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Article ; Online: Improving de novo protein binder design with deep learning.

Bennett, Nathaniel R / Coventry, Brian / Goreshnik, Inna / Huang, Buwei / Allen, Aza / Vafeados, Dionne / Peng, Ying Po / Dauparas, Justas / Baek, Minkyung / Stewart, Lance / DiMaio, Frank / De Munck, Steven / Savvides, Savvas N / Baker, David

Nature communications

2023 Volume 14, Issue 1, Page(s) 2625

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 ... ...

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.
MeSH term(s)	Deep Learning ; Protein Engineering ; Proteins/metabolism ; Protein Binding
Chemical Substances	Proteins
Language	English
Publishing date	2023-05-06
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-38328-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Parallelized identification of on- and off-target protein interactions.

Dou, Jiayi / Goreshnik, Inna / Bryan, Cassie / Baker, David / Strauch, Eva-Maria

Molecular systems design & engineering

2019 Volume 5, Issue 1, Page(s) 349–357

Abstract: Genetic selection combined with next-generation sequencing enables the simultaneous interrogation of the functionality and stability of large numbers of naturally occurring, engineered, or computationally designed protein variants in parallel. We display ...

Abstract	Genetic selection combined with next-generation sequencing enables the simultaneous interrogation of the functionality and stability of large numbers of naturally occurring, engineered, or computationally designed protein variants in parallel. We display hundreds of engineered proteins on the surface of yeast cells, select for binding to a set of target molecules by flow cytometry, and sequence the starting pool as well as selected pools to obtain enrichment values for each displayed protein with each target. We show that this high-throughput workflow of multiplex genetic selections followed by large-scale sequencing and comparative analysis allows not only the determination of relative affinities, but also the monitoring of specificity profiles for hundreds to thousands of protein-protein and protein-small molecule interactions in parallel. The approach not only identifies new interactions of designed proteins, but also detects unintended and undesirable off-target interactions. This provides a general framework for screening of engineered protein binders, which often have no negative selection or design step as part of their development pipelines. Hence, this method will be generally useful in the development of protein-based therapeutics.
Language	English
Publishing date	2019-11-26
Publishing country	England
Document type	Journal Article
ISSN	2058-9689
ISSN	2058-9689
DOI	10.1039/c9me00118b
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Article: Atomically accurate de novo design of single-domain antibodies.

bioRxiv : the preprint server for biology

2024

Abstract: Despite the central role that antibodies play in modern medicine, there is currently no way to rationally design novel antibodies to bind a specific epitope on a target. Instead, antibody discovery currently involves time-consuming immunization of an ... ...

Abstract	Despite the central role that antibodies play in modern medicine, there is currently no way to rationally design novel antibodies to bind a specific epitope on a target. Instead, antibody discovery currently involves time-consuming immunization of an animal or library screening approaches. Here we demonstrate that a fine-tuned RFdiffusion network is capable of designing de novo antibody variable heavy chains (VHH's) that bind user-specified epitopes. We experimentally confirm binders to four disease-relevant epitopes, and the cryo-EM structure of a designed VHH bound to influenza hemagglutinin is nearly identical to the design model both in the configuration of the CDR loops and the overall binding pose.
Language	English
Publishing date	2024-03-18
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.03.14.585103
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Article ; Online: An enumerative algorithm for de novo design of proteins with diverse pocket structures.

Basanta, Benjamin / Bick, Matthew J / Bera, Asim K / Norn, Christoffer / Chow, Cameron M / Carter, Lauren P / Goreshnik, Inna / Dimaio, Frank / Baker, David

Proceedings of the National Academy of Sciences of the United States of America

2020 Volume 117, Issue 36, Page(s) 22135–22145

Abstract: 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. ... ...

Abstract	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.
MeSH term(s)	Algorithms ; Binding Sites ; Computer Simulation ; High-Throughput Screening Assays ; Models, Molecular ; Nucleocytoplasmic Transport Proteins/chemistry ; Protein Conformation ; Protein Engineering ; Protein Stability
Chemical Substances	Nucleocytoplasmic Transport Proteins
Language	English
Publishing date	2020-08-24
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.2005412117
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Article ; Online: A small molecule-regulated guanine nucleotide exchange factor.

Goreshnik, Inna / Maly, Dustin J

Journal of the American Chemical Society

2010 Volume 132, Issue 3, Page(s) 938–940

Abstract: Selective, pharmacological agents are attractive tools for studying signal transduction because they allow rapid, reversible, and dose-dependent control over intracellular protein function. However, for many targets the identification of potent and ... ...

Abstract	Selective, pharmacological agents are attractive tools for studying signal transduction because they allow rapid, reversible, and dose-dependent control over intracellular protein function. However, for many targets the identification of potent and selective small molecule agonists and antagonists is a formidable challenge. An attractive strategy for circumventing this problem is to engineer a protein of interest to be sensitive to a pharmacological agent of choice. Here, we report a chemical genetic method for regulating the catalytic activity of signaling enzymes with a small molecule. This approach uses the interaction of the antiapoptotic protein Bcl-xL and a BH3 peptide as an autoinhibitory switch that can be controlled with a small molecule. We applied this strategy to the guanine nucleotide exchange factor Intersectin, which is a selective activator of the GTPase Cdc42. Replacing Intersectin's regulatory domains with the BH3 peptide/Bcl-xL binding module generated a panel of synthetic GEF constructs that can be activated with a competitive ligand. Importantly, the nucleotide exchange activities of these synthetic Intersectin constructs can be controlled in a rapid and dose-dependent manner. The modular nature of this strategy should make it useful for engineering other enzymes involved in signal transduction.
MeSH term(s)	Aniline Compounds/pharmacology ; Binding Sites ; Biphenyl Compounds/pharmacology ; Guanine Nucleotide Exchange Factors/chemistry ; Guanine Nucleotide Exchange Factors/metabolism ; Molecular Structure ; Molecular Weight ; Nitrophenols/pharmacology ; Peptide Fragments/antagonists & inhibitors ; Peptide Fragments/chemistry ; Peptide Fragments/metabolism ; Piperazines/pharmacology ; Protein Binding ; Proto-Oncogene Proteins/antagonists & inhibitors ; Proto-Oncogene Proteins/chemistry ; Proto-Oncogene Proteins/metabolism ; Rho Guanine Nucleotide Exchange Factors ; Structure-Activity Relationship ; Sulfonamides/pharmacology ; bcl-X Protein/antagonists & inhibitors ; bcl-X Protein/chemistry ; bcl-X Protein/metabolism
Chemical Substances	4-(3-dimethylamino-1-phenylsulfanylmethylpropylamino)-N-(4-(4,4-dimethylpiperidin-1-yl)benzoyl)-3-nitrobenzenesulfonamide ; ABT-737 ; Aniline Compounds ; Bax protein (53-86) ; Biphenyl Compounds ; Guanine Nucleotide Exchange Factors ; Nitrophenols ; Peptide Fragments ; Piperazines ; Proto-Oncogene Proteins ; Rho Guanine Nucleotide Exchange Factors ; Sulfonamides ; bcl-X Protein
Language	English
Publishing date	2010-01-27
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	3155-0
ISSN	1520-5126 ; 0002-7863
ISSN (online)	1520-5126
ISSN	0002-7863
DOI	10.1021/ja907886v
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Article ; Online: Computational design of a synthetic PD-1 agonist.

Bryan, Cassie M / Rocklin, Gabriel J / Bick, Matthew J / Ford, Alex / Majri-Morrison, Sonia / Kroll, Ashley V / Miller, Chad J / Carter, Lauren / Goreshnik, Inna / Kang, Alex / DiMaio, Frank / Tarbell, Kristin V / Baker, David

Proceedings of the National Academy of Sciences of the United States of America

2021 Volume 118, Issue 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 ... ...

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 K
MeSH term(s)	Animals ; Autoimmune Diseases/drug therapy ; Autoimmune Diseases/genetics ; Autoimmune Diseases/immunology ; B7-H1 Antigen/chemical synthesis ; B7-H1 Antigen/chemistry ; B7-H1 Antigen/immunology ; B7-H1 Antigen/pharmacology ; Computational Biology ; Drug Design ; Humans ; Lymphocyte Activation ; Mice ; Mice, Inbred C57BL ; Programmed Cell Death 1 Receptor/agonists ; Programmed Cell Death 1 Receptor/chemistry ; Programmed Cell Death 1 Receptor/immunology ; T-Lymphocytes/chemistry ; T-Lymphocytes/drug effects ; T-Lymphocytes/immunology
Chemical Substances	B7-H1 Antigen ; Programmed Cell Death 1 Receptor
Language	English
Publishing date	2021-07-14
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.2102164118
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Article: De novo design of diverse small molecule binders and sensors using Shape Complementary Pseudocycles.

An, Linna / Said, Meerit / Tran, Long / Majumder, Sagardip / Goreshnik, Inna / Lee, Gyu Rie / Juergens, David / Dauparas, Justas / Anishchenko, Ivan / Coventry, Brian / Bera, Asim K / Kang, Alex / Levine, Paul M / Alvarez, Valentina / Pillai, Arvind / Norn, Christoffer / Feldman, David / Zorine, Dmitri / Hicks, Derrick R /

Li, Xinting / Sanchez, Mariana Garcia / Vafeados, Dionne K / Salveson, Patrick J / Vorobieva, Anastassia A / Baker, David

bioRxiv : the preprint server for biology

2023

Abstract: A general method for designing proteins to bind and sense any small molecule of interest would be widely useful. Due to the small number of atoms to interact with, binding to small molecules with high affinity requires highly shape complementary pockets, ...

Abstract	A general method for designing proteins to bind and sense any small molecule of interest would be widely useful. Due to the small number of atoms to interact with, binding to small molecules with high affinity requires highly shape complementary pockets, and transducing binding events into signals is challenging. Here we describe an integrated deep learning and energy based approach for designing high shape complementarity binders to small molecules that are poised for downstream sensing applications. We employ deep learning generated psuedocycles with repeating structural units surrounding central pockets; depending on the geometry of the structural unit and repeat number, these pockets span wide ranges of sizes and shapes. For a small molecule target of interest, we extensively sample high shape complementarity pseudocycles to generate large numbers of customized potential binding pockets; the ligand binding poses and the interacting interfaces are then optimized for high affinity binding. We computationally design binders to four diverse molecules, including for the first time polar flexible molecules such as methotrexate and thyroxine, which are expressed at high levels and have nanomolar affinities straight out of the computer. Co-crystal structures are nearly identical to the design models. Taking advantage of the modular repeating structure of pseudocycles and central location of the binding pockets, we constructed low noise nanopore sensors and chemically induced dimerization systems by splitting the binders into domains which assemble into the original pseudocycle pocket upon target molecule addition.
Language	English
Publishing date	2023-12-21
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.12.20.572602
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Article: Computational design of sequence-specific DNA-binding proteins.

bioRxiv : the preprint server for biology

2023

Abstract: Sequence-specific DNA-binding proteins (DBPs) play critical roles in biology and biotechnology, and there has been considerable interest in the engineering of DBPs with new or altered specificities for genome editing and other applications. While there ... ...

Abstract	Sequence-specific DNA-binding proteins (DBPs) play critical roles in biology and biotechnology, and there has been considerable interest in the engineering of DBPs with new or altered specificities for genome editing and other applications. While there has been some success in reprogramming naturally occurring DBPs using selection methods, the computational design of new DBPs that recognize arbitrary target sites remains an outstanding challenge. We describe a computational method for the design of small DBPs that recognize specific target sequences through interactions with bases in the major groove, and employ this method in conjunction with experimental screening to generate binders for 5 distinct DNA targets. These binders exhibit specificity closely matching the computational models for the target DNA sequences at as many as 6 base positions and affinities as low as 30-100 nM. The crystal structure of a designed DBP-target site complex is in close agreement with the design model, highlighting the accuracy of the design method. The designed DBPs function in both
Language	English
Publishing date	2023-09-21
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.09.20.558720
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Article: Small-molecule binding and sensing with a designed protein family.

Lee, Gyu Rie / Pellock, Samuel J / Norn, Christoffer / Tischer, Doug / Dauparas, Justas / Anischenko, Ivan / Mercer, Jaron A M / Kang, Alex / Bera, Asim / Nguyen, Hannah / Goreshnik, Inna / Vafeados, Dionne / Roullier, Nicole / Han, Hannah L / Coventry, Brian / Haddox, Hugh K / Liu, David R / Yeh, Andy Hsien-Wei / Baker, David

bioRxiv : the preprint server for biology

2023

Abstract: Despite transformative advances in protein design with deep learning, the design of small-molecule-binding proteins and sensors for arbitrary ligands remains a grand challenge. Here we combine deep learning and physics-based methods to generate a family ... ...

Abstract	Despite transformative advances in protein design with deep learning, the design of small-molecule-binding proteins and sensors for arbitrary ligands remains a grand challenge. Here we combine deep learning and physics-based methods to generate a family of proteins with diverse and designable pocket geometries, which we employ to computationally design binders for six chemically and structurally distinct small-molecule targets. Biophysical characterization of the designed binders revealed nanomolar to low micromolar binding affinities and atomic-level design accuracy. The bound ligands are exposed at one edge of the binding pocket, enabling the
Language	English
Publishing date	2023-11-02
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.11.01.565201
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Article ; Online: De novo design of modular peptide-binding proteins by superhelical matching.

Nature

2023 Volume 616, Issue 7957, Page(s) 581–589

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 ... ...

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 backbone
MeSH term(s)	Amino Acid Sequence ; Models, Molecular ; Peptides/chemistry ; Peptides/metabolism ; Proteins/chemistry ; Proteins/metabolism ; Protein Engineering/methods ; Hydrogen Bonding ; Protein Binding ; Protein Folding ; Protein Conformation
Chemical Substances	Peptides ; Proteins
Language	English
Publishing date	2023-04-05
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/s41586-023-05909-9
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