1
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Avizemer Z, Martí-Gómez C, Hoch SY, McCandlish DM, Fleishman SJ. Evolutionary paths that link orthogonal pairs of binding proteins. RESEARCH SQUARE 2023:rs.3.rs-2836905. [PMID: 37131620 PMCID: PMC10153392 DOI: 10.21203/rs.3.rs-2836905/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Some protein binding pairs exhibit extreme specificities that functionally insulate them from homologs. Such pairs evolve mostly by accumulating single-point mutations, and mutants are selected if their affinity exceeds the threshold required for function1-4. Thus, homologous and high-specificity binding pairs bring to light an evolutionary conundrum: how does a new specificity evolve while maintaining the required affinity in each intermediate5,6? Until now, a fully functional single-mutation path that connects two orthogonal pairs has only been described where the pairs were mutationally close thus enabling experimental enumeration of all intermediates2. We present an atomistic and graph-theoretical framework for discovering low molecular strain single-mutation paths that connect two extant pairs, enabling enumeration beyond experimental capability. We apply it to two orthogonal bacterial colicin endonuclease-immunity pairs separated by 17 interface mutations7. We were not able to find a strain-free and functional path in the sequence space defined by the two extant pairs. But including mutations that bridge amino acids that cannot be exchanged through single-nucleotide mutations led us to a strain-free 19-mutation trajectory that is completely viable in vivo. Our experiments show that the specificity switch is remarkably abrupt, resulting from only one radical mutation on each partner. Furthermore, each of the critical specificity-switch mutations increases fitness, demonstrating that functional divergence could be driven by positive Darwinian selection. These results reveal how even radical functional changes in an epistatic fitness landscape may evolve.
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Affiliation(s)
- Ziv Avizemer
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001, Rehovot, Israel
| | - Carlos Martí-Gómez
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | - Shlomo Yakir Hoch
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001, Rehovot, Israel
| | - David M. McCandlish
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | - Sarel J. Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001, Rehovot, Israel
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2
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Praetorius F, Leung PJY, Tessmer MH, Broerman A, Demakis C, Dishman AF, Pillai A, Idris A, Juergens D, Dauparas J, Li X, Levine PM, Lamb M, Ballard RK, Gerben SR, Nguyen H, Kang A, Sankaran B, Bera AK, Volkman BF, Nivala J, Stoll S, Baker D. Design of stimulus-responsive two-state hinge proteins. Science 2023; 381:754-760. [PMID: 37590357 PMCID: PMC10697137 DOI: 10.1126/science.adg7731] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 07/11/2023] [Indexed: 08/19/2023]
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.
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Affiliation(s)
- Florian Praetorius
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Philip J. Y. Leung
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Graduate Program in Molecular Engineering, University of Washington, Seattle, WA, USA
| | - Maxx H. Tessmer
- Department of Chemistry, University of Washington, Seattle, WA, USA
| | - Adam Broerman
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Department of Chemical Engineering, University of Washington, Seattle, WA, USA
| | - Cullen Demakis
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Graduate Program in Biological Physics, Structure, and Design, University of Washington, Seattle, Washington, USA
| | - Acacia F. Dishman
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA
- Medical Scientist Training Program, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Arvind Pillai
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Abbas Idris
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - David Juergens
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Graduate Program in Molecular Engineering, University of Washington, Seattle, WA, USA
| | - Justas Dauparas
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Xinting Li
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Paul M. Levine
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Mila Lamb
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Ryanne K. Ballard
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Stacey R. Gerben
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Hannah Nguyen
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Alex Kang
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Banumathi Sankaran
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Asim K. Bera
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Brian F. Volkman
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Jeff Nivala
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
- Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA
| | - Stefan Stoll
- Department of Chemistry, University of Washington, Seattle, WA, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA,USA
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3
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Yu TC, Thornton ZT, Hannon WW, DeWitt WS, Radford CE, Matsen FA, Bloom JD. A biophysical model of viral escape from polyclonal antibodies. Virus Evol 2022; 8:veac110. [PMID: 36582502 PMCID: PMC9793855 DOI: 10.1093/ve/veac110] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 11/12/2022] [Accepted: 11/29/2022] [Indexed: 12/14/2022] Open
Abstract
A challenge in studying viral immune escape is determining how mutations combine to escape polyclonal antibodies, which can potentially target multiple distinct viral epitopes. Here we introduce a biophysical model of this process that partitions the total polyclonal antibody activity by epitope and then quantifies how each viral mutation affects the antibody activity against each epitope. We develop software that can use deep mutational scanning data to infer these properties for polyclonal antibody mixtures. We validate this software using a computationally simulated deep mutational scanning experiment and demonstrate that it enables the prediction of escape by arbitrary combinations of mutations. The software described in this paper is available at https://jbloomlab.github.io/polyclonal.
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Affiliation(s)
- Timothy C Yu
- Basic Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Computational Biology Program, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Molecular and Cellular Biology Graduate Program, University of Washington, 1959 NE Pacifc Street, Seattle, WA 98195, USA
| | - Zorian T Thornton
- Computational Biology Program, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195, USA
| | - William W Hannon
- Basic Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Computational Biology Program, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Molecular and Cellular Biology Graduate Program, University of Washington, 1959 NE Pacifc Street, Seattle, WA 98195, USA
| | - William S DeWitt
- Computational Biology Program, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195, USA
| | - Caelan E Radford
- Basic Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Computational Biology Program, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Molecular and Cellular Biology Graduate Program, University of Washington, 1959 NE Pacifc Street, Seattle, WA 98195, USA
| | - Frederick A Matsen
- Computational Biology Program, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195, USA
- Howard Hughes Medical Institute, 1100 Fairview Ave N, Seattle, WA 98109, USA
| | - Jesse D Bloom
- Basic Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Computational Biology Program, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195, USA
- Howard Hughes Medical Institute, 1100 Fairview Ave N, Seattle, WA 98109, USA
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4
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Listov D, Lipsh‐Sokolik R, Rosset S, Yang C, Correia BE, Fleishman SJ. Assessing and enhancing foldability in designed proteins. Protein Sci 2022; 31:e4400. [PMID: 36040259 PMCID: PMC9375437 DOI: 10.1002/pro.4400] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 07/09/2022] [Accepted: 07/11/2022] [Indexed: 11/11/2022]
Affiliation(s)
- Dina Listov
- Department of Biomolecular Sciences Weizmann Institute of Science Rehovot Israel
| | | | - Stéphane Rosset
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland
| | - Che Yang
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland
| | - Bruno E. Correia
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland
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5
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Elazar A, Chandler NJ, Davey AS, Weinstein JY, Nguyen JV, Trenker R, Cross RS, Jenkins MR, Call MJ, Call ME, Fleishman SJ. De novo-designed transmembrane domains tune engineered receptor functions. eLife 2022; 11:75660. [PMID: 35506657 PMCID: PMC9068223 DOI: 10.7554/elife.75660] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 04/14/2022] [Indexed: 12/20/2022] Open
Abstract
De novo-designed receptor transmembrane domains (TMDs) present opportunities for precise control of cellular receptor functions. We developed a de novo design strategy for generating programmed membrane proteins (proMPs): single-pass α-helical TMDs that self-assemble through computationally defined and crystallographically validated interfaces. We used these proMPs to program specific oligomeric interactions into a chimeric antigen receptor (CAR) that we expressed in mouse primary T cells and found that both in vitro CAR T cell cytokine release and in vivo antitumor activity scaled linearly with the oligomeric state encoded by the receptor TMD, from monomers up to tetramers. All programmed CARs stimulated substantially lower T cell cytokine release relative to the commonly used CD28 TMD, which we show elevated cytokine release through lateral recruitment of the endogenous T cell costimulatory receptor CD28. Precise design using orthogonal and modular TMDs thus provides a new way to program receptor structure and predictably tune activity for basic or applied synthetic biology.
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Affiliation(s)
- Assaf Elazar
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Nicholas J Chandler
- Structural Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
| | - Ashleigh S Davey
- Structural Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
| | - Jonathan Y Weinstein
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Julie V Nguyen
- Structural Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Raphael Trenker
- Structural Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
| | - Ryan S Cross
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia.,Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Misty R Jenkins
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia.,Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,La Trobe Institute of Molecular Science, La Trobe University, Bundoora, Victoria, Australia
| | - Melissa J Call
- Structural Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
| | - Matthew E Call
- Structural Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
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6
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Affiliation(s)
- Amir Aharoni
- Department of Life Sciences Ben‐Gurion University of the Negev Be’er Sheva Israel
| | - Sarel J. Fleishman
- Department of Biomolecular Sciences Weizmann Institute of Science Rehovot Israel
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7
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Schoeder C, Schmitz S, Adolf-Bryfogle J, Sevy AM, Finn JA, Sauer MF, Bozhanova NG, Mueller BK, Sangha AK, Bonet J, Sheehan JH, Kuenze G, Marlow B, Smith ST, Woods H, Bender BJ, Martina CE, del Alamo D, Kodali P, Gulsevin A, Schief WR, Correia BE, Crowe JE, Meiler J, Moretti R. Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design. Biochemistry 2021; 60:825-846. [PMID: 33705117 PMCID: PMC7992133 DOI: 10.1021/acs.biochem.0c00912] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 03/02/2021] [Indexed: 01/16/2023]
Abstract
Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.
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Affiliation(s)
- Clara
T. Schoeder
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Samuel Schmitz
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Jared Adolf-Bryfogle
- Department
of Immunology and Microbiology, The Scripps
Research Institute, La Jolla, California 92037, United States
- IAVI
Neutralizing Antibody Center, The Scripps
Research Institute, La Jolla, California 92037, United States
| | - Alexander M. Sevy
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Chemical
and Physical Biology Program, Vanderbilt
University, Nashville, Tennessee 37232-0301, United States
- Vanderbilt
Vaccine Center, Vanderbilt University Medical
Center, Nashville, Tennessee 37232-0417, United States
| | - Jessica A. Finn
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Vanderbilt
Vaccine Center, Vanderbilt University Medical
Center, Nashville, Tennessee 37232-0417, United States
- Department
of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States
| | - Marion F. Sauer
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Chemical
and Physical Biology Program, Vanderbilt
University, Nashville, Tennessee 37232-0301, United States
- Vanderbilt
Vaccine Center, Vanderbilt University Medical
Center, Nashville, Tennessee 37232-0417, United States
| | - Nina G. Bozhanova
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Benjamin K. Mueller
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Amandeep K. Sangha
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Jaume Bonet
- Institute
of Bioengineering, École Polytechnique
Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Jonathan H. Sheehan
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Georg Kuenze
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Institute
for Drug Discovery, University Leipzig Medical
School, 04103 Leipzig, Germany
| | - Brennica Marlow
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Chemical
and Physical Biology Program, Vanderbilt
University, Nashville, Tennessee 37232-0301, United States
| | - Shannon T. Smith
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Chemical
and Physical Biology Program, Vanderbilt
University, Nashville, Tennessee 37232-0301, United States
| | - Hope Woods
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Chemical
and Physical Biology Program, Vanderbilt
University, Nashville, Tennessee 37232-0301, United States
| | - Brian J. Bender
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Department
of Pharmacology, Vanderbilt University, Nashville, Tennessee 37212, United States
| | - Cristina E. Martina
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Diego del Alamo
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Chemical
and Physical Biology Program, Vanderbilt
University, Nashville, Tennessee 37232-0301, United States
| | - Pranav Kodali
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - Alican Gulsevin
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
| | - William R. Schief
- Department
of Immunology and Microbiology, The Scripps
Research Institute, La Jolla, California 92037, United States
- IAVI
Neutralizing Antibody Center, The Scripps
Research Institute, La Jolla, California 92037, United States
| | - Bruno E. Correia
- Institute
of Bioengineering, École Polytechnique
Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - James E. Crowe
- Vanderbilt
Vaccine Center, Vanderbilt University Medical
Center, Nashville, Tennessee 37232-0417, United States
- Department
of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States
- Department
of Pediatrics, Vanderbilt University Medical
Center, Nashville, Tennessee 37232, United States
| | - Jens Meiler
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
- Institute
for Drug Discovery, University Leipzig Medical
School, 04103 Leipzig, Germany
| | - Rocco Moretti
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37212, United States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37240-7917, United States
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8
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Lipsh-Sokolik R, Listov D, Fleishman SJ. The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes. Protein Sci 2020; 30:151-159. [PMID: 33040418 PMCID: PMC7737780 DOI: 10.1002/pro.3970] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 10/07/2020] [Accepted: 10/09/2020] [Indexed: 12/12/2022]
Abstract
The functional sites of many protein families are dominated by diverse backbone regions that lack secondary structure (loops) but fold stably into their functionally competent state. Nevertheless, the design of structured loop regions from scratch, especially in functional sites, has met with great difficulty. We therefore developed an approach, called AbDesign, to exploit the natural modularity of many protein families and computationally assemble a large number of new backbones by combining naturally occurring modular fragments. This strategy yielded large, atomically accurate, and highly efficient proteins, including antibodies and enzymes exhibiting dozens of mutations from any natural protein. The combinatorial backbone‐conformation space that can be accessed by AbDesign even for a modestly sized family of homologs may exceed the diversity in the entire PDB, providing the sub‐Ångstrom level of control over the positioning of active‐site groups that is necessary for obtaining highly active proteins. This manuscript describes how to implement the pipeline using code that is freely available at https://github.com/Fleishman‐Lab/AbDesign_for_enzymes.
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Affiliation(s)
| | - Dina Listov
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
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9
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Weinstein J, Khersonsky O, Fleishman SJ. Practically useful protein-design methods combining phylogenetic and atomistic calculations. Curr Opin Struct Biol 2020; 63:58-64. [PMID: 32505941 DOI: 10.1016/j.sbi.2020.04.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Accepted: 04/06/2020] [Indexed: 12/11/2022]
Abstract
Our ability to design new or improved biomolecular activities depends on understanding the sequence-function relationships in proteins. The large size and fold complexity of most proteins, however, obscure these relationships, and protein-optimization methods continue to rely on laborious experimental iterations. Recently, a deeper understanding of the roles of stability-threshold effects and biomolecular epistasis in proteins has led to the development of hybrid methods that combine phylogenetic analysis with atomistic design calculations. These methods enable reliable and even single-step optimization of protein stability, expressibility, and activity in proteins that were considered outside the scope of computational design. Furthermore, ancestral-sequence reconstruction produces insights on missing links in the evolution of enzymes and binders that may be used in protein design. Through the combination of phylogenetic and atomistic calculations, the long-standing goal of general computational methods that can be universally applied to study and optimize proteins finally seems within reach.
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Affiliation(s)
- Jonathan Weinstein
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Olga Khersonsky
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel.
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel.
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10
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Trudeau DL, Tawfik DS. Protein engineers turned evolutionists-the quest for the optimal starting point. Curr Opin Biotechnol 2019; 60:46-52. [PMID: 30611116 DOI: 10.1016/j.copbio.2018.12.002] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 11/22/2018] [Accepted: 12/03/2018] [Indexed: 12/12/2022]
Abstract
The advent of laboratory directed evolution yielded a fruitful crosstalk between the disciplines of molecular evolution and bio-engineering. Here, we outline recent developments in both disciplines with respect to how one can identify the best starting points for directed evolution, such that highly efficient and robust tailor-made enzymes can be obtained with minimal optimization. Directed evolution studies have highlighted essential features of engineer-able enzymes: highly stable, mutationally robust enzymes with the capacity to accept a broad range of substrates. Robust, evolvable enzymes can be inferred from the natural sequence record. Broad substrate spectrum relates to conformational plasticity and can also be predicted by phylogenetic analyses and/or by computational design. Overall, an increasingly powerful toolkit is becoming available for identifying optimal starting points including network analyses of enzyme superfamilies and other bioinformatics methods.
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Affiliation(s)
- Devin L Trudeau
- Department of Biomolecular Sciences, Weizmann Institute of Science, 234 Herzl Street, Rehovot 7610001, Israel
| | - Dan S Tawfik
- Department of Biomolecular Sciences, Weizmann Institute of Science, 234 Herzl Street, Rehovot 7610001, Israel.
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11
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Sormanni P, Aprile FA, Vendruscolo M. Third generation antibody discovery methods: in silico rational design. Chem Soc Rev 2018; 47:9137-9157. [PMID: 30298157 DOI: 10.1039/c8cs00523k] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Owing to their outstanding performances in molecular recognition, antibodies are extensively used in research and applications in molecular biology, biotechnology and medicine. Recent advances in experimental and computational methods are making it possible to complement well-established in vivo (first generation) and in vitro (second generation) methods of antibody discovery with novel in silico (third generation) approaches. Here we describe the principles of computational antibody design and review the state of the art in this field. We then present Modular, a method that implements the rational design of antibodies in a modular manner, and describe the opportunities offered by this approach.
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Affiliation(s)
- Pietro Sormanni
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
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12
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Netzer R, Listov D, Lipsh R, Dym O, Albeck S, Knop O, Kleanthous C, Fleishman SJ. Ultrahigh specificity in a network of computationally designed protein-interaction pairs. Nat Commun 2018; 9:5286. [PMID: 30538236 PMCID: PMC6290019 DOI: 10.1038/s41467-018-07722-9] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 11/21/2018] [Indexed: 01/21/2023] Open
Abstract
Protein networks in all organisms comprise homologous interacting pairs. In these networks, some proteins are specific, interacting with one or a few binding partners, whereas others are multispecific and bind a range of targets. We describe an algorithm that starts from an interacting pair and designs dozens of new pairs with diverse backbone conformations at the binding site as well as new binding orientations and sequences. Applied to a high-affinity bacterial pair, the algorithm results in 18 new ones, with cognate affinities from pico- to micromolar. Three pairs exhibit 3-5 orders of magnitude switch in specificity relative to the wild type, whereas others are multispecific, collectively forming a protein-interaction network. Crystallographic analysis confirms design accuracy, including in new backbones and polar interactions. Preorganized polar interaction networks are responsible for high specificity, thus defining design principles that can be applied to program synthetic cellular interaction networks of desired affinity and specificity. The molecular basis of ultrahigh specificity in protein-protein interactions remains obscure. The authors present a computational method to design atomically accurate new pairs exhibiting >100,000-fold specificity switches, generating a large and complex interaction network.
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Affiliation(s)
- Ravit Netzer
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001, Rehovot, Israel
| | - Dina Listov
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001, Rehovot, Israel
| | - Rosalie Lipsh
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001, Rehovot, Israel
| | - Orly Dym
- Structural Proteomics Unit, Weizmann Institute of Science, 7610001, Rehovot, Israel
| | - Shira Albeck
- Structural Proteomics Unit, Weizmann Institute of Science, 7610001, Rehovot, Israel
| | - Orli Knop
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001, Rehovot, Israel
| | - Colin Kleanthous
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, UK
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001, Rehovot, Israel.
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Goldenzweig A, Fleishman SJ. Principles of Protein Stability and Their Application in Computational Design. Annu Rev Biochem 2018; 87:105-129. [PMID: 29401000 DOI: 10.1146/annurev-biochem-062917-012102] [Citation(s) in RCA: 157] [Impact Index Per Article: 26.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Proteins are increasingly used in basic and applied biomedical research. Many proteins, however, are only marginally stable and can be expressed in limited amounts, thus hampering research and applications. Research has revealed the thermodynamic, cellular, and evolutionary principles and mechanisms that underlie marginal stability. With this growing understanding, computational stability design methods have advanced over the past two decades starting from methods that selectively addressed only some aspects of marginal stability. Current methods are more general and, by combining phylogenetic analysis with atomistic design, have shown drastic improvements in solubility, thermal stability, and aggregation resistance while maintaining the protein's primary molecular activity. Stability design is opening the way to rational engineering of improved enzymes, therapeutics, and vaccines and to the application of protein design methodology to large proteins and molecular activities that have proven challenging in the past.
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Affiliation(s)
- Adi Goldenzweig
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 76100, Israel;
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 76100, Israel;
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14
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Abstract
Natural proteins must both fold into a stable conformation and exert their molecular function. To date, computational design has successfully produced stable and atomically accurate proteins by using so-called "ideal" folds rich in regular secondary structures and almost devoid of loops and destabilizing elements, such as cavities. Molecular function, such as binding and catalysis, however, often demands nonideal features, including large and irregular loops and buried polar interaction networks, which have remained challenging for fold design. Through five design/experiment cycles, we learned principles for designing stable and functional antibody variable fragments (Fvs). Specifically, we (i) used sequence-design constraints derived from antibody multiple-sequence alignments, and (ii) during backbone design, maintained stabilizing interactions observed in natural antibodies between the framework and loops of complementarity-determining regions (CDRs) 1 and 2. Designed Fvs bound their ligands with midnanomolar affinities and were as stable as natural antibodies, despite having >30 mutations from mammalian antibody germlines. Furthermore, crystallographic analysis demonstrated atomic accuracy throughout the framework and in four of six CDRs in one design and atomic accuracy in the entire Fv in another. The principles we learned are general, and can be implemented to design other nonideal folds, generating stable, specific, and precise antibodies and enzymes.
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15
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Nanda V, Belure SV, Shir OM. Searching for the Pareto frontier in multi-objective protein design. Biophys Rev 2017; 9:339-344. [PMID: 28799089 DOI: 10.1007/s12551-017-0288-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Accepted: 07/25/2017] [Indexed: 12/26/2022] Open
Abstract
The goal of protein engineering and design is to identify sequences that adopt three-dimensional structures of desired function. Often, this is treated as a single-objective optimization problem, identifying the sequence-structure solution with the lowest computed free energy of folding. However, many design problems are multi-state, multi-specificity, or otherwise require concurrent optimization of multiple objectives. There may be tradeoffs among objectives, where improving one feature requires compromising another. The challenge lies in determining solutions that are part of the Pareto optimal set-designs where no further improvement can be achieved in any of the objectives without degrading one of the others. Pareto optimality problems are found in all areas of study, from economics to engineering to biology, and computational methods have been developed specifically to identify the Pareto frontier. We review progress in multi-objective protein design, the development of Pareto optimization methods, and present a specific case study using multi-objective optimization methods to model the tradeoff between three parameters, stability, specificity, and complexity, of a set of interacting synthetic collagen peptides.
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Affiliation(s)
- Vikas Nanda
- Center for Advanced Biotechnology and Medicine, Rutgers University, Piscataway, NJ, USA.
- Department of Biochemistry and Molecular Biophysics, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA.
| | - Sandeep V Belure
- Center for Advanced Biotechnology and Medicine, Rutgers University, Piscataway, NJ, USA
- Department of Biochemistry and Molecular Biophysics, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Ofer M Shir
- Department of Computer Science, Tel-Hai College, Kiryat Shmona, Upper Galilee, Israel
- The Galilee Research Institute-Migal, Kiryat Shmona, Upper Galilee, Israel
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Paladino A, Marchetti F, Rinaldi S, Colombo G. Protein design: from computer models to artificial intelligence. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2017. [DOI: 10.1002/wcms.1318] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Antonella Paladino
- Biomolecular Simulations & Computational Chemistry Group; Istituto Istituto di Chimica del Riconoscimento Molecolare, CNR; Milano Italy
| | - Filippo Marchetti
- Biomolecular Simulations & Computational Chemistry Group; Istituto Istituto di Chimica del Riconoscimento Molecolare, CNR; Milano Italy
| | - Silvia Rinaldi
- Biomolecular Simulations & Computational Chemistry Group; Istituto Istituto di Chimica del Riconoscimento Molecolare, CNR; Milano Italy
| | - Giorgio Colombo
- Biomolecular Simulations & Computational Chemistry Group; Istituto Istituto di Chimica del Riconoscimento Molecolare, CNR; Milano Italy
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Khersonsky O, Fleishman SJ. Incorporating an allosteric regulatory site in an antibody through backbone design. Protein Sci 2017; 26:807-813. [PMID: 28142198 DOI: 10.1002/pro.3126] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2016] [Revised: 01/20/2017] [Accepted: 01/24/2017] [Indexed: 12/17/2022]
Abstract
Allosteric regulation underlies living cells' ability to sense changes in nutrient and signaling-molecule concentrations, but the ability to computationally design allosteric regulation into non-allosteric proteins has been elusive. Allosteric-site design is complicated by the requirement to encode the relative stabilities of active and inactive conformations of the same protein in the presence and absence of both ligand and effector. To address this challenge, we used Rosetta to design the backbone of the flexible heavy-chain complementarity-determining region 3 (HCDR3), and used geometric matching and sequence optimization to place a Zn2+ -coordination site in a fluorescein-binding antibody. We predicted that due to HCDR3's flexibility, the fluorescein-binding pocket would configure properly only upon Zn2+ application. We found that regulation by Zn2+ was reversible and sensitive to the divalent ion's identity, and came at the cost of reduced antibody stability and fluorescein-binding affinity. Fluorescein bound at an order of magnitude higher affinity in the presence of Zn2+ than in its absence, and the increase in fluorescein affinity was due almost entirely to faster fluorescein on-rate, suggesting that Zn2+ preorganized the antibody for fluorescein binding. Mutation analysis demonstrated the extreme sensitivity of Zn2+ regulation on the atomic details in and around the metal-coordination site. The designed antibody could serve to study how allosteric regulation evolved from non-allosteric binding proteins, and suggests a way to designing molecular sensors for environmental and biomedical targets.
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Affiliation(s)
- Olga Khersonsky
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
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18
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Affiliation(s)
- Ravit Netzer
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.
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Bar-Even A, Milo R, Noor E, Tawfik DS. The Moderately Efficient Enzyme: Futile Encounters and Enzyme Floppiness. Biochemistry 2015. [DOI: 10.1021/acs.biochem.5b00621] [Citation(s) in RCA: 75] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Arren Bar-Even
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany
| | | | - Elad Noor
- Institute
of Molecular Systems Biology, ETH Zurich, Auguste-Piccard-Hof 1, CH-8093 Zurich, Switzerland
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20
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Lapidoth GD, Baran D, Pszolla GM, Norn C, Alon A, Tyka MD, Fleishman SJ. AbDesign: An algorithm for combinatorial backbone design guided by natural conformations and sequences. Proteins 2015; 83:1385-406. [PMID: 25670500 PMCID: PMC4881815 DOI: 10.1002/prot.24779] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Revised: 01/13/2015] [Accepted: 01/26/2015] [Indexed: 12/20/2022]
Abstract
Computational design of protein function has made substantial progress, generating new enzymes, binders, inhibitors, and nanomaterials not previously seen in nature. However, the ability to design new protein backbones for function--essential to exert control over all polypeptide degrees of freedom--remains a critical challenge. Most previous attempts to design new backbones computed the mainchain from scratch. Here, instead, we describe a combinatorial backbone and sequence optimization algorithm called AbDesign, which leverages the large number of sequences and experimentally determined molecular structures of antibodies to construct new antibody models, dock them against target surfaces and optimize their sequence and backbone conformation for high stability and binding affinity. We used the algorithm to produce antibody designs that target the same molecular surfaces as nine natural, high-affinity antibodies; in five cases interface sequence identity is above 30%, and in four of those the backbone conformation at the core of the antibody binding surface is within 1 Å root-mean square deviation from the natural antibodies. Designs recapitulate polar interaction networks observed in natural complexes, and amino acid sidechain rigidity at the designed binding surface, which is likely important for affinity and specificity, is high compared to previous design studies. In designed anti-lysozyme antibodies, complementarity-determining regions (CDRs) at the periphery of the interface, such as L1 and H2, show greater backbone conformation diversity than the CDRs at the core of the interface, and increase the binding surface area compared to the natural antibody, potentially enhancing affinity and specificity.
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Affiliation(s)
- Gideon D. Lapidoth
- Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Dror Baran
- Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Gabriele M. Pszolla
- Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Christoffer Norn
- Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Assaf Alon
- Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Michael D. Tyka
- Google Inc., 1600 Amphitheatre Pkwy, Mountain View, CA 94043
| | - Sarel J. Fleishman
- Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel
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