxing Cao, Neville Bethel, Piper Heine, Analisa Murray, Stacey Gerben, Lauren Carter, Marcos Miranda, Babak Negahdari, Sangwon Lee, Cole Trapnell, Ying Zheng, Charles E. Murry, Devin K. Schweppe, Benjamin S. Freedman, Lance Stewart, Damian C. Ekiert, Joseph Schlessinger, Jay Shendure, Gira Bhabha, Hannele Ruohola-Baker, David Baker,
Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies Journal Article
In: Cell, 2024.
@article{Edman2024,
title = {Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies},
author = {Natasha I. Edman,
Ashish Phal,
Rachel L. Redler,
Thomas Schlichthaerle,
Sanjay R. Srivatsan,
Devon Duron Ehnes,
Ali Etemadi,
Seong J. An,
Andrew Favor,
Zhe Li,
Florian Praetorius,
Max Gordon,
Thomas Vincent,
Silvia Marchiano,
Leslie Blakely,
Chuwei Lin,
Wei Yang,
Brian Coventry,
Derrick R. Hicks,
Longxing Cao,
Neville Bethel,
Piper Heine,
Analisa Murray,
Stacey Gerben,
Lauren Carter,
Marcos Miranda,
Babak Negahdari,
Sangwon Lee,
Cole Trapnell,
Ying Zheng,
Charles E. Murry,
Devin K. Schweppe,
Benjamin S. Freedman,
Lance Stewart,
Damian C. Ekiert,
Joseph Schlessinger,
Jay Shendure,
Gira Bhabha,
Hannele Ruohola-Baker,
David Baker, },
url = {https://authors.elsevier.com/sd/article/S0092-8674(24)00534-8, Cell (Open Access)
https://www.bakerlab.org/wp-content/uploads/2024/06/Cell_13439_Modulation_of_FGF_pathway_signalling_2024.pdf, PDF},
doi = {10.1016/j.cell.2024.05.025},
year = {2024},
date = {2024-06-10},
journal = {Cell},
abstract = {Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Erin C. Yang, Robby Divine, Marcos C. Miranda, Andrew J. Borst, Will Sheffler, Jason Z. Zhang, Justin Decarreau, Amijai Saragovi, Mohamad Abedi, Nicolas Goldbach, Maggie Ahlrichs, Craig Dobbins, Alexis Hand, Suna Cheng, Mila Lamb, Paul M. Levine, Sidney Chan, Rebecca Skotheim, Jorge Fallas, George Ueda, Joshua Lubner, Masaharu Somiya, Alena Khmelinskaia, Neil P. King, David Baker
Computational design of non-porous pH-responsive antibody nanoparticles Journal Article
In: Nature Structural & Molecular Biololgy, 2024.
@article{Yang2024,
title = {Computational design of non-porous pH-responsive antibody nanoparticles},
author = {Erin C. Yang and Robby Divine and Marcos C. Miranda and Andrew J. Borst and Will Sheffler and Jason Z. Zhang and Justin Decarreau and Amijai Saragovi and Mohamad Abedi and Nicolas Goldbach and Maggie Ahlrichs and Craig Dobbins and Alexis Hand and Suna Cheng and Mila Lamb and Paul M. Levine and Sidney Chan and Rebecca Skotheim and Jorge Fallas and George Ueda and Joshua Lubner and Masaharu Somiya and Alena Khmelinskaia and Neil P. King and David Baker},
url = {https://www.nature.com/articles/s41594-024-01288-5, NSMB [Open Access]
https://www.bakerlab.org/wp-content/uploads/2024/05/Yang-etal-NSMB2024-s41594-024-01288-5.pdf, PDF},
doi = {10.1038/s41594-024-01288-5},
year = {2024},
date = {2024-05-09},
urldate = {2024-05-09},
journal = {Nature Structural & Molecular Biololgy},
publisher = {Springer Science and Business Media LLC},
abstract = {Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and is important for targeted delivery of biologics. Here we describe the design of octahedral non-porous nanoparticles with a targeting antibody on the two-fold symmetry axis, a designed trimer programmed to disassemble below a tunable pH transition point on the three-fold axis, and a designed tetramer on the four-fold symmetry axis. Designed non-covalent interfaces guide cooperative nanoparticle assembly from independently purified components, and a cryo-EM density map closely matches the computational design model. The designed nanoparticles can package protein and nucleic acid payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between 5.9 and 6.7. The ability to incorporate almost any antibody into a non-porous pH-dependent nanoparticle opens up new routes to antibody-directed targeted delivery.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Timothy W. Craven, Mark D. Nolan, Jonathan Bailey, Samir Olatunji, Samantha J. Bann, Katherine Bowen, Nikita Ostrovitsa, Thaina M. Da Costa, Ross D. Ballantine, Dietmar Weichert, Paul M. Levine, Lance J. Stewart, Gaurav Bhardwaj, Joan A. Geoghegan, Stephen A. Cochrane, Eoin M. Scanlan, Martin Caffrey, David Baker
Computational Design of Cyclic Peptide Inhibitors of a Bacterial Membrane Lipoprotein Peptidase Journal Article
In: ACS Chemical Biology, 2024.
@article{Craven2024,
title = {Computational Design of Cyclic Peptide Inhibitors of a Bacterial Membrane Lipoprotein Peptidase},
author = {Timothy W. Craven and Mark D. Nolan and Jonathan Bailey and Samir Olatunji and Samantha J. Bann and Katherine Bowen and Nikita Ostrovitsa and Thaina M. Da Costa and Ross D. Ballantine and Dietmar Weichert and Paul M. Levine and Lance J. Stewart and Gaurav Bhardwaj and Joan A. Geoghegan and Stephen A. Cochrane and Eoin M. Scanlan and Martin Caffrey and David Baker},
url = {https://pubs.acs.org/doi/10.1021/acschembio.4c00076, ACS Chem. Bio. [Open Access]
https://www.bakerlab.org/wp-content/uploads/2024/05/craven-et-al-2024-computational-design-of-cyclic-peptide-inhibitors-of-a-bacterial-membrane-lipoprotein-peptidase.pdf, PDF},
doi = {10.1021/acschembio.4c00076},
year = {2024},
date = {2024-05-07},
urldate = {2024-05-07},
journal = {ACS Chemical Biology},
publisher = {American Chemical Society (ACS)},
abstract = {There remains a critical need for new antibiotics against multi-drug-resistant Gram-negative bacteria, a major global threat that continues to impact mortality rates. Lipoprotein signal peptidase II is an essential enzyme in the lipoprotein biosynthetic pathway of Gram-negative bacteria, making it an attractive target for antibacterial drug discovery. Although natural inhibitors of LspA have been identified, such as the cyclic depsipeptide globomycin, poor stability and production difficulties limit their use in a clinical setting. We harness computational design to generate stable de novo cyclic peptide analogues of globomycin. Only 12 peptides needed to be synthesized and tested to yield potent inhibitors, avoiding costly preparation of large libraries and screening campaigns. The most potent analogues showed comparable or better antimicrobial activity than globomycin in microdilution assays against ESKAPE-E pathogens. This work highlights computational design as a general strategy to combat antibiotic resistance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Patrick J. Salveson, Adam P. Moyer, Meerit Y. Said, Gizem Gӧkçe, Xinting Li, Alex Kang, Hannah Nguyen, Asim K. Bera, Paul M. Levine, Gaurav Bhardwaj, David Baker
Expansive discovery of chemically diverse structured macrocyclic oligoamides Journal Article
In: Science, 2024.
@article{Salveson2024,
title = {Expansive discovery of chemically diverse structured macrocyclic oligoamides},
author = {Patrick J. Salveson and Adam P. Moyer and Meerit Y. Said and Gizem Gӧkçe and Xinting Li and Alex Kang and Hannah Nguyen and Asim K. Bera and Paul M. Levine and Gaurav Bhardwaj and David Baker},
url = {https://www.science.org/doi/abs/10.1126/science.adk1687, Science
https://www.bakerlab.org/wp-content/uploads/2024/04/Salveson-et-al-Science-2024.pdf, PDF},
doi = {10.1126/science.adk1687},
year = {2024},
date = {2024-04-25},
urldate = {2024-01-01},
journal = {Science},
abstract = {Small macrocycles with four or fewer amino acids are among the most potent natural products known, but there is currently no way to systematically generate such compounds. We describe a computational method for identifying ordered macrocycles composed of alpha, beta, gamma, and 17 other amino acid backbone chemistries, which we used to predict 14.9 million closed cycles composed of >42,000 monomer combinations. We chemically synthesized 18 macrocycles predicted to adopt single low-energy states and determined their x-ray or nuclear magnetic resonance structures; 15 of these were very close to the design models. We illustrate the therapeutic potential of these macrocycle designs by developing selective inhibitors of three protein targets of current interest. By opening up a vast space of readily synthesizable drug-like macrocycles, our results should considerably enhance structure-based drug design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hao Shen, Eric M. Lynch, Susrut Akkineni, Joseph L. Watson, Justin Decarreau, Neville P. Bethel, Issa Benna, William Sheffler, Daniel Farrell, Frank DiMaio, Emmanuel Derivery, James J. De Yoreo, Justin Kollman, David Baker
De novo design of pH-responsive self-assembling helical protein filaments Journal Article
In: Nature Nanotechnology, 2024.
@article{Shen2024,
title = {De novo design of pH-responsive self-assembling helical protein filaments},
author = {Hao Shen and Eric M. Lynch and Susrut Akkineni and Joseph L. Watson and Justin Decarreau and Neville P. Bethel and Issa Benna and William Sheffler and Daniel Farrell and Frank DiMaio and Emmanuel Derivery and James J. De Yoreo and Justin Kollman and David Baker},
url = {https://link.springer.com/article/10.1038/s41565-024-01641-1, Nature Nanotechnology [Open Access]
https://www.bakerlab.org/wp-content/uploads/2024/04/s41565-024-01641-1.pdf, PDF},
doi = {10.1038/s41565-024-01641-1},
year = {2024},
date = {2024-04-03},
urldate = {2024-04-03},
journal = {Nature Nanotechnology},
publisher = {Springer Science and Business Media LLC},
abstract = {Biological evolution has led to precise and dynamic nanostructures that reconfigure in response to pH and other environmental conditions. However, designing micrometre-scale protein nanostructures that are environmentally responsive remains a challenge. Here we describe the de novo design of pH-responsive protein filaments built from subunits containing six or nine buried histidine residues that assemble into micrometre-scale, well-ordered fibres at neutral pH. The cryogenic electron microscopy structure of an optimized design is nearly identical to the computational design model for both the subunit internal geometry and the subunit packing into the fibre. Electron, fluorescent and atomic force microscopy characterization reveal a sharp and reversible transition from assembled to disassembled fibres over 0.3 pH units, and rapid fibre disassembly in less than 1 s following a drop in pH. The midpoint of the transition can be tuned by modulating buried histidine-containing hydrogen bond networks. Computational protein design thus provides a route to creating unbound nanomaterials that rapidly respond to small pH changes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sangmin Lee, Ryan D. Kibler, Quinton Dowling, Yang Hsia, Neil P. King, David Baker
Expanding protein nanocages through designed symmetry-breaking Online
2024.
@online{Lee2024,
title = {Expanding protein nanocages through designed symmetry-breaking},
author = {Sangmin Lee and Ryan D. Kibler and Quinton Dowling and Yang Hsia and Neil P. King and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2024/04/Expanding-protein-nanocages-through-designed-symmetry-breaking.pdf},
year = {2024},
date = {2024-04-02},
journal = {self published},
abstract = {Polyhedral protein nanocages have had considerable success as vaccine platforms (1–3) and are promising vehicles for biologics delivery (4–7). Hence there is considerable interest in designing larger and more complex structures capable of displaying larger numbers of antigens or packaging larger cargos. However, the regular polyhedra are the largest closed structures in which all subunits have identical local environments (8–11), and thus accessing larger and more complex closed structures requires breaking local symmetry. Viruses solve this problem by placing chemically distinct but structurally similar chains in unique environments (pseudosymmetry) (12) or utilizing identical subunits that adopt different conformations in different environments (quasisymmetry) (13–15) to access higher triangulation (T) number (13) structures with larger numbers of subunits and interior volumes. A promising route to designing larger and more complex nanocages is to start from regular polyhedral nanocages (T=1) constructed from a symmetric homotrimeric building block, isolate cyclic arrangements of these building blocks by substituting in pseudosymmetric heterotrimers, and then build T=4 and larger structures by combining these with additional homo- and heterotrimers. Here we provide a high-level geometric overview of this design approach to illustrate how tradeoffs between design diversity and design economy can be used to achieve different design outcomes, as demonstrated experimentally in two accompanying papers, Lee et al (16) and Dowling et al (17).},
howpublished = {self published},
keywords = {},
pubstate = {published},
tppubtype = {online}
}
Sanaa Mansoor, Minkyung Baek, Hahnbeom Park, Gyu Rie Lee, David Baker
Protein Ensemble Generation Through Variational Autoencoder Latent Space Sampling Journal Article
In: J. Chem. Theory Comput., 2024.
@article{Mansoor2024,
title = {Protein Ensemble Generation Through Variational Autoencoder Latent Space Sampling},
author = {Sanaa Mansoor and Minkyung Baek and Hahnbeom Park and Gyu Rie Lee and David Baker},
url = {https://pubs.acs.org/doi/10.1021/acs.jctc.3c01057, J. Chem. Theory Comput.
https://www.bakerlab.org/wp-content/uploads/2024/05/mansoor-et-al-2024-protein-ensemble-generation-through-variational-autoencoder-latent-space-sampling.pdf, PDF},
doi = {10.1021/acs.jctc.3c01057},
year = {2024},
date = {2024-03-28},
urldate = {2024-04-09},
journal = {J. Chem. Theory Comput.},
publisher = {American Chemical Society (ACS)},
abstract = {Mapping the ensemble of protein conformations that contribute to function and can be targeted by small molecule drugs remains an outstanding challenge. Here, we explore the use of variational autoencoders for reducing the challenge of dimensionality in the protein structure ensemble generation problem. We convert high-dimensional protein structural data into a continuous, low-dimensional representation, carry out a search in this space guided by a structure quality metric, and then use RoseTTAFold guided by the sampled structural information to generate 3D structures. We use this approach to generate ensembles for the cancer relevant protein K-Ras, train the VAE on a subset of the available K-Ras crystal structures and MD simulation snapshots, and assess the extent of sampling close to crystal structures withheld from training. We find that our latent space sampling procedure rapidly generates ensembles with high structural quality and is able to sample within 1 Å of held-out crystal structures, with a consistency higher than that of MD simulation or AlphaFold2 prediction. The sampled structures sufficiently recapitulate the cryptic pockets in the held-out K-Ras structures to allow for small molecule docking.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Timothy F. Huddy, Yang Hsia, Ryan D. Kibler, Jinwei Xu, Neville Bethel, Deepesh Nagarajan, Rachel Redler, Philip J. Y. Leung, Connor Weidle, Alexis Courbet, Erin C. Yang, Asim K. Bera, Nicolas Coudray, S. John Calise, Fatima A. Davila-Hernandez, Hannah L. Han, Kenneth D. Carr, Zhe Li, Ryan McHugh, Gabriella Reggiano, Alex Kang, Banumathi Sankaran, Miles S. Dickinson, Brian Coventry, T. J. Brunette, Yulai Liu, Justas Dauparas, Andrew J. Borst, Damian Ekiert, Justin M. Kollman, Gira Bhabha, David Baker
Blueprinting extendable nanomaterials with standardized protein blocks Journal Article
In: Nature, 2024.
@article{Huddy2024,
title = {Blueprinting extendable nanomaterials with standardized protein blocks},
author = {Timothy F. Huddy and Yang Hsia and Ryan D. Kibler and Jinwei Xu and Neville Bethel and Deepesh Nagarajan and Rachel Redler and Philip J. Y. Leung and Connor Weidle and Alexis Courbet and Erin C. Yang and Asim K. Bera and Nicolas Coudray and S. John Calise and Fatima A. Davila-Hernandez and Hannah L. Han and Kenneth D. Carr and Zhe Li and Ryan McHugh and Gabriella Reggiano and Alex Kang and Banumathi Sankaran and Miles S. Dickinson and Brian Coventry and T. J. Brunette and Yulai Liu and Justas Dauparas and Andrew J. Borst and Damian Ekiert and Justin M. Kollman and Gira Bhabha and David Baker},
url = {https://www.nature.com/articles/s41586-024-07188-4, Nature [Open Access]},
doi = {10.1038/s41586-024-07188-4},
year = {2024},
date = {2024-03-13},
urldate = {2024-03-13},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight ‘train track’ assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence–structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to ‘back of an envelope’ architectural blueprints.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rohith Krishna, Jue Wang, Woody Ahern, Pascal Sturmfels, Preetham Venkatesh, Indrek Kalvet, Gyu Rie Lee, Felix S. Morey-Burrows, Ivan Anishchenko, Ian R. Humphreys, Ryan McHugh, Dionne Vafeados, Xinting Li, George A. Sutherland, Andrew Hitchcock, C. Neil Hunter, Alex Kang, Evans Brackenbrough, Asim K. Bera, Minkyung Baek, Frank DiMaio, David Baker
Generalized biomolecular modeling and design with RoseTTAFold All-Atom Journal Article
In: Science, 2024.
@article{Krishna2024,
title = {Generalized biomolecular modeling and design with RoseTTAFold All-Atom},
author = {Rohith Krishna and Jue Wang and Woody Ahern and Pascal Sturmfels and Preetham Venkatesh and Indrek Kalvet and Gyu Rie Lee and Felix S. Morey-Burrows and Ivan Anishchenko and Ian R. Humphreys and Ryan McHugh and Dionne Vafeados and Xinting Li and George A. Sutherland and Andrew Hitchcock and C. Neil Hunter and Alex Kang and Evans Brackenbrough and Asim K. Bera and Minkyung Baek and Frank DiMaio and David Baker},
url = {https://www.science.org/stoken/author-tokens/ST-1739/full, Science [Full Access Link]
https://www.bakerlab.org/wp-content/uploads/2024/03/science.adl2528.pdf, PDF},
doi = {10.1126/science.adl2528},
year = {2024},
date = {2024-03-07},
urldate = {2024-03-07},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {Deep learning methods have revolutionized protein structure prediction and design but are currently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA) which combines a residue-based representation of amino acids and DNA bases with an atomic representation of all other groups to model assemblies containing proteins, nucleic acids, small molecules, metals, and covalent modifications given their sequences and chemical structures. By fine tuning on denoising tasks we obtain RFdiffusionAA, which builds protein structures around small molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we design and experimentally validate, through crystallography and binding measurements, proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and the light harvesting molecule bilin.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rubul Mout, Ross C. Bretherton, Justin Decarreau, Sangmin Lee, Nicole Gregorio, Natasha I. Edman, Maggie Ahlrichs, Yang Hsia, Danny D. Sahtoe, George Ueda, Alee Sharma, Rebecca Schulman, Cole A. DeForest, David Baker
De novo design of modular protein hydrogels with programmable intra- and extracellular viscoelasticity Journal Article
In: Proceedings of the National Academy of Sciences, 2024.
@article{Mout2024,
title = {De novo design of modular protein hydrogels with programmable intra- and extracellular viscoelasticity},
author = {Rubul Mout, Ross C. Bretherton, Justin Decarreau, Sangmin Lee, Nicole Gregorio, Natasha I. Edman, Maggie Ahlrichs, Yang Hsia, Danny D. Sahtoe, George Ueda, Alee Sharma, Rebecca Schulman, Cole A. DeForest, David Baker},
url = {https://www.pnas.org/doi/full/10.1073/pnas.2309457121, PNAS [Open Access]},
doi = {10.1073/pnas.2309457121},
year = {2024},
date = {2024-01-30},
urldate = {2024-01-30},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Relating the macroscopic properties of protein-based materials to their underlying component microstructure is an outstanding challenge. Here, we exploit computational design to specify the size, flexibility, and valency of de novo protein building blocks, as well as the interaction dynamics between them, to investigate how molecular parameters govern the macroscopic viscoelasticity of the resultant protein hydrogels. We construct gel systems from pairs of symmetric protein homo-oligomers, each comprising 2, 5, 24, or 120 individual protein components, that are crosslinked either physically or covalently into idealized step-growth biopolymer networks. Through rheological assessment, we find that the covalent linkage of multifunctional precursors yields hydrogels whose viscoelasticity depends on the crosslink length between the constituent building blocks. In contrast, reversibly crosslinking the homo-oligomeric components with a computationally designed heterodimer results in viscoelastic biomaterials exhibiting fluid-like properties under rest and low shear, but solid-like behavior at higher frequencies. Exploiting the unique genetic encodability of these materials, we demonstrate the assembly of protein networks within living mammalian cells and show via fluorescence recovery after photobleaching (FRAP) that mechanical properties can be tuned intracellularly in a manner similar to formulations formed extracellularly. We anticipate that the ability to modularly construct and systematically program the viscoelastic properties of designer protein-based materials could have broad utility in biomedicine, with applications in tissue engineering, therapeutic delivery, and synthetic biology.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
David Baker, George Church
Protein design meets biosecurity Journal Article
In: Science, 2024.
@article{Baker2024,
title = {Protein design meets biosecurity},
author = {David Baker and George Church},
url = {https://www.science.org/doi/10.1126/science.ado1671, Science [Open Access]
https://www.bakerlab.org/wp-content/uploads/2024/04/Baker-Church-Protein-design-meets-biosecurity-Science-25-Jan-2024.pdf, PDF},
doi = {10.1126/science.ado1671},
year = {2024},
date = {2024-01-26},
urldate = {2024-01-26},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {The power and accuracy of computational protein design have been increasing rapidly with the incorporation of artificial intelligence (AI) approaches. This promises to transform biotechnology, enabling advances across sustainability and medicine. DNA synthesis plays a critical role in materializing designed proteins. However, as with all major revolutionary changes, this technology is vulnerable to misuse and the production of dangerous biological agents. To enable the full benefits of this revolution while mitigating risks that may emerge, all synthetic gene sequence and synthesis data should be collected and stored in repositories that are only queried in emergencies to ensure that protein design proceeds in a safe, secure, and trustworthy manner.},
howpublished = {Science},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Jason Zhang, William Nguyen, Nathan Greenwood, John Rose, Shao-En Ong, Dustin Maly, David Baker
Computationally designed sensors detect endogenous Ras activity and signaling effectors at subcellular resolution Journal Article
In: Nature Biotechnology, 2024.
@article{Zhang2024,
title = {Computationally designed sensors detect endogenous Ras activity and signaling effectors at subcellular resolution},
author = {Jason Zhang, William Nguyen, Nathan Greenwood, John Rose, Shao-En Ong, Dustin Maly, David Baker},
url = {https://www.nature.com/articles/s41587-023-02107-w, Nature Biotechnology [Open Access]},
doi = {10.1038/s41587-023-02107-w},
year = {2024},
date = {2024-01-25},
journal = {Nature Biotechnology},
abstract = {The utility of genetically encoded biosensors for sensing the activity of signaling proteins has been hampered by a lack of strategies for matching sensor sensitivity to the physiological concentration range of the target. Here we used computational protein design to generate intracellular sensors of Ras activity (LOCKR-based Sensor for Ras activity (Ras-LOCKR-S)) and proximity labelers of the Ras signaling environment (LOCKR-based, Ras activity-dependent Proximity Labeler (Ras-LOCKR-PL)). These tools allow the detection of endogenous Ras activity and labeling of the surrounding environment at subcellular resolution. Using these sensors in human cancer cell lines, we identified Ras-interacting proteins in oncogenic EML4-Alk granules and found that Src-Associated in Mitosis 68-kDa (SAM68) protein specifically enhances Ras activity in the granules. The ability to subcellularly localize endogenous Ras activity should deepen our understanding of Ras function in health and disease and may suggest potential therapeutic strategies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kiera H Sumida, Reyes Núñez-Franco, Indrek Kalvet, Samuel J Pellock, Basile I M Wicky, Lukas F Milles, Justas Dauparas, Jue Wang, Yakov Kipnis, Noel Jameson, Alex Kang, Joshmyn De La Cruz, Banumathi Sankaran, Asim K Bera, Gonzalo Jiménez-Osés, David Baker
Improving Protein Expression, Stability, and Function with ProteinMPNN Journal Article
In: JACS, 2024.
@article{Sumida2024,
title = {Improving Protein Expression, Stability, and Function with ProteinMPNN},
author = {Kiera H Sumida and Reyes Núñez-Franco and Indrek Kalvet and Samuel J Pellock and Basile I M Wicky and Lukas F Milles and Justas Dauparas and Jue Wang and Yakov Kipnis and Noel Jameson and Alex Kang and Joshmyn De La Cruz and Banumathi Sankaran and Asim K Bera and Gonzalo Jiménez-Osés and David Baker},
url = {https://pubs.acs.org/doi/10.1021/jacs.3c10941, JACS [Open Access]},
doi = {10.1021/jacs.3c10941},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {JACS},
abstract = {Natural proteins are highly optimized for function but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here, we show that the deep neural network ProteinMPNN, together with evolutionary and structural information, provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
COLLABORATOR LED
Alexandr Baryshev, Alyssa La Fleur, Benjamin Groves, Cirstyn Michel, David Baker, Ajasja Ljubetič, Georg Seelig
Massively parallel measurement of protein–protein interactions by sequencing using MP3-seq Journal Article
In: Nature Chemical Biology, 2024.
@article{Baryshev2024,
title = {Massively parallel measurement of protein–protein interactions by sequencing using MP3-seq},
author = {Alexandr Baryshev and Alyssa La Fleur and Benjamin Groves and Cirstyn Michel and David Baker and Ajasja Ljubetič and Georg Seelig},
url = {https://www.nature.com/articles/s41589-024-01718-x, Nature Chemical Biology [Open Access]},
doi = {10.1038/s41589-024-01718-x},
year = {2024},
date = {2024-08-27},
urldate = {2024-08-27},
journal = {Nature Chemical Biology},
publisher = {Springer Science and Business Media LLC},
abstract = {Protein–protein interactions (PPIs) regulate many cellular processes and engineered PPIs have cell and gene therapy applications. Here, we introduce massively parallel PPI measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Lastly, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics-based energy terms to predict MP3-seq values. We find that AF-M-based models could be valuable for prescreening interactions but experimentally measuring interactions remains necessary to rank their strengths quantitatively.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Jason Z. Zhang, Shao-En Ong, David Baker, Dustin J. Maly
Single-cell sensor analyses reveal signaling programs enabling Ras-G12C drug resistance Journal Article
In: Nature Chemical Biology, 2024.
@article{Zhang2024b,
title = {Single-cell sensor analyses reveal signaling programs enabling Ras-G12C drug resistance},
author = {Jason Z. Zhang and Shao-En Ong and David Baker and Dustin J. Maly},
url = {https://www.nature.com/articles/s41589-024-01684-4, Nat Chem Biol [Open Access]},
doi = {10.1038/s41589-024-01684-4},
year = {2024},
date = {2024-08-05},
urldate = {2024-08-05},
journal = {Nature Chemical Biology},
publisher = {Springer Science and Business Media LLC},
abstract = {Clinical resistance to rat sarcoma virus (Ras)-G12C inhibitors is a challenge. A subpopulation of cancer cells has been shown to undergo genomic and transcriptional alterations to facilitate drug resistance but the immediate adaptive effects on Ras signaling in response to these drugs at the single-cell level is not well understood. Here, we used Ras biosensors to profile the activity and signaling environment of endogenous Ras at the single-cell level. We found that a subpopulation of KRas-G12C cells treated with Ras-G12C-guanosine-diphosphate inhibitors underwent adaptive signaling and metabolic changes driven by wild-type Ras at the Golgi and mutant KRas at the mitochondria, respectively. Our Ras biosensors identified major vault protein as a mediator of Ras activation through its scaffolding of Ras signaling pathway components and metabolite channels. Overall, methods including ours that facilitate direct analysis on the single-cell level can report the adaptations that subpopulations of cells adopt in response to cancer therapies, thus providing insight into drug resistance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Justin A. Peruzzi, Taylor F. Gunnels, Hailey I. Edelstein, Peilong Lu, David Baker, Joshua N. Leonard, Neha P. Kamat
Enhancing extracellular vesicle cargo loading and functional delivery by engineering protein-lipid interactions Journal Article
In: Nature Communications, 2024.
@article{Peruzzi2024b,
title = {Enhancing extracellular vesicle cargo loading and functional delivery by engineering protein-lipid interactions},
author = {Justin A. Peruzzi and Taylor F. Gunnels and Hailey I. Edelstein and Peilong Lu and David Baker and Joshua N. Leonard and Neha P. Kamat},
url = {https://www.nature.com/articles/s41467-024-49678-z [Nature Communications, Open Access]},
doi = {10.1038/s41467-024-49678-z},
year = {2024},
date = {2024-07-04},
urldate = {2024-12-00},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
abstract = {Naturally generated lipid nanoparticles termed extracellular vesicles (EVs) hold significant promise as engineerable therapeutic delivery vehicles. However, active loading of protein cargo into EVs in a manner that is useful for delivery remains a challenge. Here, we demonstrate that by rationally designing proteins to traffic to the plasma membrane and associate with lipid rafts, we can enhance loading of protein cargo into EVs for a set of structurally diverse transmembrane and peripheral membrane proteins. We then demonstrate the capacity of select lipid tags to mediate increased EV loading and functional delivery of an engineered transcription factor to modulate gene expression in target cells. We envision that this technology could be leveraged to develop new EV-based therapeutics that deliver a wide array of macromolecular cargo.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Casper A. Goverde, Martin Pacesa, Nicolas Goldbach, Lars J. Dornfeld, Petra E. M. Balbi, Sandrine Georgeon, Stéphane Rosset, Srajan Kapoor, Jagrity Choudhury, Justas Dauparas, Christian Schellhaas, Simon Kozlov, David Baker, Sergey Ovchinnikov, Alex J. Vecchio, Bruno E. Correia
Computational design of soluble and functional membrane protein analogues Journal Article
In: Nature, 2024, ISSN: 1476-4687.
@article{Goverde2024,
title = {Computational design of soluble and functional membrane protein analogues},
author = {Casper A. Goverde and Martin Pacesa and Nicolas Goldbach and Lars J. Dornfeld and Petra E. M. Balbi and Sandrine Georgeon and Stéphane Rosset and Srajan Kapoor and Jagrity Choudhury and Justas Dauparas and Christian Schellhaas and Simon Kozlov and David Baker and Sergey Ovchinnikov and Alex J. Vecchio and Bruno E. Correia},
url = {https://www.nature.com/articles/s41586-024-07601-y, Nature [Open Access]
},
doi = {10.1038/s41586-024-07601-y},
issn = {1476-4687},
year = {2024},
date = {2024-06-19},
urldate = {2024-06-19},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
abstract = {De novo design of complex protein folds using solely computational means remains a substantial challenge. Here we use a robust deep learning pipeline to design complex folds and soluble analogues of integral membrane proteins. Unique membrane topologies, such as those from G-protein-coupled receptors, are not found in the soluble proteome, and we demonstrate that their structural features can be recapitulated in solution. Biophysical analyses demonstrate the high thermal stability of the designs, and experimental structures show remarkable design accuracy. The soluble analogues were functionalized with native structural motifs, as a proof of concept for bringing membrane protein functions to the soluble proteome, potentially enabling new approaches in drug discovery. In summary, we have designed complex protein topologies and enriched them with functionalities from membrane proteins, with high experimental success rates, leading to a de facto expansion of the functional soluble fold space.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sarah J. Wait, Marc Expòsit, Sophia Lin, Michael Rappleye, Justin Daho Lee, Samuel A. Colby, Lily Torp, Anthony Asencio, Annette Smith, Michael Regnier, Farid Moussavi-Harami, David Baker, Christina K. Kim, Andre Berndt
Machine learning-guided engineering of genetically encoded fluorescent calcium indicators Journal Article
In: Nature Computational Science, 2024.
@article{Wait2024,
title = {Machine learning-guided engineering of genetically encoded fluorescent calcium indicators},
author = {Sarah J. Wait and Marc Expòsit and Sophia Lin and Michael Rappleye and Justin Daho Lee and Samuel A. Colby and Lily Torp and Anthony Asencio and Annette Smith and Michael Regnier and Farid Moussavi-Harami and David Baker and Christina K. Kim and Andre Berndt},
url = {https://www.nature.com/articles/s43588-024-00611-w, Nat Comp Sci
https://www.bakerlab.org/wp-content/uploads/2024/03/s43588-024-00611-w.pdf, PDF},
doi = {10.1038/s43588-024-00611-w},
year = {2024},
date = {2024-03-21},
urldate = {2024-03-00},
journal = {Nature Computational Science},
publisher = {Springer Science and Business Media LLC},
abstract = {Here we used machine learning to engineer genetically encoded fluorescent indicators, protein-based sensors critical for real-time monitoring of biological activity. We used machine learning to predict the outcomes of sensor mutagenesis by analyzing established libraries that link sensor sequences to functions. Using the GCaMP calcium indicator as a scaffold, we developed an ensemble of three regression models trained on experimentally derived GCaMP mutation libraries. The trained ensemble performed an in silico functional screen on 1,423 novel, uncharacterized GCaMP variants. As a result, we identified the ensemble-derived GCaMP (eGCaMP) variants, eGCaMP and eGCaMP+, which achieve both faster kinetics and larger ∆F/F0 responses upon stimulation than previously published fast variants. Furthermore, we identified a combinatorial mutation with extraordinary dynamic range, eGCaMP2+, which outperforms the tested sixth-, seventh- and eighth-generation GCaMPs. These findings demonstrate the value of machine learning as a tool to facilitate the efficient engineering of proteins for desired biophysical characteristics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
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}
}
Fatima A Davila-Hernandez, Biao Jin, Harley Pyles, Shuai Zhang, Zheming Wang, Timothy F Huddy, Asim K Bera, Alex Kang, Chun-Long Chen, James J De Yoreo, David Baker
Directing polymorph specific calcium carbonate formation with de novo protein templates Journal Article
In: Nature Communications, vol. 14, no. 1, pp. 8191, 2023, ISSN: 2041-1723.
@article{Davila-Hernandez2023,
title = {Directing polymorph specific calcium carbonate formation with de novo protein templates},
author = {Fatima A Davila-Hernandez and Biao Jin and Harley Pyles and Shuai Zhang and Zheming Wang and Timothy F Huddy and Asim K Bera and Alex Kang and Chun-Long Chen and James J De Yoreo and David Baker},
url = {https://www.nature.com/articles/s41467-023-43608-1, Nature Communications (Open Access)},
doi = {10.1038/s41467-023-43608-1},
issn = {2041-1723},
year = {2023},
date = {2023-12-01},
urldate = {2023-12-01},
journal = {Nature Communications},
volume = {14},
number = {1},
pages = {8191},
abstract = {Biomolecules modulate inorganic crystallization to generate hierarchically structured biominerals, but the atomic structure of the organic-inorganic interfaces that regulate mineralization remain largely unknown. We hypothesized that heterogeneous nucleation of calcium carbonate could be achieved by a structured flat molecular template that pre-organizes calcium ions on its surface. To test this hypothesis, we design helical repeat proteins (DHRs) displaying regularly spaced carboxylate arrays on their surfaces and find that both protein monomers and protein-Ca supramolecular assemblies directly nucleate nano-calcite with non-natural {110} or {202} faces while vaterite, which forms first in the absence of the proteins, is bypassed. These protein-stabilized nanocrystals then assemble by oriented attachment into calcite mesocrystals. We find further that nanocrystal size and polymorph can be tuned by varying the length and surface chemistry of the designed protein templates. Thus, bio-mineralization can be programmed using de novo protein design, providing a route to next-generation hybrid materials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Edin Muratspahić, Kristine Deibler, Jianming Han, Nataša Tomašević, Kirtikumar B Jadhav, Aina-Leonor Olivé-Marti, Nadine Hochrainer, Roland Hellinger, Johannes Koehbach, Jonathan F Fay, Mohammad Homaidur Rahman, Lamees Hegazy, Timothy W Craven, Balazs R Varga, Gaurav Bhardwaj, Kevin Appourchaux, Susruta Majumdar, Markus Muttenthaler, Parisa Hosseinzadeh, David J Craik, Mariana Spetea, Tao Che, David Baker, Christian W Gruber
Design and structural validation of peptide-drug conjugate ligands of the kappa-opioid receptor Journal Article
In: Nature Communications, 2023.
@article{Muratspahić2023,
title = {Design and structural validation of peptide-drug conjugate ligands of the kappa-opioid receptor},
author = {Edin Muratspahić and Kristine Deibler and Jianming Han and Nataša Tomašević and Kirtikumar B Jadhav and Aina-Leonor Olivé-Marti and Nadine Hochrainer and Roland Hellinger and Johannes Koehbach and Jonathan F Fay and Mohammad Homaidur Rahman and Lamees Hegazy and Timothy W Craven and Balazs R Varga and Gaurav Bhardwaj and Kevin Appourchaux and Susruta Majumdar and Markus Muttenthaler and Parisa Hosseinzadeh and David J Craik and Mariana Spetea and Tao Che and David Baker and Christian W Gruber},
url = {https://www.nature.com/articles/s41467-023-43718-w, Nature Communications [Open Access]},
doi = {10.1038/s41467-023-43718-w},
year = {2023},
date = {2023-12-01},
urldate = {2023-12-01},
journal = {Nature Communications},
abstract = {Despite the increasing number of GPCR structures and recent advances in peptide design, the development of efficient technologies allowing rational design of high-affinity peptide ligands for single GPCRs remains an unmet challenge. Here, we develop a computational approach for designing conjugates of lariat-shaped macrocyclized peptides and a small molecule opioid ligand. We demonstrate its feasibility by discovering chemical scaffolds for the kappa-opioid receptor (KOR) with desired pharmacological activities. The designed De Novo Cyclic Peptide (DNCP)-β-naloxamine (NalA) exhibit in vitro potent mixed KOR agonism/mu-opioid receptor (MOR) antagonism, nanomolar binding affinity, selectivity, and efficacy bias at KOR. Proof-of-concept in vivo efficacy studies demonstrate that DNCP-β-NalA(1) induces a potent KOR-mediated antinociception in male mice. The high-resolution cryo-EM structure (2.6 Å) of the DNCP-β-NalA-KOR-Gi1 complex and molecular dynamics simulations are harnessed to validate the computational design model. This reveals a network of residues in ECL2/3 and TM6/7 controlling the intrinsic efficacy of KOR. In general, our computational de novo platform overcomes extensive lead optimization encountered in ultra-large library docking and virtual small molecule screening campaigns and offers innovation for GPCR ligand discovery. This may drive the development of next-generation therapeutics for medical applications such as pain conditions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Minkyung Baek, Ryan McHugh, Ivan Anishchenko, Hanlun Jiang, David Baker, Frank DiMaio
Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA Journal Article
In: Nature Methods, 2023.
@article{Baek2023,
title = {Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA},
author = {Minkyung Baek and Ryan McHugh and Ivan Anishchenko and Hanlun Jiang and David Baker and Frank DiMaio},
url = {https://www.nature.com/articles/s41592-023-02086-5, Nature Methods [Open Access]},
doi = {10.1038/s41592-023-02086-5},
year = {2023},
date = {2023-11-23},
urldate = {2023-11-23},
journal = {Nature Methods},
publisher = {Springer Science and Business Media LLC},
abstract = {Protein–RNA and protein–DNA complexes play critical roles in biology. Despite considerable recent advances in protein structure prediction, the prediction of the structures of protein–nucleic acid complexes without homology to known complexes is a largely unsolved problem. Here we extend the RoseTTAFold machine learning protein-structure-prediction approach to additionally predict nucleic acid and protein–nucleic acid complexes. We develop a single trained network, RoseTTAFoldNA, that rapidly produces three-dimensional structure models with confidence estimates for protein–DNA and protein–RNA complexes. Here we show that confident predictions have considerably higher accuracy than current state-of-the-art methods. RoseTTAFoldNA should be broadly useful for modeling the structure of naturally occurring protein–nucleic acid complexes, and for designing sequence-specific RNA and DNA-binding proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Zhe Li, Shunzhi Wang, Una Nattermann, Asim K Bera, Andrew J Borst, Muammer Y Yaman, Matthew J Bick, Erin C Yang, William Sheffler, Byeongdu Lee, Soenke Seifert, Greg L Hura, Hannah Nguyen, Alex Kang, Radhika Dalal, Joshua M Lubner, Yang Hsia, Hugh Haddox, Alexis Courbet, Quinton Dowling, Marcos Miranda, Andrew Favor, Ali Etemadi, Natasha I Edman, Wei Yang, Connor Weidle, Banumathi Sankaran, Babak Negahdari, Michael B Ross, David S Ginger, David Baker
Accurate computational design of three-dimensional protein crystals Journal Article
In: Nature Materials, 2023.
@article{Li2023,
title = {Accurate computational design of three-dimensional protein crystals},
author = {Zhe Li and Shunzhi Wang and Una Nattermann and Asim K Bera and Andrew J Borst and Muammer Y Yaman and Matthew J Bick and Erin C Yang and William Sheffler and Byeongdu Lee and Soenke Seifert and Greg L Hura and Hannah Nguyen and Alex Kang and Radhika Dalal and Joshua M Lubner and Yang Hsia and Hugh Haddox and Alexis Courbet and Quinton Dowling and Marcos Miranda and Andrew Favor and Ali Etemadi and Natasha I Edman and Wei Yang and Connor Weidle and Banumathi Sankaran and Babak Negahdari and Michael B Ross and David S Ginger and David Baker},
url = {https://rdcu.be/doHL5, Nature Methods},
doi = {10.1038/s41563-023-01683-1},
year = {2023},
date = {2023-10-16},
urldate = {2023-10-01},
journal = {Nature Materials},
abstract = {Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain–side-chain interactions across protein–protein interfaces is an outstanding challenge. Here we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein–protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Anindya Roy, Lei Shi, Ashley Chang, Xianchi Dong, Andres Fernandez, John C. Kraft, Jing Li, Viet Q. Le, Rebecca Viazzo Winegar, Gerald Maxwell Cherf, Dean Slocum, P. Daniel Poulson, Garrett E. Casper, Mary L. Vallecillo-Zúniga, Jonard Corpuz Valdoz, Marcos C. Miranda, Hua Bai, Yakov Kipnis, Audrey Olshefsky, Tanu Priya, Lauren Carter, Rashmi Ravichandran, Cameron M. Chow, Max R. Johnson, Suna Cheng, McKaela Smith, Catherine Overed-Sayer, Donna K. Finch, David Lowe, Asim K. Bera, Gustavo Matute-Bello, Timothy P. Birkland, Frank DiMaio, Ganesh Raghu, Jennifer R. Cochran, Lance J. Stewart, Melody G. Campbell, Pam M. Van Ry, Timothy Springer, David Baker
De novo design of highly selective miniprotein inhibitors of integrins αvβ6 and αvβ8 Journal Article
In: Nature Communications, 2023.
@article{Roy2023,
title = {De novo design of highly selective miniprotein inhibitors of integrins αvβ6 and αvβ8},
author = {Anindya Roy and Lei Shi and Ashley Chang and Xianchi Dong and Andres Fernandez and John C. Kraft and Jing Li and Viet Q. Le and Rebecca Viazzo Winegar and Gerald Maxwell Cherf and Dean Slocum and P. Daniel Poulson and Garrett E. Casper and Mary L. Vallecillo-Zúniga and Jonard Corpuz Valdoz and Marcos C. Miranda and Hua Bai and Yakov Kipnis and Audrey Olshefsky and Tanu Priya and Lauren Carter and Rashmi Ravichandran and Cameron M. Chow and Max R. Johnson and Suna Cheng and McKaela Smith and Catherine Overed-Sayer and Donna K. Finch and David Lowe and Asim K. Bera and Gustavo Matute-Bello and Timothy P. Birkland and Frank DiMaio and Ganesh Raghu and Jennifer R. Cochran and Lance J. Stewart and Melody G. Campbell and Pam M. Van Ry and Timothy Springer and David Baker},
url = {https://www.nature.com/articles/s41467-023-41272-z, Nature Communications [Open Access]},
doi = {10.1038/s41467-023-41272-z},
year = {2023},
date = {2023-09-13},
urldate = {2023-12-00},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
abstract = {The RGD (Arg-Gly-Asp)-binding integrins αvβ6 and αvβ8 are clinically validated cancer and fibrosis targets of considerable therapeutic importance. Compounds that can discriminate between homologous αvβ6 and αvβ8 and other RGD integrins, stabilize specific conformational states, and have high thermal stability could have considerable therapeutic utility. Existing small molecule and antibody inhibitors do not have all these properties, and hence new approaches are needed. Here we describe a generalized method for computationally designing RGD-containing miniproteins selective for a single RGD integrin heterodimer and conformational state. We design hyperstable, selective αvβ6 and αvβ8 inhibitors that bind with picomolar affinity. CryoEM structures of the designed inhibitor-integrin complexes are very close to the computational design models, and show that the inhibitors stabilize specific conformational states of the αvβ6 and the αvβ8 integrins. In a lung fibrosis mouse model, the αvβ6 inhibitor potently reduced fibrotic burden and improved overall lung mechanics, demonstrating the therapeutic potential of de novo designed integrin binding proteins with high selectivity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sanaa Mansoor, Minkyung Baek, David Juergens, Joseph L. Watson, David Baker
Zero‐shot Mutation Effect Prediction on Protein Stability and Function using RoseTTAFold Journal Article
In: Protein Science, 2023.
@article{Mansoor2023,
title = {Zero‐shot Mutation Effect Prediction on Protein Stability and Function using RoseTTAFold},
author = {Sanaa Mansoor and Minkyung Baek and David Juergens and Joseph L. Watson and David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pro.4780, Protein Science
https://www.bakerlab.org/wp-content/uploads/2023/09/Protein-Science-2023-Mansoor.pdf, PDF},
doi = {10.1002/pro.4780},
year = {2023},
date = {2023-09-11},
urldate = {2023-09-11},
journal = {Protein Science},
publisher = {Wiley},
abstract = {Predicting the effects of mutations on protein function and stability is an outstanding challenge. Here, we assess the performance of a variant of RoseTTAFold jointly trained for sequence and structure recovery, RFjoint, for mutation effect prediction. Without any further training, we achieve comparable accuracy in predicting mutation effects for a diverse set of protein families using RFjoint to both another zero‐shot model (MSA Transformer) and a model which requires specific training on a particular protein family for mutation effect prediction (DeepSequence). Thus, although the architecture of RFjoint was developed to address the protein design problem of scaffolding functional motifs, RFjoint acquired an understanding of the mutational landscapes of proteins during model training that is equivalent to that of recently developed large protein language models. The ability to simultaneously reason over protein structure and sequence could enable even more precise mutation effect predictions following supervised training on the task. These results suggest that RFjoint has a quite broad understanding of protein sequence‐structure landscapes, and can be viewed as a joint model for protein sequence and structure which could be broadly useful for protein modeling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Neville P. Bethel, Andrew J. Borst, Fabio Parmeggiani, Matthew J. Bick, TJ Brunette, Hannah Nguyen, Alex Kang, Asim K. Bera, Lauren Carter, Marcos C. Miranda, Ryan D. Kibler, Mila Lamb, Xinting Li, Banumathi Sankaran, David Baker
Precisely patterned nanofibres made from extendable protein multiplexes Journal Article
In: Nature Chemistry, 2023.
@article{Bethel2023,
title = {Precisely patterned nanofibres made from extendable protein multiplexes},
author = {Neville P. Bethel and Andrew J. Borst and Fabio Parmeggiani and Matthew J. Bick and TJ Brunette and Hannah Nguyen and Alex Kang and Asim K. Bera and Lauren Carter and Marcos C. Miranda and Ryan D. Kibler and Mila Lamb and Xinting Li and Banumathi Sankaran and David Baker},
url = {https://rdcu.be/dloEi, Nature Chemistry [Open Access]},
doi = {10.1038/s41557-023-01314-x},
year = {2023},
date = {2023-09-04},
urldate = {2023-09-04},
journal = {Nature Chemistry},
publisher = {Springer Science and Business Media LLC},
abstract = {Molecular systems with coincident cyclic and superhelical symmetry axes have considerable advantages for materials design as they can be readily lengthened or shortened by changing the length of the constituent monomers. Among proteins, alpha-helical coiled coils have such symmetric, extendable architectures, but are limited by the relatively fixed geometry and flexibility of the helical protomers. Here we describe a systematic approach to generating modular and rigid repeat protein oligomers with coincident C2 to C8 and superhelical symmetry axes that can be readily extended by repeat propagation. From these building blocks, we demonstrate that a wide range of unbounded fibres can be systematically designed by introducing hydrophilic surface patches that force staggering of the monomers; the geometry of such fibres can be precisely tuned by varying the number of repeat units in the monomer and the placement of the hydrophilic patches.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Nicolas Goldbach, Issa Benna, Basile I. M. Wicky, Jacob T. Croft, Lauren Carter, Asim K. Bera, Hannah Nguyen, Alex Kang, Banumathi Sankaran, Erin C. Yang, Kelly K. Lee, David Baker
De novo design of monomeric helical bundles for pH-controlled membrane lysis Journal Article
In: Protein Science, 2023.
@article{Goldbach2023,
title = {De novo design of monomeric helical bundles for pH-controlled membrane lysis},
author = {Nicolas Goldbach and Issa Benna and Basile I. M. Wicky and Jacob T. Croft and Lauren Carter and Asim K. Bera and Hannah Nguyen and Alex Kang and Banumathi Sankaran and Erin C. Yang and Kelly K. Lee and David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pro.4769, Protein Science
https://www.bakerlab.org/wp-content/uploads/2023/08/Protein-Science-2023-Goldbach.pdf, PDF},
doi = {https://doi.org/10.1002/pro.4769},
year = {2023},
date = {2023-08-26},
urldate = {2023-08-26},
journal = {Protein Science},
abstract = {Targeted intracellular delivery via receptor-mediated endocytosis requires the delivered cargo to escape the endosome to prevent lysosomal degradation. This can in principle be achieved by membrane lysis tightly restricted to endosomal membranes upon internalization to avoid general membrane insertion and lysis. Here we describe the design of small monomeric proteins with buried histidine containing pH-responsive hydrogen bond networks and membrane permeating amphipathic helices. Of 30 designs that were experimentally tested, all expressed in E. coli, 13 were monomeric with the expected secondary structure, and 4 designs disrupted artificial liposomes in a pH-dependent manner. Mutational analysis showed that the buried histidine hydrogen bond networks mediate pH-responsiveness and control lysis of model membranes within a very narrow range of pH (6.0 - 5.5) with almost no lysis occurring at neutral pH. These tightly controlled lytic monomers could help mediate endosomal escape in designed targeted delivery platforms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Florian Praetorius, Philip J. Y. Leung, Maxx H. Tessmer, Adam Broerman, Cullen Demakis, Acacia F. Dishman, Arvind Pillai, Abbas Idris, David Juergens, Justas Dauparas, Xinting Li, Paul M. Levine, Mila Lamb, Ryanne K. Ballard, Stacey R. Gerben, Hannah Nguyen, Alex Kang, Banumathi Sankaran, Asim K. Bera, Brian F. Volkman, Jeff Nivala, Stefan Stoll, David Baker
Design of stimulus-responsive two-state hinge proteins Journal Article
In: Science, 2023.
@article{Praetorius2023,
title = {Design of stimulus-responsive two-state hinge proteins},
author = {Florian Praetorius and Philip J. Y. Leung and Maxx H. Tessmer and Adam Broerman and Cullen Demakis and Acacia F. Dishman and Arvind Pillai and Abbas Idris and David Juergens and Justas Dauparas and Xinting Li and Paul M. Levine and Mila Lamb and Ryanne K. Ballard and Stacey R. Gerben and Hannah Nguyen and Alex Kang and Banumathi Sankaran and Asim K. Bera and Brian F. Volkman and Jeff Nivala and Stefan Stoll and David Baker},
url = {https://www.science.org/stoken/author-tokens/ST-1381/full, Science (Free Access)},
doi = {10.1126/science.adg7731},
year = {2023},
date = {2023-08-17},
urldate = {2023-08-17},
journal = {Science},
abstract = {In nature, proteins that switch between two conformations in response to environmental stimuli structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Designing proteins with two distinct but fully structured conformations is a challenge for protein design as it requires sculpting an energy landscape with two distinct minima. Here we describe the design of “hinge” proteins that populate one designed state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, double electron-electron resonance spectroscopy, and binding measurements demonstrate that despite the significant structural differences the two states are designed with atomic level accuracy and that the conformational and binding equilibria are closely coupled. Natural proteins often adopt multiple conformational states, thereby changing their activity or binding partners in response to another protein, small molecule, or other stimulus. It has been difficult to engineer such conformational switching between two folded states in human-designed proteins. Praetorius et al. developed a hinge-like protein by simultaneously considering both desired states in the design process. The successful designs exhibited a large shift in conformation upon binding to a target peptide helix, which could be tailored for specificity. The authors characterized the protein structures, binding kinetics, and conformational equilibrium of the designs. This work provides the groundwork for generating protein switches that respond to biological triggers and can produce conformational changes that modulate protein assemblies. —Michael A. Funk A two-state design of protein switches that couple effector binding to a conformational change is discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Kalvet, Indrek and Ortmayer, Mary and Zhao, Jingming and Crawshaw, Rebecca and Ennist, Nathan M. and Levy, Colin and Roy, Anindya and Green, Anthony P. and Baker, David
Design of Heme Enzymes with a Tunable Substrate Binding Pocket Adjacent to an Open Metal Coordination Site Journal Article
In: J. Am. Chem. Soc., 2023.
@article{nokey,
title = {Design of Heme Enzymes with a Tunable Substrate Binding Pocket Adjacent to an Open Metal Coordination Site},
author = {Kalvet, Indrek
and Ortmayer, Mary
and Zhao, Jingming
and Crawshaw, Rebecca
and Ennist, Nathan M.
and Levy, Colin
and Roy, Anindya
and Green, Anthony P.
and Baker, David},
url = {https://pubs.acs.org/doi/full/10.1021/jacs.3c02742, ACS (Open Access)},
doi = {10.1021/jacs.3c02742},
year = {2023},
date = {2023-07-05},
urldate = {2023-07-05},
journal = {J. Am. Chem. Soc.},
abstract = {The catalytic versatility of pentacoordinated iron is highlighted by the broad range of natural and engineered activities of heme enzymes such as cytochrome P450s, which position a porphyrin cofactor coordinating a central iron atom below an open substrate binding pocket. This catalytic prowess has inspired efforts to design de novo helical bundle scaffolds that bind porphyrin cofactors. However, such designs lack the large open substrate binding pocket of P450s, and hence, the range of chemical transformations accessible is limited. Here, with the goal of combining the advantages of the P450 catalytic site geometry with the almost unlimited customizability of de novo protein design, we design a high-affinity heme-binding protein, dnHEM1, with an axial histidine ligand, a vacant coordination site for generating reactive intermediates, and a tunable distal pocket for substrate binding. A 1.6 Å X-ray crystal structure of dnHEM1 reveals excellent agreement to the design model with key features programmed as intended. The incorporation of distal pocket substitutions converted dnHEM1 into a proficient peroxidase with a stable neutral ferryl intermediate. In parallel, dnHEM1 was redesigned to generate enantiocomplementary carbene transferases for styrene cyclopropanation (up to 93% isolated yield, 5000 turnovers, 97:3 e.r.) by reconfiguring the distal pocket to accommodate calculated transition state models. Our approach now enables the custom design of enzymes containing cofactors adjacent to binding pockets with an almost unlimited variety of shapes and functionalities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Lutz, Isaac D. and Wang, Shunzhi and Norn, Christoffer and Courbet, Alexis and Borst, Andrew J. and Zhao, Yan Ting and Dosey, Annie and Cao, Longxing and Xu, Jinwei and Leaf, Elizabeth M. and Treichel, Catherine and Litvicov, Patrisia and Li, Zhe and Goodson, Alexander D. and Rivera-Sánchez, Paula and Bratovianu, Ana-Maria and Baek, Minkyung and King, Neil P. and Ruohola-Baker, Hannele and Baker, David
Top-down design of protein architectures with reinforcement learning Journal Article
In: Science, 2023.
@article{Lutz2023,
title = {Top-down design of protein architectures with reinforcement learning},
author = {Lutz, Isaac D.
and Wang, Shunzhi
and Norn, Christoffer
and Courbet, Alexis
and Borst, Andrew J.
and Zhao, Yan Ting
and Dosey, Annie
and Cao, Longxing
and Xu, Jinwei
and Leaf, Elizabeth M.
and Treichel, Catherine
and Litvicov, Patrisia
and Li, Zhe
and Goodson, Alexander D.
and Rivera-Sánchez, Paula
and Bratovianu, Ana-Maria
and Baek, Minkyung
and King, Neil P.
and Ruohola-Baker, Hannele
and Baker, David},
url = {https://www.science.org/doi/10.1126/science.adf6591, Science
https://www.ipd.uw.edu/wp-content/uploads/2023/04/science.adf6591.pdf, PDF},
doi = {10.1126/science.adf6591},
year = {2023},
date = {2023-04-20},
journal = {Science},
abstract = {As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a “top-down” reinforcement learning–based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo–electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Wu, Kejia and Bai, Hua and Chang, Ya-Ting and Redler, Rachel and McNally, Kerrie E. and Sheffler, William and Brunette, T. J. and Hicks, Derrick R. and Morgan, Tomos E. and Stevens, Tim J. and Broerman, Adam and Goreshnik, Inna and DeWitt, Michelle and Chow, Cameron M. and Shen, Yihang and Stewart, Lance and Derivery, Emmanuel and Silva, Daniel Adriano and Bhabha, Gira and Ekiert, Damian C. and Baker, David
De novo design of modular peptide-binding proteins by superhelical matching Journal Article
In: Nature, 2023.
@article{Wu2023,
title = {De novo design of modular peptide-binding proteins by superhelical matching},
author = {Wu, Kejia
and Bai, Hua
and Chang, Ya-Ting
and Redler, Rachel
and McNally, Kerrie E.
and Sheffler, William
and Brunette, T. J.
and Hicks, Derrick R.
and Morgan, Tomos E.
and Stevens, Tim J.
and Broerman, Adam
and Goreshnik, Inna
and DeWitt, Michelle
and Chow, Cameron M.
and Shen, Yihang
and Stewart, Lance
and Derivery, Emmanuel
and Silva, Daniel Adriano
and Bhabha, Gira
and Ekiert, Damian C.
and Baker, David},
url = {https://www.nature.com/articles/s41586-023-05909-9, Nature (Open-access)},
doi = {10.1038/s41586-023-05909-9},
year = {2023},
date = {2023-04-05},
urldate = {2023-04-05},
journal = {Nature},
abstract = {General approaches for designing sequence-specific peptide-binding proteins would have wide utility in proteomics and synthetic biology. However, designing peptide-binding proteins is challenging, as most peptides do not have defined structures in isolation, and hydrogen bonds must be made to the buried polar groups in the peptide backbone1–3. Here, inspired by natural and re-engineered protein–peptide systems4–11, we set out to design proteins made out of repeating units that bind peptides with repeating sequences, with a one-to-one correspondence between the repeat units of the protein and those of the peptide. We use geometric hashing to identify protein backbones and peptide-docking arrangements that are compatible with bidentate hydrogen bonds between the side chains of the protein and the peptide backbone12. The remainder of the protein sequence is then optimized for folding and peptide binding. We design repeat proteins to bind to six different tripeptide-repeat sequences in polyproline II conformations. The proteins are hyperstable and bind to four to six tandem repeats of their tripeptide targets with nanomolar to picomolar affinities in vitro and in living cells. Crystal structures reveal repeating interactions between protein and peptide interactions as designed, including ladders of hydrogen bonds from protein side chains to peptide backbones. By redesigning the binding interfaces of individual repeat units, specificity can be achieved for non-repeating peptide sequences and for disordered regions of native proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Yeh, Andy Hsien-Wei Norn, Christoffer Kipnis, Yakov Tischer, Doug Pellock, Samuel J. Evans, Declan Ma, Pengchen Lee, Gyu Rie Zhang, Jason Z. Anishchenko, Ivan Coventry, Brian Cao, Longxing Dauparas, Justas Halabiya, Samer DeWitt, Michelle Carter, Lauren Houk, K. N. Baker, David
De novo design of luciferases using deep learning Journal Article
In: Nature, 2023.
@article{Yeh2023,
title = {De novo design of luciferases using deep learning},
author = {Yeh, Andy Hsien-Wei
Norn, Christoffer
Kipnis, Yakov
Tischer, Doug
Pellock, Samuel J.
Evans, Declan
Ma, Pengchen
Lee, Gyu Rie
Zhang, Jason Z.
Anishchenko, Ivan
Coventry, Brian
Cao, Longxing
Dauparas, Justas
Halabiya, Samer
DeWitt, Michelle
Carter, Lauren
Houk, K. N.
Baker, David},
url = {https://www.nature.com/articles/s41586-023-05696-3, Nature (Open Access)},
doi = {10.1038/s41586-023-05696-3},
year = {2023},
date = {2023-02-22},
journal = {Nature},
abstract = {De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds1,2, but has been limited by a lack of suitable protein structures and the complexity of native protein sequence–structure relationships. Here we describe a deep-learning-based ‘family-wide hallucination’ approach that generates large numbers of idealized protein structures containing diverse pocket shapes and designed sequences that encode them. We use these scaffolds to design artificial luciferases that selectively catalyse the oxidative chemiluminescence of the synthetic luciferin substrates diphenylterazine3 and 2-deoxycoelenterazine. The designed active sites position an arginine guanidinium group adjacent to an anion that develops during the reaction in a binding pocket with high shape complementarity. For both luciferin substrates, we obtain designed luciferases with high selectivity; the most active of these is a small (13.9 kDa) and thermostable (with a melting temperature higher than 95 °C) enzyme that has a catalytic efficiency on diphenylterazine (kcat/Km = 106 M−1 s−1) comparable to that of native luciferases, but a much higher substrate specificity. The creation of highly active and specific biocatalysts from scratch with broad applications in biomedicine is a key milestone for computational enzyme design, and our approach should enable generation of a wide range of luciferases and other enzymes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Amir Motmaen, Justas Dauparas, Minkyung Baek, Mohamad H. Abedi, David Baker, Philip Bradley
Peptide-binding specificity prediction using fine-tuned protein structure prediction networks Journal Article
In: Proceedings of the National Academy of Sciences, 2023.
@article{nokey,
title = {Peptide-binding specificity prediction using fine-tuned protein structure prediction networks},
author = {Amir Motmaen, Justas Dauparas, Minkyung Baek, Mohamad H. Abedi, David Baker, Philip Bradley},
url = {https://www.pnas.org/doi/10.1073/pnas.2216697120, PNAS (Open Access)},
doi = {10.1073/pnas.2216697120},
year = {2023},
date = {2023-02-21},
urldate = {2023-02-21},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Peptide-binding proteins play key roles in biology, and predicting their binding specificity is a long-standing challenge. While considerable protein structural information is available, the most successful current methods use sequence information alone, in part because it has been a challenge to model the subtle structural changes accompanying sequence substitutions. Protein structure prediction networks such as AlphaFold model sequence-structure relationships very accurately, and we reasoned that if it were possible to specifically train such networks on binding data, more generalizable models could be created. We show that placing a classifier on top of the AlphaFold network and fine-tuning the combined network parameters for both classification and structure prediction accuracy leads to a model with strong generalizable performance on a wide range of Class I and Class II peptide-MHC interactions that approaches the overall performance of the state-of-the-art NetMHCpan sequence-based method. The peptide-MHC optimized model shows excellent performance in distinguishing binding and non-binding peptides to SH3 and PDZ domains. This ability to generalize well beyond the training set far exceeds that of sequence-only models and should be particularly powerful for systems where less experimental data are available.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
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}
}
Hutchinson, Geoffrey B. and Abiona, Olubukola M. and Ziwawo, Cynthia T. and Werner, Anne P. and Ellis, Daniel and Tsybovsky, Yaroslav and Leist, Sarah R. and Palandjian, Charis and West, Ande and Fritch, Ethan J. and Wang, Nianshuang and Wrapp, Daniel and Boyoglu-Barnum, Seyhan and Ueda, George and Baker, David and Kanekiyo, Masaru and McLellan, Jason S. and Baric, Ralph S. and King, Neil P. and Graham, Barney S. and Corbett-Helaire, Kizzmekia S.
Nanoparticle display of prefusion coronavirus spike elicits S1-focused cross-reactive antibody response against diverse coronavirus subgenera Journal Article
In: Nature Communications, 2023.
@article{Hutchinson2023,
title = {Nanoparticle display of prefusion coronavirus spike elicits S1-focused cross-reactive antibody response against diverse coronavirus subgenera},
author = {Hutchinson, Geoffrey B.
and Abiona, Olubukola M.
and Ziwawo, Cynthia T.
and Werner, Anne P.
and Ellis, Daniel
and Tsybovsky, Yaroslav
and Leist, Sarah R.
and Palandjian, Charis
and West, Ande
and Fritch, Ethan J.
and Wang, Nianshuang
and Wrapp, Daniel
and Boyoglu-Barnum, Seyhan
and Ueda, George
and Baker, David
and Kanekiyo, Masaru
and McLellan, Jason S.
and Baric, Ralph S.
and King, Neil P.
and Graham, Barney S.
and Corbett-Helaire, Kizzmekia S.},
url = {https://www.nature.com/articles/s41467-023-41661-4, Nature Communications (Open Access)},
doi = {10.1038/s41467-023-41661-4},
year = {2023},
date = {2023-10-04},
journal = {Nature Communications},
abstract = {Multivalent antigen display is a fast-growing area of interest toward broadly protective vaccines. Current nanoparticle-based vaccine candidates demonstrate the ability to confer antibody-mediated immunity against divergent strains of notably mutable viruses. In coronaviruses, this work is predominantly aimed at targeting conserved epitopes of the receptor binding domain. However, targeting conserved non-RBD epitopes could limit the potential for antigenic escape. To explore new potential targets, we engineered protein nanoparticles displaying coronavirus prefusion-stabilized spike (CoV_S-2P) trimers derived from MERS-CoV, SARS-CoV-1, SARS-CoV-2, hCoV-HKU1, and hCoV-OC43 and assessed their immunogenicity in female mice. Monotypic SARS-1 nanoparticles elicit cross-neutralizing antibodies against MERS-CoV and protect against MERS-CoV challenge. MERS and SARS nanoparticles elicit S1-focused antibodies, revealing a conserved site on the S N-terminal domain. Moreover, mosaic nanoparticles co-displaying distinct CoV_S-2P trimers elicit antibody responses to distant cross-group antigens and protect male and female mice against MERS-CoV challenge. Our findings will inform further efforts toward the development of pan-coronavirus vaccines.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Joseph L. Watson, Lara K. Kruger, Ariel J. Ben-Sasson, Alice Bittleston, Marta N. Shahbazi, Vicente Jose Planelles-Herrero, Joseph E. Chambers, James D. Manton, David Baker,, Emmanuel Derivery
Synthetic Par polarity induces cytoskeleton asymmetry in unpolarized mammalian cells Journal Article
In: Cell, 2023.
@article{Watson2023b,
title = {Synthetic Par polarity induces cytoskeleton asymmetry in unpolarized mammalian cells},
author = {Joseph L. Watson, Lara K. Kruger, Ariel J. Ben-Sasson, Alice Bittleston, Marta N. Shahbazi, Vicente Jose Planelles-Herrero, Joseph E. Chambers, James D. Manton, David Baker, and Emmanuel Derivery},
url = {https://www.cell.com/cell/fulltext/S0092-8674(23)00968-6, Cell [Open Access]},
year = {2023},
date = {2023-09-28},
journal = {Cell},
abstract = {Polarized cells rely on a polarized cytoskeleton to function. Yet, how cortical polarity cues induce cytoskeleton polarization remains elusive. Here, we capitalized on recently established designed 2D protein arrays to ectopically engineer cortical polarity of virtually any protein of interest during mitosis in various cell types. This enables direct manipulation of polarity signaling and the identification of the cortical cues sufficient for cytoskeleton polarization. Using this assay, we dissected the logic of the Par complex pathway, a key regulator of cytoskeleton polarity during asymmetric cell division. We show that cortical clustering of any Par complex subunit is sufficient to trigger complex assembly and that the primary kinetic barrier to complex assembly is the relief of Par6 autoinhibition. Further, we found that inducing cortical Par complex polarity induces two hallmarks of asymmetric cell division in unpolarized mammalian cells: spindle orientation, occurring via Par3, and central spindle asymmetry, depending on aPKC activity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ammar Alghadeer, Sesha Hanson-Drury, Anjali P. Patni, Devon D. Ehnes, Yan Ting Zhao, Zicong Li, Ashish Phal, Thomas Vincent, Yen C. Lim, Diana O’Day, Cailyn H. Spurrell, Aishwarya A. Gogate, Hai Zhang, Arikketh Devi, Yuliang Wang, Lea Starita, Dan Doherty, Ian A. Glass, Jay Shendure, Benjamin S. Freedman, David Baker, Mary C. Regier, Julie Mathieu, Hannele Ruohola-Baker
Single-cell census of human tooth development enables generation of human enamel Journal Article
In: Developmental Cell, 2023.
@article{ALGHADEER2023,
title = {Single-cell census of human tooth development enables generation of human enamel},
author = {Ammar Alghadeer and Sesha Hanson-Drury and Anjali P. Patni and Devon D. Ehnes and Yan Ting Zhao and Zicong Li and Ashish Phal and Thomas Vincent and Yen C. Lim and Diana O’Day and Cailyn H. Spurrell and Aishwarya A. Gogate and Hai Zhang and Arikketh Devi and Yuliang Wang and Lea Starita and Dan Doherty and Ian A. Glass and Jay Shendure and Benjamin S. Freedman and David Baker and Mary C. Regier and Julie Mathieu and Hannele Ruohola-Baker},
url = {https://www.cell.com/developmental-cell/fulltext/S1534-5807(23)00360-X, Developmental Cell
https://www.bakerlab.org/wp-content/uploads/2023/08/PIIS153458072300360X.pdf, PDF},
doi = {https://doi.org/10.1016/j.devcel.2023.07.013},
year = {2023},
date = {2023-08-14},
urldate = {2023-08-14},
journal = {Developmental Cell},
abstract = {Summary
Tooth enamel secreted by ameloblasts (AMs) is the hardest material in the human body, acting as a shield to protect the teeth. However, the enamel is gradually damaged or partially lost in over 90% of adults and cannot be regenerated due to a lack of ameloblasts in erupted teeth. Here, we use single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) to establish a spatiotemporal single-cell census for the developing human tooth and identify regulatory mechanisms controlling the differentiation process of human ameloblasts. We identify key signaling pathways involved between the support cells and ameloblasts during fetal development and recapitulate those findings in human ameloblast in vitro differentiation from induced pluripotent stem cells (iPSCs). We furthermore develop a disease model of amelogenesis imperfecta in a three-dimensional (3D) organoid system and show AM maturation to mineralized structure in vivo. These studies pave the way for future regenerative dentistry.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Tooth enamel secreted by ameloblasts (AMs) is the hardest material in the human body, acting as a shield to protect the teeth. However, the enamel is gradually damaged or partially lost in over 90% of adults and cannot be regenerated due to a lack of ameloblasts in erupted teeth. Here, we use single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) to establish a spatiotemporal single-cell census for the developing human tooth and identify regulatory mechanisms controlling the differentiation process of human ameloblasts. We identify key signaling pathways involved between the support cells and ameloblasts during fetal development and recapitulate those findings in human ameloblast in vitro differentiation from induced pluripotent stem cells (iPSCs). We furthermore develop a disease model of amelogenesis imperfecta in a three-dimensional (3D) organoid system and show AM maturation to mineralized structure in vivo. These studies pave the way for future regenerative dentistry.
Enrico Rennella, Danny D. Sahtoe, David Baker,, Lewis E. Kay
Exploiting conformational dynamics to modulate the function of designed proteins Journal Article
In: Proceedings of the National Academy of Sciences, 2023.
@article{nokey,
title = {Exploiting conformational dynamics to modulate the function of designed proteins},
author = {Enrico Rennella, Danny D. Sahtoe, David Baker, and Lewis E. Kay
},
url = {https://www.pnas.org/doi/10.1073/pnas.2303149120, PNAS},
doi = {10.1073/pnas.2303149120},
year = {2023},
date = {2023-04-24},
journal = {Proceedings of the National Academy of Sciences},
abstract = {With the recent success in calculating protein structures from amino acid sequences using artificial intelligence-based algorithms, an important next step is to decipher how dynamics is encoded by the primary protein sequence so as to better predict function. Such dynamics information is critical for protein design, where strategies could then focus not only on sequences that fold into particular structures that perform a given task, but would also include low-lying excited protein states that could influence the function of the designed protein. Herein, we illustrate the importance of dynamics in modulating the function of C34, a designed α/β protein that captures β-strands of target ligands and is a member of a family of proteins designed to sequester β-strands and β hairpins of aggregation-prone molecules that lead to a variety of pathologies. Using a strategy to “see” regions of apo C34 that are invisible to NMR spectroscopy as a result of pervasive conformational exchange, as well as a mutagenesis approach whereby C34 molecules are stabilized into a single conformer, we determine the structures of the predominant conformations that are sampled by C34 and show that these attenuate the affinity for cognate peptide. Subsequently, the observed motion is exploited to develop an allosterically regulated peptide binder whose binding affinity can be controlled through the addition of a second molecule. Our study emphasizes the unique role that NMR can play in directing the design process and in the construction of new molecules with more complex functionality.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Watson, Paris R. and Gupta, Suchetana and Hosseinzadeh, Parisa and Brown, Benjamin P. and Baker, David and Christianson, David W.
Macrocyclic Octapeptide Binding and Inferences on Protein Substrate Binding to Histone Deacetylase 6 Journal Article
In: ACS Chemical Biology, 2023.
@article{Watson0000,
title = {Macrocyclic Octapeptide Binding and Inferences on Protein Substrate Binding to Histone Deacetylase 6},
author = {Watson, Paris R.
and Gupta, Suchetana
and Hosseinzadeh, Parisa
and Brown, Benjamin P.
and Baker, David
and Christianson, David W.},
url = {https://pubs.acs.org/doi/full/10.1021/acschembio.3c00113, ACS Chem. Biol.
https://www.bakerlab.org/wp-content/uploads/2023/04/acschembio.3c00113.pdf, PDF},
doi = {10.1021/acschembio.3c00113},
year = {2023},
date = {2023-04-07},
urldate = {2023-04-07},
journal = {ACS Chemical Biology},
abstract = {Histone deacetylases (HDACs) are essential for the regulation of myriad biological processes, and their aberrant function is implicated in cancer, neurodegeneration, and other diseases. The cytosolic isozyme HDAC6 is unique among the greater family of deacetylases in that it contains two catalytic domains, CD1 and CD2. HDAC6 CD2 is responsible for tubulin deacetylase and tau deacetylase activities, inhibition of which is a key goal as new therapeutic approaches are explored. Of particular interest as HDAC inhibitors are naturally occurring cyclic tetrapeptides such as Trapoxin A or HC Toxin, or the cyclic depsipeptides Largazole and Romidepsin. Even more intriguing are larger, computationally designed macrocyclic peptide inhibitors. Here, we report the 2.0 Å resolution crystal structure of HDAC6 CD2 complexed with macrocyclic octapeptide 1. Comparison with the previously reported structure of the complex with macrocyclic octapeptide 2 reveals that a potent thiolate–zinc interaction made by the unnatural amino acid (S)-2-amino-7-sulfanylheptanoic acid contributes to nanomolar inhibitory potency for each inhibitor. Apart from this zinc-binding residue, octapeptides adopt strikingly different overall conformations and make few direct hydrogen bonds with the protein. Intermolecular interactions are dominated by water-mediated hydrogen bonds; in essence, water molecules appear to cushion the enzyme–octapeptide interface. In view of the broad specificity observed for protein substrates of HDAC6 CD2, we suggest that the binding of macrocyclic octapeptides may mimic certain features of the binding of macromolecular protein substrates.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Yang, Huilin and Ulge, Umut Y. and Quijano-Rubio, Alfredo and Bernstein, Zachary J. and Maestas, David R. and Chun, Jung-Ho and Wang, Wentao and Lin, Jian-Xin and Jude, Kevin M. and Singh, Srujan and Orcutt-Jahns, Brian T. and Li, Peng and Mou, Jody and Chung, Liam and Kuo, Yun-Huai and Ali, Yasmin H. and Meyer, Aaron S. and Grayson, Warren L. and Heller, Nicola M. and Garcia, K. Christopher and Leonard, Warren J. and Silva, Daniel-Adriano and Elisseeff, Jennifer H. and Baker, David and Spangler, Jamie B.
Design of cell-type-specific hyperstable IL-4 mimetics via modular de novo scaffolds Journal Article
In: Nature Chemical Biology, 2023.
@article{Yang2023,
title = {Design of cell-type-specific hyperstable IL-4 mimetics via modular de novo scaffolds},
author = {Yang, Huilin
and Ulge, Umut Y.
and Quijano-Rubio, Alfredo
and Bernstein, Zachary J.
and Maestas, David R.
and Chun, Jung-Ho
and Wang, Wentao
and Lin, Jian-Xin
and Jude, Kevin M.
and Singh, Srujan
and Orcutt-Jahns, Brian T.
and Li, Peng
and Mou, Jody
and Chung, Liam
and Kuo, Yun-Huai
and Ali, Yasmin H.
and Meyer, Aaron S.
and Grayson, Warren L.
and Heller, Nicola M.
and Garcia, K. Christopher
and Leonard, Warren J.
and Silva, Daniel-Adriano
and Elisseeff, Jennifer H.
and Baker, David
and Spangler, Jamie B.},
url = {https://www.nature.com/articles/s41589-023-01313-6, Nature Chemical Biology
https://www.bakerlab.org/wp-content/uploads/2023/05/s41589-023-01313-6-1.pdf, PDF},
doi = {10.1038/s41589-023-01313-6},
year = {2023},
date = {2023-04-06},
journal = {Nature Chemical Biology},
abstract = {The interleukin-4 (IL-4) cytokine plays a critical role in modulating immune homeostasis. Although there is great interest in harnessing this cytokine as a therapeutic in natural or engineered formats, the clinical potential of native IL-4 is limited by its instability and pleiotropic actions. Here, we design IL-4 cytokine mimetics (denoted Neo-4) based on a de novo engineered IL-2 mimetic scaffold and demonstrate that these cytokines can recapitulate physiological functions of IL-4 in cellular and animal models. In contrast with natural IL-4, Neo-4 is hyperstable and signals exclusively through the type I IL-4 receptor complex, providing previously inaccessible insights into differential IL-4 signaling through type I versus type II receptors. Because of their hyperstability, our computationally designed mimetics can directly incorporate into sophisticated biomaterials that require heat processing, such as three-dimensional-printed scaffolds. Neo-4 should be broadly useful for interrogating IL-4 biology, and the design workflow will inform targeted cytokine therapeutic development.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Wang, Jing Yang (John) and Khmelinskaia, Alena and Sheffler, William and Miranda, Marcos C. and Antanasijevic, Aleksandar and Borst, Andrew J. and Torres, Susana V. and Shu, Chelsea and Hsia, Yang and Nattermann, Una and Ellis, Daniel and Walkey, Carl and Ahlrichs, Maggie and Chan, Sidney and Kang, Alex and Nguyen, Hannah and Sydeman, Claire and Sankaran, Banumathi and Wu, Mengyu and Bera, Asim K. and Carter, Lauren and Fiala, Brooke and Murphy, Michael and Baker, David and Ward, Andrew B. and King, Neil P.
Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains Journal Article
In: Proceedings of the National Academy of Sciences, 2023.
@article{Wang2023,
title = {Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains},
author = {Wang, Jing Yang (John)
and Khmelinskaia, Alena
and Sheffler, William
and Miranda, Marcos C.
and Antanasijevic, Aleksandar
and Borst, Andrew J.
and Torres, Susana V.
and Shu, Chelsea
and Hsia, Yang
and Nattermann, Una
and Ellis, Daniel
and Walkey, Carl
and Ahlrichs, Maggie
and Chan, Sidney
and Kang, Alex
and Nguyen, Hannah
and Sydeman, Claire
and Sankaran, Banumathi
and Wu, Mengyu
and Bera, Asim K.
and Carter, Lauren
and Fiala, Brooke
and Murphy, Michael
and Baker, David
and Ward, Andrew B.
and King, Neil P.},
url = {https://www.pnas.org/doi/10.1073/pnas.2214556120, PNAS (Open Access)},
doi = {10.1073/pnas.2214556120},
year = {2023},
date = {2023-03-08},
urldate = {2023-03-08},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Computationally designed protein nanoparticles have recently emerged as a promising platform for the development of new vaccines and biologics. For many applications, secretion of designed nanoparticles from eukaryotic cells would be advantageous, but in practice, they often secrete poorly. Here we show that designed hydrophobic interfaces that drive nanoparticle assembly are often predicted to form cryptic transmembrane domains, suggesting that interaction with the membrane insertion machinery could limit efficient secretion. We develop a general computational protocol, the Degreaser, to design away cryptic transmembrane domains without sacrificing protein stability. The retroactive application of the Degreaser to previously designed nanoparticle components and nanoparticles considerably improves secretion, and modular integration of the Degreaser into design pipelines results in new nanoparticles that secrete as robustly as naturally occurring protein assemblies. Both the Degreaser protocol and the nanoparticles we describe may be broadly useful in biotechnological applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Lin, Dingchang and Li, Xiuyuan and Moult, Eric and Park, Pojeong and Tang, Benjamin and Shen, Hao and Grimm, Jonathan B. and Falco, Natalie and Jia, Bill Z. and Baker, David and Lavis, Luke D. and Cohen, Adam E.
Time-tagged ticker tapes for intracellular recordings Journal Article
In: Nature Biotechnology, 2023.
@article{Lin2023,
title = {Time-tagged ticker tapes for intracellular recordings},
author = {Lin, Dingchang
and Li, Xiuyuan
and Moult, Eric
and Park, Pojeong
and Tang, Benjamin
and Shen, Hao
and Grimm, Jonathan B.
and Falco, Natalie
and Jia, Bill Z.
and Baker, David
and Lavis, Luke D.
and Cohen, Adam E.},
url = {https://www.nature.com/articles/s41587-022-01524-7, Nature Biotechnology
https://www.bakerlab.org/wp-content/uploads/2023/01/s41587-022-01524-7.pdf, PDF},
doi = {10.1038/s41587-022-01524-7},
year = {2023},
date = {2023-01-02},
journal = {Nature Biotechnology},
abstract = {Recording transcriptional histories of a cell would enable deeper understanding of cellular developmental trajectories and responses to external perturbations. Here we describe an engineered protein fiber that incorporates diverse fluorescent marks during its growth to store a ticker tape-like history. An embedded HaloTag reporter incorporates user-supplied dyes, leading to colored stripes that map the growth of each individual fiber to wall clock time. A co-expressed eGFP tag driven by a promoter of interest records a history of transcriptional activation. High-resolution multi-spectral imaging on fixed samples reads the cellular histories, and interpolation of eGFP marks relative to HaloTag timestamps provides accurate absolute timing. We demonstrate recordings of doxycycline-induced transcription in HEK cells and cFos promoter activation in cultured neurons, with a single-cell absolute accuracy of 30–40 minutes over a 12-hour recording. The protein-based ticker tape design we present here could be generalized to achieve massively parallel single-cell recordings of diverse physiological modalities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Florian Praetorius, Philip J. Y. Leung, Maxx H. Tessmer, Adam Broerman, Cullen Demakis, Acacia F. Dishman, Arvind Pillai, Abbas Idris, David Juergens, Justas Dauparas, Xinting Li, Paul M. Levine, Mila Lamb, Ryanne K. Ballard, Stacey R. Gerben, Hannah Nguyen, Alex Kang, Banumathi Sankaran, Asim K. Bera, Brian F. Volkman, Jeff Nivala, Stefan Stoll, David Baker
Design of stimulus-responsive two-state hinge proteins Journal Article
In: Science, vol. 381, no. 6659, pp. 754-760, 2023.
@article{doi:10.1126/science.adg7731b,
title = {Design of stimulus-responsive two-state hinge proteins},
author = {Florian Praetorius and Philip J. Y. Leung and Maxx H. Tessmer and Adam Broerman and Cullen Demakis and Acacia F. Dishman and Arvind Pillai and Abbas Idris and David Juergens and Justas Dauparas and Xinting Li and Paul M. Levine and Mila Lamb and Ryanne K. Ballard and Stacey R. Gerben and Hannah Nguyen and Alex Kang and Banumathi Sankaran and Asim K. Bera and Brian F. Volkman and Jeff Nivala and Stefan Stoll and David Baker},
url = {https://www.science.org/doi/abs/10.1126/science.adg7731},
doi = {10.1126/science.adg7731},
year = {2023},
date = {2023-01-01},
journal = {Science},
volume = {381},
number = {6659},
pages = {754-760},
abstract = {In nature, proteins that switch between two conformations in response to environmental stimuli structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Designing proteins with two distinct but fully structured conformations is a challenge for protein design as it requires sculpting an energy landscape with two distinct minima. Here we describe the design of “hinge” proteins that populate one designed state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, double electron-electron resonance spectroscopy, and binding measurements demonstrate that despite the significant structural differences the two states are designed with atomic level accuracy and that the conformational and binding equilibria are closely coupled. Natural proteins often adopt multiple conformational states, thereby changing their activity or binding partners in response to another protein, small molecule, or other stimulus. It has been difficult to engineer such conformational switching between two folded states in human-designed proteins. Praetorius et al. developed a hinge-like protein by simultaneously considering both desired states in the design process. The successful designs exhibited a large shift in conformation upon binding to a target peptide helix, which could be tailored for specificity. The authors characterized the protein structures, binding kinetics, and conformational equilibrium of the designs. This work provides the groundwork for generating protein switches that respond to biological triggers and can produce conformational changes that modulate protein assemblies. —Michael A. Funk A two-state design of protein switches that couple effector binding to a conformational change is discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2022
FROM THE LAB
Bermeo, Sherry and Favor, Andrew and Chang, Ya-Ting and Norris, Andrew and Boyken, Scott E. and Hsia, Yang and Haddox, Hugh K. and Xu, Chunfu and Brunette, T. J. and Wysocki, Vicki H. and Bhabha, Gira and Ekiert, Damian C. and Baker, David
De novo design of obligate ABC-type heterotrimeric proteins Journal Article
In: Nature Structural & Molecular Biology, 2022.
@article{Bermeo2022,
title = {De novo design of obligate ABC-type heterotrimeric proteins},
author = {Bermeo, Sherry
and Favor, Andrew
and Chang, Ya-Ting
and Norris, Andrew
and Boyken, Scott E.
and Hsia, Yang
and Haddox, Hugh K.
and Xu, Chunfu
and Brunette, T. J.
and Wysocki, Vicki H.
and Bhabha, Gira
and Ekiert, Damian C.
and Baker, David},
url = {https://www.nature.com/articles/s41594-022-00879-4, Nature Structural & Molecular Biology (Open Access)},
doi = {10.1038/s41594-022-00879-4},
year = {2022},
date = {2022-12-15},
journal = {Nature Structural & Molecular Biology},
abstract = {The de novo design of three protein chains that associate to form a heterotrimer (but not any of the possible two-chain heterodimers) and that can drive the assembly of higher-order branching structures is an important challenge for protein design. We designed helical heterotrimers with specificity conferred by buried hydrogen bond networks and large aromatic residues to enhance shape complementary packing. We obtained ten designs for which all three chains cooperatively assembled into heterotrimers with few or no other species present. Crystal structures of a helical bundle heterotrimer and extended versions, with helical repeat proteins fused to individual subunits, showed all three chains assembling in the designed orientation. We used these heterotrimers as building blocks to construct larger cyclic oligomers, which were structurally validated by electron microscopy. Our three-way junction designs provide new routes to complex protein nanostructures and enable the scaffolding of three distinct ligands for modulation of cell signaling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kipnis, Yakov and Chaib, Anissa Ouald and Vorobieva, Anastassia A. and Cai, Guangyang and Reggiano, Gabriella and Basanta, Benjamin and Kumar, Eshan and Mittl, Peer R.E. and Hilvert, Donald and Baker, David
Design and optimization of enzymatic activity in a de novo β-barrel scaffold Journal Article
In: Protein Science, 2022.
@article{Kipnis2022,
title = {Design and optimization of enzymatic activity in a de novo β-barrel scaffold},
author = {Kipnis, Yakov
and Chaib, Anissa Ouald
and Vorobieva, Anastassia A.
and Cai, Guangyang
and Reggiano, Gabriella
and Basanta, Benjamin
and Kumar, Eshan
and Mittl, Peer R.E.
and Hilvert, Donald
and Baker, David},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/pro.4405, Protein Science
https://www.bakerlab.org/wp-content/uploads/2022/10/Protein-Science-2022-Kipnis-Design-and-optimization-of-enzymatic-activity-in-a-de-novo-‐barrel-scaffold.pdf, PDF},
doi = {10.1002/pro.4405},
year = {2022},
date = {2022-11-01},
urldate = {2022-11-01},
journal = {Protein Science},
abstract = {While native scaffolds offer a large diversity of shapes and topologies for enzyme engineering, their often unpredictable behavior in response to sequence modification makes de novo generated scaffolds an exciting alternative. Here we explore the customization of the backbone and sequence of a de novo designed eight stranded ?-barrel protein to create catalysts for a retro-aldolase model reaction. We show that active and specific catalysts can be designed in this fold and use directed evolution to further optimize activity and stereoselectivity. Our results support previous suggestions that different folds have different inherent amenability to evolution and this property could account, in part, for the distribution of natural enzymes among different folds.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Quijano-Rubio, Alfredo and Bhuiyan, Aladdin M. and Yang, Huilin and Leung, Isabel and Bello, Elisa and Ali, Lestat R. and Zhangxu, Kevin and Perkins, Jilliane and Chun, Jung-Ho and Wang, Wentao and Lajoie, Marc J. and Ravichandran, Rashmi and Kuo, Yun-Huai and Dougan, Stephanie K. and Riddell, Stanley R. and Spangler, Jamie B. and Dougan, Michael and Silva, Daniel-Adriano and Baker, David
A split, conditionally active mimetic of IL-2 reduces the toxicity of systemic cytokine therapy Journal Article
In: Nature Biotechnology, 2022.
@article{Quijano-Rubio2022,
title = {A split, conditionally active mimetic of IL-2 reduces the toxicity of systemic cytokine therapy},
author = {Quijano-Rubio, Alfredo
and Bhuiyan, Aladdin M.
and Yang, Huilin
and Leung, Isabel
and Bello, Elisa
and Ali, Lestat R.
and Zhangxu, Kevin
and Perkins, Jilliane
and Chun, Jung-Ho
and Wang, Wentao
and Lajoie, Marc J.
and Ravichandran, Rashmi
and Kuo, Yun-Huai
and Dougan, Stephanie K.
and Riddell, Stanley R.
and Spangler, Jamie B.
and Dougan, Michael
and Silva, Daniel-Adriano
and Baker, David},
url = {https://www.nature.com/articles/s41587-022-01510-z, Nature Biotechnology
https://www.bakerlab.org/wp-content/uploads/2022/11/s41587-022-01510-z.pdf, PDF},
doi = {10.1038/s41587-022-01510-z},
year = {2022},
date = {2022-10-31},
journal = {Nature Biotechnology},
abstract = {The therapeutic potential of recombinant cytokines has been limited by the severe side effects of systemic administration. We describe a strategy to reduce the dose-limiting toxicities of monomeric cytokines by designing two components that require colocalization for activity and that can be independently targeted to restrict activity to cells expressing two surface markers. We demonstrate the approach with a previously designed mimetic of cytokines interleukin-2 and interleukin-15—Neoleukin-2/15 (Neo-2/15)—both for trans-activating immune cells surrounding targeted tumor cells and for cis-activating directly targeted immune cells. In trans-activation mode, tumor antigen targeting of the two components enhanced antitumor activity and attenuated toxicity compared with systemic treatment in syngeneic mouse melanoma models. In cis-activation mode, immune cell targeting of the two components selectively expanded CD8+ T cells in a syngeneic mouse melanoma model and promoted chimeric antigen receptor T cell activation in a lymphoma xenograft model, enhancing antitumor efficacy in both cases.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Said, Meerit Y., Kang, Christine S., Wang, Shunzhi, Sheffler, William, Salveson, Patrick J., Bera, Asim K., Kang, Alex, Nguyen, Hannah, Ballard, Ryanne, Li, Xinting, Bai, Hua, Stewart, Lance, Levine, Paul, Baker, David
Exploration of Structured Symmetric Cyclic Peptides as Ligands for Metal-Organic Frameworks Journal Article
In: Chemistry of Materials, 2022.
@article{Said2022,
title = {Exploration of Structured Symmetric Cyclic Peptides as Ligands for Metal-Organic Frameworks},
author = {Said, Meerit Y. and Kang, Christine S. and Wang, Shunzhi and Sheffler, William and Salveson, Patrick J. and Bera, Asim K. and Kang, Alex and Nguyen, Hannah and Ballard, Ryanne and Li, Xinting and Bai, Hua and Stewart, Lance and Levine, Paul and Baker, David},
url = {https://pubs.acs.org/doi/10.1021/acs.chemmater.2c02597, Chem. Mater.
https://www.bakerlab.org/wp-content/uploads/2022/10/Said_etal_ChemMater2022_CyclicPeptideMOFs.pdf, PDF},
doi = {/10.1021/acs.chemmater.2c02597},
year = {2022},
date = {2022-10-25},
urldate = {2022-10-25},
journal = {Chemistry of Materials},
abstract = {Despite remarkable advances in the assembly of highly structured coordination polymers and metal–organic frameworks, the rational design of such materials using more conformationally flexible organic ligands such as peptides remains challenging. In an effort to make the design of such materials fully programmable, we first developed a computational design method for generating metal-mediated 3D frameworks using rigid and symmetric peptide macrocycles with metal-coordinating sidechains. We solved the structures of six crystalline networks involving conformationally constrained 6 to 12 residue cyclic peptides with C2, C3, and S2 internal symmetry and three different types of metals (Zn2+, Co2+, or Cu2+) by single-crystal X-ray diffraction, which reveals how the peptide sequences, backbone symmetries, and metal coordination preferences drive the assembly of the resulting structures. In contrast to smaller ligands, these peptides associate through peptide–peptide interactions without full coordination of the metals, contrary to one of the assumptions underlying our computational design method. The cyclic peptides are the largest peptidic ligands reported to form crystalline coordination polymers with transition metals to date, and while more work is required to develop methods for fully programming their crystal structures, the combination of high chemical diversity with synthetic accessibility makes them attractive building blocks for engineering a broader set of new crystalline materials for use in applications such as sensing, asymmetric catalysis, and chiral separation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Chidyausiku, Tamuka M. and Mendes, Soraia R. and Klima, Jason C. and Nadal, Marta and Eckhard, Ulrich and Roel-Touris, Jorge and Houliston, Scott and Guevara, Tibisay and Haddox, Hugh K. and Moyer, Adam and Arrowsmith, Cheryl H. and Gomis-Rüth, F. Xavier and Baker, David and Marcos, Enrique
De novo design of immunoglobulin-like domains Journal Article
In: Nature Communications, 2022.
@article{Chidyausiku2022,
title = {De novo design of immunoglobulin-like domains},
author = {Chidyausiku, Tamuka M.
and Mendes, Soraia R.
and Klima, Jason C.
and Nadal, Marta
and Eckhard, Ulrich
and Roel-Touris, Jorge
and Houliston, Scott
and Guevara, Tibisay
and Haddox, Hugh K.
and Moyer, Adam
and Arrowsmith, Cheryl H.
and Gomis-Rüth, F. Xavier
and Baker, David
and Marcos, Enrique},
url = {https://www.nature.com/articles/s41467-022-33004-6, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2022/10/Chidyausiku_etal_NatComm_Design_of_innunoglobulin-like_domains.pdf, PDF},
year = {2022},
date = {2022-10-03},
urldate = {2022-10-03},
journal = {Nature Communications},
abstract = {Antibodies, and antibody derivatives such as nanobodies, contain immunoglobulin-like (Ig) β-sandwich scaffolds which anchor the hypervariable antigen-binding loops and constitute the largest growing class of drugs. Current engineering strategies for this class of compounds rely on naturally existing Ig frameworks, which can be hard to modify and have limitations in manufacturability, designability and range of action. Here, we develop design rules for the central feature of the Ig fold architecture—the non-local cross-β structure connecting the two β-sheets—and use these to design highly stable Ig domains de novo, confirm their structures through X-ray crystallography, and show they can correctly scaffold functional loops. Our approach opens the door to the design of antibody-like scaffolds with tailored structures and superior biophysical properties.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
B. I. M. Wicky, L. F. Milles, A. Courbet, R. J. Ragotte, J. Dauparas, E. Kinfu, S. Tipps, R. D. Kibler, M. Baek, F. DiMaio, X. Li, L. Carter, A. Kang, H. Nguyen, A. K. Bera, D. Baker
Hallucinating symmetric protein assemblies Journal Article
In: Science, 2022.
@article{Wicky2022,
title = {Hallucinating symmetric protein assemblies},
author = {B. I. M. Wicky and L. F. Milles and A. Courbet and R. J. Ragotte and J. Dauparas and E. Kinfu and S. Tipps and R. D. Kibler and M. Baek and F. DiMaio and X. Li and L. Carter and A. Kang and H. Nguyen and A. K. Bera and D. Baker},
url = {https://www.science.org/doi/abs/10.1126/science.add1964, Science
https://www.bakerlab.org/wp-content/uploads/2022/09/Wicky_etal_Science2022_Hallucinating_symmetric_protein_assemblies.pdf, PDF
},
doi = {10.1126/science.add1964},
year = {2022},
date = {2022-09-15},
journal = {Science},
abstract = {Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of 7 designs are very close to the computational models (median RMSD: 0.6 Å), as are 3 cryoEM structures of giant 10 nanometer rings with up to 1550 residues and C33 symmetry; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be generated using deep learning, and pave the way for the design of increasingly complex components for nanomachines and biomaterials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dauparas, J. and Anishchenko, I. and Bennett, N. and Bai, H. and Ragotte, R. J. and Milles, L. F. and Wicky, B. I. M. and Courbet, A. and de Haas, R. J. and Bethel, N. and Leung, P. J. Y. and Huddy, T. F. and Pellock, S. and Tischer, D. and Chan, F. and Koepnick, B. and Nguyen, H. and Kang, A. and Sankaran, B. and Bera, A. K. and King, N. P. and Baker, D.
Robust deep learning–based protein sequence design using ProteinMPNN Journal Article
In: Science, 2022.
@article{Dauparas2022,
title = {Robust deep learning–based protein sequence design using ProteinMPNN},
author = {Dauparas, J.
and Anishchenko, I.
and Bennett, N.
and Bai, H.
and Ragotte, R. J.
and Milles, L. F.
and Wicky, B. I. M.
and Courbet, A.
and de Haas, R. J.
and Bethel, N.
and Leung, P. J. Y.
and Huddy, T. F.
and Pellock, S.
and Tischer, D.
and Chan, F.
and Koepnick, B.
and Nguyen, H.
and Kang, A.
and Sankaran, B.
and Bera, A. K.
and King, N. P.
and Baker, D.},
url = {https://www.science.org/doi/abs/10.1126/science.add2187, Science
https://www.bakerlab.org/wp-content/uploads/2022/09/Dauparas_etal_Science2022_Sequence_design_via_ProteinMPNN.pdf, PDF},
doi = {10.1126/science.add2187},
year = {2022},
date = {2022-09-15},
journal = {Science},
abstract = {While deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here we describe a deep learning–based protein sequence design method, ProteinMPNN, with outstanding performance in both in silico and experimental tests. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4%, compared to 32.9% for Rosetta. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. We demonstrate the broad utility and high accuracy of ProteinMPNN using X-ray crystallography, cryoEM and functional studies by rescuing previously failed designs, made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target binding proteins},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Gaurav Bhardwaj, Jacob O’Connor, Stephen Rettie, Yen-Hua Huang, Theresa A. Ramelot, Vikram Khipple Mulligan, Gizem Gokce Alpkilic, Jonathan Palmer, Asim K. Bera, Matthew J. Bick, Maddalena Di Piazza, Xinting Li, Parisa Hosseinzadeh, Timothy W. Craven, Roberto Tejero, Anna Lauko, Ryan Choi, Calina Glynn, Linlin Dong, Robert Griffin, Wesley C. van Voorhis, Jose Rodriguez, Lance Stewart, Gaetano T. Montelione, David Craik, David Baker
Accurate de novo design of membrane-traversing macrocycles Journal Article
In: Cell, 2022.
@article{Bhardwaj2022,
title = {Accurate de novo design of membrane-traversing macrocycles},
author = {Gaurav Bhardwaj and Jacob O’Connor and Stephen Rettie and Yen-Hua Huang and Theresa A. Ramelot and Vikram Khipple Mulligan and Gizem Gokce Alpkilic and Jonathan Palmer and Asim K. Bera and Matthew J. Bick and Maddalena {Di Piazza} and Xinting Li and Parisa Hosseinzadeh and Timothy W. Craven and Roberto Tejero and Anna Lauko and Ryan Choi and Calina Glynn and Linlin Dong and Robert Griffin and Wesley C. {van Voorhis} and Jose Rodriguez and Lance Stewart and Gaetano T. Montelione and David Craik and David Baker},
url = {https://www.sciencedirect.com/science/article/pii/S0092867422009229?via%3Dihub, Cell
https://www.bakerlab.org/wp-content/uploads/2022/08/1-s2.0-S0092867422009229-main.pdf, PDF},
doi = {10.1016/j.cell.2022.07.019},
year = {2022},
date = {2022-08-29},
urldate = {2022-08-29},
journal = {Cell},
abstract = {We use computational design coupled with experimental characterization to systematically investigate the design principles for macrocycle membrane permeability and oral bioavailability. We designed 184 6–12 residue macrocycles with a wide range of predicted structures containing noncanonical backbone modifications and experimentally determined structures of 35; 29 are very close to the computational models. With such control, we show that membrane permeability can be systematically achieved by ensuring all amide (NH) groups are engaged in internal hydrogen bonding interactions. 84 designs over the 6–12 residue size range cross membranes with an apparent permeability greater than 1 × 10−6 cm/s. Designs with exposed NH groups can be made membrane permeable through the design of an alternative isoenergetic fully hydrogen-bonded state favored in the lipid membrane. The ability to robustly design membrane-permeable and orally bioavailable peptides with high structural accuracy should contribute to the next generation of designed macrocycle therapeutics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Yang, Erin C. and Divine, Robby and Kang, Christine S. and Chan, Sidney and Arenas, Elijah and Subol, Zoe and Tinker, Peter and Manninen, Hayden and Feichtenbiner, Alicia and Mustafa, Talal and Hallowell, Julia and Orr, Isiac and Haddox, Hugh and Koepnick, Brian and O’Connor, Jacob and Haydon, Ian C. and Herpoldt, Karla-Luise and Wormer, Kandise Van and Abell, Celine and Baker, David and Khmelinskaia, Alena and King, Neil P.
Increasing Computational Protein Design Literacy through Cohort-Based Learning for Undergraduate Students Journal Article
In: Journal of Chemical Education, 2022.
@article{Yang2022,
title = {Increasing Computational Protein Design Literacy through Cohort-Based Learning for Undergraduate Students},
author = {Yang, Erin C.
and Divine, Robby
and Kang, Christine S.
and Chan, Sidney
and Arenas, Elijah
and Subol, Zoe
and Tinker, Peter
and Manninen, Hayden
and Feichtenbiner, Alicia
and Mustafa, Talal
and Hallowell, Julia
and Orr, Isiac
and Haddox, Hugh
and Koepnick, Brian
and O’Connor, Jacob
and Haydon, Ian C.
and Herpoldt, Karla-Luise
and Wormer, Kandise Van
and Abell, Celine
and Baker, David
and Khmelinskaia, Alena
and King, Neil P.},
url = {https://pubs.acs.org/doi/full/10.1021/acs.jchemed.2c00500, Journal of Chemical Education
https://www.bakerlab.org/wp-content/uploads/2022/08/Yang2022acs.jchemed.2c00500.pdf, PDF},
year = {2022},
date = {2022-08-05},
urldate = {2022-08-05},
journal = {Journal of Chemical Education},
abstract = {Undergraduate research experiences can improve student success in graduate education and STEM careers. During the COVID-19 pandemic, undergraduate researchers at our institution and many others lost their work–study research positions due to interruption of in-person research activities. This imposed a financial burden on the students and eliminated an important learning opportunity. To address these challenges, we created a paid, fully remote, cohort-based research curriculum in computational protein design. Our curriculum used existing protein design methods as a platform to first educate and train undergraduate students and then to test research hypotheses. In the first phase, students learned computational methods to assess the stability of designed protein assemblies. In the second phase, students used a larger data set to identify factors that could improve the accuracy of current protein design algorithms. This cohort-based program created valuable new research opportunities for undergraduates at our institute and enhanced the undergraduates’ feeling of connection with the lab. Students learned transferable and useful skills such as literature review, programming basics, data analysis, hypothesis testing, and scientific communication. Our program provides a model of structured computational research training opportunities for undergraduate researchers in any field for organizations looking to expand educational access.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Derrick R. Hicks, Madison A. Kennedy, Kirsten A. Thompson, Michelle DeWitt, Brian Coventry, Alex Kang, Asim K. Bera, T. J. Brunette, Banumathi Sankaran, Barry Stoddard, David Baker
De novo design of protein homodimers containing tunable symmetric protein pockets Journal Article
In: Proceedings of the National Academy of Sciences, 2022.
@article{Hicks2022,
title = {De novo design of protein homodimers containing tunable symmetric protein pockets},
author = {Derrick R. Hicks and Madison A. Kennedy and Kirsten A. Thompson and Michelle DeWitt and Brian Coventry and Alex Kang and Asim K. Bera and T. J. Brunette and Banumathi Sankaran and Barry Stoddard and David Baker},
url = {https://www.pnas.org/doi/abs/10.1073/pnas.2113400119, PNAS
https://www.bakerlab.org/wp-content/uploads/2022/07/pnas.2113400119.pdf, Download PDF},
doi = {10.1073/pnas.2113400119},
year = {2022},
date = {2022-07-21},
urldate = {2022-07-21},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Proteins capable of binding arbitrary small molecules could enable the generation of new biosensors or medicines. While considerable progress has been made in recent years to design proteins from scratch capable of binding asymmetric molecules, little work has been done to facilitate the binding of symmetric molecules. Here, we present a method for generating libraries of C2 symmetric proteins with diverse central cavities that could be functionalized in the future to bind a range of C2 symmetric small molecules for applications such as ligand controllable cell engineering. We show that 31% of our designed proteins fold to the desired quaternary state, when experimentally characterized, and are hyperstable. Function follows form in biology, and the binding of small molecules requires proteins with pockets that match the shape of the ligand. For design of binding to symmetric ligands, protein homo-oligomers with matching symmetry are advantageous as each protein subunit can make identical interactions with the ligand. Here, we describe a general approach to designing hyperstable C2 symmetric proteins with pockets of diverse size and shape. We first designed repeat proteins that sample a continuum of curvatures but have low helical rise, then docked these into C2 symmetric homodimers to generate an extensive range of C2 symmetric cavities. We used this approach to design thousands of C2 symmetric homodimers, and characterized 101 of them experimentally. Of these, the geometry of 31 were confirmed by small angle X-ray scattering and 2 were shown by crystallographic analyses to be in close agreement with the computational design models. These scaffolds provide a rich set of starting points for binding a wide range of C2 symmetric compounds.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Jue Wang, Sidney Lisanza, David Juergens, Doug Tischer, Joseph L. Watson, Karla M. Castro, Robert Ragotte, Amijai Saragovi, Lukas F. Milles, Minkyung Baek, Ivan Anishchenko, Wei Yang, Derrick R. Hicks, Marc Expòsit, Thomas Schlichthaerle, Jung-Ho Chun, Justas Dauparas, Nathaniel Bennett, Basile I. M. Wicky, Andrew Muenks, Frank DiMaio, Bruno Correia, Sergey Ovchinnikov, David Baker
Scaffolding protein functional sites using deep learning Journal Article
In: Science, 2022.
@article{Wang2022,
title = {Scaffolding protein functional sites using deep learning},
author = {Jue Wang and Sidney Lisanza and David Juergens and Doug Tischer and Joseph L. Watson and Karla M. Castro and Robert Ragotte and Amijai Saragovi and Lukas F. Milles and Minkyung Baek and Ivan Anishchenko and Wei Yang and Derrick R. Hicks and Marc Expòsit and Thomas Schlichthaerle and Jung-Ho Chun and Justas Dauparas and Nathaniel Bennett and Basile I. M. Wicky and Andrew Muenks and Frank DiMaio and Bruno Correia and Sergey Ovchinnikov and David Baker },
url = {https://www.science.org/doi/abs/10.1126/science.abn2100, Science
https://www.ipd.uw.edu/wp-content/uploads/2022/07/science.abn2100.pdf, Download PDF},
doi = {10.1126/science.abn2100},
year = {2022},
date = {2022-07-21},
urldate = {2022-07-21},
journal = {Science},
abstract = {The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing to prespecify the fold or secondary structure of the scaffold. The first approach, “constrained hallucination,” optimizes sequences such that their predicted structures contain the desired functional site. The second approach, “inpainting,” starts from the functional site and fills in additional sequence and structure to create a viable protein scaffold in a single forward pass through a specifically trained RoseTTAFold network. We use these two methods to design candidate immunogens, receptor traps, metalloproteins, enzymes, and protein-binding proteins and validate the designs using a combination of in silico and experimental tests. Protein design has had success in finding sequences that fold into a desired conformation, but designing functional proteins remains challenging. Wang et al. describe two deep-learning methods to design proteins that contain prespecified functional sites. In the first, they found sequences predicted to fold into stable structures that contain the functional site. In the second, they retrained a structure prediction network to recover the sequence and full structure of a protein given only the functional site. The authors demonstrate their methods by designing proteins containing a variety of functional motifs. —VV Deep-learning methods enable the scaffolding of desired functional residues within a well-folded designed protein.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Zhang, Jason Z. and Yeh, Hsien-Wei and Walls, Alexandra C. and Wicky, Basile I. M. and Sprouse, Kaitlin R. and VanBlargan, Laura A. and Treger, Rebecca and Quijano-Rubio, Alfredo and Pham, Minh N. and Kraft, John C. and Haydon, Ian C. and Yang, Wei and DeWitt, Michelle and Bowen, John E. and Chow, Cameron M. and Carter, Lauren and Ravichandran, Rashmi and Wener, Mark H. and Stewart, Lance and Veesler, David and Diamond, Michael S. and Greninger, Alexander L. and Koelle, David M. and Baker, David
Thermodynamically coupled biosensors for detecting neutralizing antibodies against SARS-CoV-2 variants Journal Article
In: Nature Biotechnology, 2022.
@article{Zhang2022,
title = {Thermodynamically coupled biosensors for detecting neutralizing antibodies against SARS-CoV-2 variants},
author = {Zhang, Jason Z.
and Yeh, Hsien-Wei
and Walls, Alexandra C.
and Wicky, Basile I. M.
and Sprouse, Kaitlin R.
and VanBlargan, Laura A.
and Treger, Rebecca
and Quijano-Rubio, Alfredo
and Pham, Minh N.
and Kraft, John C.
and Haydon, Ian C.
and Yang, Wei
and DeWitt, Michelle
and Bowen, John E.
and Chow, Cameron M.
and Carter, Lauren
and Ravichandran, Rashmi
and Wener, Mark H.
and Stewart, Lance
and Veesler, David
and Diamond, Michael S.
and Greninger, Alexander L.
and Koelle, David M.
and Baker, David},
url = {https://www.nature.com/articles/s41587-022-01280-8, Nature Biotechnology
https://www.bakerlab.org/wp-content/uploads/2022/04/Zhang_etal_NatureBiotech_Thermodynamically_coupled_biosensors_for_detecting_nAbs_against_SARSCoV2_variants.pdf, Download PDF},
year = {2022},
date = {2022-04-28},
urldate = {2022-04-28},
journal = {Nature Biotechnology},
abstract = {We designed a protein biosensor that uses thermodynamic coupling for sensitive and rapid detection of neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in serum. The biosensor is a switchable, caged luciferase–receptor-binding domain (RBD) construct that detects serum-antibody interference with the binding of virus RBD to angiotensin-converting enzyme 2 (ACE-2) as a proxy for neutralization. Our coupling approach does not require target modification and can better distinguish sample-to-sample differences in analyte binding affinity and abundance than traditional competition-based assays.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A. Courbet, J. Hansen, Y. Hsia, N. Bethel, Y.-J. Park, C. Xu, A. Moyer, S. E. Boyken, G. Ueda, U. Nattermann, D. Nagarajan, D. Silva, W. Sheffler, J. Quispe, A. Nord, N. King, P. Bradley, D. Veesler, J. Kollman, D. Baker
Computational design of mechanically coupled axle-rotor protein assemblies Journal Article
In: Science, 2022.
@article{Courbet2022,
title = {Computational design of mechanically coupled axle-rotor protein assemblies},
author = {A. Courbet and J. Hansen and Y. Hsia and N. Bethel and Y.-J. Park and C. Xu and A. Moyer and S. E. Boyken and G. Ueda and U. Nattermann and D. Nagarajan and D. Silva and W. Sheffler and J. Quispe and A. Nord and N. King and P. Bradley and D. Veesler and J. Kollman and D. Baker},
url = {https://www.science.org/doi/abs/10.1126/science.abm1183, Science
https://www.bakerlab.org/wp-content/uploads/2022/04/science.abm1183.pdf, Download PDF},
year = {2022},
date = {2022-04-21},
urldate = {2022-04-21},
journal = {Science},
abstract = {Natural molecular machines contain protein components that undergo motion relative to each other. Designing such mechanically constrained nanoscale protein architectures with internal degrees of freedom is an outstanding challenge for computational protein design. Here we explore the de novo construction of protein machinery from designed axle and rotor components with internal cyclic or dihedral symmetry. We find that the axle-rotor systems assemble in vitro and in vivo as designed. Using cryo–electron microscopy, we find that these systems populate conformationally variable relative orientations reflecting the symmetry of the coupled components and the computationally designed interface energy landscape. These mechanical systems with internal degrees of freedom are a step toward the design of genetically encodable nanomachines. Protein rotary machines such as ATP synthase contain axle-like and ring-like components and couple biochemical energy to the mechanical work of rotating the components relative to each other. Courbet et al. have taken a step toward designing such axel-rotor nanomachines. A structural requirement is that interactions between the components must be strong enough to allow assembly but still allow different rotational states to be populated. The authors met this design challenge and computationally designed ring-like protein topologies (rotors) with a range of inner diameters that accommodate designed axle-like binding partners. The systems assemble and populate the different rotational states anticipated by the designs. These rotational energy landscapes provide one of two needed elements for a directional motor. —VV Computationally designed self-assembling axle-rotor protein systems populate multiple rotational states.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
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}
}
Levine, Paul M., Craven, Timothy W., Li, Xinting, Balana, Aaron T., Bird, Gregory H., Godes, Marina, Salveson, Patrick J., Erickson, Patrick W., Lamb, Mila, Ahlrichs, Maggie, Murphy, Michael, Ogohara, Cassandra, Said, Meerit Y., Walensky, Loren D., Pratt, Matthew R., Baker, David
Generation of Potent and Stable GLP-1 Analogues Via “Serine Ligation” Journal Article
In: ACS Chemical Biology, 2022.
@article{nokey,
title = {Generation of Potent and Stable GLP-1 Analogues Via “Serine Ligation”},
author = {Levine, Paul M. and Craven, Timothy W. and Li, Xinting and Balana, Aaron T. and Bird, Gregory H. and Godes, Marina and Salveson, Patrick J. and Erickson, Patrick W. and Lamb, Mila and Ahlrichs, Maggie and Murphy, Michael and Ogohara, Cassandra and Said, Meerit Y. and Walensky, Loren D. and Pratt, Matthew R. and Baker, David},
url = {https://pubs.acs.org/doi/abs/10.1021/acschembio.2c00075, ACS Chemical Biology
https://www.bakerlab.org/wp-content/uploads/2022/03/Levine_etal_ACSChemBio2022_GLP-1_ananlogues_by_serine_ligation.pdf, Download PDF},
doi = {10.1021/acschembio.2c00075},
year = {2022},
date = {2022-03-23},
journal = {ACS Chemical Biology},
abstract = {Peptide and protein bioconjugation technologies have revolutionized our ability to site-specifically or chemoselectively install a variety of functional groups for applications in chemical biology and medicine, including the enhancement of bioavailability. Here, we introduce a site-specific bioconjugation strategy inspired by chemical ligation at serine that relies on a noncanonical amino acid containing a 1-amino-2-hydroxy functional group and a salicylaldehyde ester. More specifically, we harness this technology to generate analogues of glucagon-like peptide-1 that resemble Semaglutide, a long-lasting blockbuster drug currently used in the clinic to regulate glucose levels in the blood. We identify peptides that are more potent than unmodified peptide and equipotent to Semaglutide in a cell-based activation assay, improve the stability in human serum, and increase glucose disposal efficiency in vivo. This approach demonstrates the potential of “serine ligation” for various applications in chemical biology, with a particular focus on generating stabilized peptide therapeutics.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Minkyung Baek, David Baker
Deep learning and protein structure modeling Journal Article
In: Nature Methods, 2022.
@article{Baek2022,
title = {Deep learning and protein structure modeling},
author = {Minkyung Baek and David Baker},
url = {https://www.nature.com/articles/s41592-021-01360-8, Nature Methods
https://www.bakerlab.org/wp-content/uploads/2022/01/Baek_Baker_NatureMethods2022_Deep_Learning_and_Protein_Structure_Modeling.pdf, Download PDF
},
doi = {10.1038/s41592-021-01360-8},
year = {2022},
date = {2022-01-22},
urldate = {2022-01-22},
journal = {Nature Methods},
abstract = {Deep learning has transformed protein structure modeling. Here we relate AlphaFold and RoseTTAFold to classical physically based approaches to protein structure prediction, and discuss the many areas of structural biology that are likely to be affected by further advances in deep learning.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Danny D. Sahtoe, Florian Praetorius, Alexis Courbet, Yang Hsia, Basile I. M. Wicky, Natasha I. Edman, Lauren M. Miller, Bart J. R. Timmermans, Justin Decarreau, Hana M. Morris, Alex Kang, Asim K. Bera, David Baker
Reconfigurable asymmetric protein assemblies through implicit negative design Journal Article
In: Science, 2022.
@article{Sahtoe2022,
title = {Reconfigurable asymmetric protein assemblies through implicit negative design},
author = {Danny D. Sahtoe and Florian Praetorius and Alexis Courbet and Yang Hsia and Basile I. M. Wicky and Natasha I. Edman and Lauren M. Miller and Bart J. R. Timmermans and Justin Decarreau and Hana M. Morris and Alex Kang and Asim K. Bera and David Baker},
url = {https://www.science.org/doi/pdf/10.1126/science.abj7662
https://www.bakerlab.org/wp-content/uploads/2022/01/Sahtoe_etal_Science2022_Diverse_protein_assemblies_by_implicit_negative_design.pdf},
doi = {10.1126/science.abj7662},
year = {2022},
date = {2022-01-21},
urldate = {2022-01-21},
journal = {Science},
abstract = {Asymmetric multiprotein complexes that undergo subunit exchange play central roles in biology but present a challenge for design because the components must not only contain interfaces that enable reversible association but also be stable and well behaved in isolation. We use implicit negative design to generate β sheet–mediated heterodimers that can be assembled into a wide variety of complexes. The designs are stable, folded, and soluble in isolation and rapidly assemble upon mixing, and crystal structures are close to the computational models. We construct linearly arranged hetero-oligomers with up to six different components, branched hetero-oligomers, closed C4-symmetric two-component rings, and hetero-oligomers assembled on a cyclic homo-oligomeric central hub and demonstrate that such complexes can readily reconfigure through subunit exchange. Our approach provides a general route to designing asymmetric reconfigurable protein systems. Protein complexes play important roles in biological processes, and many complexes are dynamic, with subunits exchanging to facilitate different functions. It has been challenging to design stable and soluble monomeric proteins that reversibly associate into hetero-oligomers. Sahtoe et al. used a strategy called implicit negative design to construct proteins with interaction interfaces that drive association with a selected partner but not self-association. The resulting designs are stably folded in solution and provide the modules for assembly into a wide variety of complexes. They can be functionalized, allowing target proteins to be displayed in defined geometries, and complex subunits can be exchanged by varying the available concentrations of components. —VV De novo designed protein building blocks can be modularly combined to create customized protein assemblies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
COLLABORATOR LED
Joon Sung Park, Jungyuen Choi, Longxing Cao, Jyotidarsini Mohanty, Yoshihisa Suzuki, Andy Park, David Baker, Joseph Schlessinger, Sangwon Lee
Isoform-specific inhibition of FGFR signaling achieved by a de-novo-designed mini-protein Journal Article
In: Cell Reports, 2022.
@article{nokey,
title = {Isoform-specific inhibition of FGFR signaling achieved by a de-novo-designed mini-protein},
author = {Joon Sung Park and Jungyuen Choi and Longxing Cao and Jyotidarsini Mohanty and Yoshihisa Suzuki and Andy Park and David Baker and Joseph Schlessinger and Sangwon Lee},
url = {https://www.sciencedirect.com/science/article/pii/S2211124722014012#!, Cell Reports
https://www.bakerlab.org/wp-content/uploads/2022/10/1-s2.0-S2211124722014012-main.pdf, PDF},
doi = {10.1016/j.celrep.2022.111545},
year = {2022},
date = {2022-10-25},
journal = {Cell Reports},
abstract = {Cellular signaling by fibroblast growth factor receptors (FGFRs) is a highly regulated process mediated by specific interactions between distinct subsets of fibroblast growth factor (FGF) ligands and two FGFR isoforms generated by alternative splicing: an epithelial b- and mesenchymal c-isoforms. Here, we investigate the properties of a mini-protein, mb7, developed by an in silico design strategy to bind to the ligand-binding region of FGFR2. We describe structural, biophysical, and cellular analyses demonstrating that mb7 binds with high affinity to the c-isoforms of FGFR, resulting in inhibition of cellular signaling induced by a subset of FGFs that preferentially activate c-isoforms of FGFR. Notably, as mb7 blocks interaction between FGFR with Klotho proteins, it functions as an antagonist of the metabolic hormones FGF19 and FGF21, providing mechanistic insights and strategies for the development of therapeutics for diseases driven by aberrantly activated FGFRs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sen, Neeladri and Anishchenko, Ivan and Bordin N and Sillitoe, Ian and Velankar, Sameer and Baker, David and Orengo, Christine
Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs Journal Article
In: Briefings in Bioinformatics, 2022.
@article{Sen2022,
title = {Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs},
author = {Sen, Neeladri
and Anishchenko, Ivan
and Bordin N
and Sillitoe, Ian
and Velankar, Sameer
and Baker, David
and Orengo, Christine},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294430/},
doi = {10.1093/bib/bbac187},
year = {2022},
date = {2022-07-18},
journal = {Briefings in Bioinformatics},
abstract = {Mutations in human proteins lead to diseases. The structure of these proteins can help understand the mechanism of such diseases and develop therapeutics against them. With improved deep learning techniques, such as RoseTTAFold and AlphaFold, we can predict the structure of proteins even in the absence of structural homologs. We modeled and extracted the domains from 553 disease-associated human proteins without known protein structures or close homologs in the Protein Databank. We noticed that the model quality was higher and the Root mean square deviation (RMSD) lower between AlphaFold and RoseTTAFold models for domains that could be assigned to CATH families as compared to those which could only be assigned to Pfam families of unknown structure or could not be assigned to either. We predicted ligand-binding sites, protein-protein interfaces and conserved residues in these predicted structures. We then explored whether the disease-associated missense mutations were in the proximity of these predicted functional sites, whether they destabilized the protein structure based on ddG calculations or whether they were predicted to be pathogenic. We could explain 80% of these disease-associated mutations based on proximity to functional sites, structural destabilization or pathogenicity. When compared to polymorphisms, a larger percentage of disease-associated missense mutations were buried, closer to predicted functional sites, predicted as destabilizing and pathogenic. Usage of models from the two state-of-the-art techniques provide better confidence in our predictions, and we explain 93 additional mutations based on RoseTTAFold models which could not be explained based solely on AlphaFold models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Macé, Kévin and Vadakkepat, Abhinav K. and Redzej, Adam and Lukoyanova, Natalya and Oomen, Clasien and Braun, Nathalie and Ukleja, Marta and Lu, Fang and Costa, Tiago R. D. and Orlova, Elena V. and Baker, David and Cong, Qian and Waksman, Gabriel
Cryo-EM structure of a type IV secretion system Journal Article
In: Nature, 2022.
@article{Macé2022,
title = {Cryo-EM structure of a type IV secretion system},
author = {Macé, Kévin
and Vadakkepat, Abhinav K.
and Redzej, Adam
and Lukoyanova, Natalya
and Oomen, Clasien
and Braun, Nathalie
and Ukleja, Marta
and Lu, Fang
and Costa, Tiago R. D.
and Orlova, Elena V.
and Baker, David
and Cong, Qian
and Waksman, Gabriel},
url = {https://www.nature.com/articles/s41586-022-04859-y, Nature
https://www.bakerlab.org/wp-content/uploads/2022/08/Mace2022s41586-022-04859-y.pdf, PDF},
doi = {10.1038/s41586-022-04859-y},
year = {2022},
date = {2022-07-01},
urldate = {2022-07-01},
journal = {Nature},
abstract = {Bacterial conjugation is the fundamental process of unidirectional transfer of DNAs, often plasmid DNAs, from a donor cell to a recipient cell1. It is the primary means by which antibiotic resistance genes spread among bacterial populations2,3. In Gram-negative bacteria, conjugation is mediated by a large transport apparatus—the conjugative type IV secretion system (T4SS)—produced by the donor cell and embedded in both its outer and inner membranes. The T4SS also elaborates a long extracellular filament—the conjugative pilus—that is essential for DNA transfer4,5. Here we present a high-resolution cryo-electron microscopy (cryo-EM) structure of a 2.8 megadalton T4SS complex composed of 92 polypeptides representing 8 of the 10 essential T4SS components involved in pilus biogenesis. We added the two remaining components to the structural model using co-evolution analysis of protein interfaces, to enable the reconstitution of the entire system including the pilus. This structure describes the exceptionally large protein–protein interaction network required to assemble the many components that constitute a T4SS and provides insights on the unique mechanism by which they elaborate pili.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Sarah L. Lovelock, Rebecca Crawshaw, Sophie Basler, Colin Levy, David Baker, Donald Hilvert, Anthony P. Green
The road to fully programmable protein catalysis Journal Article
In: Nature, 2022.
@article{Lovelock2022,
title = {The road to fully programmable protein catalysis},
author = {Sarah L. Lovelock and Rebecca Crawshaw and Sophie Basler and Colin Levy and David Baker and Donald Hilvert and Anthony P. Green
},
url = {https://www.nature.com/articles/s41586-022-04456-z, Nature
https://www.bakerlab.org/wp-content/uploads/2022/06/s41586-022-04456-z.pdf, Download PDF},
doi = {10.1038/s41586-022-04456-z},
year = {2022},
date = {2022-06-01},
journal = {Nature},
abstract = {The ability to design efficient enzymes from scratch would have a profound effect on chemistry, biotechnology and medicine. Rapid progress in protein engineering over the past decade makes us optimistic that this ambition is within reach. The development of artificial enzymes containing metal cofactors and noncanonical organocatalytic groups shows how protein structure can be optimized to harness the reactivity of nonproteinogenic elements. In parallel, computational methods have been used to design protein catalysts for diverse reactions on the basis of fundamental principles of transition state stabilization. Although the activities of designed catalysts have been quite low, extensive laboratory evolution has been used to generate efficient enzymes. Structural analysis of these systems has revealed the high degree of precision that will be needed to design catalysts with greater activity. To this end, emerging protein design methods, including deep learning, hold particular promise for improving model accuracy. Here we take stock of key developments in the field and highlight new opportunities for innovation that should allow us to transition beyond the current state of the art and enable the robust design of biocatalysts to address societal needs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Yao, Sicong, Moyer, Adam, Zheng, Yiwu, Shen, Yang, Meng, Xiaoting, Yuan, Chong, Zhao, Yibing, Yao, Hongwei, Baker, David, Wu, Chuanliu
De novo design and directed folding of disulfide-bridged peptide heterodimers Journal Article
In: Nature Communications, 2022.
@article{Yao2022,
title = {De novo design and directed folding of disulfide-bridged peptide heterodimers},
author = {Yao, Sicong and Moyer, Adam and Zheng, Yiwu and Shen, Yang and Meng, Xiaoting and Yuan, Chong and Zhao, Yibing and Yao, Hongwei and Baker, David and Wu, Chuanliu},
url = {https://www.nature.com/articles/s41467-022-29210-x, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2022/03/Yao_etal_NatComms2022_Design_of_directed_folding_of_disulfile_bridged_peptide_heterodimers.pdf, Download PDF},
year = {2022},
date = {2022-03-22},
urldate = {2022-03-22},
journal = {Nature Communications},
abstract = {Peptide heterodimers are prevalent in nature, which are not only functional macromolecules but molecular tools for chemical and synthetic biology. Computational methods have also been developed to design heterodimers of advanced functions. However, these peptide heterodimers are usually formed through noncovalent interactions, which are prone to dissociate and subject to concentration-dependent nonspecific aggregation. Heterodimers crosslinked with interchain disulfide bonds are more stable, but it represents a formidable challenge for both the computational design of heterodimers and the manipulation of disulfide pairing for heterodimer synthesis and applications. Here, we report the design, synthesis and application of interchain disulfide-bridged peptide heterodimers with mutual orthogonality by combining computational de novo designs with a directed disulfide pairing strategy. These heterodimers can be used as not only scaffolds for generating functional molecules but chemical tools or building blocks for protein labeling and construction of crosslinking hybrids. This study thus opens the door for using this unexplored dimeric structure space for many biological applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Singer, Jedediah M., Novotney, Scott, Strickland, Devin, Haddox, Hugh K., Leiby, Nicholas, Rocklin, Gabriel J., Chow, Cameron M., Roy, Anindya, Bera, Asim K., Motta, Francis C., Cao, Longxing, Strauch, Eva-Maria, Chidyausiku, Tamuka M., Ford, Alex, Ho, Ethan, Zaitzeff, Alexander, Mackenzie, Craig O., Eramian, Hamed, DiMaio, Frank, Grigoryan, Gevorg, Vaughn, Matthew, Stewart, Lance J., Baker, David, Klavins, Eric
Large-scale design and refinement of stable proteins using sequence-only models Journal Article
In: PLoS ONE, 2022.
@article{Singer2022,
title = {Large-scale design and refinement of stable proteins using sequence-only models},
author = {Singer, Jedediah M. and Novotney, Scott and Strickland, Devin and Haddox, Hugh K. and Leiby, Nicholas and Rocklin, Gabriel J. and Chow, Cameron M. and Roy, Anindya and Bera, Asim K. and Motta, Francis C. and Cao, Longxing and Strauch, Eva-Maria and Chidyausiku, Tamuka M. and Ford, Alex and Ho, Ethan and Zaitzeff, Alexander and Mackenzie, Craig O. and Eramian, Hamed and DiMaio, Frank and Grigoryan, Gevorg and Vaughn, Matthew and Stewart, Lance J. and Baker, David and Klavins, Eric
},
doi = {doi.org/10.1371/journal.pone.0265020},
year = {2022},
date = {2022-03-14},
urldate = {2022-03-14},
journal = {PLoS ONE},
abstract = {Engineered proteins generally must possess a stable structure in order to achieve their designed function. Stable designs, however, are astronomically rare within the space of all possible amino acid sequences. As a consequence, many designs must be tested computationally and experimentally in order to find stable ones, which is expensive in terms of time and resources. Here we use a high-throughput, low-fidelity assay to experimentally evaluate the stability of approximately 200,000 novel proteins. These include a wide range of sequence perturbations, providing a baseline for future work in the field. We build a neural network model that predicts protein stability given only sequences of amino acids, and compare its performance to the assayed values. We also report another network model that is able to generate the amino acid sequences of novel stable proteins given requested secondary sequences. Finally, we show that the predictive model—despite weaknesses including a noisy data set—can be used to substantially increase the stability of both expert-designed and model-generated proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Mike T. Veling, Dan T. Nguyen, Nicole N. Thadani, Michela E. Oster, Nathan J. Rollins, Kelly P. Brock, Neville P. Bethel, Samuel Lim, David Baker, Jeffrey C. Way, Debora S. Marks, Roger L. Chang, and Pamela A. Silver
Natural and Designed Proteins Inspired by Extremotolerant Organisms Can Form Condensates and Attenuate Apoptosis in Human Cells Journal Article
In: ACS Synthetic Biology, 2022.
@article{Veling2022,
title = {Natural and Designed Proteins Inspired by Extremotolerant Organisms Can Form Condensates and Attenuate Apoptosis in Human Cells},
author = {Mike T. Veling and Dan T. Nguyen and Nicole N. Thadani and Michela E. Oster and Nathan J. Rollins and Kelly P. Brock and Neville P. Bethel and Samuel Lim, David Baker and Jeffrey C. Way and Debora S. Marks and Roger L. Chang and and Pamela A. Silver},
url = {https://pubs.acs.org/doi/abs/10.1021/acssynbio.1c00572, ACS Synthetic Biology
https://www.bakerlab.org/wp-content/uploads/2022/02/Veling_etal_ACSSynBio_Feb2022.pdf, Download PDF},
doi = {10.1021/acssynbio.1c00572},
year = {2022},
date = {2022-02-18},
journal = {ACS Synthetic Biology},
abstract = {Many organisms can survive extreme conditions and successfully recover to normal life. This extremotolerant behavior has been attributed in part to repetitive, amphipathic, and intrinsically disordered proteins that are upregulated in the protected state. Here, we assemble a library of approximately 300 naturally occurring and designed extremotolerance-associated proteins to assess their ability to protect human cells from chemically induced apoptosis. We show that several proteins from tardigrades, nematodes, and the Chinese giant salamander are apoptosis-protective. Notably, we identify a region of the human ApoE protein with similarity to extremotolerance-associated proteins that also protects against apoptosis. This region mirrors the phase separation behavior seen with such proteins, like the tardigrade protein CAHS2. Moreover, we identify a synthetic protein, DHR81, that shares this combination of elevated phase separation propensity and apoptosis protection. Finally, we demonstrate that driving protective proteins into the condensate state increases apoptosis protection, and highlights the ability of DHR81 condensates to sequester caspase-7. Taken together, this work draws a link between extremotolerance-associated proteins, condensate formation, and designing human cellular protection.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Taylor H. Nguyen, Galen Dods, Mariana Gomez-Schiavon, Muziyue Wu, Zibo Chen, Ryan Kibler, David Baker, Hana El-Samad, Andrew H. Ng
In: GEN Biotechnology, 2022.
@article{Nguyen2022,
title = {Competitive Displacement of De Novo Designed HeteroDimers Can Reversibly Control Protein–Protein Interactions and Implement Feedback in Synthetic Circuits},
author = {Taylor H. Nguyen and Galen Dods and Mariana Gomez-Schiavon and Muziyue Wu and Zibo Chen and Ryan Kibler and David Baker and Hana El-Samad and Andrew H. Ng},
url = {https://www.liebertpub.com/doi/10.1089/genbio.2021.0011, GEN Biotechnology
},
doi = {10.1089/genbio.2021.0011},
year = {2022},
date = {2022-02-16},
urldate = {2022-02-16},
journal = {GEN Biotechnology},
abstract = {Dynamic dimerization is a common regulatory interaction between biological molecules, underpinning many signaling functions. Because of its ubiquity, many biological engineering efforts have focused on building dimerizing proteins, such as the SYNZIPs and de novo Designed HeteroDimers (DHDs). Using the DHDs as a model system, we show that low-affinity protein interactions can be competitively displaced by a high-affinity “dominant negative” heterodimer. We demonstrate the utility of this signaling motif by using competitive displacement to implement negative feedback in a synthetic circuit. Competitive displacement could be extended to other heterodimer systems to expand the functionality of protein circuits and enable new biotechnology applications.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Linder, Johannes, La Fleur, Alyssa, Chen, Zibo, Ljubetič, Ajasja, Baker, David, Kannan, Sreeram, Seelig, Georg
Interpreting neural networks for biological sequences by learning stochastic masks Journal Article
In: Nature Machine Intelligence, 2022.
@article{Linder2022,
title = {Interpreting neural networks for biological sequences by learning stochastic masks},
author = {Linder, Johannes and La Fleur, Alyssa and Chen, Zibo and Ljubetič, Ajasja and Baker, David and Kannan, Sreeram and Seelig, Georg},
url = {https://www.nature.com/articles/s42256-021-00428-6, Nature Machine Intelligence},
doi = {10.1038/s42256-021-00428-6},
year = {2022},
date = {2022-01-25},
urldate = {2022-01-25},
journal = {Nature Machine Intelligence},
abstract = {Sequence-based neural networks can learn to make accurate predictions from large biological datasets, but model interpretation remains challenging. Many existing feature attribution methods are optimized for continuous rather than discrete input patterns and assess individual feature importance in isolation, making them ill-suited for interpreting nonlinear interactions in molecular sequences. Here, building on work in computer vision and natural language processing, we developed an approach based on deep learning—scrambler networks—wherein the most important sequence positions are identified with learned input masks. Scramblers learn to predict position-specific scoring matrices where unimportant nucleotides or residues are scrambled by raising their entropy. We apply scramblers to interpret the effects of genetic variants, uncover nonlinear interactions between cis-regulatory elements, explain binding specificity for protein–protein interactions, and identify structural determinants of de novo-designed proteins. We show that scramblers enable efficient attribution across large datasets and result in high-quality explanations, often outperforming state-of-the-art methods.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Toshifumi Fujioka, Nobutaka Numoto, Hiroyuki Akama, Kola Shilpa, Michiko Oka, Prodip K. Roy, Yarkali Krishna, Nobutoshi Ito, David Baker, Masayuki Oda, Fujie Tanaka
Varying the Directionality of Protein Catalysts for Aldol and Retro-Aldol Reactions Journal Article
In: ChemBioChem, vol. 23, no. 2, pp. e202100435, 2022.
@article{https://doi.org/10.1002/cbic.202100435,
title = {Varying the Directionality of Protein Catalysts for Aldol and Retro-Aldol Reactions},
author = {Toshifumi Fujioka and Nobutaka Numoto and Hiroyuki Akama and Kola Shilpa and Michiko Oka and Prodip K. Roy and Yarkali Krishna and Nobutoshi Ito and David Baker and Masayuki Oda and Fujie Tanaka},
url = {https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cbic.202100435},
doi = {https://doi.org/10.1002/cbic.202100435},
year = {2022},
date = {2022-01-01},
journal = {ChemBioChem},
volume = {23},
number = {2},
pages = {e202100435},
abstract = {Abstract Natural aldolase enzymes and created retro-aldolase protein catalysts often catalyze both aldol and retro-aldol reactions depending on the concentrations of the reactants and the products. Here, we report that the directionality of protein catalysts can be altered by replacing one amino acid. The protein catalyst derived from a scaffold of a previously reported retro-aldolase catalyst, catalyzed aldol reactions more efficiently than the previously reported retro-aldolase catalyst. The retro-aldolase catalyst efficiently catalyzed the retro-aldol reaction but was less efficient in catalyzing the aldol reaction. The results indicate that protein catalysts with varying levels of directionality in usually reversibly catalyzed aldol and retro-aldol reactions can be generated from the same protein scaffold.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Brian L. Trippe, Buwei Huang, Erika A. DeBenedictis, Brian Coventry, Nicholas Bhattacharya, Kevin K. Yang, David Baker, Lorin Crawford
Randomized gates eliminate bias in sort-seq assays Journal Article
In: Protein Science, vol. 31, no. 9, pp. e4401, 2022.
@article{https://doi.org/10.1002/pro.4401,
title = {Randomized gates eliminate bias in sort-seq assays},
author = {Brian L. Trippe and Buwei Huang and Erika A. DeBenedictis and Brian Coventry and Nicholas Bhattacharya and Kevin K. Yang and David Baker and Lorin Crawford},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pro.4401},
doi = {https://doi.org/10.1002/pro.4401},
year = {2022},
date = {2022-01-01},
journal = {Protein Science},
volume = {31},
number = {9},
pages = {e4401},
abstract = {Abstract Sort-seq assays are a staple of the biological engineering toolkit, allowing researchers to profile many groups of cells based on any characteristic that can be tied to fluorescence. However, current approaches, which segregate cells into bins deterministically based on their measured fluorescence, introduce systematic bias. We describe a surprising result: one can obtain unbiased estimates by incorporating randomness into sorting. We validate this approach in simulation and experimentally, and describe extensions for both estimating group level variances and for using multi-bin sorters.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2021
FROM THE LAB
Anishchenko, Ivan and Pellock, Samuel J. and Chidyausiku, Tamuka M. and Ramelot, Theresa A. and Ovchinnikov, Sergey and Hao, Jingzhou and Bafna, Khushboo and Norn, Christoffer and Kang, Alex and Bera, Asim K. and DiMaio, Frank and Carter, Lauren and Chow, Cameron M. and Montelione, Gaetano T. and Baker, David
De novo protein design by deep network hallucination Journal Article
In: Nature, 2021.
@article{Anishchenko2021,
title = {De novo protein design by deep network hallucination},
author = {Anishchenko, Ivan
and Pellock, Samuel J.
and Chidyausiku, Tamuka M.
and Ramelot, Theresa A.
and Ovchinnikov, Sergey
and Hao, Jingzhou
and Bafna, Khushboo
and Norn, Christoffer
and Kang, Alex
and Bera, Asim K.
and DiMaio, Frank
and Carter, Lauren
and Chow, Cameron M.
and Montelione, Gaetano T.
and Baker, David},
url = {https://www.nature.com/articles/s41586-021-04184-w
https://www.bakerlab.org/wp-content/uploads/2022/01/Anishchenko_etal_Nature2021_DeepNetworkHallucination.pdf},
doi = {10.1038/s41586-021-04184-w},
year = {2021},
date = {2021-12-01},
urldate = {2021-12-01},
journal = {Nature},
abstract = {There has been considerable recent progress in protein structure prediction using deep neural networks to predict inter-residue distances from amino acid sequences1–3. Here we investigate whether the information captured by such networks is sufficiently rich to generate new folded proteins with sequences unrelated to those of the naturally occurring proteins used in training the models. We generate random amino acid sequences, and input them into the trRosetta structure prediction network to predict starting residue–residue distance maps, which, as expected, are quite featureless. We then carry out Monte Carlo sampling in amino acid sequence space, optimizing the contrast (Kullback–Leibler divergence) between the inter-residue distance distributions predicted by the network and background distributions averaged over all proteins. Optimization from different random starting points resulted in novel proteins spanning a wide range of sequences and predicted structures. We obtained synthetic genes encoding 129 of the network-‘hallucinated’ sequences, and expressed and purified the proteins in Escherichia coli; 27 of the proteins yielded monodisperse species with circular dichroism spectra consistent with the hallucinated structures. We determined the three-dimensional structures of three of the hallucinated proteins, two by X-ray crystallography and one by NMR, and these closely matched the hallucinated models. Thus, deep networks trained to predict native protein structures from their sequences can be inverted to design new proteins, and such networks and methods should contribute alongside traditional physics-based models to the de novo design of proteins with new functions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ian R. Humphreys, Jimin Pei, Minkyung Baek, Aditya Krishnakumar, Ivan Anishchenko, Sergey Ovchinnikov, Jing Zhang, Travis J. Ness, Sudeep Banjade, Saket R. Bagde, Viktoriya G. Stancheva, Xiao-Han Li, Kaixian Liu, Zhi Zheng, Daniel J. Barrero, Upasana Roy, Jochen Kuper, Israel S. Fernández, Barnabas Szakal, Dana Branzei, Josep Rizo, Caroline Kisker, Eric C. Greene, Sue Biggins, Scott Keeney, Elizabeth A. Miller, J. Christopher Fromme, Tamara L. Hendrickson, Qian Cong, David Baker
Computed structures of core eukaryotic protein complexes Journal Article
In: Science, 2021.
@article{Humphreys2012,
title = {Computed structures of core eukaryotic protein complexes},
author = {Ian R. Humphreys and Jimin Pei and Minkyung Baek and Aditya Krishnakumar and Ivan Anishchenko and Sergey Ovchinnikov and Jing Zhang and Travis J. Ness and Sudeep Banjade and Saket R. Bagde and Viktoriya G. Stancheva and Xiao-Han Li and Kaixian Liu and Zhi Zheng and Daniel J. Barrero and Upasana Roy and Jochen Kuper and Israel S. Fernández and Barnabas Szakal and Dana Branzei and Josep Rizo and Caroline Kisker and Eric C. Greene and Sue Biggins and Scott Keeney and Elizabeth A. Miller and J. Christopher Fromme and Tamara L. Hendrickson and Qian Cong and David Baker},
url = {https://www.science.org/doi/10.1126/science.abm4805, Science
https://www.bakerlab.org/wp-content/uploads/2022/06/science.abm4805.pdf, Download PDF},
doi = {10.1126/science.abm4805},
year = {2021},
date = {2021-11-11},
urldate = {2021-11-11},
journal = {Science},
abstract = {Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coevolution analysis and deep-learning-based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes within the Saccharomyces cerevisiae proteome. We use a combination of RoseTTAFold and AlphaFold to screen through paired multiple sequence alignments for 8.3 million pairs of yeast proteins, identify 1,505 likely to interact, and build structure models for 106 previously unidentified assemblies and 806 that have not been structurally characterized. These complexes, which have as many as 5 subunits, play roles in almost all key processes in eukaryotic cells and provide broad insights into biological function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Woodall, Nicholas B. and Weinberg, Zara and Park, Jesslyn and Busch, Florian and Johnson, Richard S. and Feldbauer, Mikayla J. and Murphy, Michael and Ahlrichs, Maggie and Yousif, Issa and MacCoss, Michael J. and Wysocki, Vicki H. and El-Samad, Hana and Baker, David
De novo design of tyrosine and serine kinase-driven protein switches Journal Article
In: Nature Structural & Molecular Biology, 2021.
@article{Woodall2021,
title = {De novo design of tyrosine and serine kinase-driven protein switches},
author = {Woodall, Nicholas B.
and Weinberg, Zara
and Park, Jesslyn
and Busch, Florian
and Johnson, Richard S.
and Feldbauer, Mikayla J.
and Murphy, Michael
and Ahlrichs, Maggie
and Yousif, Issa
and MacCoss, Michael J.
and Wysocki, Vicki H.
and El-Samad, Hana
and Baker, David},
url = {https://www.nature.com/articles/s41594-021-00649-8, Nature Structural & Molecular Biology
https://www.bakerlab.org/wp-content/uploads/2021/09/De-novo-design-of-tyrosine-and-serine-kinase-driven-protein-switches.pdf, Download PDF},
doi = {10.1038/s41594-021-00649-8},
year = {2021},
date = {2021-09-13},
urldate = {2021-09-13},
journal = {Nature Structural & Molecular Biology},
abstract = {Kinases play central roles in signaling cascades, relaying information from the outside to the inside of mammalian cells. De novo designed protein switches capable of interfacing with tyrosine kinase signaling pathways would open new avenues for controlling cellular behavior, but, so far, no such systems have been described. Here we describe the de novo design of two classes of protein switch that link phosphorylation by tyrosine and serine kinases to protein-protein association. In the first class, protein-protein association is required for phosphorylation by the kinase, while in the second class, kinase activity drives protein-protein association. We design systems that couple protein binding to kinase activity on the immunoreceptor tyrosine-based activation motif central to T-cell signaling, and kinase activity to reconstitution of green fluorescent protein fluorescence from fragments and the inhibition of the protease calpain. The designed switches are reversible and function in vitro and in cells with up to 40-fold activation of switching by phosphorylation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Minkyung Baek, Ivan Anishchenko, Hahnbeom Park, Ian R. Humphreys, David Baker
Protein oligomer modeling guided by predicted inter-chain contacts in CASP14 Journal Article
In: Proteins, 2021.
@article{Baek2021b,
title = {Protein oligomer modeling guided by predicted inter-chain contacts in CASP14},
author = {Minkyung Baek and Ivan Anishchenko and Hahnbeom Park and Ian R. Humphreys and David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.26197, Proteins},
doi = {10.1002/prot.26197},
year = {2021},
date = {2021-07-29},
urldate = {2021-07-29},
journal = {Proteins},
abstract = {For CASP14, we developed deep learning-based methods for predicting homo-oligomeric and hetero-oligomeric contacts and used them for oligomer modeling. To build structure models, we developed an oligomer structure generation method that utilizes predicted inter-chain contacts to guide iterative restrained minimization from random backbone structures. We supplemented this gradient-based fold-and-dock method with template-based and ab initio docking approaches using deep learning-based subunit predictions on 29 assembly targets. These methods produced oligomer models with summed Z-scores 5.5 units higher than the next best group, with the fold-and-dock method having the best relative performance. Over the eight targets for which this method was used, the best of the five submitted models had average oligomer TM-score of 0.71 (average oligomer TM-score of the next best group: 0.64), and explicit modeling of inter-subunit interactions improved modeling of six out of 40 individual domains (ΔGDT-TS > 2.0).
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Baek, Minkyung and DiMaio, Frank and Anishchenko, Ivan and Dauparas, Justas and Ovchinnikov, Sergey and Lee, Gyu Rie and Wang, Jue and Cong, Qian and Kinch, Lisa N. and Schaeffer, R. Dustin and Millán, Claudia and Park, Hahnbeom and Adams, Carson and Glassman, Caleb R. and DeGiovanni, Andy and Pereira, Jose H. and Rodrigues, Andria V. and van Dijk, Alberdina A. and Ebrecht, Ana C. and Opperman, Diederik J. and Sagmeister, Theo and Buhlheller, Christoph and Pavkov-Keller, Tea and Rathinaswamy, Manoj K. and Dalwadi, Udit and Yip, Calvin K. and Burke, John E. and Garcia, K. Christopher and Grishin, Nick V. and Adams, Paul D. and Read, Randy J. and Baker, David
Accurate prediction of protein structures and interactions using a three-track neural network Journal Article
In: Science, 2021.
@article{Baek2021,
title = {Accurate prediction of protein structures and interactions using a three-track neural network},
author = {Baek, Minkyung
and DiMaio, Frank
and Anishchenko, Ivan
and Dauparas, Justas
and Ovchinnikov, Sergey
and Lee, Gyu Rie
and Wang, Jue
and Cong, Qian
and Kinch, Lisa N.
and Schaeffer, R. Dustin
and Millán, Claudia
and Park, Hahnbeom
and Adams, Carson
and Glassman, Caleb R.
and DeGiovanni, Andy
and Pereira, Jose H.
and Rodrigues, Andria V.
and van Dijk, Alberdina A.
and Ebrecht, Ana C.
and Opperman, Diederik J.
and Sagmeister, Theo
and Buhlheller, Christoph
and Pavkov-Keller, Tea
and Rathinaswamy, Manoj K.
and Dalwadi, Udit
and Yip, Calvin K.
and Burke, John E.
and Garcia, K. Christopher
and Grishin, Nick V.
and Adams, Paul D.
and Read, Randy J.
and Baker, David},
url = {http://science.sciencemag.org/content/early/2021/07/14/science.abj8754, Science
https://www.ipd.uw.edu/wp-content/uploads/2021/07/Baek_etal_Science2021_RoseTTAFold.pdf, Download PDF},
doi = {10.1126/science.abj8754},
year = {2021},
date = {2021-07-15},
urldate = {2021-07-15},
journal = {Science},
abstract = {DeepMind presented remarkably accurate predictions at the recent CASP14 protein structure prediction assessment conference. We explored network architectures incorporating related ideas and obtained the best performance with a three-track network in which information at the 1D sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging X-ray crystallography and cryo-EM structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches which require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Nobuyasu Koga, Rie Koga, Gaohua Liu, Javier Castellanos, Gaetano T. Montelione, David Baker
Role of backbone strain in de novo design of complex α/β protein structures Journal Article
In: Nature Communications, 2021.
@article{Koga2021,
title = {Role of backbone strain in de novo design of complex α/β protein structures},
author = {Nobuyasu Koga and Rie Koga and Gaohua Liu and Javier Castellanos and Gaetano T. Montelione and David Baker
},
url = {https://www.nature.com/articles/s41467-021-24050-7, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2021/07/Koga_NatComm2021.pdf, Download PDF},
doi = {10.1038/s41467-021-24050-7},
year = {2021},
date = {2021-06-24},
urldate = {2021-06-24},
journal = {Nature Communications},
abstract = {We previously elucidated principles for designing ideal proteins with completely consistent local and non-local interactions which have enabled the design of a wide range of new αβ-proteins with four or fewer β-strands. The principles relate local backbone structures to supersecondary-structure packing arrangements of α-helices and β-strands. Here, we test the generality of the principles by employing them to design larger proteins with five- and six- stranded β-sheets flanked by α-helices. The initial designs were monomeric in solution with high thermal stability, and the nuclear magnetic resonance (NMR) structure of one was close to the design model, but for two others the order of strands in the β-sheet was swapped. Investigation into the origins of this strand swapping suggested that the global structures of the design models were more strained than the NMR structures. We incorporated explicit consideration of global backbone strain into the design methodology, and succeeded in designing proteins with the intended unswapped strand arrangements. These results illustrate the value of experimental structure determination in guiding improvement of de novo design, and the importance of consistency between local, supersecondary, and global tertiary interactions in determining protein topology. The augmented set of principles should inform the design of larger functional proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Case, James Brett and Chen, Rita E. and Cao, Longxing and Ying, Baoling and Winkler, Emma S. and Johnson, Max and Goreshnik, Inna and Pham, Minh N. and Shrihari, Swathi and Kafai, Natasha M. and Bailey, Adam L. and Xie, Xuping and Shi, Pei-Yong and Ravichandran, Rashmi and Carter, Lauren and Stewart, Lance and Baker, David and Diamond, Michael S.
Ultrapotent miniproteins targeting the SARS-CoV-2 receptor-binding domain protect against infection and disease Journal Article
In: Cell Host & Microbe, 2021.
@article{Case2021,
title = {Ultrapotent miniproteins targeting the SARS-CoV-2 receptor-binding domain protect against infection and disease},
author = {Case, James Brett
and Chen, Rita E.
and Cao, Longxing
and Ying, Baoling
and Winkler, Emma S.
and Johnson, Max
and Goreshnik, Inna
and Pham, Minh N.
and Shrihari, Swathi
and Kafai, Natasha M.
and Bailey, Adam L.
and Xie, Xuping
and Shi, Pei-Yong
and Ravichandran, Rashmi
and Carter, Lauren
and Stewart, Lance
and Baker, David
and Diamond, Michael S.},
url = {https://www.cell.com/cell-host-microbe/fulltext/S1931-3128(21)00286-9, Cell Host & Microbe
https://www.bakerlab.org/wp-content/uploads/2021/07/Case_etal_CellHostMicrobe_Ultrapotent-miniproteins-targeting-the-SARS-CoV-2-receptor-binding-domain-protect-against-infection-and-disease.pdf, Download PDF},
doi = {10.1016/j.chom.2021.06.008},
year = {2021},
date = {2021-06-18},
urldate = {2021-06-18},
journal = {Cell Host & Microbe},
abstract = {Despite the introduction of public health measures and spike protein-based vaccines to mitigate the COVID-19 pandemic, SARS-CoV-2 infections and deaths continue to have a global impact. Previously, we used a structural design approach to develop picomolar range miniproteins targeting the SARS-CoV-2 spike receptor binding domain. Here, we investigated the capacity of modified versions of one lead miniprotein, LCB1, to protect against SARS-CoV-2-mediated lung disease in mice. Systemic administration of LCB1-Fc reduced viral burden, diminished immune cell infiltration and inflammation, and completely prevented lung disease and pathology. A single intranasal dose of LCB1v1.3 reduced SARS-CoV-2 infection in the lung when given as many as five days before or two days after virus inoculation. Importantly, LCB1v1.3 protected in vivo against a historical strain (WA1/2020), an emerging B.1.1.7 strain, and a strain encoding key E484K and N501Y spike protein substitutions. These data support development of LCB1v1.3 for prevention or treatment of SARS-CoV-2 infection.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Vulovic, Ivan, Yao, Qing, Park, Young-Jun, Courbet, Alexis, Norris, Andrew, Busch, Florian, Sahasrabuddhe, Aniruddha, Merten, Hannes, Sahtoe, Danny D., Ueda, George, Fallas, Jorge A., Weaver, Sara J., Hsia, Yang, Langan, Robert A., Pl"uckthun, Andreas, Wysocki, Vicki H., Veesler, David, Jensen, Grant J., Baker, David
Generation of ordered protein assemblies using rigid three-body fusion Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 23, 2021.
@article{Vulovic2021,
title = {Generation of ordered protein assemblies using rigid three-body fusion},
author = {Vulovic, Ivan and Yao, Qing and Park, Young-Jun and Courbet, Alexis and Norris, Andrew and Busch, Florian and Sahasrabuddhe, Aniruddha and Merten, Hannes and Sahtoe, Danny D. and Ueda, George and Fallas, Jorge A. and Weaver, Sara J. and Hsia, Yang and Langan, Robert A. and Pl{"u}ckthun, Andreas and Wysocki, Vicki H. and Veesler, David and Jensen, Grant J. and Baker, David},
url = {https://www.pnas.org/content/118/23/e2015037118, PNAS
},
doi = {10.1073/pnas.2015037118},
year = {2021},
date = {2021-06-08},
urldate = {2021-06-08},
journal = {Proceedings of the National Academy of Sciences},
volume = {118},
number = {23},
abstract = {Protein nanomaterial design is an emerging discipline with applications in medicine and beyond. A long-standing design approach uses genetic fusion to join protein homo-oligomer subunits via α-helical linkers to form more complex symmetric assemblies, but this method is hampered by linker flexibility and a dearth of geometric solutions. Here, we describe a general computational method for rigidly fusing homo-oligomer and spacer building blocks to generate user-defined architectures that generates far more geometric solutions than previous approaches. The fusion junctions are then optimized using Rosetta to minimize flexibility. We apply this method to design and test 92 dihedral symmetric protein assemblies using a set of designed homodimers and repeat protein building blocks. Experimental validation by native mass spectrometry, small-angle X-ray scattering, and negative-stain single-particle electron microscopy confirms the assembly states for 11 designs. Most of these assemblies are constructed from designed ankyrin repeat proteins (DARPins), held in place on one end by α-helical fusion and on the other by a designed homodimer interface, and we explored their use for cryogenic electron microscopy (cryo-EM) structure determination by incorporating DARPin variants selected to bind targets of interest. Although the target resolution was limited by preferred orientation effects and small scaffold size, we found that the dual anchoring strategy reduced the flexibility of the target-DARPIN complex with respect to the overall assembly, suggesting that multipoint anchoring of binding domains could contribute to cryo-EM structure determination of small proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
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}
}
Hsia, Yang and Mout, Rubul and Sheffler, William and Edman, Natasha I. and Vulovic, Ivan and Park, Young-Jun and Redler, Rachel L. and Bick, Matthew J. and Bera, Asim K. and Courbet, Alexis and Kang, Alex and Brunette, T. J. and Nattermann, Una and Tsai, Evelyn and Saleem, Ayesha and Chow, Cameron M. and Ekiert, Damian and Bhabha, Gira and Veesler, David and Baker, David
Design of multi-scale protein complexes by hierarchical building block fusion Journal Article
In: Nature Communications, 2021.
@article{Hsia2012,
title = {Design of multi-scale protein complexes by hierarchical building block fusion},
author = {Hsia, Yang
and Mout, Rubul
and Sheffler, William
and Edman, Natasha I.
and Vulovic, Ivan
and Park, Young-Jun
and Redler, Rachel L.
and Bick, Matthew J.
and Bera, Asim K.
and Courbet, Alexis
and Kang, Alex
and Brunette, T. J.
and Nattermann, Una
and Tsai, Evelyn
and Saleem, Ayesha
and Chow, Cameron M.
and Ekiert, Damian
and Bhabha, Gira
and Veesler, David
and Baker, David},
url = {https://www.nature.com/articles/s41467-021-22276-z, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2021/04/Hsia_etal_NatComms_WORMS.pdf, Download PDF},
doi = {10.1038/s41467-021-22276-z},
year = {2021},
date = {2021-04-16},
urldate = {2021-04-16},
journal = {Nature Communications},
abstract = {A systematic and robust approach to generating complex protein nanomaterials would have broad utility. We develop a hierarchical approach to designing multi-component protein assemblies from two classes of modular building blocks: designed helical repeat proteins (DHRs) and helical bundle oligomers (HBs). We first rigidly fuse DHRs to HBs to generate a large library of oligomeric building blocks. We then generate assemblies with cyclic, dihedral, and point group symmetries from these building blocks using architecture guided rigid helical fusion with new software named WORMS. X-ray crystallography and cryo-electron microscopy characterization show that the hierarchical design approach can accurately generate a wide range of assemblies, including a 43 nm diameter icosahedral nanocage. The computational methods and building block sets described here provide a very general route to de novo designed protein nanomaterials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Divine, Robby, Dang, Ha V., Ueda, George, Fallas, Jorge A., Vulovic, Ivan, Sheffler, William, Saini, Shally, Zhao, Yan Ting, Raj, Infencia Xavier, Morawski, Peter A., Jennewein, Madeleine F., Homad, Leah J., Wan, Yu-Hsin, Tooley, Marti R., Seeger, Franziska, Etemadi, Ali, Fahning, Mitchell L., Lazarovits, James, Roederer, Alex, Walls, Alexandra C., Stewart, Lance, Mazloomi, Mohammadali, King, Neil P., Campbell, Daniel J., McGuire, Andrew T., Stamatatos, Leonidas, Ruohola-Baker, Hannele, Mathieu, Julie, Veesler, David, Baker, David
Designed proteins assemble antibodies into modular nanocages Journal Article
In: Science, vol. 372, no. 6537, 2021.
@article{Divine2021,
title = {Designed proteins assemble antibodies into modular nanocages},
author = {Divine, Robby and Dang, Ha V. and Ueda, George and Fallas, Jorge A. and Vulovic, Ivan and Sheffler, William and Saini, Shally and Zhao, Yan Ting and Raj, Infencia Xavier and Morawski, Peter A. and Jennewein, Madeleine F. and Homad, Leah J. and Wan, Yu-Hsin and Tooley, Marti R. and Seeger, Franziska and Etemadi, Ali and Fahning, Mitchell L. and Lazarovits, James and Roederer, Alex and Walls, Alexandra C. and Stewart, Lance and Mazloomi, Mohammadali and King, Neil P. and Campbell, Daniel J. and McGuire, Andrew T. and Stamatatos, Leonidas and Ruohola-Baker, Hannele and Mathieu, Julie and Veesler, David and Baker, David},
url = {https://science.sciencemag.org/content/372/6537/eabd9994.full.pdf, Science
https://www.bakerlab.org/wp-content/uploads/2021/04/Divine_etal_Science2021_Antibody_nanocages.pdf, Download PDF},
doi = {10.1126/science.abd9994},
year = {2021},
date = {2021-04-02},
urldate = {2021-04-02},
journal = {Science},
volume = {372},
number = {6537},
abstract = {Antibodies are broadly used in therapies and as research tools because they can be generated against a wide range of targets. Efficacy can often be increased by clustering antibodies in multivalent assemblies. Divine et al. designed antibody nanocages from two components: One is an antibody-binding homo-oligomic protein and the other is the antibody itself. Computationally designed proteins drive the assembly of antibody nanocages in a range of architectures, allowing control of the symmetry and the antibody valency. The multivalent display enhances antibody-dependent signaling, and nanocages displaying antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein effectively neutralize pseudovirus.Science, this issue p. eabd9994INTRODUCTIONAntibodies that bind tightly to targets of interest play central roles in biological research and medicine. Clusters of antibodies, typically generated by fusing antibodies to polymers or genetically linking antibody fragments together, can enhance signaling. Currently lacking are approaches for making antibody assemblies with a range of precisely specified architectures and valencies.RATIONALEWe set out to computationally design proteins that assemble antibodies into precise architectures with different valencies and symmetries. We developed an approach to designing proteins that position antibodies or Fc-fusions on the twofold symmetry axes of regular dihedral and polyhedral architectures. We hypothesized that such designs could robustly drive arbitrary antibodies into homogeneous and structurally well-defined nanocages and that such assemblies could have pronounced effects on cell signaling.RESULTSAntibody cage (AbC){textendash}forming designs were created by rigidly fusing antibody constant domain{textendash}binding modules to cyclic oligomers through helical spacer domains such that the symmetry axes of the dimeric antibody and cyclic oligomer are at orientations that generate different dihedral or polyhedral (e.g., tetrahedral, octahedral, or icosahedral) architectures. The junction regions between the connected building blocks were optimized to fold to the designed structures. Synthetic genes encoding the designs were expressed in bacterial cultures; of 48 structurally characterized designs, eight assemblies matched the design models. Successful designs encompass D2 dihedral (three designs), T32 tetrahedral (two designs), O42 octahedral (one design), and I52 icosahedral (two designs) architectures; these contain 2, 6, 12, or 30 antibodies, respectively.We investigated the effects of AbCs on cell signaling. AbCs formed with a death receptor{textendash}targeting antibody induced apoptosis of tumor cell lines that were unaffected by the soluble antibody or the native ligand. Angiopoietin pathway signaling, CD40 signaling, and T cell proliferation were all enhanced by assembling Fc-fusions or antibodies in AbCs. AbC formation also enhanced in vitro viral neutralization of a severe acute respiratory syndrome coronavirus 2 pseudovirus.CONCLUSIONWe have designed multiple antibody cage{textendash}forming proteins that precisely cluster any protein A{textendash}binding antibody into nanocages with controlled valency and geometry. AbCs can be formed with 2, 6, 12, or 30 antibodies simply by mixing the antibody with the corresponding designed protein, without the need for any covalent modification of the antibody. Incorporating receptor binding or virus-neutralizing antibodies into AbCs enhanced their biological activity across a range of cell systems. We expect that our rapid and robust approach for assembling antibodies into homogeneous and ordered nanocages without the need for covalent modification will have broad utility in research and medicine.Designed proteins assemble antibodies into large symmetric architectures.Designed antibody-clustering proteins (light gray) assemble antibodies (purple) into diverse nanocage architectures (top). Antibody nanocages enhance cell signaling compared with free antibodies (bottom).IMAGE: IAN HAYDON, INSTITUTE FOR PROTEIN DESIGNMultivalent display of receptor-engaging antibodies or ligands can enhance their activity. Instead of achieving multivalency by attachment to preexisting scaffolds, here we unite form and function by the computational design of nanocages in which one structural component is an antibody or Fc-ligand fusion and the second is a designed antibody-binding homo-oligomer that drives nanocage assembly. Structures of eight nanocages determined by electron microscopy spanning dihedral, tetrahedral, octahedral, and icosahedral architectures with 2, 6, 12, and 30 antibodies per nanocage, respectively, closely match the corresponding computational models. Antibody nanocages targeting cell surface receptors enhance signaling compared with free antibodies or Fc-fusions in death receptor 5 (DR5){textendash}mediated apoptosis, angiopoietin-1 receptor (Tie2){textendash}mediated angiogenesis, CD40 activation, and T cell proliferation. Nanocage assembly also increases severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pseudovirus neutralization by α-SARS-CoV-2 monoclonal antibodies and Fc{textendash}angiotensin-converting enzyme 2 (ACE2) fusion proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mulligan, Vikram Khipple, Workman, Sean, Sun, Tianjun, Rettie, Stephen, Li, Xinting, Worrall, Liam J., Craven, Timothy W., King, Dustin T., Hosseinzadeh, Parisa, Watkins, Andrew M., Renfrew, P. Douglas, Guffy, Sharon, Labonte, Jason W., Moretti, Rocco, Bonneau, Richard, Strynadka, Natalie C. J., Baker, David
Computationally designed peptide macrocycle inhibitors of New Delhi metallo-β-lactamase 1 Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 12, 2021.
@article{Mulligan2021,
title = {Computationally designed peptide macrocycle inhibitors of New Delhi metallo-β-lactamase 1},
author = {Mulligan, Vikram Khipple and Workman, Sean and Sun, Tianjun and Rettie, Stephen and Li, Xinting and Worrall, Liam J. and Craven, Timothy W. and King, Dustin T. and Hosseinzadeh, Parisa and Watkins, Andrew M. and Renfrew, P. Douglas and Guffy, Sharon and Labonte, Jason W. and Moretti, Rocco and Bonneau, Richard and Strynadka, Natalie C. J. and Baker, David},
url = {https://www.pnas.org/content/118/12/e2012800118.full, PNAS
https://www.bakerlab.org/wp-content/uploads/2021/03/Mulligen_etal_PNAS2021_Macrocycle_inhibitors.pdf, Download PDF},
doi = {10.1073/pnas.2012800118},
year = {2021},
date = {2021-03-23},
urldate = {2021-03-23},
journal = {Proceedings of the National Academy of Sciences},
volume = {118},
number = {12},
abstract = {The rise of antibiotic resistance calls for new therapeutics targeting resistance factors such as the New Delhi metallo-β-lactamase 1 (NDM-1), a bacterial enzyme that degrades β-lactam antibiotics. We present structure-guided computational methods for designing peptide macrocycles built from mixtures of L- and D-amino acids that are able to bind to and inhibit targets of therapeutic interest. Our methods explicitly consider the propensity of a peptide to favor a binding-competent conformation, which we found to predict rank order of experimentally observed IC50 values across seven designed NDM-1- inhibiting peptides. We were able to determine X-ray crystal structures of three of the designed inhibitors in complex with NDM-1, and in all three the conformation of the peptide is very close to the computationally designed model. In two of the three structures, the binding mode with NDM-1 is also very similar to the design model, while in the third, we observed an alternative binding mode likely arising from internal symmetry in the shape of the design combined with flexibility of the target. Although challenges remain in robustly predicting target backbone changes, binding mode, and the effects of mutations on binding affinity, our methods for designing ordered, binding-competent macrocycles should have broad applicability to a wide range of therapeutic targets.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Norn, Christoffer, Wicky, Basile I. M., Juergens, David, Liu, Sirui, Kim, David, Tischer, Doug, Koepnick, Brian, Anishchenko, Ivan, Baker, David, Ovchinnikov, Sergey
Protein sequence design by conformational landscape optimization Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 11, 2021.
@article{Norn2021,
title = {Protein sequence design by conformational landscape optimization},
author = {Norn, Christoffer and Wicky, Basile I. M. and Juergens, David and Liu, Sirui and Kim, David and Tischer, Doug and Koepnick, Brian and Anishchenko, Ivan and Baker, David and Ovchinnikov, Sergey},
url = {https://www.pnas.org/content/118/11/e2017228118, PNAS
https://www.bakerlab.org/wp-content/uploads/2021/03/Norn_etal_PNAS2021_LandscapeOptimization.pdf, Download PDF},
doi = {10.1073/pnas.2017228118},
year = {2021},
date = {2021-03-16},
urldate = {2021-03-16},
journal = {Proceedings of the National Academy of Sciences},
volume = {118},
number = {11},
abstract = {Almost all proteins fold to their lowest free energy state, which is determined by their amino acid sequence. Computational protein design has primarily focused on finding sequences that have very low energy in the target designed structure. However, what is most relevant during folding is not the absolute energy of the folded state but the energy difference between the folded state and the lowest-lying alternative states. We describe a deep learning approach that captures aspects of the folding landscape, in particular the presence of structures in alternative energy minima, and show that it can enhance current protein design methods.The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen{textquoteright}s thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowest energy state. As this calculation involves not only all possible amino acid sequences but also, all possible structures, most current approaches focus instead on the more tractable problem of finding the lowest-energy amino acid sequence for the desired structure, often checking by protein structure prediction in a second step that the desired structure is indeed the lowest-energy conformation for the designed sequence, and typically discarding a large fraction of designed sequences for which this is not the case. Here, we show that by backpropagating gradients through the transform-restrained Rosetta (trRosetta) structure prediction network from the desired structure to the input amino acid sequence, we can directly optimize over all possible amino acid sequences and all possible structures in a single calculation. We find that trRosetta calculations, which consider the full conformational landscape, can be more effective than Rosetta single-point energy estimations in predicting folding and stability of de novo designed proteins. We compare sequence design by conformational landscape optimization with the standard energy-based sequence design methodology in Rosetta and show that the former can result in energy landscapes with fewer alternative energy minima. We show further that more funneled energy landscapes can be designed by combining the strengths of the two approaches: the low-resolution trRosetta model serves to disfavor alternative states, and the high-resolution Rosetta model serves to create a deep energy minimum at the design target structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Coventry B, Baker D
Protein sequence optimization with a pairwise decomposable penalty for buried unsatisfied hydrogen bonds Journal Article
In: PLoS Computational Biology, 2021.
@article{Coventry2021,
title = {Protein sequence optimization with a pairwise decomposable penalty for buried unsatisfied hydrogen bonds},
author = {Coventry B and Baker D},
url = {https://doi.org/10.1371/journal.pcbi.1008061, PLoS Computational Biology
https://www.bakerlab.org/wp-content/uploads/2021/03/journal.pcbi_.1008061.pdf, Download PDF},
year = {2021},
date = {2021-03-08},
urldate = {2021-03-08},
journal = {PLoS Computational Biology},
abstract = {In aqueous solution, polar groups make hydrogen bonds with water, and hence burial of such groups in the interior of a protein is unfavorable unless the loss of hydrogen bonds with water is compensated by formation of new ones with other protein groups. For this reason, buried “unsatisfied” polar groups making no hydrogen bonds are very rare in proteins. Efficiently representing the energetic cost of unsatisfied hydrogen bonds with a pairwise-decomposable energy term during protein design is challenging since whether or not a group is satisfied depends on all of its neighbors. Here we describe a method for assigning a pairwise-decomposable energy to sidechain rotamers such that following combinatorial sidechain packing, buried unsaturated polar atoms are penalized. The penalty can be any quadratic function of the number of unsatisfied polar groups, and can be computed very rapidly. We show that inclusion of this term in Rosetta sidechain packing calculations substantially reduces the number of buried unsatisfied polar groups.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Vorobieva, Anastassia A., White, Paul, Liang, Binyong, Horne, Jim E., Bera, Asim K., Chow, Cameron M., Gerben, Stacey, Marx, Sinduja, Kang, Alex, Stiving, Alyssa Q., Harvey, Sophie R., Marx, Dagan C., Khan, G. Nasir, Fleming, Karen G., Wysocki, Vicki H., Brockwell, David J., Tamm, Lukas K., Radford, Sheena E., Baker, David
De novo design of transmembrane beta barrels Journal Article
In: Science, vol. 371, no. 6531, 2021.
@article{Vorobieva2021,
title = {De novo design of transmembrane beta barrels},
author = {Vorobieva, Anastassia A. and White, Paul and Liang, Binyong and Horne, Jim E. and Bera, Asim K. and Chow, Cameron M. and Gerben, Stacey and Marx, Sinduja and Kang, Alex and Stiving, Alyssa Q. and Harvey, Sophie R. and Marx, Dagan C. and Khan, G. Nasir and Fleming, Karen G. and Wysocki, Vicki H. and Brockwell, David J. and Tamm, Lukas K. and Radford, Sheena E. and Baker, David},
url = {https://science.sciencemag.org/content/371/6531/eabc8182, Science
https://www.bakerlab.org/wp-content/uploads/2021/02/Vorobieva_etal_Science2021_De_Novo_Transmembrane_beta_barrels.pdf, Download PDF},
doi = {10.1126/science.abc8182},
year = {2021},
date = {2021-02-19},
urldate = {2021-02-19},
journal = {Science},
volume = {371},
number = {6531},
abstract = {Computational design offers the possibility of making proteins with customized structures and functions. The range of accessible protein scaffolds has expanded with the design of increasingly complex cytoplasmic proteins and, recently, helical membrane proteins. Vorobieva et al. describe the successful computational design of eight-stranded transmembrane β-barrel proteins (TMBs). Using an iterative approach, they show the importance of negative design to prevent off-target structures and gain insight into the sequence determinants of TMB folding. Twenty-three designs satisfied biochemical screens for a TMB structure, and two structures were experimentally validated by nuclear magnetic resonance spectroscopy or x-ray crystallography. This is a step toward the custom design of pores for applications such as single-molecule sequencing.Science, this issue p. eabc8182INTRODUCTIONDespite their key biological roles, only a few proteins that fold into lipid membranes have been designed de novo. A class of membrane proteins{textemdash}transmembrane β barrels (TMBs){textemdash}forms a continuous sheet that closes on itself in lipid membranes. In addition to the challenge of designing β-sheet proteins, which are prone to misfolding and aggregation if folding is not properly controlled, the computational design of TMBs is complicated by limited understanding of TMB folding. As a result, no TMB has been designed de novo to date.Although the folding of TMBs in vivo is catalyzed by the β-barrel assembly machinery (BAM), many TMBs can also fold spontaneously in synthetic membranes to form stable pores, making them attractive for biotechnology and single-molecule analytical applications. Hence, de novo design of TMBs has potential both for understanding the determinants of TMB folding and membrane insertion and for the custom engineering of TMB nanopores.RATIONALEWe used de novo protein design to distill key principles of TMB folding through several design-build-test cycles. We iterated between hypothesis formulation, its implementation into computational design methods, and experimental characterization of the resulting proteins. To focus on the fundamental principles of TMB folding in the absence of complications due to interactions with chaperones and BAM in vivo, we focused on the challenge of de novo design of eight-stranded TMBs, which can fold and assemble into synthetic lipid membranes.RESULTSWe used a combination of purely geometric models and explicit Rosetta protein structure simulations to determine the constraints that β-strand connectivity and membrane embedding place on the TMB architecture. Through a series of design-build-test cycles, we found that, unlike almost all other classes of proteins, locally destabilizing sequences are critical for expression and folding of TMBs, and that the β-turns that translocate through the bilayer during folding have to be destabilized to enable correct assembly in the membrane. Our results suggest that premature formation of β hairpins may result in off-target β-sheet structures that compete with proper membrane insertion and folding, and hence the β hairpins of TMBs must be designed such that they are only transiently formed prior to membrane insertion, when the protein is in an aqueous environment. In the hydrophobic environment of the lipid bilayer, the full TMB can assemble because the membrane-facing nonpolar residues, which would tend to cluster nonspecifically in an aqueous environment, instead make favorable interactions with the lipids. As the TMB assembles, the β hairpins are stabilized by interactions with the neighboring β strands.Using computational methods that incorporate the above insights, we designed TMB sequences that successfully fold and assemble into both detergent micelles and lipid bilayers. Two of the designs were highly stable and could fold into liposomes more rapidly and reversibly than the transmembrane domain of the model outer membrane protein A (tOmpA) of Escherichia coli. A nuclear magnetic resonance solution structure and a high-resolution crystal structure for two different designs closely match the design models, showing that the TMB design method developed here can generate new structures with atomic-level accuracy.CONCLUSIONThis study elucidates key principles for de novo design of transmembrane β barrels, ranging from constraints on β-barrel architecture and β-hairpin design, as well as local and global sequence features. Our designs provide starting points for the bottom-up elucidation of the molecular mechanisms underlying TMB folding and interactions with the cellular outer membrane folding and insertion machinery. More generally, our work demonstrates that TMBs can be designed with atomic-level accuracy and opens the door to custom design of nanopores tailored for applications such as single-molecule sensing and sequencing.De novo{textendash}designed eight-stranded transmembrane β barrels fold spontaneously and reversibly into synthetic lipid membranes.The illustration shows the crystal structure of the protein TMB2.17 designed in this study, which adopts a structure identical to the design model.Credit: Ian Haydon.Transmembrane β-barrel proteins (TMBs) are of great interest for single-molecule analytical technologies because they can spontaneously fold and insert into membranes and form stable pores, but the range of pore properties that can be achieved by repurposing natural TMBs is limited. We leverage the power of de novo computational design coupled with a {textquotedblleft}hypothesis, design, and test{textquotedblright} approach to determine TMB design principles, notably, the importance of negative design to slow β-sheet assembly. We design new eight-stranded TMBs, with no homology to known TMBs, that insert and fold reversibly into synthetic lipid membranes and have nuclear magnetic resonance and x-ray crystal structures very similar to the computational models. These advances should enable the custom design of pores for a wide range of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Klima, Jason C. and Doyle, Lindsey A. and Lee, Justin Daho and Rappleye, Michael and Gagnon, Lauren A. and Lee, Min Yen and Barros, Emilia P. and Vorobieva, Anastassia A. and Dou, Jiayi and Bremner, Samantha and Quon, Jacob S. and Chow, Cameron M. and Carter, Lauren and Mack, David L. and Amaro, Rommie E. and Vaughan, Joshua C. and Berndt, Andre and Stoddard, Barry L. and Baker, David
Incorporation of sensing modalities into de novo designed fluorescence-activating proteins Journal Article
In: Nature Communications, vol. 856, no. 12, pp. 2041–1723, 2021.
@article{Klima2021,
title = {Incorporation of sensing modalities into de novo designed fluorescence-activating proteins},
author = {Klima, Jason C.
and Doyle, Lindsey A.
and Lee, Justin Daho
and Rappleye, Michael
and Gagnon, Lauren A.
and Lee, Min Yen
and Barros, Emilia P.
and Vorobieva, Anastassia A.
and Dou, Jiayi
and Bremner, Samantha
and Quon, Jacob S.
and Chow, Cameron M.
and Carter, Lauren
and Mack, David L.
and Amaro, Rommie E.
and Vaughan, Joshua C.
and Berndt, Andre
and Stoddard, Barry L.
and Baker, David},
url = {https://www.nature.com/articles/s41467-020-18911-w, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2021/02/Klima_etal_NatComm2021_Sensing_modalities_in_fluorescent_proteins.pdf, Download PDF},
doi = {10.1038/s41467-020-18911-w},
year = {2021},
date = {2021-02-08},
urldate = {2021-02-08},
journal = {Nature Communications},
volume = {856},
number = {12},
pages = {2041–1723},
abstract = {Through the efforts of many groups, a wide range of fluorescent protein reporters and sensors based on green fluorescent protein and its relatives have been engineered in recent years. Here we explore the incorporation of sensing modalities into de novo designed fluorescence-activating proteins, called mini-fluorescence-activating proteins (mFAPs), that bind and stabilize the fluorescent cis-planar state of the fluorogenic compound DFHBI. We show through further design that the fluorescence intensity and specificity of mFAPs for different chromophores can be tuned, and the fluorescence made sensitive to pH and Ca2+ for real-time fluorescence reporting. Bipartite split mFAPs enable real-time monitoring of protein–protein association and (unlike widely used split GFP reporter systems) are fully reversible, allowing direct readout of association and dissociation events. The relative ease with which sensing modalities can be incorporated and advantages in smaller size and photostability make de novo designed fluorescence-activating proteins attractive candidates for optical sensor engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Ben-Sasson, Ariel J., Watson, Joseph L., Sheffler, William, Johnson, Matthew Camp, Bittleston, Alice, Somasundaram, Logeshwaran, Decarreau, Justin, Jiao, Fang, Chen, Jiajun, Mela, Ioanna, Drabek, Andrew A., Jarrett, Sanchez M., Blacklow, Stephen C., Kaminski, Clemens F., Hura, Greg L., De Yoreo, James J., Kollman, Justin M., Ruohola-Baker, Hannele, Derivery, Emmanuel, Baker, David
Design of biologically active binary protein 2D materials Journal Article
In: Nature, 2021.
@article{Ben-Sasson2020,
title = {Design of biologically active binary protein 2D materials},
author = {Ben-Sasson, Ariel J. and Watson, Joseph L. and Sheffler, William and Johnson, Matthew Camp and Bittleston, Alice and Somasundaram, Logeshwaran and Decarreau, Justin and Jiao, Fang and Chen, Jiajun and Mela, Ioanna and Drabek, Andrew A. and Jarrett, Sanchez M. and Blacklow, Stephen C. and Kaminski, Clemens F. and Hura, Greg L. and De Yoreo, James J. and Kollman, Justin M. and Ruohola-Baker, Hannele and Derivery, Emmanuel and Baker, David},
url = {https://www.nature.com/articles/s41586-020-03120-8, Nature
https://www.bakerlab.org/wp-content/uploads/2021/02/Ben-Sasson_Nature2021_Binary_2D_arrays.pdf, Download PDF},
doi = {10.1038/s41586-020-03120-8},
year = {2021},
date = {2021-01-06},
urldate = {2021-01-06},
journal = {Nature},
abstract = {Ordered two-dimensional arrays such as S-layers1,2 and designed analogues3–5 have intrigued bioengineers6,7, but with the exception of a single lattice formed with flexible linkers8, they are constituted from just one protein component. Materials composed of two components have considerable potential advantages for modulating assembly dynamics and incorporating more complex functionality9–12. Here we describe a computational method to generate co-assembling binary layers by designing rigid interfaces between pairs of dihedral protein building blocks, and use it to design a p6m lattice. The designed array components are soluble at millimolar concentrations, but when combined at nanomolar concentrations, they rapidly assemble into nearly crystalline micrometre-scale arrays nearly identical to the computational design model in vitro and in cells without the need for a two-dimensional support. Because the material is designed from the ground up, the components can be readily functionalized and their symmetry reconfigured, enabling formation of ligand arrays with distinguishable surfaces, which we demonstrate can drive extensive receptor clustering, downstream protein recruitment and signalling. Using atomic force microscopy on supported bilayers and quantitative microscopy on living cells, we show that arrays assembled on membranes have component stoichiometry and structure similar to arrays formed in vitro, and that our material can therefore impose order onto fundamentally disordered substrates such as cell membranes. In contrast to previously characterized cell surface receptor binding assemblies such as antibodies and nanocages, which are rapidly endocytosed, we find that large arrays assembled at the cell surface suppress endocytosis in a tunable manner, with potential therapeutic relevance for extending receptor engagement and immune evasion. Our work provides a foundation for a synthetic cell biology in which multi-protein macroscale materials are designed to modulate cell responses and reshape synthetic and living systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
COLLABORATOR LED
Crawshaw, Rebecca and Crossley, Amy E. and Johannissen, Linus and Burke, Ashleigh J. and Hay, Sam and Levy, Colin and Baker, David and Lovelock, Sarah L. and Green, Anthony P.
Engineering an efficient and enantioselective enzyme for the Morita-Baylis-Hillman reaction Journal Article
In: Nature Chemistry, 2021.
@article{Crawshaw2021,
title = {Engineering an efficient and enantioselective enzyme for the Morita-Baylis-Hillman reaction},
author = {Crawshaw, Rebecca
and Crossley, Amy E.
and Johannissen, Linus
and Burke, Ashleigh J.
and Hay, Sam
and Levy, Colin
and Baker, David
and Lovelock, Sarah L.
and Green, Anthony P.},
url = {https://www.nature.com/articles/s41557-021-00833-9
https://www.bakerlab.org/wp-content/uploads/2022/01/Crawshaw_etal_NatChem_Engineering_enantioselective_enzyme_Morita-Baylis-Hillman_reaction.pdf},
doi = {10.1038/s41557-021-00833-9},
year = {2021},
date = {2021-12-16},
journal = {Nature Chemistry},
abstract = {The combination of computational design and directed evolution could offer a general strategy to create enzymes with new functions. So far, this approach has delivered enzymes for a handful of model reactions. Here we show that new catalytic mechanisms can be engineered into proteins to accelerate more challenging chemical transformations. Evolutionary optimization of a primitive design afforded an efficient and enantioselective enzyme (BH32.14) for the Morita–Baylis–Hillman (MBH) reaction. BH32.14 is suitable for preparative-scale transformations, accepts a broad range of aldehyde and enone coupling partners and is able to promote selective monofunctionalizations of dialdehydes. Crystallographic, biochemical and computational studies reveal that BH32.14 operates via a sophisticated catalytic mechanism comprising a His23 nucleophile paired with a judiciously positioned Arg124. This catalytic arginine shuttles between conformational states to stabilize multiple oxyanion intermediates and serves as a genetically encoded surrogate of privileged bidentate hydrogen-bonding catalysts (for example, thioureas). This study demonstrates that elaborate catalytic devices can be built from scratch to promote demanding multi-step processes not observed in nature.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Patricia M. Legler and Stephen F. Little and Jeffrey Senft and Rowena Schokman and John H. Carra and Jaimee R. Compton and Donald Chabot and Steven Tobery and David P. Fetterer and Justin B. Siegel and David Baker and Arthur M. Friedlander
Treatment of experimental anthrax with pegylated circularly permuted capsule depolymerase Journal Article
In: Science Translational Medicine, 2021.
@article{Friedlander2021,
title = {Treatment of experimental anthrax with pegylated circularly permuted capsule depolymerase},
author = {Patricia M. Legler
and Stephen F. Little
and Jeffrey Senft
and Rowena Schokman
and John H. Carra
and Jaimee R. Compton
and Donald Chabot
and Steven Tobery
and David P. Fetterer
and Justin B. Siegel
and David Baker
and Arthur M. Friedlander},
url = {https://www.science.org/doi/10.1126/scitranslmed.abh1682
https://www.bakerlab.org/wp-content/uploads/2022/01/Legler_etal_ScienceTransMed2021_Treatment_of_anthrax_by_capsule_depolymerase.pdf},
doi = {10.1126/scitranslmed.abh1682},
year = {2021},
date = {2021-12-08},
journal = {Science Translational Medicine},
abstract = {Anthrax is considered one of the most dangerous bioweapon agents, and concern about multidrug-resistant strains has led to the development of alternative therapeutic approaches that target the antiphagocytic capsule, an essential virulence determinant of Bacillus anthracis, the causative agent. Capsule depolymerase is a γ-glutamyltransferase that anchors the capsule to the cell wall of B. anthracis. Encapsulated strains of B. anthracis can be treated with recombinant capsule depolymerase to enzymatically remove the capsule and promote phagocytosis and killing by human neutrophils. Here, we show that pegylation improved the pharmacokinetic and therapeutic properties of a previously described variant of capsule depolymerase, CapD-CP, when delivered 24 hours after exposure every 8 hours for 2 days for the treatment of mice infected with B. anthracis. Mice infected with 382 LD50 of B. anthracis spores from a nontoxigenic encapsulated strain were completely protected (10 of 10) after treatment with the pegylated PEG-CapD-CPS334C, whereas 10% of control mice (1 of 10) survived with control treatment using bovine serum albumin (P < 0.0001, log-rank analysis). Treatment of mice infected with five LD50 of a fully virulent toxigenic, encapsulated B. anthracis strain with PEG-CapD-CPS334C protected 80% (8 of 10) of the animals, whereas 20% of controls (2 of 10) survived (P = 0.0125, log-rank analysis). This strategy renders B. anthracis susceptible to innate immune responses and does not rely on antibiotics. These findings suggest that enzyme-catalyzed removal of the capsule may be a potential therapeutic strategy for the treatment of multidrug- or vaccine-resistant anthrax and other bacterial infections.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Du, Zongyang and Su, Hong and Wang, Wenkai and Ye, Lisha and Wei, Hong and Peng, Zhenling and Anishchenko, Ivan and Baker, David and Yang, Jianyi
The trRosetta server for fast and accurate protein structure prediction Journal Article
In: Nature Protocols, 2021.
@article{Du2021,
title = {The trRosetta server for fast and accurate protein structure prediction},
author = {Du, Zongyang
and Su, Hong
and Wang, Wenkai
and Ye, Lisha
and Wei, Hong
and Peng, Zhenling
and Anishchenko, Ivan
and Baker, David
and Yang, Jianyi},
url = {https://www.nature.com/articles/s41596-021-00628-9
https://www.bakerlab.org/wp-content/uploads/2022/01/Du_etal_NatProt2021_trRosetta_server.pdf},
doi = {10.1038/s41596-021-00628-9},
year = {2021},
date = {2021-12-01},
urldate = {2021-12-01},
journal = {Nature Protocols},
abstract = {The trRosetta (transform-restrained Rosetta) server is a web-based platform for fast and accurate protein structure prediction, powered by deep learning and Rosetta. With the input of a protein’s amino acid sequence, a deep neural network is first used to predict the inter-residue geometries, including distance and orientations. The predicted geometries are then transformed as restraints to guide the structure prediction on the basis of direct energy minimization, which is implemented under the framework of Rosetta. The trRosetta server distinguishes itself from other similar structure prediction servers in terms of rapid and accurate de novo structure prediction. As an illustration, trRosetta was applied to two Pfam families with unknown structures, for which the predicted de novo models were estimated to have high accuracy. Nevertheless, to take advantage of homology modeling, homologous templates are used as additional inputs to the network automatically. In general, it takes ~1 h to predict the final structure for a typical protein with ~300 amino acids, using a maximum of 10 CPU cores in parallel in our cluster system. To enable large-scale structure modeling, a downloadable package of trRosetta with open-source codes is available as well. A detailed guidance for using the package is also available in this protocol. The server and the package are available at https://yanglab.nankai.edu.cn/trRosetta/ and https://yanglab.nankai.edu.cn/trRosetta/download/, respectively.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Muammer Y Yaman, Kathryn N Guye, Maxim Ziatdinov, Hao Shen, David Baker, Sergei V Kalinin, David S Ginger
Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis Journal Article
In: Soft Matter, 2021.
@article{Yaman2021,
title = {Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis},
author = {Muammer Y Yaman and Kathryn N Guye and Maxim Ziatdinov and Hao Shen and David Baker and Sergei V Kalinin and David S Ginger
},
url = {https://pubmed.ncbi.nlm.nih.gov/34128040/
https://www.bakerlab.org/wp-content/uploads/2021/06/Muammer_etal_SoftMatter2021_Aisngment_along_nanofibers.pdf},
doi = {10.1039/d1sm00645b},
year = {2021},
date = {2021-06-15},
journal = {Soft Matter},
abstract = {In this study, we focus on exploring the directional assembly of anisotropic Au nanorods along de novo designed 1D protein nanofiber templates. Using machine learning and automated image processing, we analyze scanning electron microscopy (SEM) images to study how the attachment density and alignment fidelity are influenced by variables such as the aspect ratio of the Au nanorods, and the salt concentration of the solution. We find that the Au nanorods prefer to align parallel to the protein nanofibers. This preference decreases with increasing salt concentration, but is only weakly sensitive to the nanorod aspect ratio. While the overall specific Au nanorod attachment density to the protein fibers increases with increasing solution ionic strength, this increase is dominated primarily by non-specific binding to the substrate background, and we find that greater specific attachment (nanorods attached to the nanofiber template as compared to the substrates) occurs at the lower studied salt concentrations, with the maximum ratio of specific to non-specific binding occurring when the protein fiber solutions are prepared in 75 mM NaCl concentration.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Boyoglu-Barnum, Seyhan and Ellis, Daniel and Gillespie, Rebecca A. and Hutchinson, Geoffrey B. and Park, Young-Jun and Moin, Syed M. and Acton, Oliver J. and Ravichandran, Rashmi and Murphy, Mike and Pettie, Deleah and Matheson, Nick and Carter, Lauren and Creanga, Adrian and Watson, Michael J. and Kephart, Sally and Ataca, Sila and Vaile, John R. and Ueda, George and Crank, Michelle C. and Stewart, Lance and Lee, Kelly K. and Guttman, Miklos and Baker, David and Mascola, John R. and Veesler, David and Graham, Barney S. and King, Neil P. and Kanekiyo, Masaru
Quadrivalent influenza nanoparticle vaccines induce broad protection Journal Article
In: Nature, 2021.
@article{Boyoglu-Barnum2021,
title = {Quadrivalent influenza nanoparticle vaccines induce broad protection},
author = {Boyoglu-Barnum, Seyhan
and Ellis, Daniel
and Gillespie, Rebecca A.
and Hutchinson, Geoffrey B.
and Park, Young-Jun
and Moin, Syed M.
and Acton, Oliver J.
and Ravichandran, Rashmi
and Murphy, Mike
and Pettie, Deleah
and Matheson, Nick
and Carter, Lauren
and Creanga, Adrian
and Watson, Michael J.
and Kephart, Sally
and Ataca, Sila
and Vaile, John R.
and Ueda, George
and Crank, Michelle C.
and Stewart, Lance
and Lee, Kelly K.
and Guttman, Miklos
and Baker, David
and Mascola, John R.
and Veesler, David
and Graham, Barney S.
and King, Neil P.
and Kanekiyo, Masaru},
url = {https://www.nature.com/articles/s41586-021-03365-x
https://www.bakerlab.org/wp-content/uploads/2021/04/Nature2021_NanoparticleFluVaccine.pdf},
doi = {10.1038/s41586-021-03365-x},
year = {2021},
date = {2021-03-24},
journal = {Nature},
abstract = {Influenza vaccines that confer broad and durable protection against diverse viral strains would have a major effect on global health, as they would lessen the need for annual vaccine reformulation and immunization. Here we show that computationally designed, two-component nanoparticle immunogens induce potently neutralizing and broadly protective antibody responses against a wide variety of influenza viruses. The nanoparticle immunogens contain 20 haemagglutinin glycoprotein trimers in an ordered array, and their assembly in vitro enables the precisely controlled co-display of multiple distinct haemagglutinin proteins in defined ratios. Nanoparticle immunogens that co-display the four haemagglutinins of licensed quadrivalent influenza vaccines elicited antibody responses in several animal models against vaccine-matched strains that were equivalent to or better than commercial quadrivalent influenza vaccines, and simultaneously induced broadly protective antibody responses to heterologous viruses by targeting the subdominant yet conserved haemagglutinin stem. The combination of potent receptor-blocking and cross-reactive stem-directed antibodies induced by the nanoparticle immunogens makes them attractive candidates for a supraseasonal influenza vaccine candidate with the potential to replace conventional seasonal vaccines.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Naozumi Hiranuma, Hahnbeom Park, Minkyung Baek, Ivan Anishchenko, Justas Dauparas, David Baker
Improved protein structure refinement guided by deep learning based accuracy estimation Journal Article
In: Nature Communications, vol. 12, no. 1340, 2021.
@article{Hiranuma2021,
title = {Improved protein structure refinement guided by deep learning based accuracy estimation},
author = {Naozumi Hiranuma and Hahnbeom Park and Minkyung Baek and Ivan Anishchenko and Justas Dauparas and David Baker
},
url = {https://www.nature.com/articles/s41467-021-21511-x, Nature Communications
https://www.bakerlab.org/wp-content/uploads/2021/02/Hiranuma_etal_NatureComms2021_DeepLearningStructureRefinement.pdf, Download PDF},
doi = {10.1038/s41467-021-21511-x},
year = {2021},
date = {2021-02-26},
urldate = {2021-02-26},
journal = {Nature Communications},
volume = {12},
number = {1340},
abstract = {We develop a deep learning framework (DeepAccNet) that estimates per-residue accuracy and residue-residue distance signed error in protein models and uses these predictions to guide Rosetta protein structure refinement. The network uses 3D convolutions to evaluate local atomic environments followed by 2D convolutions to provide their global contexts and outperforms other methods that similarly predict the accuracy of protein structure models. Overall accuracy predictions for X-ray and cryoEM structures in the PDB correlate with their resolution, and the network should be broadly useful for assessing the accuracy of both predicted structure models and experimentally determined structures and identifying specific regions likely to be in error. Incorporation of the accuracy predictions at multiple stages in the Rosetta refinement protocol considerably increased the accuracy of the resulting protein structure models, illustrating how deep learning can improve search for global energy minima of biomolecules.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hahnbeom Park, Guangfeng Zhou, Minkyung Baek, David Baker, Frank DiMaio
Force Field Optimization Guided by Small Molecule Crystal Lattice Data Enables Consistent Sub-Angstrom Protein–Ligand Docking Journal Article
In: Journal of Chemical Theory and Computation, 2021.
@article{Park2021,
title = {Force Field Optimization Guided by Small Molecule Crystal Lattice Data Enables Consistent Sub-Angstrom Protein–Ligand Docking},
author = {Hahnbeom Park and Guangfeng Zhou and Minkyung Baek and David Baker and Frank DiMaio},
url = {https://pubs.acs.org/doi/full/10.1021/acs.jctc.0c01184
https://www.bakerlab.org/wp-content/uploads/2021/02/Park_etal_JCTC2021_Small_mol_force_field_optimization.pdf},
doi = {10.1021/acs.jctc.0c01184},
year = {2021},
date = {2021-02-12},
journal = {Journal of Chemical Theory and Computation},
abstract = {Accurate and rapid calculation of protein-small molecule interaction free energies is critical for computational drug discovery. Because of the large chemical space spanned by drug-like molecules, classical force fields contain thousands of parameters describing atom-pair distance and torsional preferences; each parameter is typically optimized independently on simple representative molecules. Here, we describe a new approach in which small molecule force field parameters are jointly optimized guided by the rich source of information contained within thousands of available small molecule crystal structures. We optimize parameters by requiring that the experimentally determined molecular lattice arrangements have lower energy than all alternative lattice arrangements. Thousands of independent crystal lattice-prediction simulations were run on each of 1386 small molecule crystal structures, and energy function parameters of an implicit solvent energy model were optimized, so native crystal lattice arrangements had the lowest energy. The resulting energy model was implemented in Rosetta, together with a rapid genetic algorithm docking method employing grid-based scoring and receptor flexibility. The success rate of bound structure recapitulation in cross-docking on 1112 complexes was improved by more than 10% over previously published methods, with solutions within <1 Å in over half of the cases. Our results demonstrate that small molecule crystal structures are a rich source of information for guiding molecular force field development, and the improved Rosetta energy function should increase accuracy in a wide range of small molecule structure prediction and design studies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ziatdinov, Maxim and Zhang, Shuai and Dollar, Orion and Pfaendtner, Jim and Mundy, Christopher J. and Li, Xin and Pyles, Harley and Baker, David and De Yoreo, James J. and Kalinin, Sergei V.
Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data Journal Article
In: Nano Letters, 2021.
@article{Ziatdinov2021,
title = {Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data},
author = {Ziatdinov, Maxim
and Zhang, Shuai
and Dollar, Orion
and Pfaendtner, Jim
and Mundy, Christopher J.
and Li, Xin
and Pyles, Harley
and Baker, David
and De Yoreo, James J.
and Kalinin, Sergei V.},
url = {https://pubs.acs.org/doi/10.1021/acs.nanolett.0c03447},
doi = {10.1021/acs.nanolett.0c03447},
year = {2021},
date = {2021-01-13},
journal = {Nano Letters},
abstract = {The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. The deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2020
FROM THE LAB
Vikram Khipple Mulligan, Christine S. Kang, Michael R. Sawaya, Stephen Rettie, Xinting Li, Inna Antselovich, Timothy W. Craven, Andrew M. Watkins, Jason W. Labonte, Frank DiMaio, Todd O. Yeates, David Baker
Computational design of mixed chirality peptide macrocycles with internal symmetry Journal Article
In: Protein Science, 2020.
@article{Mulligan2020,
title = {Computational design of mixed chirality peptide macrocycles with internal symmetry},
author = {Vikram Khipple Mulligan and Christine S. Kang and Michael R. Sawaya and Stephen Rettie and Xinting Li and Inna Antselovich and Timothy W. Craven and Andrew M. Watkins and Jason W. Labonte and Frank DiMaio and Todd O. Yeates and David Baker},
url = {https://onlinelibrary.wiley.com/doi/epdf/10.1002/pro.3974
https://www.bakerlab.org/wp-content/uploads/2020/10/Mulligan2020-Computational-design-of-mixed-chirality-peptide-macrocycles-with-internal-symmetry.pdf},
doi = {10.1002/pro.3974},
year = {2020},
date = {2020-10-15},
journal = {Protein Science},
abstract = {Cyclic symmetry is frequent in protein and peptide homo‐oligomers, but extremely rare within a single chain, as it is not compatible with free N‐ and C‐termini. Here we describe the computational design of mixed‐chirality peptide macrocycles with rigid structures that feature internal cyclic symmetries or improper rotational symmetries inaccessible to natural proteins. Crystal structures of three C2‐ and C3‐symmetric macrocycles, and of six diverse S2‐symmetric macrocycles, match the computationally‐designed models with backbone heavy‐atom RMSD values of 1 å or better. Crystal structures of an S4‐symmetric macrocycle (consisting of a sequence and structure segment mirrored at each of three successive repeats) designed to bind zinc reveal a large‐scale zinc‐driven conformational change from an S4‐symmetric apo‐state to a nearly inverted S4‐symmetric holo‐state almost identical to the design model. This work demonstrates the power of computational design for exploring symmetries and structures not found in nature, and for creating synthetic switchable systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Chunfu Xu, Peilong Lu, Tamer M. Gamal El-Din, Xue Y. Pei, Matthew C. Johnson, Atsuko Uyeda, Matthew J. Bick, Qi Xu, Daohua Jiang, Hua Bai, Gabriella Reggiano, Yang Hsia, T J Brunette, Jiayi Dou, Dan Ma, Eric M. Lynch, Scott E. Boyken, Po-Ssu Huang, Lance Stewart, Frank DiMaio, Justin M. Kollman, Ben F. Luisi, Tomoaki Matsuura, William A. Catterall, David Baker
Computational design of transmembrane pores Journal Article
In: Nature, vol. 585, pp. 129–134, 2020.
@article{Xu2020,
title = {Computational design of transmembrane pores},
author = {Chunfu Xu and Peilong Lu and Tamer M. Gamal El-Din and Xue Y. Pei and Matthew C. Johnson and Atsuko Uyeda and Matthew J. Bick and Qi Xu and Daohua Jiang and Hua Bai and Gabriella Reggiano and Yang Hsia and T J Brunette and Jiayi Dou and Dan Ma and Eric M. Lynch and Scott E. Boyken and Po-Ssu Huang and Lance Stewart and Frank DiMaio and Justin M. Kollman and Ben F. Luisi and Tomoaki Matsuura and William A. Catterall and David Baker },
url = {https://www.bakerlab.org/wp-content/uploads/2020/08/Xuetal_Nature2020_DeNovoPores.pdf
https://www.nature.com/articles/s41586-020-2646-5},
doi = {10.1038/s41586-020-2646-5},
year = {2020},
date = {2020-08-26},
journal = {Nature},
volume = {585},
pages = {129–134},
abstract = {Transmembrane channels and pores have key roles in fundamental biological processes and in biotechnological applications such as DNA nanopore sequencing, resulting in considerable interest in the design of pore-containing proteins. Synthetic amphiphilic peptides have been found to form ion channels, and there have been recent advances in de novo membrane protein design and in redesigning naturally occurring channel-containing proteins. However, the de novo design of stable, well-defined transmembrane protein pores that are capable of conducting ions selectively or are large enough to enable the passage of small-molecule fluorophores remains an outstanding challenge. Here we report the computational design of protein pores formed by two concentric rings of α-helices that are stable and monodisperse in both their water-soluble and their transmembrane forms. Crystal structures of the water-soluble forms of a 12-helical pore and a 16-helical pore closely match the computational design models. Patch-clamp electrophysiology experiments show that, when expressed in insect cells, the transmembrane form of the 12-helix pore enables the passage of ions across the membrane with high selectivity for potassium over sodium; ion passage is blocked by specific chemical modification at the pore entrance. When incorporated into liposomes using in vitro protein synthesis, the transmembrane form of the 16-helix pore—but not the 12-helix pore—enables the passage of biotinylated Alexa Fluor 488. A cryo-electron microscopy structure of the 16-helix transmembrane pore closely matches the design model. The ability to produce structurally and functionally well-defined transmembrane pores opens the door to the creation of designer channels and pores for a wide variety of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Lajoie, Marc J. and Boyken, Scott E. and Salter, Alexander I. and Bruffey, Jilliane and Rajan, Anusha and Langan, Robert A. and Olshefsky, Audrey and Muhunthan, Vishaka and Bick, Matthew J. and Gewe, Mesfin and Quijano-Rubio, Alfredo and Johnson, JayLee and Lenz, Garreck and Nguyen, Alisha and Pun, Suzie and Correnti, Colin E. and Riddell, Stanley R. and Baker, David
Designed protein logic to target cells with precise combinations of surface antigens Journal Article
In: Science, 2020.
@article{Lajoie2020,
title = {Designed protein logic to target cells with precise combinations of surface antigens },
author = {Lajoie, Marc J. and
Boyken, Scott E. and
Salter, Alexander I. and
Bruffey, Jilliane and
Rajan, Anusha and
Langan, Robert A. and
Olshefsky, Audrey and
Muhunthan, Vishaka and
Bick, Matthew J. and
Gewe, Mesfin and
Quijano-Rubio, Alfredo and
Johnson, JayLee and
Lenz, Garreck and
Nguyen, Alisha and
Pun, Suzie and
Correnti, Colin E. and
Riddell, Stanley R. and
Baker, David},
url = {https://science.sciencemag.org/content/early/2020/08/19/science.aba6527
https://www.bakerlab.org/wp-content/uploads/2020/08/Lajoie-coLOCKR2020.pdf},
doi = {10.1126/science.aba6527},
year = {2020},
date = {2020-08-20},
journal = {Science},
abstract = {Precise cell targeting is challenging because most mammalian cell types lack a single surface marker that distinguishes them from other cells. A solution would be to target cells based on specific combinations of proteins present on their surfaces. We design colocalization-dependent protein switches (Co-LOCKR) that perform AND, OR, and NOT Boolean logic operations. These switches activate through a conformational change only when all conditions are met, generating rapid, transcription-independent responses at single-cell resolution within complex cell populations. We implement AND gates to redirect T cell specificity against tumor cells expressing two surface antigens while avoiding off-target recognition of single-antigen cells, and 3-input switches that add NOT or OR logic to avoid or include cells expressing a third antigen. Thus, de novo designed proteins can perform computations on the surface of cells, integrating multiple distinct binding interactions into a single output.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Ueda, George, Antanasijevic, Aleksandar, Fallas, Jorge A, Sheffler, William, Copps, Jeffrey, Ellis, Daniel, Hutchinson, Geoffrey B, Moyer, Adam, Yasmeen, Anila, Tsybovsky, Yaroslav, Park, Young-Jun, Bick, Matthew J, Sankaran, Banumathi, Gillespie, Rebecca A, Brouwer, Philip JM, Zwart, Peter H, Veesler, David, Kanekiyo, Masaru, Graham, Barney S, Sanders, Rogier W, Moore, John P, Klasse, Per Johan, Ward, Andrew B, King, Neil P, Baker, David
Tailored design of protein nanoparticle scaffolds for multivalent presentation of viral glycoprotein antigens Journal Article
In: eLife, vol. 9, pp. e57659, 2020.
@article{Ueda2020,
title = {Tailored design of protein nanoparticle scaffolds for multivalent presentation of viral glycoprotein antigens},
author = {Ueda, George and Antanasijevic, Aleksandar and Fallas, Jorge A and Sheffler, William and Copps, Jeffrey and Ellis, Daniel and Hutchinson, Geoffrey B and Moyer, Adam and Yasmeen, Anila and Tsybovsky, Yaroslav and Park, Young-Jun and Bick, Matthew J and Sankaran, Banumathi and Gillespie, Rebecca A and Brouwer, Philip JM and Zwart, Peter H and Veesler, David and Kanekiyo, Masaru and Graham, Barney S and Sanders, Rogier W and Moore, John P and Klasse, Per Johan and Ward, Andrew B and King, Neil P and Baker, David},
url = {https://elifesciences.org/articles/57659},
doi = {10.7554/eLife.57659},
year = {2020},
date = {2020-08-04},
journal = {eLife},
volume = {9},
pages = {e57659},
abstract = {Multivalent presentation of viral glycoproteins can substantially increase the elicitation of antigen-specific antibodies. To enable a new generation of anti-viral vaccines, we designed self-assembling protein nanoparticles with geometries tailored to present the ectodomains of influenza, HIV, and RSV viral glycoprotein trimers. We first textit{de novo} designed trimers tailored for antigen fusion, featuring N-terminal helices positioned to match the C termini of the viral glycoproteins. Trimers that experimentally adopted their designed configurations were incorporated as components of tetrahedral, octahedral, and icosahedral nanoparticles, which were characterized by cryo-electron microscopy and assessed for their ability to present viral glycoproteins. Electron microscopy and antibody binding experiments demonstrated that the designed nanoparticles presented antigenically intact prefusion HIV-1 Env, influenza hemagglutinin, and RSV F trimers in the predicted geometries. This work demonstrates that antigen-displaying protein nanoparticles can be designed from scratch, and provides a systematic way to investigate the influence of antigen presentation geometry on the immune response to vaccination.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Wei, Kathy Y., Moschidi, Danai, Bick, Matthew J., Nerli, Santrupti, McShan, Andrew C., Carter, Lauren P., Huang, Po-Ssu, Fletcher, Daniel A., Sgourakis, Nikolaos G., Boyken, Scott E., Baker, David
Computational design of closely related proteins that adopt two well-defined but structurally divergent folds Journal Article
In: Proceedings of the National Academy of Sciences, 2020.
@article{Wei2020,
title = {Computational design of closely related proteins that adopt two well-defined but structurally divergent folds},
author = {Wei, Kathy Y. and Moschidi, Danai and Bick, Matthew J. and Nerli, Santrupti and McShan, Andrew C. and Carter, Lauren P. and Huang, Po-Ssu and Fletcher, Daniel A. and Sgourakis, Nikolaos G. and Boyken, Scott E. and Baker, David
},
url = {https://www.pnas.org/content/early/2020/03/17/1914808117
https://www.ipd.uw.edu/wp-content/uploads/2020/03/Wei_PNAS_2020.pdf},
doi = {10.1073/pnas.1914808117},
year = {2020},
date = {2020-03-17},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Computational protein design has focused primarily on the design of sequences which fold to single stable states, but in biology many proteins adopt multiple states. We used de novo protein design to generate very closely related proteins that adopt two very different states—a short state and a long state, like a viral fusion protein—and then created a single molecule that can be found in both forms. Our proteins, poised between forms, are a starting point for the design of triggered shape changes.The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used for de novo design of proteins that fold to a single state with a deep free-energy minimum, and to reengineer natural proteins to alter their dynamics or fold, the de novo design of closely related sequences which adopt well-defined but structurally divergent structures remains an outstanding challenge. We designed closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations — one short (~66 Å height) and the other long (~100 Å height) — reminiscent of the conformational transition of viral fusion proteins. Crystallographic and NMR spectroscopic characterization shows that both the short- and long-state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large-scale conformational switches between structurally divergent forms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Chen, Zibo, Kibler, Ryan D., Hunt, Andrew, Busch, Florian, Pearl, Jocelynn, Jia, Mengxuan, VanAernum, Zachary L., Wicky, Basile I. M., Dods, Galen, Liao, Hanna, Wilken, Matthew S., Ciarlo, Christie, Green, Shon, El-Samad, Hana, Stamatoyannopoulos, John, Wysocki, Vicki H., Jewett, Michael C., Boyken, Scott E., Baker, David
De novo design of protein logic gates Journal Article
In: Science, vol. 368, no. 6486, pp. 78-84, 2020.
@article{Chen2020,
title = {De novo design of protein logic gates},
author = {Chen, Zibo and Kibler, Ryan D. and Hunt, Andrew and Busch, Florian and Pearl, Jocelynn and Jia, Mengxuan and VanAernum, Zachary L. and Wicky, Basile I. M. and Dods, Galen and Liao, Hanna and Wilken, Matthew S. and Ciarlo, Christie and Green, Shon and El-Samad, Hana and Stamatoyannopoulos, John and Wysocki, Vicki H. and Jewett, Michael C. and Boyken, Scott E. and Baker, David},
url = {https://science.sciencemag.org/content/368/6486/78
https://www.bakerlab.org/wp-content/uploads/2020/04/Chen2020_DeNovoProteinLogicGates.pdf},
doi = {10.1126/science.aay2790},
year = {2020},
date = {2020-03-04},
journal = {Science},
volume = {368},
number = {6486},
pages = {78-84},
abstract = {The design of modular protein logic for regulating protein function at the posttranscriptional level is a challenge for synthetic biology. Here, we describe the design of two-input AND, OR, NAND, NOR, XNOR, and NOT gates built from de novo–designed proteins. These gates regulate the association of arbitrary protein units ranging from split enzymes to transcriptional machinery in vitro, in yeast and in primary human T cells, where they control the expression of the TIM3 gene related to T cell exhaustion. Designed binding interaction cooperativity, confirmed by native mass spectrometry, makes the gates largely insensitive to stoichiometric imbalances in the inputs, and the modularity of the approach enables ready extension to three-input OR, AND, and disjunctive normal form gates. The modularity and cooperativity of the control elements, coupled with the ability to de novo design an essentially unlimited number of protein components, should enable the design of sophisticated posttranslational control logic over a wide range of biological functions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Yang, Jianyi, Anishchenko, Ivan, Park, Hahnbeom, Peng, Zhenling, Ovchinnikov, Sergey, Baker, David
Improved protein structure prediction using predicted interresidue orientations Journal Article
In: Proceedings of the National Academy of Sciences, 2020, ISBN: 0027-8424.
@article{Yang2020,
title = {Improved protein structure prediction using predicted interresidue orientations},
author = {Yang, Jianyi and Anishchenko, Ivan and Park, Hahnbeom and Peng, Zhenling and Ovchinnikov, Sergey and Baker, David},
url = {https://www.pnas.org/content/early/2020/01/01/1914677117
https://www.bakerlab.org/wp-content/uploads/2020/01/Yang2020_ImprovedStructurePredictionInterresidueOrientations.pdf
},
doi = {10.1073/pnas.1914677117},
isbn = {0027-8424},
year = {2020},
date = {2020-01-02},
journal = {Proceedings of the National Academy of Sciences},
abstract = {Protein structure prediction is a longstanding challenge in computational biology. Through extension of deep learning-based prediction to interresidue orientations in addition to distances, and the development of a constrained optimization by Rosetta, we show that more accurate models can be generated. Results on a set of 18 de novo-designed proteins suggests the proposed method should be directly applicable to current challenges in de novo protein design.The prediction of interresidue contacts and distances from coevolutionary data using deep learning has considerably advanced protein structure prediction. Here, we build on these advances by developing a deep residual network for predicting interresidue orientations, in addition to distances, and a Rosetta-constrained energy-minimization protocol for rapidly and accurately generating structure models guided by these restraints. In benchmark tests on 13th Community-Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP13)- and Continuous Automated Model Evaluation (CAMEO)-derived sets, the method outperforms all previously described structure-prediction methods. Although trained entirely on native proteins, the network consistently assigns higher probability to de novo-designed proteins, identifying the key fold-determining residues and providing an independent quantitative measure of the "ideality" of a protein structure. The method promises to be useful for a broad range of protein structure prediction and design problems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
COLLABORATOR LED
Caldwell, Shane J., Haydon, Ian C., Piperidou, Nikoletta, Huang, Po-Ssu, Bick, Matthew J., Sjöström, H. Sebastian, Hilvert, Donald, Baker, David, Zeymer, Cathleen
Tight and specific lanthanide binding in a de novo TIM barrel with a large internal cavity designed by symmetric domain fusion Journal Article
In: Proceedings of the National Academy of Sciences, 2020.
@article{Caldwell2020,
title = {Tight and specific lanthanide binding in a de novo TIM barrel with a large internal cavity designed by symmetric domain fusion},
author = {Caldwell, Shane J. and Haydon, Ian C. and Piperidou, Nikoletta and Huang, Po-Ssu and Bick, Matthew J. and Sjöström, H. Sebastian and Hilvert, Donald and Baker, David and Zeymer, Cathleen
},
url = {https://www.bakerlab.org/wp-content/uploads/2020/11/Caldwell_et_al_PNAS_TIM_barrel_metal_binding.pdf
https://www.pnas.org/content/early/2020/11/13/2008535117},
doi = {10.1073/pnas.2008535117},
year = {2020},
date = {2020-11-17},
journal = {Proceedings of the National Academy of Sciences},
abstract = {De novo protein design has succeeded in generating a large variety of globular proteins, but the construction of protein scaffolds with cavities that could accommodate large signaling molecules, cofactors, and substrates remains an outstanding challenge. The long, often flexible loops that form such cavities in many natural proteins are difficult to precisely program and thus challenging for computational protein design. Here we describe an alternative approach to this problem. We fused two stable proteins with C2 symmetry—a de novo designed dimeric ferredoxin fold and a de novo designed TIM barrel—such that their symmetry axes are aligned to create scaffolds with large cavities that can serve as binding pockets or enzymatic reaction chambers. The crystal structures of two such designs confirm the presence of a 420 cubic Ångström chamber defined by the top of the designed TIM barrel and the bottom of the ferredoxin dimer. We functionalized the scaffold by installing a metal-binding site consisting of four glutamate residues close to the symmetry axis. The protein binds lanthanide ions with very high affinity as demonstrated by tryptophan-enhanced terbium luminescence. This approach can be extended to other metals and cofactors, making this scaffold a modular platform for the design of binding proteins and biocatalysts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Robin L. Kirkpatrick, Kieran Lewis, Robert A. Langan, Marc J. Lajoie, Scott E. Boyken, Madeleine Eakman, David Baker, Jesse G. Zalatan
Conditional Recruitment to a DNA-Bound CRISPR–Cas Complex Using a Colocalization-Dependent Protein Switch Journal Article
In: ACS Synthetic Biology, 2020.
@article{Kirkpatrick2020,
title = {Conditional Recruitment to a DNA-Bound CRISPR–Cas Complex Using a Colocalization-Dependent Protein Switch},
author = {Robin L. Kirkpatrick and Kieran Lewis and Robert A. Langan and Marc J. Lajoie and Scott E. Boyken and Madeleine Eakman and David Baker and Jesse G. Zalatan},
url = {https://pubs.acs.org/doi/full/10.1021/acssynbio.0c00012
https://www.bakerlab.org/wp-content/uploads/2020/08/Kirkpatrick2020-LOCKR-CRISPR.pdf},
doi = {10.1021/acssynbio.0c00012},
year = {2020},
date = {2020-08-20},
journal = {ACS Synthetic Biology},
abstract = {To spatially control biochemical functions at specific sites within a genome, we have engineered a synthetic switch that activates when bound to its DNA target site. The system uses two CRISPR–Cas complexes to colocalize components of a de novo-designed protein switch (Co-LOCKR) to adjacent sites in the genome. Colocalization triggers a conformational change in the switch from an inactive closed state to an active open state with an exposed functional peptide. We prototype the system in yeast and demonstrate that DNA binding triggers activation of the switch, recruitment of a transcription factor, and expression of a downstream reporter gene. This DNA-triggered Co-LOCKR switch provides a platform to engineer sophisticated functions that should only be executed at a specific target site within the genome, with potential applications in a wide range of synthetic systems including epigenetic regulation, imaging, and genetic logic circuits.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2019
FROM THE LAB
Park, Jooyoung, Selvaraj, Brinda, McShan, Andrew C, Boyken, Scott E, Wei, Kathy Y, Oberdorfer, Gustav, DeGrado, William, Sgourakis, Nikolaos G, Cuneo, Matthew J, Myles, Dean AA, Baker, David
De novo design of a homo-trimeric amantadine-binding protein Journal Article
In: eLife, 2019.
@article{Park2019b,
title = {De novo design of a homo-trimeric amantadine-binding protein},
author = {Park, Jooyoung and Selvaraj, Brinda and McShan, Andrew C and Boyken, Scott E and Wei, Kathy Y and Oberdorfer, Gustav and DeGrado, William and Sgourakis, Nikolaos G and Cuneo, Matthew J and Myles, Dean AA and Baker, David
},
editor = {Wolberger, Cynthia and Fleishman, Sarel Jacob and Anderson, Ross},
url = {https://elifesciences.org/articles/47839.pdf},
doi = {10.7554/eLife.47839},
year = {2019},
date = {2019-12-19},
journal = {eLife},
abstract = {The computational design of a symmetric protein homo-oligomer that binds a symmetry-matched small molecule larger than a metal ion has not yet been achieved. We used de novo protein design to create a homo-trimeric protein that binds the Ctextsubscript{3} symmetric small molecule drug amantadine with each protein monomer making identical interactions with each face of the small molecule. Solution NMR data show that the protein has regular three-fold symmetry and undergoes localized structural changes upon ligand binding. A high-resolution X-ray structure reveals a close overall match to the design model with the exception of water molecules in the amantadine binding site not included in the Rosetta design calculations, and a neutron structure provides experimental validation of the computationally designed hydrogen-bond networks. Exploration of approaches to generate a small molecule inducible homo-trimerization system based on the design highlight challenges that must be overcome to computationally design such systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Brian D. Weitzner, Yakov Kipnis, A. Gerard Daniel, Donald Hilvert, David Baker
A computational method for design of connected catalytic networks in proteins Journal Article
In: Protein Science, 2019.
@article{Weitzner2019,
title = {A computational method for design of connected catalytic networks in proteins},
author = {Brian D. Weitzner, Yakov Kipnis, A. Gerard Daniel, Donald Hilvert, David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pro.3757
https://www.bakerlab.org/wp-content/uploads/2020/02/Weitzner_et_al-2019-Protein_Science-1.pdf},
doi = {DOI10.1002/pro .3757},
year = {2019},
date = {2019-10-23},
journal = {Protein Science},
abstract = {Computational design of new active sites has generally proceeded by geometrically defining interactions between the reaction transition state(s) and surrounding side-chain functional groups which maximize transition-state stabilization, and then searching for sites in protein scaffolds where the specified side-chain–transition-state interactions can be realized. A limitation of this approach is that the interactions between the side chains themselves are not constrained. An extensive connected hydrogen bond network involving the catalytic residues was observed in a designed retroaldolase following directed evolution. Such connected networks could increase catalytic activity by preorganizing active site residues in catalytically competent orientations, and enabling concerted interactions between side chains during catalysis, for example proton shuffling. We developed a method for designing active sites in which the catalytic side chains, in addition to making interactions with the transition state, are also involved in extensive hydrogen bond networks. Because of the added constraint of hydrogen-bond connectivity between the catalytic side chains, to find solutions, a wider range of interactions between these side chains and the transition state must be considered. Our new method starts from a ChemDraw-like 2D representation of the transition state with hydrogen-bond donors, acceptors, and covalent interaction sites indicated, and all placements of side-chain functional groups that make the indicated interactions with the transition state, and are fully connected in a single hydrogen-bond network are systematically enumerated. The RosettaMatch method can then be used to identify realizations of these fully-connected active sites in protein scaffolds. The method generates many fully-connected active site solutions for a set of model reactions that are promising starting points for the design of fully-preorganized enzyme catalysts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Langan, Robert A. , Boyken, Scott E. , Ng, Andrew H. , Samson, Jennifer A. , Dods, Galen , Westbrook, Alexandra M. , Nguyen, Taylor H. , Lajoie, Marc J. , Chen, Zibo , Berger, Stephanie , Mulligan, Vikram Khipple , Dueber, John E. , Novak, Walter R. P. , El-Samad, Hana , Baker, David
De novo design of bioactive protein switches Journal Article
In: Nature, 2019.
@article{Langan2019,
title = {De novo design of bioactive protein switches},
author = {Langan, Robert A.
and Boyken, Scott E.
and Ng, Andrew H.
and Samson, Jennifer A.
and Dods, Galen
and Westbrook, Alexandra M.
and Nguyen, Taylor H.
and Lajoie, Marc J.
and Chen, Zibo
and Berger, Stephanie
and Mulligan, Vikram Khipple
and Dueber, John E.
and Novak, Walter R. P.
and El-Samad, Hana
and Baker, David},
url = {https://doi.org/10.1038/s41586-019-1432-8
https://www.nature.com/articles/s41586-019-1432-8
https://www.bakerlab.org/wp-content/uploads/2019/07/Langan_LOCKR.pdf},
doi = {10.1038/s41586-019-1432-8},
year = {2019},
date = {2019-07-24},
journal = {Nature},
abstract = {Allosteric regulation of protein function is widespread in biology, but is challenging for de novo protein design as it requires the explicit design of multiple states with comparable free energies. Here we explore the possibility of designing switchable protein systems de novo, through the modulation of competing inter- and intramolecular interactions. We design a static, five-helix ‘cage’ with a single interface that can interact either intramolecularly with a terminal ‘latch’ helix or intermolecularly with a peptide ‘key’. Encoded on the latch are functional motifs for binding, degradation or nuclear export that function only when the key displaces the latch from the cage. We describe orthogonal cage–key systems that function in vitro, in yeast and in mammalian cells with up to 40-fold activation of function by key. The ability to design switchable protein functions that are controlled by induced conformational change is a milestone for de novo protein design, and opens up new avenues for synthetic biology and cell engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ng, Andrew H. and Nguyen, Taylor H. and Gómez-Schiavon, Mariana and Dods, Galen and Langan, Robert A. and Boyken, Scott E. and Samson, Jennifer A. and Waldburger, Lucas M. and Dueber, John E. and Baker, David and El-Samad, Hana
Modular and tunable biological feedback control using a de novo protein switch Journal Article
In: Nature, 2019.
@article{Ng2019,
title = {Modular and tunable biological feedback control using a de novo protein switch},
author = {Ng, Andrew H.
and Nguyen, Taylor H.
and Gómez-Schiavon, Mariana
and Dods, Galen
and Langan, Robert A.
and Boyken, Scott E.
and Samson, Jennifer A.
and Waldburger, Lucas M.
and Dueber, John E.
and Baker, David
and El-Samad, Hana},
url = {https://doi.org/10.1038/s41586-019-1425-7
https://www.nature.com/articles/s41586-019-1425-7
https://www.bakerlab.org/wp-content/uploads/2019/07/Ng_LOCKR_circuits.pdf},
doi = {10.1038/s41586-019-1425-7},
year = {2019},
date = {2019-07-24},
journal = {Nature},
abstract = {De novo-designed proteins1–3 hold great promise as building blocks for synthetic circuits, and can complement the use of engineered variants of natural proteins4–7. One such designer protein—degronLOCKR, which is based on ‘latching orthogonal cage–key proteins’ (LOCKR) technology8—is a switch that degrades a protein of interest in vivo upon induction by a genetically encoded small peptide. Here we leverage the plug-and-play nature of degronLOCKR to implement feedback control of endogenous signalling pathways and synthetic gene circuits. We first generate synthetic negative and positive feedback in the yeast mating pathway by fusing degronLOCKR to endogenous signalling molecules, illustrating the ease with which this strategy can be used to rewire complex endogenous pathways. We next evaluate feedback control mediated by degronLOCKR on a synthetic gene circuit9, to quantify the feedback capabilities and operational range of the feedback control circuit. The designed nature of degronLOCKR proteins enables simple and rational modifications to tune feedback behaviour in both the synthetic circuit and the mating pathway. The ability to engineer feedback control into living cells represents an important milestone in achieving the full potential of synthetic biology10,11,12. More broadly, this work demonstrates the large and untapped potential of de novo design of proteins for generating tools that implement complex synthetic functionalities in cells for biotechnological and therapeutic applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hahnbeom Park, Gyu Rie Lee, David E. Kim, Ivan Anishchanka, Qian Cong, David Baker
High‐accuracy refinement using Rosetta in CASP13 Journal Article
In: Proteins, 2019.
@article{Park2019,
title = {High‐accuracy refinement using Rosetta in CASP13},
author = {Hahnbeom Park and Gyu Rie Lee and David E. Kim and Ivan Anishchanka and Qian Cong and David Baker},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.25784},
doi = {10.1002/prot.25784},
year = {2019},
date = {2019-07-20},
journal = {Proteins},
abstract = {Because proteins generally fold to their lowest free energy states, energy‐guided refinement in principle should be able to systematically improve the quality of protein structure models generated using homologous structure or co‐evolution derived information. However, because of the high dimensionality of the search space, there are far more ways to degrade the quality of a near native model than to improve it, and hence refinement methods are very sensitive to energy function errors. In CASP13, we sought to carry out a thorough search for low energy states in the neighborhood of a starting model using restraints to avoid straying too far. The approach was reasonably successful in improving both regions largely incorrect in the starting models as well core regions that started out closer to the correct structure. Models with GDT‐HA over 70 were obtained for five targets and for one of those, an accuracy of 0.5 å backbone RMSD was achieved. An important current challenge is to improve performance in refining oligomers and/or larger proteins, for which the search problem remains extremely difficult.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Qian Cong, Ivan Anishchenko, Sergey Ovchinnikov, David Baker
Protein interaction networks revealed by proteome coevolution Journal Article
In: Science, 2019.
@article{Cong2019,
title = {Protein interaction networks revealed by proteome coevolution},
author = {Qian Cong and Ivan Anishchenko and Sergey Ovchinnikov and David Baker},
url = {https://science.sciencemag.org/content/365/6449/185
https://www.bakerlab.org/wp-content/uploads/2019/07/2019_Cong_ProteomeCoevolution.pdf},
doi = {10.1126/science.aaw6718},
year = {2019},
date = {2019-07-11},
journal = {Science},
abstract = {Residue-residue coevolution has been observed across a number of protein-protein interfaces, but the extent of residue coevolution between protein families on the whole-proteome scale has not been systematically studied. We investigate coevolution between 5.4 million pairs of proteins in Escherichia coli and between 3.9 millions pairs in Mycobacterium tuberculosis. We find strong coevolution for binary complexes involved in metabolism and weaker coevolution for larger complexes playing roles in genetic information processing. We take advantage of this coevolution, in combination with structure modeling, to predict protein-protein interactions (PPIs) with an accuracy that benchmark studies suggest is considerably higher than that of proteome-wide two-hybrid and mass spectrometry screens. We identify hundreds of previously uncharacterized PPIs in E. coli and M. tuberculosis that both add components to known protein complexes and networks and establish the existence of new ones.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Harley Pyles, Shuai Zhang, James J. De Yoreo, David Baker
Controlling protein assembly on inorganic crystals through designed protein interfaces Journal Article
In: Nature, 2019.
@article{Pyles2019,
title = {Controlling protein assembly on inorganic crystals through designed protein interfaces},
author = {Harley Pyles and Shuai Zhang and James J. De Yoreo and David Baker },
url = {https://www.nature.com/articles/s41586-019-1361-6
https://www.bakerlab.org/wp-content/uploads/2019/07/2019_Pyles_MicaBinder.pdf},
doi = {10.1038/s41586-019-1361-6},
year = {2019},
date = {2019-07-10},
journal = {Nature},
abstract = {The ability of proteins and other macromolecules to interact with inorganic surfaces is essential to biological function. The proteins involved in these interactions are highly charged and often rich in carboxylic acid side chains, but the structures of most protein–inorganic interfaces are unknown. We explored the possibility of systematically designing structured protein–mineral interfaces, guided by the example of ice-binding proteins, which present arrays of threonine residues (matched to the ice lattice) that order clathrate waters into an ice-like structure6. Here we design proteins displaying arrays of up to 54 carboxylate residues geometrically matched to the potassium ion (K+) sublattice on muscovite mica (001). At low K+ concentration, individual molecules bind independently to mica in the designed orientations, whereas at high K+ concentration, the designs form two-dimensional liquid-crystal phases, which accentuate the inherent structural bias in the muscovite lattice to produce protein arrays ordered over tens of millimetres. Incorporation of designed protein–protein interactions preserving the match between the proteins and the K+ lattice led to extended self-assembled structures on mica: designed end-to-end interactions produced micrometre-long single-protein-diameter wires and a designed trimeric interface yielded extensive honeycomb arrays. The nearest-neighbour distances in these hexagonal arrays could be set digitally between 7.5 and 15.9 nanometres with 2.1-nanometre selectivity by changing the number of repeat units in the monomer. These results demonstrate that protein–inorganic lattice interactions can be systematically programmed and set the stage for designing protein–inorganic hybrid materials.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Koepnick, Brian and Flatten, Jeff and Husain, Tamir and Ford, Alex and Silva, Daniel-Adriano and Bick, Matthew J. and Bauer, Aaron and Liu, Gaohua and Ishida, Yojiro and Boykov, Alexander and Estep, Roger D. and Kleinfelter, Susan and Nørgård-Solano, Toke and Wei, Linda and Players, Foldit and Montelione, Gaetano T. and DiMaio, Frank and Popović, Zoran and Khatib, Firas and Cooper, Seth and Baker, David
De novo protein design by citizen scientists Journal Article
In: Nature, 2019.
@article{Koepnick2019,
title = {De novo protein design by citizen scientists},
author = {Koepnick, Brian
and Flatten, Jeff
and Husain, Tamir
and Ford, Alex
and Silva, Daniel-Adriano
and Bick, Matthew J.
and Bauer, Aaron
and Liu, Gaohua
and Ishida, Yojiro
and Boykov, Alexander
and Estep, Roger D.
and Kleinfelter, Susan
and Nørgård-Solano, Toke
and Wei, Linda
and Players, Foldit
and Montelione, Gaetano T.
and DiMaio, Frank
and Popović, Zoran
and Khatib, Firas
and Cooper, Seth
and Baker, David},
url = {https://doi.org/10.1038/s41586-019-1274-4
https://www.bakerlab.org/wp-content/uploads/2019/06/Koepnick_Nature2019_FolditDesign.pdf},
doi = {10.1038/s41586-019-1274-4},
year = {2019},
date = {2019-06-05},
journal = {Nature},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Boyken, Scott E., Benhaim, Mark A., Busch, Florian, Jia, Mengxuan, Bick, Matthew J., Choi, Heejun, Klima, Jason C., Chen, Zibo, Walkey, Carl, Mileant, Alexander, Sahasrabuddhe, Aniruddha, Wei, Kathy Y., Hodge, Edgar A., Byron, Sarah, Quijano-Rubio, Alfredo, Sankaran, Banumathi, King, Neil P., Lippincott-Schwartz, Jennifer, Wysocki, Vicki H., Lee, Kelly K., Baker, David
De novo design of tunable, pH-driven conformational changes Journal Article
In: Science, vol. 364, no. 6441, pp. 658-664, 2019.
@article{Boyken2019,
title = {De novo design of tunable, pH-driven conformational changes},
author = {Boyken, Scott E. and Benhaim, Mark A. and Busch, Florian and Jia, Mengxuan and Bick, Matthew J. and Choi, Heejun and Klima, Jason C. and Chen, Zibo and Walkey, Carl and Mileant, Alexander and Sahasrabuddhe, Aniruddha and Wei, Kathy Y. and Hodge, Edgar A. and Byron, Sarah and Quijano-Rubio, Alfredo and Sankaran, Banumathi and King, Neil P. and Lippincott-Schwartz, Jennifer and Wysocki, Vicki H. and Lee, Kelly K. and Baker, David
},
url = {https://science.sciencemag.org/content/364/6441/658
https://www.bakerlab.org/wp-content/uploads/2019/06/Boyken_etal2019_pH_conformational_changes.pdf},
doi = {10.1126/science.aav7897},
year = {2019},
date = {2019-05-17},
journal = {Science},
volume = {364},
number = {6441},
pages = {658-664},
abstract = {The ability of naturally occurring proteins to change conformation in response to environmental changes is critical to biological function. Although there have been advances in the de novo design of stable proteins with a single, deep free-energy minimum, the design of conformational switches remains challenging. We present a general strategy to design pH-responsive protein conformational changes by precisely preorganizing histidine residues in buried hydrogen-bond networks. We design homotrimers and heterodimers that are stable above pH 6.5 but undergo cooperative, large-scale conformational changes when the pH is lowered and electrostatic and steric repulsion builds up as the network histidine residues become protonated. The transition pH and cooperativity can be controlled through the number of histidine-containing networks and the strength of the surrounding hydrophobic interactions. Upon disassembly, the designed proteins disrupt lipid membranes both in vitro and after being endocytosed in mammalian cells. Our results demonstrate that environmentally triggered conformational changes can now be programmed by de novo protein design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dang, Luke T., Miao, Yi, Ha, Andrew, Yuki, Kanako, Park, Keunwan, Janda, Claudia Y., Jude, Kevin M., Mohan, Kritika, Ha, Nhi, Vallon, Mario, Yuan, Jenny, Vilches-Moure, José G., Kuo, Calvin J., Garcia, K. Christopher, Baker, David
Receptor subtype discrimination using extensive shape complementary designed interfaces Journal Article
In: Nature Structural & Molecular Biology, 2019, ISSN: 1545-9985.
@article{Dang2019,
title = {Receptor subtype discrimination using extensive shape complementary designed interfaces},
author = {Dang, Luke T. and Miao, Yi and Ha, Andrew and Yuki, Kanako and Park, Keunwan and Janda, Claudia Y. and Jude, Kevin M. and Mohan, Kritika and Ha, Nhi and Vallon, Mario and Yuan, Jenny and Vilches-Moure, José G. and Kuo, Calvin J. and Garcia, K. Christopher and Baker, David},
url = {https://doi.org/10.1038/s41594-019-0224-z
https://www.bakerlab.org/wp-content/uploads/2019/05/Dang2019_NSMB_ReceptorSubtypeDiscrimination.pdf},
doi = {10.1038/s41594-019-0224-z},
issn = {1545-9985},
year = {2019},
date = {2019-05-13},
journal = {Nature Structural & Molecular Biology},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
David Baker
What has de novo protein design taught us about protein folding and biophysics? Journal Article
In: Protein Science, vol. 28, no. 4, pp. 678-683, 2019.
@article{Baker2019,
title = {What has de novo protein design taught us about protein folding and biophysics?},
author = {David Baker},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/pro.3588
https://www.bakerlab.org/wp-content/uploads/2019/04/Baker-2019-Protein_Science.pdf},
doi = {10.1002/pro.3588},
year = {2019},
date = {2019-02-12},
journal = {Protein Science},
volume = {28},
number = {4},
pages = {678-683},
abstract = {Recent progress in de novo protein design has led to an explosion of new protein structures, functions and assemblies. In this essay, I consider how the successes and failures in this new area inform our understanding of the proteins in nature and, more generally, the predictive computational modeling of biological systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Silva, Daniel-Adriano and Yu, Shawn and Ulge, Umut Y. and Spangler, Jamie B. and Jude, Kevin M. and Labão-Almeida, Carlos and Ali, Lestat R. and Quijano-Rubio, Alfredo and Ruterbusch, Mikel and Leung, Isabel and Biary, Tamara and Crowley, Stephanie J. and Marcos, Enrique and Walkey, Carl D. and Weitzner, Brian D. and Pardo-Avila, Fátima and Castellanos, Javier and Carter, Lauren and Stewart, Lance and Riddell, Stanley R. and Pepper, Marion and Bernardes, Gonçalo J. L. and Dougan, Michael and Garcia, K. Christopher and Baker, David
De novo design of potent and selective mimics of IL-2 and IL-15 Journal Article
In: Nature, 2019, ISSN: 1476-4687.
@article{Silva2019,
title = {De novo design of potent and selective mimics of IL-2 and IL-15},
author = {Silva, Daniel-Adriano and
Yu, Shawn and
Ulge, Umut Y. and
Spangler, Jamie B. and
Jude, Kevin M. and
Labão-Almeida, Carlos and
Ali, Lestat R. and
Quijano-Rubio, Alfredo and
Ruterbusch, Mikel and
Leung, Isabel and
Biary, Tamara and
Crowley, Stephanie J. and
Marcos, Enrique and
Walkey, Carl D. and
Weitzner, Brian D. and
Pardo-Avila, Fátima and
Castellanos, Javier and
Carter, Lauren and
Stewart, Lance and
Riddell, Stanley R. and
Pepper, Marion and
Bernardes, Gonçalo J. L. and
Dougan, Michael and
Garcia, K. Christopher and
Baker, David
},
url = {https://www.nature.com/articles/s41586-018-0830-7
https://www.bakerlab.org/wp-content/uploads/2019/01/Silva2018_IL2-15.pdf},
doi = {10.1038/s41586-018-0830-7},
issn = {1476-4687},
year = {2019},
date = {2019-01-09},
journal = {Nature},
abstract = {We describe a de novo computational approach for designing proteins that recapitulate the binding sites of natural cytokines, but are otherwise unrelated in topology or amino acid sequence. We use this strategy to design mimics of the central immune cytokine interleukin-2 (IL-2) that bind to the IL-2 receptor βγc heterodimer (IL-2Rβγc) but have no binding site for IL-2Rα (also called CD25) or IL-15Rα (also known as CD215). The designs are hyper-stable, bind human and mouse IL-2Rβγc with higher affinity than the natural cytokines, and elicit downstream cell signalling independently of IL-2Rα and IL-15Rα. Crystal structures of the optimized design neoleukin-2/15 (Neo-2/15), both alone and in complex with IL-2Rβγc, are very similar to the designed model. Neo-2/15 has superior therapeutic activity to IL-2 in mouse models of melanoma and colon cancer, with reduced toxicity and undetectable immunogenicity. Our strategy for building hyper-stable de novo mimetics could be applied generally to signalling proteins, enabling the creation of superior therapeutic candidates.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
COLLABORATOR LED
Foight, Glenna Wink, Wang, Zhizhi, Wei, Cindy T., Jr Greisen, Per, Warner, Katrina M., Cunningham-Bryant, Daniel, Park, Keunwan, Brunette, T. J., Sheffler, William, Baker, David, Maly, Dustin J.
Multi-input chemical control of protein dimerization for programming graded cellular responses Journal Article
In: Nature Biotechnology, vol. 37, no. 10, pp. 1209-1216, 2019, ISBN: 1546-1696.
@article{Foight2019,
title = {Multi-input chemical control of protein dimerization for programming graded cellular responses},
author = {Foight, Glenna Wink and Wang, Zhizhi and Wei, Cindy T. and Jr Greisen, Per and Warner, Katrina M. and Cunningham-Bryant, Daniel and Park, Keunwan and Brunette, T. J. and Sheffler, William and Baker, David and Maly, Dustin J.},
url = {https://www.nature.com/articles/s41587-019-0242-8
https://www.bakerlab.org/wp-content/uploads/2020/06/Foight_et_al_2019_NatBiotech.pdf},
doi = {10.1038/s41587-019-0242-8},
isbn = {1546-1696},
year = {2019},
date = {2019-09-09},
journal = {Nature Biotechnology},
volume = {37},
number = {10},
pages = {1209-1216},
abstract = {Chemical and optogenetic methods for post-translationally controlling protein function have enabled modulation and engineering of cellular functions. However, most of these methods only confer single-input, single-output control. To increase the diversity of post-translational behaviors that can be programmed, we built a system based on a single protein receiver that can integrate multiple drug inputs, including approved therapeutics. Our system translates drug inputs into diverse outputs using a suite of engineered reader proteins to provide variable dimerization states of the receiver protein. We show that our single receiver protein architecture can be used to program a variety of cellular responses, including graded and proportional dual-output control of transcription and mammalian cell signaling. We apply our tools to titrate the competing activities of the Rac and Rho GTPases to control cell morphology. Our versatile tool set will enable researchers to post-translationally program mammalian cellular processes and to engineer cell therapies.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Qi Wu, Zhenling Peng, Ivan Anishchenko, Qian Cong, David Baker, Jianyi Yang
Protein contact prediction using metagenome sequence data and residual neural networks Journal Article
In: Bioinformatics, vol. 36, no. 1, 2019.
@article{Wu2019,
title = {Protein contact prediction using metagenome sequence data and residual neural networks},
author = {Qi Wu and Zhenling Peng and Ivan Anishchenko and Qian Cong and David Baker and Jianyi Yang},
url = {https://academic.oup.com/bioinformatics/article/36/1/41/5512356},
doi = {10.1093/bioinformatics/btz477},
year = {2019},
date = {2019-06-07},
journal = {Bioinformatics},
volume = {36},
number = {1},
abstract = {Motivation: Almost all protein residue contact prediction methods rely on the availability of deep multiple sequence alignments (MSAs). However, many proteins from the poorly populated families do not have sufficient number of homologs in the conventional UniProt database. Here we aim to solve this issue by exploring the rich sequence data from the metagenome sequencing projects. Results: Based on the improved MSA constructed from the metagenome sequence data, we developed MapPred, a new deep learning-based contact prediction method. MapPred consists of two component methods, DeepMSA and DeepMeta, both trained with the residual neural networks. DeepMSA was inspired by the recent method DeepCov, which was trained on 441 matrices of covariance features. By considering the symmetry of contact map, we reduced the number of matrices to 231, which makes the training more efficient in DeepMSA. Experiments show that DeepMSA outperforms DeepCov by 10–13% in precision. DeepMeta works by combining predicted contacts and other sequence profile features. Experiments on three benchmark datasets suggest that the contribution from the metagenome sequence data is significant with P-values less than 4.04E-17. MapPred is shown to be complementary and comparable the state-of-the-art methods. The success of MapPred is attributed to three factors: the deeper MSA from the metagenome sequence data, improved feature design in DeepMSA and optimized training by the residual neural networks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mohan, Kritika, Ueda, George, Kim, Ah Ram, Jude, Kevin M., Fallas, Jorge A., Guo, Yu, Hafer, Maximillian, Miao, Yi, Saxton, Robert A., Piehler, Jacob, Sankaran, Vijay G., Baker, David, Garcia, K. Christopher
Topological control of cytokine receptor signaling induces differential effects in hematopoiesis Journal Article
In: Science, vol. 364, no. 6442, 2019.
@article{Mohan2019,
title = {Topological control of cytokine receptor signaling induces differential effects in hematopoiesis},
author = {Mohan, Kritika and Ueda, George and Kim, Ah Ram and Jude, Kevin M. and Fallas, Jorge A. and Guo, Yu and Hafer, Maximillian and Miao, Yi and Saxton, Robert A. and Piehler, Jacob and Sankaran, Vijay G. and Baker, David and Garcia, K. Christopher
},
url = {https://science.sciencemag.org/content/364/6442/eaav7532
https://www.bakerlab.org/wp-content/uploads/2019/05/Mohan2019_Science_cytokinebinders.pdf},
doi = {10.1126/science.aav7532},
year = {2019},
date = {2019-05-24},
journal = {Science},
volume = {364},
number = {6442},
abstract = {Although tunable signaling by G protein–coupled receptors can be exploited through medicinal chemistry, a comparable pharmacological approach has been lacking for the modulation of signaling through dimeric receptors, such as those for cytokines. We present a strategy to modulate cytokine receptor signaling output by use of a series of designed C2-symmetric cytokine mimetics, based on the designed ankyrin repeat protein (DARPin) scaffold, that can systematically control erythropoietin receptor (EpoR) dimerization orientation and distance between monomers. We sampled a range of EpoR geometries by varying intermonomer angle and distance, corroborated by several ligand-EpoR complex crystal structures. Across the range, we observed full, partial, and biased agonism as well as stage-selective effects on hematopoiesis. This surrogate ligand strategy opens access to pharmacological modulation of therapeutically important cytokine and growth factor receptor systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Chen, Zibo, Johnson, Matthew C., Chen, Jiajun, Bick, Matthew J., Boyken, Scott E., Lin, Baihan, De Yoreo, James J., Kollman, Justin M., Baker, David, DiMaio, Frank
Self-Assembling 2D Arrays with de Novo Protein Building Blocks Journal Article
In: Journal of the American Chemical Society, 2019.
@article{Chen2019,
title = {Self-Assembling 2D Arrays with de Novo Protein Building Blocks},
author = {Chen, Zibo and Johnson, Matthew C. and Chen, Jiajun and Bick, Matthew J. and Boyken, Scott E. and Lin, Baihan and De Yoreo, James J. and Kollman, Justin M. and Baker, David and DiMaio, Frank},
url = {https://www.bakerlab.org/wp-content/uploads/2020/02/Chen2019_JACS_2Darrays.pdf
https://pubs.acs.org/doi/abs/10.1021/jacs.9b01978#},
doi = {10.1021/jacs.9b01978},
year = {2019},
date = {2019-05-03},
journal = {Journal of the American Chemical Society},
abstract = {Modular self-assembly of biomolecules in two dimensions (2D) is straightforward with DNA but has been difficult to realize with proteins, due to the lack of modular specificity similar to Watson−Crick base pairing. Here we describe a general approach to design 2D arrays using de novo designed pseudosymmetric protein building blocks. A homodimeric helical bundle was reconnected into a monomeric building block, and the surface was redesigned in Rosetta to enable self-assembly into a 2D array in the C12 layer symmetry group. Two out of ten designed arrays assembled to micrometer scale under negative stain electron microscopy, and displayed the designed lattice geometry with assembly size up to 100 nm under atomic force microscopy. The design of 2D arrays with pseudosymmetric building blocks is an important step toward the design of programmable protein self-assembly via pseudosymmetric patterning of orthogonal binding interfaces.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Jessica Marcandalli, Brooke Fiala, Sebastian Ols, Michela Perotti, Willem de van der Schueren, Joost Snijder, Edgar Hodge, Mark Benhaim, Rashmi Ravichandran, Lauren Carter, Will Sheffler, Livia Brunner, Maria Lawrenz, Patrice Dubois, Antonio Lanzavecchia, Federica Sallusto, Kelly K. Lee, David Veesler, Colin E. Correnti, Lance J. Stewart, David Baker, Karin Loré, Laurent Perez, Neil P. King,
Induction of Potent Neutralizing Antibody Responses by a Designed Protein Nanoparticle Vaccine for Respiratory Syncytial Virus Journal Article
In: Cell, vol. 176, no. 6, pp. 1420-1431, 2019.
@article{Marcandalli2019,
title = {Induction of Potent Neutralizing Antibody Responses by a Designed Protein Nanoparticle Vaccine for Respiratory Syncytial Virus},
author = {Jessica Marcandalli, Brooke Fiala, Sebastian Ols, Michela Perotti, Willem de van der Schueren, Joost Snijder, Edgar Hodge, Mark Benhaim, Rashmi Ravichandran, Lauren Carter, Will Sheffler, Livia Brunner, Maria Lawrenz, Patrice Dubois, Antonio Lanzavecchia, Federica Sallusto, Kelly K. Lee, David Veesler, Colin E. Correnti, Lance J. Stewart, David Baker, Karin Loré, Laurent Perez, Neil P. King,},
url = {https://www.cell.com/cell/pdf/S0092-8674(19)30109-6.pdf},
doi = {10.1016/j.cell.2019.01.046},
year = {2019},
date = {2019-03-07},
journal = {Cell},
volume = {176},
number = {6},
pages = {1420-1431},
abstract = {Respiratory syncytial virus (RSV) is a worldwide public health concern for which no vaccine is available. Elucidation of the prefusion structure of the RSV F glycoprotein and its identification as the main target of neutralizing antibodies have provided new opportunities for development of an effective vaccine. Here, we describe the structure-based design of a self-assembling protein nanoparticle presenting a prefusion-stabilized variant of the F glycoprotein trimer (DS-Cav1) in a repetitive array on the nanoparticle exterior. The two-component nature of the nanoparticle scaffold enabled the production of highly ordered, monodisperse immunogens that display DS-Cav1 at controllable density. In mice and nonhuman primates, the full-valency nanoparticle immunogen displaying 20 DS-Cav1 trimers induced neutralizing antibody responses ∼10-fold higher than trimeric DS-Cav1. These results motivate continued development of this promising nanoparticle RSV vaccine candidate and establish computationally designed two-component nanoparticles as a robust and customizable platform for structure-based vaccine design.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2018
FROM THE LAB
Chen, Zibo and Boyken, Scott E. and Jia, Mengxuan and Busch, Florian and Flores-Solis, David and Bick, Matthew J. and Lu, Peilong and VanAernum, Zachary L. and Sahasrabuddhe, Aniruddha and Langan, Robert A. and Bermeo, Sherry and Brunette, T. J. and Mulligan, Vikram Khipple and Carter, Lauren P. and DiMaio, Frank and Sgourakis, Nikolaos G. and Wysocki, Vicki H. and Baker, David
Programmable design of orthogonal protein heterodimers Journal Article
In: Nature, 2018, ISSN: 1476-4687.
@article{Chen2018,
title = {Programmable design of orthogonal protein heterodimers},
author = {Chen, Zibo and
Boyken, Scott E. and
Jia, Mengxuan and
Busch, Florian and
Flores-Solis, David and
Bick, Matthew J. and
Lu, Peilong and
VanAernum, Zachary L. and
Sahasrabuddhe, Aniruddha and
Langan, Robert A. and
Bermeo, Sherry and
Brunette, T. J. and
Mulligan, Vikram Khipple and
Carter, Lauren P. and
DiMaio, Frank and
Sgourakis, Nikolaos G. and
Wysocki, Vicki H. and
Baker, David},
url = {https://doi.org/10.1038/s41586-018-0802-y
https://www.bakerlab.org/wp-content/uploads/2018/12/Chen2018_heterodimers.pdf},
doi = {10.1038/s41586-018-0802-y},
issn = {1476-4687},
year = {2018},
date = {2018-12-19},
journal = {Nature},
abstract = {Specificity of interactions between two DNA strands, or between protein and DNA, is often achieved by varying bases or side chains coming off the DNA or protein backbone—for example, the bases participating in Watson–Crick pairing in the double helix, or the side chains contacting DNA in TALEN–DNA complexes. By contrast, specificity of protein–protein interactions usually involves backbone shape complementarity1, which is less modular and hence harder to generalize. Coiled-coil heterodimers are an exception, but the restricted geometry of interactions across the heterodimer interface (primarily at the heptad a and d positions2) limits the number of orthogonal pairs that can be created simply by varying side-chain interactions3,4. Here we show that protein–protein interaction specificity can be achieved using extensive and modular side-chain hydrogen-bond networks. We used the Crick generating equations5 to produce millions of four-helix backbones with varying degrees of supercoiling around a central axis, identified those accommodating extensive hydrogen-bond networks, and used Rosetta to connect pairs of helices with short loops and to optimize the remainder of the sequence. Of 97 such designs expressed in Escherichia coli, 65 formed constitutive heterodimers, and the crystal structures of four designs were in close agreement with the computational models and confirmed the designed hydrogen-bond networks. In cells, six heterodimers were fully orthogonal, and in vitro—following mixing of 32 chains from 16 heterodimer designs, denaturation in 5 M guanidine hydrochloride and reannealing—almost all of the interactions observed by native mass spectrometry were between the designed cognate pairs. The ability to design orthogonal protein heterodimers should enable sophisticated protein-based control logic for synthetic biology, and illustrates that nature has not fully explored the possibilities for programmable biomolecular interaction modalities.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Shen, Hao, Fallas, Jorge A., Lynch, Eric, Sheffler, William, Parry, Bradley, Jannetty, Nicholas, Decarreau, Justin, Wagenbach, Michael, Vicente, Juan Jesus, Chen, Jiajun, Wang, Lei, Dowling, Quinton, Oberdorfer, Gustav, Stewart, Lance, Wordeman, Linda, De Yoreo, James, Jacobs-Wagner, Christine, Kollman, Justin, Baker, David
De novo design of self-assembling helical protein filaments Journal Article
In: Science, vol. 362, no. 6415, pp. 705–709, 2018, ISSN: 0036-8075.
@article{Shen2018,
title = {De novo design of self-assembling helical protein filaments},
author = {Shen, Hao and Fallas, Jorge A. and Lynch, Eric and Sheffler, William and Parry, Bradley and Jannetty, Nicholas and Decarreau, Justin and Wagenbach, Michael and Vicente, Juan Jesus and Chen, Jiajun and Wang, Lei and Dowling, Quinton and Oberdorfer, Gustav and Stewart, Lance and Wordeman, Linda and De Yoreo, James and Jacobs-Wagner, Christine and Kollman, Justin and Baker, David},
url = {http://science.sciencemag.org/content/362/6415/705
https://www.bakerlab.org/wp-content/uploads/2018/12/Shen2018_filaments.pdf},
doi = {10.1126/science.aau3775},
issn = {0036-8075},
year = {2018},
date = {2018-11-09},
journal = {Science},
volume = {362},
number = {6415},
pages = {705–709},
abstract = {There has been some success in designing stable peptide filaments; however, mimicking the reversible assembly of many natural protein filaments is challenging. Dynamic filaments usually comprise independently folded and asymmetric proteins and using such building blocks requires the design of multiple intermonomer interfaces. Shen et al. report the design of self-assembling helical filaments based on previously designed stable repeat proteins. The filaments are micron scale, and their diameter can be tuned by varying the number of repeats in the monomer. Anchor and capping units, built from monomers that lack an interaction interface, can be used to control assembly and disassembly.Science, this issue p. 705We describe a general computational approach to designing self-assembling helical filaments from monomeric proteins and use this approach to design proteins that assemble into micrometer-scale filaments with a wide range of geometries in vivo and in vitro. Cryo{textendash}electron microscopy structures of six designs are close to the computational design models. The filament building blocks are idealized repeat proteins, and thus the diameter of the filaments can be systematically tuned by varying the number of repeat units. The assembly and disassembly of the filaments can be controlled by engineered anchor and capping units built from monomers lacking one of the interaction surfaces. The ability to generate dynamic, highly ordered structures that span micrometers from protein monomers opens up possibilities for the fabrication of new multiscale metamaterials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Marcos, Enrique and Chidyausiku, Tamuka M. and McShan, Andrew C. and Evangelidis, Thomas and Nerli, Santrupti and Carter, Lauren and Nivón, Lucas G. and Davis, Audrey and Oberdorfer, Gustav and Tripsianes, Konstantinos and Sgourakis, Nikolaos G. and Baker, David
De novo design of a non-local β-sheet protein with high stability and accuracy Journal Article
In: Nature Structural & Molecular Biology, 2018, ISSN: 1545-9985.
@article{Marcos2018,
title = {De novo design of a non-local β-sheet protein with high stability and accuracy},
author = {Marcos, Enrique and
Chidyausiku, Tamuka M. and
McShan, Andrew C. and
Evangelidis, Thomas and
Nerli, Santrupti and
Carter, Lauren and
Nivón, Lucas G. and
Davis, Audrey and
Oberdorfer, Gustav and
Tripsianes, Konstantinos and
Sgourakis, Nikolaos G. and
Baker, David},
url = {https://doi.org/10.1038/s41594-018-0141-6
https://www.bakerlab.org/wp-content/uploads/2018/11/Marcos_etal_2018.pdf},
doi = {10.1038/s41594-018-0141-6},
issn = {1545-9985},
year = {2018},
date = {2018-10-29},
journal = {Nature Structural & Molecular Biology},
abstract = {β-sheet proteins carry out critical functions in biology, and hence are attractive scaffolds for computational protein design. Despite this potential, de novo design of all-β-sheet proteins from first principles lags far behind the design of all-α or mixed-αβ domains owing to their non-local nature and the tendency of exposed β-strand edges to aggregate. Through study of loops connecting unpaired β-strands (β-arches), we have identified a series of structural relationships between loop geometry, side chain directionality and β-strand length that arise from hydrogen bonding and packing constraints on regular β-sheet structures. We use these rules to de novo design jellyroll structures with double-stranded β-helices formed by eight antiparallel β-strands. The nuclear magnetic resonance structure of a hyperthermostable design closely matched the computational model, demonstrating accurate control over the β-sheet structure and loop geometry. Our results open the door to the design of a broad range of non-local β-sheet protein structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Jiayi Dou*, Anastassia A. Vorobieva*, William Sheffler, Lindsey A. Doyle, Hahnbeom Park, Matthew J. Bick, Binchen Mao, Glenna W. Foight, Min Yen Lee, Lauren A. Gagnon, Lauren Carter, Banumathi Sankaran, Sergey Ovchinnikov, Enrique Marcos, Po-Ssu Huang, Joshua C. Vaughan, Barry L. Stoddard, David Baker
De novo design of a fluorescence-activating β-barrel Journal Article
In: Nature, 2018, ISSN: 1476-4687.
@article{1011,
title = {De novo design of a fluorescence-activating β-barrel},
author = {Jiayi Dou* and Anastassia A. Vorobieva* and William Sheffler and Lindsey A. Doyle and Hahnbeom Park and Matthew J. Bick and Binchen Mao and Glenna W. Foight and Min Yen Lee and Lauren A. Gagnon and Lauren Carter and Banumathi Sankaran and Sergey Ovchinnikov and Enrique Marcos and Po-Ssu Huang and Joshua C. Vaughan and Barry L. Stoddard and David Baker },
url = {https://www.nature.com/articles/s41586-018-0509-0
https://www.bakerlab.org/wp-content/uploads/2018/09/s41586-018-0509-0.pdf},
doi = {10.1038/s41586-018-0509-0},
issn = {1476-4687},
year = {2018},
date = {2018-09-12},
journal = {Nature},
abstract = {The regular arrangements of β-strands around a central axis in β-barrels and of α-helices in coiled coils contrast with the irregular tertiary structures of most globular proteins, and have fascinated structural biologists since they were first discovered. Simple parametric models have been used to design a wide range of α-helical coiled-coil structures, but to date there has been no success with β-barrels. Here we show that accurate de novo design of β-barrels requires considerable symmetry-breaking to achieve continuous hydrogen-bond connectivity and eliminate backbone strain. We then build ensembles of β-barrel backbone models with cavity shapes that match the fluorogenic compound DFHBI, and use a hierarchical grid-based search method to simultaneously optimize the rigid-body placement of DFHBI in these cavities and the identities of the surrounding amino acids to achieve high shape and chemical complementarity. The designs have high structural accuracy and bind and fluorescently activate DFHBI in vitro and in Escherichia coli, yeast and mammalian cells. This de novo design of small-molecule binding activity, using backbones custom-built to bind the ligand, should enable the design of increasingly sophisticated ligand-binding proteins, sensors and catalysts that are not limited by the backbone geometries available in known protein structures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Park, Hahnbeom, Ovchinnikov, Sergey, Kim, David E., DiMaio, Frank, Baker, David
Protein homology model refinement by large-scale energy optimization Journal Article
In: Proceedings of the National Academy of Sciences, vol. 115, no. 12, pp. 3054–3059, 2018, ISSN: 0027-8424.
@article{Park2018,
title = {Protein homology model refinement by large-scale energy optimization},
author = {Park, Hahnbeom and Ovchinnikov, Sergey and Kim, David E. and DiMaio, Frank and Baker, David},
url = {https://www.pnas.org/content/115/12/3054
https://www.bakerlab.org/wp-content/uploads/2019/01/Park2018_refinement.pdf},
doi = {10.1073/pnas.1719115115},
issn = {0027-8424},
year = {2018},
date = {2018-03-20},
journal = {Proceedings of the National Academy of Sciences},
volume = {115},
number = {12},
pages = {3054–3059},
abstract = {Protein structure refinement by direct global energy optimization has been a longstanding challenge in computational structural biology due to limitations in both energy function accuracy and conformational sampling. This manuscript demonstrates that with recent advances in both areas, refinement can significantly improve protein comparative models based on structures of distant homologues.Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Lu, Peilong, Min, Duyoung, DiMaio, Frank, Wei, Kathy Y., Vahey, Michael D., Boyken, Scott E., Chen, Zibo, Fallas, Jorge A., Ueda, George, Sheffler, William, Mulligan, Vikram Khipple, Xu, Wenqing, Bowie, James U., Baker, David
Accurate computational design of multipass transmembrane proteins Journal Article
In: Science, vol. 359, no. 6379, pp. 1042–1046, 2018, ISSN: 0036-8075.
@article{Lu1042,
title = {Accurate computational design of multipass transmembrane proteins},
author = {Lu, Peilong and Min, Duyoung and DiMaio, Frank and Wei, Kathy Y. and Vahey, Michael D. and Boyken, Scott E. and Chen, Zibo and Fallas, Jorge A. and Ueda, George and Sheffler, William and Mulligan, Vikram Khipple and Xu, Wenqing and Bowie, James U. and Baker, David},
url = {http://science.sciencemag.org/content/359/6379/1042
https://www.bakerlab.org/wp-content/uploads/2018/03/Lu_Science_2018.pdf},
doi = {10.1126/science.aaq1739},
issn = {0036-8075},
year = {2018},
date = {2018-03-02},
journal = {Science},
volume = {359},
number = {6379},
pages = {1042--1046},
abstract = {In recent years, soluble protein design has achieved successes such as artificial enzymes and large protein cages. Membrane proteins present a considerable design challenge, but here too there have been advances, including the design of a zinc-transporting tetramer. Lu et al. report the design of stable transmembrane monomers, homodimers, trimers, and tetramers with up to eight membrane-spanning regions in an oligomer. The designed proteins adopted the target oligomerization state and localized to the predicted cellular membranes, and crystal structures of the designed dimer and tetramer reflected the design models.Science, this issue p. 1042The computational design of transmembrane proteins with more than one membrane-spanning region remains a major challenge. We report the design of transmembrane monomers, homodimers, trimers, and tetramers with 76 to 215 residue subunits containing two to four membrane-spanning regions and up to 860 total residues that adopt the target oligomerization state in detergent solution. The designed proteins localize to the plasma membrane in bacteria and in mammalian cells, and magnetic tweezer unfolding experiments in the membrane indicate that they are very stable. Crystal structures of the designed dimer and tetramer{textemdash}a rocket-shaped structure with a wide cytoplasmic base that funnels into eight transmembrane helices{textemdash}are very close to the design models. Our results pave the way for the design of multispan membrane proteins with new functions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
COLLABORATOR LED
Day, Austin L, Greisen, Per, Doyle, Lindsey, Schena, Alberto, Stella, Nephi, Johnsson, Kai, Baker, David, Stoddard, Barry
Unintended specificity of an engineered ligand-binding protein facilitated by unpredicted plasticity of the protein fold Journal Article
In: Protein Engineering, Design and Selection, 2018.
@article{Day2018,
title = {Unintended specificity of an engineered ligand-binding protein facilitated by unpredicted plasticity of the protein fold},
author = {Day, Austin L and Greisen, Per and Doyle, Lindsey and Schena, Alberto and Stella, Nephi and Johnsson, Kai and Baker, David and Stoddard, Barry
},
url = {https://dx.doi.org/10.1093/protein/gzy031
https://www.bakerlab.org/wp-content/uploads/2019/02/Day2018.pdf},
doi = {10.1093/protein/gzy031},
year = {2018},
date = {2018-12-19},
journal = {Protein Engineering, Design and Selection},
abstract = {Attempts to create novel ligand-binding proteins often focus on formation of a binding pocket with shape complementarity against the desired ligand (particularly for compounds that lack distinct polar moieties). Although designed proteins often exhibit binding of the desired ligand, in some cases they display unintended recognition behavior. One such designed protein, that was originally intended to bind tetrahydrocannabinol (THC), was found instead to display binding of 25-hydroxy-cholecalciferol (25-D3) and was subjected to biochemical characterization, further selections for enhanced 25-D3 binding affinity and crystallographic analyses. The deviation in specificity is due in part to unexpected altertion of its conformation, corresponding to a significant change of the orientation of an α-helix and an equally large movement of a loop, both of which flank the designed ligand-binding pocket. Those changes led to engineered protein constructs that exhibit significantly more contacts and complementarity towards the 25-D3 ligand than the initial designed protein had been predicted to form towards its intended THC ligand. Molecular dynamics simulations imply that the initial computationally designed mutations may contribute to the movement of the helix. These analyses collectively indicate that accurate prediction and control of backbone dynamics conformation, through a combination of improved conformational sampling and/or de novo structure design, represents a key area of further development for the design and optimization of engineered ligand-binding proteins.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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}
}
Geiger-Schuller, Kathryn, Sforza, Kevin, Yuhas, Max, Parmeggiani, Fabio, Baker, David, Barrick, Doug
Extreme stability in de novo-designed repeat arrays is determined by unusually stable short-range interactions Journal Article
In: PNAS, vol. 115, no. 29, pp. 7539-7544, 2018, ISSN: 0027-8424.
@article{Geiger-Schuller2018,
title = {Extreme stability in de novo-designed repeat arrays is determined by unusually stable short-range interactions},
author = {Geiger-Schuller, Kathryn and Sforza, Kevin and Yuhas, Max and Parmeggiani, Fabio and Baker, David and Barrick, Doug},
url = {https://www.pnas.org/content/115/29/7539
https://www.bakerlab.org/wp-content/uploads/2019/02/Geiger-Schuller2018.pdf},
doi = {10.1073/pnas.1800283115},
issn = {0027-8424},
year = {2018},
date = {2018-07-17},
journal = {PNAS},
volume = {115},
number = {29},
pages = {7539-7544},
abstract = {We apply a statistical thermodynamic formalism to quantify the cooperativity of folding of de novo-designed helical repeat proteins (DHRs). This analysis provides a fundamental thermodynamic description of folding for de novo-designed proteins and permits comparison with naturally occurring repeat protein thermodynamics. We find that individual DHR units are intrinsically stable, unlike those of naturally occurring proteins. This observation reveals local (intrarepeat) interactions as a source of high stability in Rosetta-designed proteins and suggests that different types of DHR repeats may be combined in a single polypeptide chain, expanding the repertoire of folded DHRs for applications such as molecular recognition. Favorable intrinsic stability imparts a downhill shape to the energy landscape, suggesting that DHRs fold fast and through parallel pathways.Designed helical repeats (DHRs) are modular helix{textendash}loop{textendash}helix{textendash}loop protein structures that are tandemly repeated to form a superhelical array. Structures combining tandem DHRs demonstrate a wide range of molecular geometries, many of which are not observed in nature. Understanding cooperativity of DHR proteins provides insight into the molecular origins of Rosetta-based protein design hyperstability and facilitates comparison of energy distributions in artificial and naturally occurring protein folds. Here, we use a nearest-neighbor Ising model to quantify the intrinsic and interfacial free energies of four different DHRs. We measure the folding free energies of constructs with varying numbers of internal and terminal capping repeats for four different DHR folds, using guanidine-HCl and glycerol as destabilizing and solubilizing cosolvents. One-dimensional Ising analysis of these s