1
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Wang D, Huot M, Mohanty V, Shakhnovich EI. Biophysical principles predict fitness of SARS-CoV-2 variants. bioRxiv 2024:2023.07.23.549087. [PMID: 37577536 PMCID: PMC10418099 DOI: 10.1101/2023.07.23.549087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
SARS-CoV-2 employs its spike protein's receptor binding domain (RBD) to enter host cells. The RBD is constantly subjected to immune responses, while requiring efficient binding to host cell receptors for successful infection. However, our understanding of how RBD's biophysical properties contribute to SARS-CoV-2's epidemiological fitness remains largely incomplete. Through a comprehensive approach, comprising large-scale sequence analysis of SARS-CoV-2 variants and the discovery of a fitness function based on binding thermodynamics, we unravel the relationship between the biophysical properties of RBD variants and their contribution to viral fitness. We developed a biophysical model that uses statistical mechanics to map the molecular phenotype space, characterized by binding constants of RBD to ACE2, LY-CoV016, LY-CoV555, REGN10987, and S309, onto a epistatic fitness landscape. We validate our findings through experimentally measured and machine learning (ML) estimated binding affinities, coupled with infectivity data derived from population-level sequencing. Our analysis reveals that this model effectively predicts the fitness of novel RBD variants and can account for the epistatic interactions among mutations, including explaining the later reversal of Q493R. Our study sheds light on the impact of specific mutations on viral fitness and delivers a tool for predicting the future epidemiological trajectory of previously unseen or emerging low frequency variants. These insights offer not only greater understanding of viral evolution but also potentially aid in guiding public health decisions in the battle against COVID-19 and future pandemics.
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Affiliation(s)
- Dianzhuo Wang
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - Marian Huot
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
- Ecole Polytechnique, Institut Polytechnique de Paris
| | - Vaibhav Mohanty
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
- Harvard-MIT MD-PhD Program and Program in Health Sciences and Technology, Harvard Medical School, Boston, MA and Massachusetts Institute of Technology, Cambridge, MA
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2
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Chattaraj A, Shakhnovich EI. Separation of sticker-spacer energetics governs the coalescence of metastable biomolecular condensates. bioRxiv 2023:2023.10.03.560747. [PMID: 37873097 PMCID: PMC10592914 DOI: 10.1101/2023.10.03.560747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Biopolymer condensates often emerge as a multi-droplet state and never coalesce into one large droplet within the experimental timespan. This contradicts the prediction of classical polymer physics which suggests the existence of one large droplet beyond the phase transition. Previous work revealed that the sticker-spacer architecture of biopolymers may dynamically stabilize the multi-droplet state. Here, we simulate the condensate coalescence using metadynamics approach and reveal two distinct physical mechanisms underlying the fusion of droplets. Condensates made of sticker-spacer polymers readily undergo a kinetic arrest when stickers exhibit slow exchange while fast exchanging stickers at similar levels of saturation allow merger to equilibrium states. On the other hand, condensates composed of homopolymers fuse readily until they reach a threshold density. We also show that the inter-condensate exchange of chains offers a general mechanism that drives the fusion. We map the range of mechanisms of kinetic arrest from slow sticker exchange dynamics to density mediated in terms of energetic separation of stickers and spacers. Our predictions appear to be in excellent agreement with recent experiments probing dynamic nature of protein-RNA condensates.
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Affiliation(s)
- Aniruddha Chattaraj
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge 02138, MA, USA
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge 02138, MA, USA
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3
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Ogbunugafor CB, Guerrero RF, Miller-Dickson MD, Shakhnovich EI, Shoulders MD. Epistasis and pleiotropy shape biophysical protein subspaces associated with drug resistance. Phys Rev E 2023; 108:054408. [PMID: 38115433 PMCID: PMC10935598 DOI: 10.1103/physreve.108.054408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 09/19/2023] [Indexed: 12/21/2023]
Abstract
Protein space is a rich analogy for genotype-phenotype maps, where amino acid sequence is organized into a high-dimensional space that highlights the connectivity between protein variants. It is a useful abstraction for understanding the process of evolution, and for efforts to engineer proteins towards desirable phenotypes. Few mentions of protein space consider how protein phenotypes can be described in terms of their biophysical components, nor do they rigorously interrogate how forces like epistasis-describing the nonlinear interaction between mutations and their phenotypic consequences-manifest across these components. In this study, we deconstruct a low-dimensional protein space of a bacterial enzyme (dihydrofolate reductase; DHFR) into "subspaces" corresponding to a set of kinetic and thermodynamic traits [k_{cat}, K_{M}, K_{i}, and T_{m} (melting temperature)]. We then examine how combinations of three mutations (eight alleles in total) display pleiotropy, or unique effects on individual subspace traits. We examine protein spaces across three orthologous DHFR enzymes (Escherichia coli, Listeria grayi, and Chlamydia muridarum), adding a genotypic context dimension through which epistasis occurs across subspaces. In doing so, we reveal that protein space is a deceptively complex notion, and that future applications to bioengineering should consider how interactions between amino acid substitutions manifest across different phenotypic subspaces.
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Affiliation(s)
- C. Brandon Ogbunugafor
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Santa Fe Institute, Santa Fe, New Mexico, USA
| | - Rafael F. Guerrero
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, USA
| | | | - Eugene I. Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Matthew D. Shoulders
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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4
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Bitran A, Park K, Serebryany E, Shakhnovich EI. Co-translational formation of disulfides guides folding of the SARS-CoV-2 receptor binding domain. Biophys J 2023; 122:3238-3253. [PMID: 37422697 PMCID: PMC10465708 DOI: 10.1016/j.bpj.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 05/27/2023] [Accepted: 07/03/2023] [Indexed: 07/10/2023] Open
Abstract
Many secreted proteins, including viral proteins, contain multiple disulfide bonds. How disulfide formation is coupled to protein folding in the cell remains poorly understood at the molecular level. Here, we combine experiment and simulation to address this question as it pertains to the SARS-CoV-2 receptor binding domain (RBD). We show that the RBD can only refold reversibly if its native disulfides are present before folding. But in their absence, the RBD spontaneously misfolds into a nonnative, molten-globule-like state that is structurally incompatible with complete disulfide formation and that is highly prone to aggregation. Thus, the RBD native structure represents a metastable state on the protein's energy landscape with reduced disulfides, indicating that nonequilibrium mechanisms are needed to ensure native disulfides form before folding. Our atomistic simulations suggest that this may be achieved via co-translational folding during RBD secretion into the endoplasmic reticulum. Namely, at intermediate translation lengths, native disulfide pairs are predicted to come together with high probability, and thus, under suitable kinetic conditions, this process may lock the protein into its native state and circumvent highly aggregation-prone nonnative intermediates. This detailed molecular picture of the RBD folding landscape may shed light on SARS-CoV-2 pathology and molecular constraints governing SARS-CoV-2 evolution.
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Affiliation(s)
- Amir Bitran
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts; PhD Program in Biophysics, Harvard University, Cambridge, Massachusetts.
| | - Kibum Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Eugene Serebryany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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5
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Chowdhury S, Zielinski DC, Dalldorf C, Rodrigues JV, Palsson BO, Shakhnovich EI. Empowering drug off-target discovery with metabolic and structural analysis. Nat Commun 2023; 14:3390. [PMID: 37296102 PMCID: PMC10256842 DOI: 10.1038/s41467-023-38859-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 05/15/2023] [Indexed: 06/12/2023] Open
Abstract
Elucidating intracellular drug targets is a difficult problem. While machine learning analysis of omics data has been a promising approach, going from large-scale trends to specific targets remains a challenge. Here, we develop a hierarchic workflow to focus on specific targets based on analysis of metabolomics data and growth rescue experiments. We deploy this framework to understand the intracellular molecular interactions of the multi-valent dihydrofolate reductase-targeting antibiotic compound CD15-3. We analyse global metabolomics data utilizing machine learning, metabolic modelling, and protein structural similarity to prioritize candidate drug targets. Overexpression and in vitro activity assays confirm one of the predicted candidates, HPPK (folK), as a CD15-3 off-target. This study demonstrates how established machine learning methods can be combined with mechanistic analyses to improve the resolution of drug target finding workflows for discovering off-targets of a metabolic inhibitor.
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Affiliation(s)
- Sourav Chowdhury
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Daniel C Zielinski
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Christopher Dalldorf
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Joao V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Bernhard O Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800, Kongens Lyngby, Denmark
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
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6
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Serebryany E, Zhao VY, Park K, Bitran A, Trauger SA, Budnik B, Shakhnovich EI. Systematic conformation-to-phenotype mapping via limited deep sequencing of proteins. Mol Cell 2023; 83:1936-1952.e7. [PMID: 37267908 DOI: 10.1016/j.molcel.2023.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 01/29/2023] [Accepted: 05/03/2023] [Indexed: 06/04/2023]
Abstract
Non-native conformations drive protein-misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.
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Affiliation(s)
- Eugene Serebryany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA.
| | - Victor Y Zhao
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Kibum Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Amir Bitran
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Sunia A Trauger
- Center for Mass Spectrometry, Harvard University, Cambridge, MA 02138, USA
| | - Bogdan Budnik
- Center for Mass Spectrometry, Harvard University, Cambridge, MA 02138, USA
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA.
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7
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Scheerer D, Adkar BV, Bhattacharyya S, Levy D, Iljina M, Riven I, Dym O, Haran G, Shakhnovich EI. Allosteric communication between ligand binding domains modulates substrate inhibition in adenylate kinase. Proc Natl Acad Sci U S A 2023; 120:e2219855120. [PMID: 37094144 PMCID: PMC10160949 DOI: 10.1073/pnas.2219855120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 03/22/2023] [Indexed: 04/26/2023] Open
Abstract
Enzymes play a vital role in life processes; they control chemical reactions and allow functional cycles to be synchronized. Many enzymes harness large-scale motions of their domains to achieve tremendous catalytic prowess and high selectivity for specific substrates. One outstanding example is provided by the three-domain enzyme adenylate kinase (AK), which catalyzes phosphotransfer between ATP to AMP. Here we study the phenomenon of substrate inhibition by AMP and its correlation with domain motions. Using single-molecule FRET spectroscopy, we show that AMP does not block access to the ATP binding site, neither by competitive binding to the ATP cognate site nor by directly closing the LID domain. Instead, inhibitory concentrations of AMP lead to a faster and more cooperative domain closure by ATP, leading in turn to an increased population of the closed state. The effect of AMP binding can be modulated through mutations throughout the structure of the enzyme, as shown by the screening of an extensive AK mutant library. The mutation of multiple conserved residues reduces substrate inhibition, suggesting that substrate inhibition is an evolutionary well conserved feature in AK. Combining these insights, we developed a model that explains the complex activity of AK, particularly substrate inhibition, based on the experimentally observed opening and closing rates. Notably, the model indicates that the catalytic power is affected by the microsecond balance between the open and closed states of the enzyme. Our findings highlight the crucial role of protein motions in enzymatic activity.
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Affiliation(s)
- David Scheerer
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Bharat V Adkar
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138
| | | | - Dorit Levy
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Marija Iljina
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Inbal Riven
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Orly Dym
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Gilad Haran
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138
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8
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Ogbunugafor CB, Guerrero RF, Shakhnovich EI, Shoulders MD. Epistasis meets pleiotropy in shaping biophysical protein subspaces associated with antimicrobial resistance. bioRxiv 2023:2023.04.09.535490. [PMID: 37066177 PMCID: PMC10104174 DOI: 10.1101/2023.04.09.535490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Protein space is a rich analogy for genotype-phenotype maps, where amino acid sequence is organized into a high-dimensional space that highlights the connectivity between protein variants. It is a useful abstraction for understanding the process of evolution, and for efforts to engineer proteins towards desirable phenotypes. Few framings of protein space consider how higher-level protein phenotypes can be described in terms of their biophysical dimensions, nor do they rigorously interrogate how forces like epistasis-describing the nonlinear interaction between mutations and their phenotypic consequences-manifest across these dimensions. In this study, we deconstruct a low-dimensional protein space of a bacterial enzyme (dihydrofolate reductase; DHFR) into "subspaces" corresponding to a set of kinetic and thermodynamic traits [(kcat, KM, Ki, and Tm (melting temperature)]. We then examine how three mutations (eight alleles in total) display pleiotropy in their interactions across these subspaces. We extend this approach to examine protein spaces across three orthologous DHFR enzymes (Escherichia coli, Listeria grayi, and Chlamydia muridarum), adding a genotypic context dimension through which epistasis occurs across subspaces. In doing so, we reveal that protein space is a deceptively complex notion, and that the process of protein evolution and engineering should consider how interactions between amino acid substitutions manifest across different phenotypic subspaces.
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Affiliation(s)
- C. Brandon Ogbunugafor
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA
- Santa Fe Institute, Santa Fe, NM
| | - Rafael F. Guerrero
- Department of Biological Sciences, North Carolina State University, Raleigh, NC
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9
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Serebryany E, Zhao VY, Park K, Bitran A, Trauger SA, Budnik B, Shakhnovich EI. Systematic conformation-to-phenotype mapping via limited deep-sequencing of proteins. ArXiv 2023:2204.06159. [PMID: 36776823 PMCID: PMC9915745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/14/2023]
Abstract
Non-native conformations drive protein misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well-suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.
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Affiliation(s)
- Eugene Serebryany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | - Victor Y. Zhao
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | - Kibum Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | - Amir Bitran
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | | | - Bogdan Budnik
- Center for Mass Spectrometry, Harvard University, Cambridge, MA
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10
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Bitran A, Park K, Serebryany E, Shakhnovich EI. Cotranslational formation of disulfides guides folding of the SARS COV-2 receptor binding domain. bioRxiv 2022:2022.11.10.516025. [PMID: 36380756 PMCID: PMC9665344 DOI: 10.1101/2022.11.10.516025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Many secreted proteins contain multiple disulfide bonds. How disulfide formation is coupled to protein folding in the cell remains poorly understood at the molecular level. Here, we combine experiment and simulation to address this question as it pertains to the SARS-CoV-2 receptor binding domain (RBD). We show that, whereas RBD can refold reversibly when its disulfides are intact, their disruption causes misfolding into a nonnative molten-globule state that is highly prone to aggregation and disulfide scrambling. Thus, non-equilibrium mechanisms are needed to ensure disulfides form prior to folding in vivo. Our simulations suggest that co-translational folding may accomplish this, as native disulfide pairs are predicted to form with high probability at intermediate lengths, ultimately committing the RBD to its metastable native state and circumventing nonnative intermediates. This detailed molecular picture of the RBD folding landscape may shed light on SARS-CoV-2 pathology and molecular constraints governing SARS-CoV-2 evolution.
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11
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Serebryany E, Chowdhury S, Woods CN, Thorn DC, Watson NE, McClelland AA, Klevit RE, Shakhnovich EI. A native chemical chaperone in the human eye lens. eLife 2022; 11:76923. [PMID: 35723573 PMCID: PMC9246369 DOI: 10.7554/elife.76923] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 06/13/2022] [Indexed: 12/02/2022] Open
Abstract
Cataract is one of the most prevalent protein aggregation disorders and still the most common cause of vision loss worldwide. The metabolically quiescent core region of the human lens lacks cellular or protein turnover; it has therefore evolved remarkable mechanisms to resist light-scattering protein aggregation for a lifetime. We now report that one such mechanism involves an unusually abundant lens metabolite, myo-inositol, suppressing aggregation of lens crystallins. We quantified aggregation suppression using our previously well-characterized in vitro aggregation assays of oxidation-mimicking human γD-crystallin variants and investigated myo-inositol’s molecular mechanism of action using solution NMR, negative-stain TEM, differential scanning fluorometry, thermal scanning Raman spectroscopy, turbidimetry in redox buffers, and free thiol quantitation. Unlike many known chemical chaperones, myo-inositol’s primary target was not the native, unfolded, or final aggregated states of the protein; rather, we propose that it was the rate-limiting bimolecular step on the aggregation pathway. Given recent metabolomic evidence that it is severely depleted in human cataractous lenses compared to age-matched controls, we suggest that maintaining or restoring healthy levels of myo-inositol in the lens may be a simple, safe, and globally accessible strategy to prevent or delay lens opacification due to age-onset cataract.
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Affiliation(s)
- Eugene Serebryany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Sourav Chowdhury
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Christopher N Woods
- Department of Biochemistry, University of Washington, Seattle, United States
| | - David C Thorn
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Nicki E Watson
- Center for Nanoscale Systems, Harvard University, Cambridge, United States
| | | | - Rachel E Klevit
- Department of Biochemistry, University of Washington, Seattle, United States
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
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12
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Serebryany E, Trauger SA, Budnik B, Shakhnovich EI. Systematic Conformation‐to‐Phenotype Mapping via Limited Protein Sequencing. FASEB J 2022. [DOI: 10.1096/fasebj.2022.36.s1.l7930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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13
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Thorn DC, Serebryany E, Birrane G, Kaya AI, Shakhnovich EI. Domain‐swapped dimeric γ‐crystallin: the missing link in the evolution of oligomeric β‐crystallins. FASEB J 2022. [DOI: 10.1096/fasebj.2022.36.s1.r3926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- David C. Thorn
- Department of Chemistry and Chemical BiologyHarvard UniversityCambridgeMA
| | - Eugene Serebryany
- Department of Chemistry and Chemical BiologyHarvard UniversityCambridgeMA
| | - Gabriel Birrane
- Department of MedicineBeth Israel Deaconess Medical Center and Harvard Medical SchoolBostonMA
| | - Ali I. Kaya
- Northeastern Collaborative Acces Team and Cornell UniversityAdvanced Photon SourceLamontIL
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14
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Serebryany E, Zhao VY, Trauger SA, Budnik B, Shakhnovich EI. Systematic discovery of non-native protein conformations and their molecular and cellular phenotypes. Biophys J 2022. [DOI: 10.1016/j.bpj.2021.11.1128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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15
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Zhao VY, Rodrigues JV, Lozovsky ER, Hartl DL, Shakhnovich EI. Switching an active site helix in dihydrofolate reductase reveals limits to subdomain modularity. Biophys J 2021; 120:4738-4750. [PMID: 34571014 PMCID: PMC8595743 DOI: 10.1016/j.bpj.2021.09.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/14/2021] [Accepted: 09/22/2021] [Indexed: 11/23/2022] Open
Abstract
To what degree are individual structural elements within proteins modular such that similar structures from unrelated proteins can be interchanged? We study subdomain modularity by creating 20 chimeras of an enzyme, Escherichia coli dihydrofolate reductase (DHFR), in which a catalytically important, 10-residue α-helical sequence is replaced by α-helical sequences from a diverse set of proteins. The chimeras stably fold but have a range of diminished thermal stabilities and catalytic activities. Evolutionary coupling analysis indicates that the residues of this α-helix are under selection pressure to maintain catalytic activity in DHFR. Reversion to phenylalanine at key position 31 was found to partially restore catalytic activity, which could be explained by evolutionary coupling values. We performed molecular dynamics simulations using replica exchange with solute tempering. Chimeras with low catalytic activity exhibit nonhelical conformations that block the binding site and disrupt the positioning of the catalytically essential residue D27. Simulation observables and in vitro measurements of thermal stability and substrate-binding affinity are strongly correlated. Several E. coli strains with chromosomally integrated chimeric DHFRs can grow, with growth rates that follow predictions from a kinetic flux model that depends on the intracellular abundance and catalytic activity of DHFR. Our findings show that although α-helices are not universally substitutable, the molecular and fitness effects of modular segments can be predicted by the biophysical compatibility of the replacement segment.
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Affiliation(s)
- Victor Y Zhao
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - João V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Elena R Lozovsky
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts
| | - Daniel L Hartl
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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16
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Bhattacharyya S, Bershtein S, Adkar BV, Woodard J, Shakhnovich EI. Metabolic response to point mutations reveals principles of modulation of in vivo enzyme activity and phenotype. Mol Syst Biol 2021; 17:e10200. [PMID: 34180142 PMCID: PMC8236904 DOI: 10.15252/msb.202110200] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Revised: 05/08/2021] [Accepted: 05/11/2021] [Indexed: 12/14/2022] Open
Abstract
The relationship between sequence variation and phenotype is poorly understood. Here, we use metabolomic analysis to elucidate the molecular mechanism underlying the filamentous phenotype of E. coli strains that carry destabilizing mutations in dihydrofolate reductase (DHFR). We find that partial loss of DHFR activity causes reversible filamentation despite SOS response indicative of DNA damage, in contrast to thymineless death (TLD) achieved by complete inhibition of DHFR activity by high concentrations of antibiotic trimethoprim. This phenotype is triggered by a disproportionate drop in intracellular dTTP, which could not be explained by drop in dTMP based on the Michaelis-Menten-like in vitro activity curve of thymidylate kinase (Tmk), a downstream enzyme that phosphorylates dTMP to dTDP. Instead, we show that a highly cooperative (Hill coefficient 2.5) in vivo activity of Tmk is the cause of suboptimal dTTP levels. dTMP supplementation rescues filamentation and restores in vivo Tmk kinetics to Michaelis-Menten. Overall, this study highlights the important role of cellular environment in sculpting enzymatic kinetics with system-level implications for bacterial phenotype.
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Affiliation(s)
| | - Shimon Bershtein
- Department of Life SciencesBen‐Gurion University of the NegevBeer‐ShevaIsrael
| | - Bharat V Adkar
- Department of Chemistry and Chemical BiologyHarvard UniversityCambridgeMAUSA
| | - Jaie Woodard
- Department of Chemistry and Chemical BiologyHarvard UniversityCambridgeMAUSA
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17
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Graff DE, Shakhnovich EI, Coley CW. Accelerating high-throughput virtual screening through molecular pool-based active learning. Chem Sci 2021; 12:7866-7881. [PMID: 34168840 PMCID: PMC8188596 DOI: 10.1039/d0sc06805e] [Citation(s) in RCA: 80] [Impact Index Per Article: 26.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Accepted: 04/26/2021] [Indexed: 12/13/2022] Open
Abstract
Structure-based virtual screening is an important tool in early stage drug discovery that scores the interactions between a target protein and candidate ligands. As virtual libraries continue to grow (in excess of 108 molecules), so too do the resources necessary to conduct exhaustive virtual screening campaigns on these libraries. However, Bayesian optimization techniques, previously employed in other scientific discovery problems, can aid in their exploration: a surrogate structure-property relationship model trained on the predicted affinities of a subset of the library can be applied to the remaining library members, allowing the least promising compounds to be excluded from evaluation. In this study, we explore the application of these techniques to computational docking datasets and assess the impact of surrogate model architecture, acquisition function, and acquisition batch size on optimization performance. We observe significant reductions in computational costs; for example, using a directed-message passing neural network we can identify 94.8% or 89.3% of the top-50 000 ligands in a 100M member library after testing only 2.4% of candidate ligands using an upper confidence bound or greedy acquisition strategy, respectively. Such model-guided searches mitigate the increasing computational costs of screening increasingly large virtual libraries and can accelerate high-throughput virtual screening campaigns with applications beyond docking.
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Affiliation(s)
- David E Graff
- Department of Chemistry and Chemical Biology, Harvard University Cambridge MA USA
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University Cambridge MA USA
| | - Connor W Coley
- Department of Chemical Engineering, MIT Cambridge MA USA
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18
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Razban RM, Dasmeh P, Serohijos AWR, Shakhnovich EI. Avoidance of protein unfolding constrains protein stability in long-term evolution. Biophys J 2021; 120:2413-2424. [PMID: 33932438 PMCID: PMC8390877 DOI: 10.1016/j.bpj.2021.03.042] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 02/24/2021] [Accepted: 03/17/2021] [Indexed: 11/28/2022] Open
Abstract
Every amino acid residue can influence a protein's overall stability, making stability highly susceptible to change throughout evolution. We consider the distribution of protein stabilities evolutionarily permittable under two previously reported protein fitness functions: flux dynamics and misfolding avoidance. We develop an evolutionary dynamics theory and find that it agrees better with an extensive protein stability data set for dihydrofolate reductase orthologs under the misfolding avoidance fitness function rather than the flux dynamics fitness function. Further investigation with ribonuclease H data demonstrates that not any misfolded state is avoided; rather, it is only the unfolded state. At the end, we discuss how our work pertains to the universal protein abundance-evolutionary rate correlation seen across organisms' proteomes. We derive a closed-form expression relating protein abundance to evolutionary rate that captures Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens experimental trends without fitted parameters.
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Affiliation(s)
- Rostam M Razban
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Pouria Dasmeh
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts; Departement de Biochimie, Université de Montréal, Montreal, Quebec, Canada
| | | | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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19
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Chen Q, Xiao Y, Shakhnovich EI, Zhang W, Mu W. Semi-rational design and molecular dynamics simulations study of the thermostability enhancement of cellobiose 2-epimerases. Int J Biol Macromol 2020; 154:1356-1365. [DOI: 10.1016/j.ijbiomac.2019.11.015] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 10/29/2019] [Accepted: 11/04/2019] [Indexed: 01/19/2023]
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20
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Abstract
Multivalent biopolymers phase separate into membrane-less organelles (MLOs) which exhibit liquid-like behavior. Here, we explore formation of prototypical MOs from multivalent proteins on various time and length scales and show that the kinetically arrested metastable multi-droplet state is a dynamic outcome of the interplay between two competing processes: a diffusion-limited encounter between proteins, and the exhaustion of available valencies within smaller clusters. Clusters with satisfied valencies cannot coalesce readily, resulting in metastable, long-living droplets. In the regime of dense clusters akin to phase-separation, we observe co-existing assemblies, in contrast to the single, large equilibrium-like cluster. A system-spanning network encompassing all multivalent proteins was only observed at high concentrations and large interaction valencies. In the regime favoring large clusters, we observe a slow-down in the dynamics of the condensed phase, potentially resulting in loss of function. Therefore, metastability could be a hallmark of dynamic functional droplets formed by sticker-spacer proteins.
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Affiliation(s)
- Srivastav Ranganathan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
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21
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Zhou Q, Yang D, Wu M, Guo Y, Guo W, Zhong L, Cai X, Dai A, Jang W, Shakhnovich EI, Liu ZJ, Stevens RC, Lambert NA, Babu MM, Wang MW, Zhao S. Common activation mechanism of class A GPCRs. eLife 2019; 8:e50279. [PMID: 31855179 PMCID: PMC6954041 DOI: 10.7554/elife.50279] [Citation(s) in RCA: 264] [Impact Index Per Article: 52.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 12/19/2019] [Indexed: 12/26/2022] Open
Abstract
Class A G-protein-coupled receptors (GPCRs) influence virtually every aspect of human physiology. Understanding receptor activation mechanism is critical for discovering novel therapeutics since about one-third of all marketed drugs target members of this family. GPCR activation is an allosteric process that couples agonist binding to G-protein recruitment, with the hallmark outward movement of transmembrane helix 6 (TM6). However, what leads to TM6 movement and the key residue level changes of this movement remain less well understood. Here, we report a framework to quantify conformational changes. By analyzing the conformational changes in 234 structures from 45 class A GPCRs, we discovered a common GPCR activation pathway comprising of 34 residue pairs and 35 residues. The pathway unifies previous findings into a common activation mechanism and strings together the scattered key motifs such as CWxP, DRY, Na+ pocket, NPxxY and PIF, thereby directly linking the bottom of ligand-binding pocket with G-protein coupling region. Site-directed mutagenesis experiments support this proposition and reveal that rational mutations of residues in this pathway can be used to obtain receptors that are constitutively active or inactive. The common activation pathway provides the mechanistic interpretation of constitutively activating, inactivating and disease mutations. As a module responsible for activation, the common pathway allows for decoupling of the evolution of the ligand binding site and G-protein-binding region. Such an architecture might have facilitated GPCRs to emerge as a highly successful family of proteins for signal transduction in nature.
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Affiliation(s)
- Qingtong Zhou
- iHuman InstituteShanghaiTech UniversityShanghaiChina
| | - Dehua Yang
- The CAS Key Laboratory of Receptor ResearchShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
- The National Center for Drug ScreeningShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
| | - Meng Wu
- iHuman InstituteShanghaiTech UniversityShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
- School of Life Science and TechnologyShanghaiTech UniversityShanghaiChina
| | - Yu Guo
- iHuman InstituteShanghaiTech UniversityShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
- School of Life Science and TechnologyShanghaiTech UniversityShanghaiChina
| | - Wanjing Guo
- The CAS Key Laboratory of Receptor ResearchShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
- The National Center for Drug ScreeningShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
| | - Li Zhong
- The CAS Key Laboratory of Receptor ResearchShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
- The National Center for Drug ScreeningShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
| | - Xiaoqing Cai
- The CAS Key Laboratory of Receptor ResearchShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
- The National Center for Drug ScreeningShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
| | - Antao Dai
- The CAS Key Laboratory of Receptor ResearchShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
- The National Center for Drug ScreeningShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
| | - Wonjo Jang
- Department of Pharmacology and Toxicology, Medical College of GeorgiaAugusta UniversityAugustaUnited States
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical BiologyHarvard UniversityCambridgeUnited States
| | - Zhi-Jie Liu
- iHuman InstituteShanghaiTech UniversityShanghaiChina
- School of Life Science and TechnologyShanghaiTech UniversityShanghaiChina
| | - Raymond C Stevens
- iHuman InstituteShanghaiTech UniversityShanghaiChina
- School of Life Science and TechnologyShanghaiTech UniversityShanghaiChina
| | - Nevin A Lambert
- Department of Pharmacology and Toxicology, Medical College of GeorgiaAugusta UniversityAugustaUnited States
| | - M Madan Babu
- MRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
| | - Ming-Wei Wang
- The CAS Key Laboratory of Receptor ResearchShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
- The National Center for Drug ScreeningShanghai Institute of Materia Medica, Chinese Academy of SciencesShanghaiChina
- School of Life Science and TechnologyShanghaiTech UniversityShanghaiChina
- School of PharmacyFudan UniversityShanghaiChina
| | - Suwen Zhao
- iHuman InstituteShanghaiTech UniversityShanghaiChina
- School of Life Science and TechnologyShanghaiTech UniversityShanghaiChina
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22
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Rodrigues JV, Shakhnovich EI. Adaptation to mutational inactivation of an essential gene converges to an accessible suboptimal fitness peak. eLife 2019; 8:50509. [PMID: 31573512 PMCID: PMC6828540 DOI: 10.7554/elife.50509] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 09/30/2019] [Indexed: 12/14/2022] Open
Abstract
The mechanisms of adaptation to inactivation of essential genes remain unknown. Here we inactivate E. coli dihydrofolate reductase (DHFR) by introducing D27G,N,F chromosomal mutations in a key catalytic residue with subsequent adaptation by an automated serial transfer protocol. The partial reversal G27- > C occurred in three evolutionary trajectories. Conversely, in one trajectory for D27G and in all trajectories for D27F,N strains adapted to grow at very low metabolic supplement (folAmix) concentrations but did not escape entirely from supplement auxotrophy. Major global shifts in metabolome and proteome occurred upon DHFR inactivation, which were partially reversed in adapted strains. Loss-of-function mutations in two genes, thyA and deoB, ensured adaptation to low folAmix by rerouting the 2-Deoxy-D-ribose-phosphate metabolism from glycolysis towards synthesis of dTMP. Multiple evolutionary pathways of adaptation converged to a suboptimal solution due to the high accessibility to loss-of-function mutations that block the path to the highest, yet least accessible, fitness peak. Predicting how viruses and bacteria evolve remains a challenge. The ability to anticipate when and how bacteria might develop drug resistance would make treating life-threatening diseases easier and could potentially help prevent drug resistance altogether. Studying bacterial evolution under different conditions and cataloguing all possible DNA mutations that allow these bacteria to survive are crucial steps in predicting the appearance of drug resistance. Studies have revealed that bacteria can adapt to sources of stress, such as antibiotics, in different ways – each involving mutations in distinct genes. However, not all the mutations provide the same benefits to the organism, and the factors that influence how bacteria will adapt are unclear. Now, Rodrigues and Shakhnovich have used a new approach to push the adaptation ability of the bacterium Escherichia coli to the limit. First, they genetically engineered different E. coli strains by introducing distinct mutations to an enzyme the bacterium needs to make DNA. These mutations make the resulting strains dependent on external molecules to synthesize new DNA. Next, the cells were grown in conditions where the supply of these DNA precursors was progressively decreased, forcing them to adapt. The obvious way for bacteria to adapt to these conditions would be to ‘revert’ the mutations that Rodrigues and Shakhnovich introduced in the first place. By using this approach, Rodrigues and Shakhnovich were able to test how often the obvious evolutionary solution happens compared with presumably less-preferred alternative routes. In rare cases, a specific mutation did restore the activity of the enzyme that enabled DNA synthesis. However, in most cases the bacteria found a different evolutionary solution whereby they all adapt to the decrease in external DNA precursors in the same way, but not by reverting the original mutation. Instead, further mutations disrupt the activity of two metabolic genes, allowing the cells to use the external DNA precursors more efficiently, and keep building DNA. These cells are therefore able to survive even when the levels of the external DNA components are very low, but they will die in the complete absence of these precursor molecules. This evolutionary solution leads to a non-optimal effect: mutations that restore the activity of the original enzyme, which are the best solution when the two metabolic genes are intact, are no longer as effective. This finding represents a clear example of interactions between genes determining evolutionary outcomes. Rodrigues and Shakhnovich showed that, since it is more likely for a random mutation to disrupt a gene than to revert a previous mutation, adaptations that are less-than-optimal but still work might predominate simply because they happen faster. Understanding why certain evolutionary adaptations prevail is an important step in predicting evolution and may lead to breakthroughs in many areas. For example, if scientists can identify mutations likely to make bacteria resistant to drugs, it may be possible to act proactively against the bacterial strains that carry those mutations. Eventually, if the factors that lead to specific adaptations are known, it may be possible to exploit this knowledge to create weaknesses in the bacteria’s own defences.
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Affiliation(s)
- João V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
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23
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J S Loureiro R, Vila-Viçosa D, Machuqueiro M, Shakhnovich EI, F N Faísca P. The Early Phase of β2m Aggregation: An Integrative Computational Study Framed on the D76N Mutant and the ΔN6 Variant. Biomolecules 2019; 9:biom9080366. [PMID: 31416179 PMCID: PMC6722664 DOI: 10.3390/biom9080366] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Revised: 08/08/2019] [Accepted: 08/13/2019] [Indexed: 12/12/2022] Open
Abstract
Human β2-microglobulin (b2m) protein is classically associated with dialysis-related amyloidosis (DRA). Recently, the single point mutant D76N was identified as the causative agent of a hereditary systemic amyloidosis affecting visceral organs. To get insight into the early stage of the β2m aggregation mechanism, we used molecular simulations to perform an in depth comparative analysis of the dimerization phase of the D76N mutant and the ΔN6 variant, a cleaved form lacking the first six N-terminal residues, which is a major component of ex vivo amyloid plaques from DRA patients. We also provide first glimpses into the tetramerization phase of D76N at physiological pH. Results from extensive protein–protein docking simulations predict an essential role of the C- and N-terminal regions (both variants), as well as of the BC-loop (ΔN6 variant), DE-loop (both variants) and EF-loop (D76N mutant) in dimerization. The terminal regions are more relevant under acidic conditions while the BC-, DE- and EF-loops gain importance at physiological pH. Our results recapitulate experimental evidence according to which Tyr10 (A-strand), Phe30 and His31 (BC-loop), Trp60 and Phe62 (DE-loop) and Arg97 (C-terminus) act as dimerization hot-spots, and further predict the occurrence of novel residues with the ability to nucleate dimerization, namely Lys-75 (EF-loop) and Trp-95 (C-terminus). We propose that D76N tetramerization is mainly driven by the self-association of dimers via the N-terminus and DE-loop, and identify Arg3 (N-terminus), Tyr10, Phe56 (D-strand) and Trp60 as potential tetramerization hot-spots.
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Affiliation(s)
- Rui J S Loureiro
- BioISI-Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
| | - Diogo Vila-Viçosa
- BioISI-Biosystems & Integrative Sciences Institute and Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
| | - Miguel Machuqueiro
- BioISI-Biosystems & Integrative Sciences Institute and Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Patrícia F N Faísca
- BioISI-Biosystems & Integrative Sciences Institute and Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal.
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24
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Rotem A, Serohijos AWR, Chang CB, Wolfe JT, Fischer AE, Mehoke TS, Zhang H, Tao Y, Lloyd Ung W, Choi JM, Rodrigues JV, Kolawole AO, Koehler SA, Wu S, Thielen PM, Cui N, Demirev PA, Giacobbi NS, Julian TR, Schwab K, Lin JS, Smith TJ, Pipas JM, Wobus CE, Feldman AB, Weitz DA, Shakhnovich EI. Evolution on the Biophysical Fitness Landscape of an RNA Virus. Mol Biol Evol 2019; 35:2390-2400. [PMID: 29955873 PMCID: PMC6188569 DOI: 10.1093/molbev/msy131] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics that propagates millions of independent small viral subpopulations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction, an atypical case in evolution. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs between molecular traits of viral proteins shape viral evolution.
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Affiliation(s)
- Assaf Rotem
- Department of Physics, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - Adrian W R Serohijos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA.,Département de Biochimie et Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, Montréal, QC, Canada
| | - Connie B Chang
- Department of Physics, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.,Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT
| | - Joshua T Wolfe
- Applied Physics Laboratory, Johns Hopkins University, Laurel, MD
| | - Audrey E Fischer
- Applied Physics Laboratory, Johns Hopkins University, Laurel, MD
| | - Thomas S Mehoke
- Applied Physics Laboratory, Johns Hopkins University, Laurel, MD
| | - Huidan Zhang
- Department of Physics, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.,Key Laboratory of Cell Biology, Department of Cell Biology, Ministry of Public Health, China Medical University, Shenyang, China.,Key Laboratory of Medical Cell Biology, Ministry of Education, China Medical University, Shenyang, China
| | - Ye Tao
- Department of Physics, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - W Lloyd Ung
- Department of Physics, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - Jeong-Mo Choi
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | - João V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | - Abimbola O Kolawole
- Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI
| | - Stephan A Koehler
- Department of Physics, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - Susan Wu
- Applied Physics Laboratory, Johns Hopkins University, Laurel, MD
| | - Peter M Thielen
- Applied Physics Laboratory, Johns Hopkins University, Laurel, MD
| | - Naiwen Cui
- Department of Physics, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - Plamen A Demirev
- Applied Physics Laboratory, Johns Hopkins University, Laurel, MD
| | | | - Timothy R Julian
- Environmental Health Sciences and the Hopkins Water Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.,Department of Environmental Microbiology, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Dübendorf, Switzerland
| | - Kellogg Schwab
- Environmental Health Sciences and the Hopkins Water Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Jeffrey S Lin
- Applied Physics Laboratory, Johns Hopkins University, Laurel, MD
| | - Thomas J Smith
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch at Galveston, Galveston, TX
| | - James M Pipas
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA
| | - Christiane E Wobus
- Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI
| | - Andrew B Feldman
- Department of Emergency Medicine, Johns Hopkins Medicine, Baltimore, MD
| | - David A Weitz
- Department of Physics, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
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25
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Rodrigues JV, Ogbunugafor CB, Hartl DL, Shakhnovich EI. Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity. Protein Sci 2019; 28:1359-1367. [PMID: 31095809 DOI: 10.1002/pro.3646] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 05/13/2019] [Indexed: 01/12/2023]
Abstract
While reverse genetics and functional genomics have long affirmed the role of individual mutations in determining protein function, there have been fewer studies addressing how large-scale changes in protein sequences, such as in entire modular segments, influence protein function and evolution. Given how recombination can reassort protein sequences, these types of changes may play an underappreciated role in how novel protein functions evolve in nature. Such studies could aid our understanding of whether certain organismal phenotypes related to protein function-such as growth in the presence or absence of an antibiotic-are robust with respect to the identity of certain modular segments. In this study, we combine molecular genetics with biochemical and biophysical methods to gain a better understanding of protein modularity in dihydrofolate reductase (DHFR), an enzyme target of antibiotics also widely used as a model for protein evolution. We replace an integral α-helical segment of Escherichia coli DHFR with segments from a number of different organisms (many nonmicrobial) and examine how these chimeric enzymes affect organismal phenotypes (e.g., resistance to an antibiotic) as well as biophysical properties of the enzyme (e.g., thermostability). We find that organismal phenotypes and enzyme properties are highly sensitive to the identity of DHFR modules, and that this chimeric approach can create enzymes with diverse biophysical characteristics.
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Affiliation(s)
- João V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - C Brandon Ogbunugafor
- Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island
| | - Daniel L Hartl
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
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26
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Abstract
Mutation rate is a key determinant of the pace as well as outcome of evolution, and variability in this rate has been shown in different scenarios to play a key role in evolutionary adaptation and resistance evolution under stress caused by selective pressure. Here we investigate the dynamics of resistance fixation in a bacterial population with variable mutation rates, and we show that evolutionary outcomes are most sensitive to mutation rate variations when the population is subject to environmental and demographic conditions that suppress the evolutionary advantage of high-fitness subpopulations. By directly mapping a biophysical fitness function to the system-level dynamics of the population, we show that both low and very high, but not intermediate, levels of stress in the form of an antibiotic result in a disproportionate effect of hypermutation on resistance fixation. We demonstrate how this behavior is directly tied to the extent of genetic hitchhiking in the system, the propagation of high-mutation rate cells through association with high-fitness mutations. Our results indicate a substantial role for mutation rate flexibility in the evolution of antibiotic resistance under conditions that present a weak advantage over wildtype to resistant cells.
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Affiliation(s)
- Dalit Engelhardt
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA
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27
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Serebryany E, Yu S, Trauger SA, Budnik B, Shakhnovich EI. Disulfide Exchange and Self-Catalyzed Aggregation in Cataract-Associated Human Gamma-D Crystallin. Biophys J 2019. [DOI: 10.1016/j.bpj.2018.11.1743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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28
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Manhart M, Adkar BV, Shakhnovich EI. Trade-offs between microbial growth phases lead to frequency-dependent and non-transitive selection. Proc Biol Sci 2019; 285:rspb.2017.2459. [PMID: 29445020 DOI: 10.1098/rspb.2017.2459] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Accepted: 01/25/2018] [Indexed: 11/12/2022] Open
Abstract
Mutations in a microbial population can increase the frequency of a genotype not only by increasing its exponential growth rate, but also by decreasing its lag time or adjusting the yield (resource efficiency). The contribution of multiple life-history traits to selection is a critical question for evolutionary biology as we seek to predict the evolutionary fates of mutations. Here we use a model of microbial growth to show that there are two distinct components of selection corresponding to the growth and lag phases, while the yield modulates their relative importance. The model predicts rich population dynamics when there are trade-offs between phases: multiple strains can coexist or exhibit bistability due to frequency-dependent selection, and strains can engage in rock-paper-scissors interactions due to non-transitive selection. We characterize the environmental conditions and patterns of traits necessary to realize these phenomena, which we show to be readily accessible to experiments. Our results provide a theoretical framework for analysing high-throughput measurements of microbial growth traits, especially interpreting the pleiotropy and correlations between traits across mutants. This work also highlights the need for more comprehensive measurements of selection in simple microbial systems, where the concept of an ordinary fitness landscape breaks down.
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Affiliation(s)
- Michael Manhart
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Bharat V Adkar
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
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29
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Razban RM, Gilson AI, Durfee N, Strobelt H, Dinkla K, Choi JM, Pfister H, Shakhnovich EI. ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms’ proteomes. Bioinformatics 2018; 34:4140. [DOI: 10.1093/bioinformatics/bty516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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30
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Razban RM, Gilson AI, Durfee N, Strobelt H, Dinkla K, Choi JM, Pfister H, Shakhnovich EI. ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms' proteomes. Bioinformatics 2018; 34:3557-3565. [PMID: 29741573 PMCID: PMC6184454 DOI: 10.1093/bioinformatics/bty370] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 03/27/2018] [Accepted: 05/03/2018] [Indexed: 01/27/2023] Open
Abstract
Motivation Protein evolution spans time scales and its effects span the length of an organism. A web app named ProteomeVis is developed to provide a comprehensive view of protein evolution in the Saccharomyces cerevisiae and Escherichia coli proteomes. ProteomeVis interactively creates protein chain graphs, where edges between nodes represent structure and sequence similarities within user-defined ranges, to study the long time scale effects of protein structure evolution. The short time scale effects of protein sequence evolution are studied by sequence evolutionary rate (ER) correlation analyses with protein properties that span from the molecular to the organismal level. Results We demonstrate the utility and versatility of ProteomeVis by investigating the distribution of edges per node in organismal protein chain universe graphs (oPCUGs) and putative ER determinants. S.cerevisiae and E.coli oPCUGs are scale-free with scaling constants of 1.79 and 1.56, respectively. Both scaling constants can be explained by a previously reported theoretical model describing protein structure evolution. Protein abundance most strongly correlates with ER among properties in ProteomeVis, with Spearman correlations of -0.49 (P-value < 10-10) and -0.46 (P-value < 10-10) for S.cerevisiae and E.coli, respectively. This result is consistent with previous reports that found protein expression to be the most important ER determinant. Availability and implementation ProteomeVis is freely accessible at http://proteomevis.chem.harvard.edu. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Rostam M Razban
- Department of Chemistry & Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Amy I Gilson
- Department of Chemistry & Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Niamh Durfee
- Department of Chemistry & Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Hendrik Strobelt
- School of Engineering & Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Kasper Dinkla
- School of Engineering & Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Jeong-Mo Choi
- Department of Chemistry & Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Hanspeter Pfister
- School of Engineering & Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Eugene I Shakhnovich
- Department of Chemistry & Chemical Biology, Harvard University, Cambridge, MA, USA
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31
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Serebryany E, Yu S, Trauger SA, Budnik B, Shakhnovich EI. Dynamic disulfide exchange in a crystallin protein in the human eye lens promotes cataract-associated aggregation. J Biol Chem 2018; 293:17997-18009. [PMID: 30242128 DOI: 10.1074/jbc.ra118.004551] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Revised: 09/14/2018] [Indexed: 12/31/2022] Open
Abstract
Increased light scattering in the eye lens due to aggregation of the long-lived lens proteins, crystallins, is the cause of cataract disease. Several mutations in the gene encoding human γD-crystallin (HγD) cause misfolding and aggregation. Cataract-associated substitutions at Trp42 cause the protein to aggregate in vitro from a partially unfolded intermediate locked by an internal disulfide bridge, and proteomic evidence suggests a similar aggregation precursor is involved in age-onset cataract. Surprisingly, WT HγD can promote aggregation of the W42Q variant while itself remaining soluble. Here, a search for a biochemical mechanism for this interaction has revealed a previously unknown oxidoreductase activity in HγD. Using in vitro oxidation, mutational analysis, cysteine labeling, and MS, we have assigned this activity to a redox-active internal disulfide bond that is dynamically exchanged among HγD molecules. The W42Q variant acts as a disulfide sink, reducing oxidized WT and forming a distinct internal disulfide that kinetically traps the aggregation-prone intermediate. Our findings suggest a redox "hot potato" competition among WT and mutant or modified polypeptides wherein variants with the lowest kinetic stability are trapped in aggregation-prone intermediate states upon accepting disulfides from more stable variants. Such reactions may occur in other long-lived proteins that function in oxidizing environments. In these cases, aggregation may be forestalled by inhibiting disulfide flow toward mutant or damaged polypeptides.
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Affiliation(s)
- Eugene Serebryany
- From the Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138
| | - Shuhuai Yu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122 Jiangsu, China
| | | | - Bogdan Budnik
- Mass Spectrometry and Proteomics Resource Laboratory, Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts 02138
| | - Eugene I Shakhnovich
- From the Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138.
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32
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Abstract
A central goal of protein-folding theory is to predict the stochastic dynamics of transition paths-the rare trajectories that transit between the folded and unfolded ensembles-using only thermodynamic information, such as a low-dimensional equilibrium free-energy landscape. However, commonly used one-dimensional landscapes typically fall short of this aim, because an empirical coordinate-dependent diffusion coefficient has to be fit to transition-path trajectory data in order to reproduce the transition-path dynamics. We show that an alternative, first-principles free-energy landscape predicts transition-path statistics that agree well with simulations and single-molecule experiments without requiring dynamical data as an input. This "topological configuration" model assumes that distinct, native-like substructures assemble on a time scale that is slower than native-contact formation but faster than the folding of the entire protein. Using only equilibrium simulation data to determine the free energies of these coarse-grained intermediate states, we predict a broad distribution of transition-path transit times that agrees well with the transition-path durations observed in simulations. We further show that both the distribution of finite-time displacements on a one-dimensional order parameter and the ensemble of transition-path trajectories generated by the model are consistent with the simulated transition paths. These results indicate that a landscape based on transient folding intermediates, which are often hidden by one-dimensional projections, can form the basis of a predictive model of protein-folding transition-path dynamics.
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Affiliation(s)
- William M Jacobs
- Department of Chemistry and Chemical Biology , Harvard University , 12 Oxford Street , Cambridge , Massachusetts 02138 , United States
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology , Harvard University , 12 Oxford Street , Cambridge , Massachusetts 02138 , United States
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33
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Bhattacharyya S, Jacobs WM, Adkar BV, Yan J, Zhang W, Shakhnovich EI. Accessibility of the Shine-Dalgarno Sequence Dictates N-Terminal Codon Bias in E. coli. Mol Cell 2018; 70:894-905.e5. [PMID: 29883608 DOI: 10.1016/j.molcel.2018.05.008] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 02/14/2018] [Accepted: 05/03/2018] [Indexed: 10/14/2022]
Abstract
Despite considerable efforts, no physical mechanism has been shown to explain N-terminal codon bias in prokaryotic genomes. Using a systematic study of synonymous substitutions in two endogenous E. coli genes, we show that interactions between the coding region and the upstream Shine-Dalgarno (SD) sequence modulate the efficiency of translation initiation, affecting both intracellular mRNA and protein levels due to the inherent coupling of transcription and translation in E. coli. We further demonstrate that far-downstream mutations can also modulate mRNA levels by occluding the SD sequence through the formation of non-equilibrium secondary structures. By contrast, a non-endogenous RNA polymerase that decouples transcription and translation largely alleviates the effects of synonymous substitutions on mRNA levels. Finally, a complementary statistical analysis of the E. coli genome specifically implicates avoidance of intra-molecular base pairing with the SD sequence. Our results provide general physical insights into the coding-level features that optimize protein expression in prokaryotes.
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Affiliation(s)
- Sanchari Bhattacharyya
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA, USA
| | - William M Jacobs
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA, USA
| | - Bharat V Adkar
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA, USA
| | - Jin Yan
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA, USA; College of Chemical Engineering, Sichuan University, Chengdu 610065, Sichuan, China
| | - Wenli Zhang
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA, USA; State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA, USA.
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34
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Valleau S, Studer RA, Häse F, Kreisbeck C, Saer RG, Blankenship RE, Shakhnovich EI, Aspuru-Guzik A. Absence of Selection for Quantum Coherence in the Fenna-Matthews-Olson Complex: A Combined Evolutionary and Excitonic Study. ACS Cent Sci 2017; 3:1086-1095. [PMID: 29104925 PMCID: PMC5658757 DOI: 10.1021/acscentsci.7b00269] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Indexed: 06/07/2023]
Abstract
We present a study on the evolution of the Fenna-Matthews-Olson bacterial photosynthetic pigment-protein complex. This protein complex functions as an antenna. It transports absorbed photons-excitons-to a reaction center where photosynthetic reactions initiate. The efficiency of exciton transport is therefore fundamental for the photosynthetic bacterium's survival. We have reconstructed an ancestor of the complex to establish whether coherence in the exciton transport was selected for or optimized over time. We have also investigated the role of optimizing free energy variation upon folding in evolution. We studied whether mutations which connect the ancestor to current day species were stabilizing or destabilizing from a thermodynamic viewpoint. From this study, we established that most of these mutations were thermodynamically neutral. Furthermore, we did not see a large change in exciton transport efficiency or coherence, and thus our results predict that exciton coherence was not specifically selected for.
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Affiliation(s)
- Stéphanie Valleau
- Department
of Chemistry and Chemical Biology, Harvard
University, Cambridge, Massachusetts 02138, United States
| | - Romain A. Studer
- European
Bioinformatics Institute (EMBL-EBI),
Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, U.K.
| | - Florian Häse
- Department
of Chemistry and Chemical Biology, Harvard
University, Cambridge, Massachusetts 02138, United States
| | - Christoph Kreisbeck
- Department
of Chemistry and Chemical Biology, Harvard
University, Cambridge, Massachusetts 02138, United States
| | - Rafael G. Saer
- Departments
of Biology and Chemistry, Washington University
in Saint Louis, One Brookings
Drive, St. Louis, Missouri 63130, United States
| | - Robert E. Blankenship
- Departments
of Biology and Chemistry, Washington University
in Saint Louis, One Brookings
Drive, St. Louis, Missouri 63130, United States
| | - Eugene I. Shakhnovich
- Department
of Chemistry and Chemical Biology, Harvard
University, Cambridge, Massachusetts 02138, United States
| | - Alán Aspuru-Guzik
- Department
of Chemistry and Chemical Biology, Harvard
University, Cambridge, Massachusetts 02138, United States
- Bio-inspired
Solar Energy Program, Canadian Institute
for Advanced Research, Toronto, Ontario M5G 1Z8, Canada
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35
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Loureiro RJS, Vila-Viçosa D, Machuqueiro M, Shakhnovich EI, Faísca PFN. A tale of two tails: The importance of unstructured termini in the aggregation pathway of β2-microglobulin. Proteins 2017; 85:2045-2057. [DOI: 10.1002/prot.25358] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 07/13/2017] [Accepted: 07/22/2017] [Indexed: 12/14/2022]
Affiliation(s)
- Rui J. S. Loureiro
- BioISI - Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa; Lisboa Portugal
| | - Diogo Vila-Viçosa
- Centro de Química e Bioquímica; Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade de Lisboa; Lisboa Portugal
| | - Miguel Machuqueiro
- Centro de Química e Bioquímica; Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade de Lisboa; Lisboa Portugal
| | - Eugene I. Shakhnovich
- Department of Chemistry and Chemical Biology; Harvard University; Cambridge Massachusetts
| | - Patricia F. N. Faísca
- BioISI - Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa; Lisboa Portugal
- Departamento de Física; Faculdade de Ciências, Universidade de Lisboa; Lisboa Portugal
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36
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Jacobs WM, Shakhnovich EI. Structure-Based Prediction of Protein-Folding Transition Paths. Biophys J 2017; 111:925-36. [PMID: 27602721 PMCID: PMC5018131 DOI: 10.1016/j.bpj.2016.06.031] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Revised: 06/08/2016] [Accepted: 06/27/2016] [Indexed: 12/24/2022] Open
Abstract
We propose a general theory to describe the distribution of protein-folding transition paths. We show that transition paths follow a predictable sequence of high-free-energy transient states that are separated by free-energy barriers. Each transient state corresponds to the assembly of one or more discrete, cooperative units, which are determined directly from the native structure. We show that the transition state on a folding pathway is reached when a small number of critical contacts are formed between a specific set of substructures, after which folding proceeds downhill in free energy. This approach suggests a natural resolution for distinguishing parallel folding pathways and provides a simple means to predict the rate-limiting step in a folding reaction. Our theory identifies a common folding mechanism for proteins with diverse native structures and establishes general principles for the self-assembly of polymers with specific interactions.
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Affiliation(s)
- William M Jacobs
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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37
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Chéron N, Shakhnovich EI. Effect of sampling on BACE-1 ligands binding free energy predictions via MM-PBSA calculations. J Comput Chem 2017; 38:1941-1951. [PMID: 28568844 DOI: 10.1002/jcc.24839] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Revised: 05/02/2017] [Accepted: 05/04/2017] [Indexed: 01/04/2023]
Abstract
The BACE-1 enzyme is a prime target to find a cure to Alzheimer's disease. In this article, we used the MM-PBSA approach to compute the binding free energies of 46 reported ligands to this enzyme. After showing that the most probable protonation state of the catalytic dyad is mono-protonated (on ASP32), we performed a thorough analysis of the parameters influencing the sampling of the conformational space (in total, more than 35 μs of simulations were performed). We show that ten simulations of 2 ns gives better results than one of 50 ns. We also investigated the influence of the protein force field, the water model, the periodic boundary conditions artifacts (box size), as well as the ionic strength. Amber03 with TIP3P, a minimal distance of 1.0 nm between the protein and the box edges and a ionic strength of I = 0.2 M provides the optimal correlation with experiments. Overall, when using these parameters, a Pearson correlation coefficient of R = 0.84 (R2 = 0.71) is obtained for the 46 ligands, spanning eight orders of magnitude of Kd (from 0.017 nm to 2000 μM, i.e., from -14.7 to -3.7 kcal/mol), with a ligand size from 22 to 136 atoms (from 138 to 937 g/mol). After a two-parameter fit of the binding affinities for 12 of the ligands, an error of RMSD = 1.7 kcal/mol was obtained for the remaining ligands. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Nicolas Chéron
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, 02138.,Département de Chimie, UMR 8640 PASTEUR, Ecole Normale Supérieure, PSL Research University, UPMC Univ. Paris 06, CNRS, 24 rue Lhomond, Paris, 75005, France
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, 02138
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38
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Adkar BV, Manhart M, Bhattacharyya S, Tian J, Musharbash M, Shakhnovich EI. Optimization of lag phase shapes the evolution of a bacterial enzyme. Nat Ecol Evol 2017; 1:149. [PMID: 28812634 DOI: 10.1038/s41559-017-0149] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2016] [Accepted: 03/22/2017] [Indexed: 01/09/2023]
Abstract
Mutations provide the variation that drives evolution, yet their effects on fitness remain poorly understood. Here we explore how mutations in the essential enzyme adenylate kinase (Adk) of Escherichia coli affect multiple phases of population growth. We introduce a biophysical fitness landscape for these phases, showing how they depend on molecular and cellular properties of Adk. We find that Adk catalytic capacity in the cell (the product of activity and abundance) is the major determinant of mutational fitness effects. We show that bacterial lag times are at a well-defined optimum with respect to Adk's catalytic capacity, while exponential growth rates are only weakly affected by variation in Adk. Direct pairwise competitions between strains show how environmental conditions modulate the outcome of a competition where growth rates and lag times have a tradeoff, shedding light on the multidimensional nature of fitness and its importance in the evolutionary optimization of enzymes.
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Affiliation(s)
- Bharat V Adkar
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA
| | - Michael Manhart
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA
| | - Sanchari Bhattacharyya
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA
| | - Jian Tian
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA.,Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Michael Musharbash
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA
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39
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Debroise T, Shakhnovich EI, Chéron N. A Hybrid Knowledge-Based and Empirical Scoring Function for Protein–Ligand Interaction: SMoG2016. J Chem Inf Model 2017; 57:584-593. [DOI: 10.1021/acs.jcim.6b00610] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Affiliation(s)
- Théau Debroise
- Department
of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Eugene I. Shakhnovich
- Department
of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Nicolas Chéron
- Department
of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
- Ecole Normale Supérieure, PSL Research University, UPMC Univ. Paris 06, CNRS, Département de Chimie,
UMR 8640 PASTEUR, 24 rue
Lhomond, 75005 Paris, France
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40
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Abstract
In this Letter we investigate a direct relationship between a graph's topology and the free energy of a spin system on the graph. We develop a method of separating topological and energetic contributions to the free energy, and find that considering the topology is sufficient to qualitatively compare the free energies of different graph systems at high temperature, even when the energetics are not fully known. This method was applied to the metal lattice system with defects, and we found that it partially explains why point defects are more stable than high-dimensional defects. Given the energetics, we can even quantitatively compare free energies of different graph structures via a closed form of linear graph contributions. The closed form is applied to predict the sequence-space free energy of lattice proteins, which is a key factor determining the designability of a protein structure.
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Affiliation(s)
- Jeong-Mo Choi
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA
| | - Amy I Gilson
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA
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41
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Serebryany E, Woodard JC, Adkar BV, Shabab M, King JA, Shakhnovich EI. An Internal Disulfide Locks a Misfolded Aggregation-Prone Intermediate in Cataract-Linked Mutants of Human Gamma-D Crystallin. Biophys J 2017. [DOI: 10.1016/j.bpj.2016.11.923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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42
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Abstract
This protocol is used to assay the effect of protein over-expression on fitness of E. coli. It is based on a plasmid expression of a protein of interest from an arabinose-regulated pBAD promoter followed by the measurement of the intracellular protein abundance by Western blot along with the measurement of growth parameters of E. coli cell expressing this protein.
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Affiliation(s)
| | - Shimon Bershtein
- Department of Life Sciences, Ben-Gurion University of the Negev, POB 653, Beer-Sheva, Israel
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge MA, USA
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43
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Bhattacharyya S, Bershtein S, Yan J, Argun T, Gilson AI, Trauger SA, Shakhnovich EI. Transient protein-protein interactions perturb E. coli metabolome and cause gene dosage toxicity. eLife 2016; 5. [PMID: 27938662 PMCID: PMC5176355 DOI: 10.7554/elife.20309] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Accepted: 12/09/2016] [Indexed: 12/31/2022] Open
Abstract
Gene dosage toxicity (GDT) is an important factor that determines optimal levels of protein abundances, yet its molecular underpinnings remain unknown. Here, we demonstrate that overexpression of DHFR in E. coli causes a toxic metabolic imbalance triggered by interactions with several functionally related enzymes. Though deleterious in the overexpression regime, surprisingly, these interactions are beneficial at physiological concentrations, implying their functional significance in vivo. Moreover, we found that overexpression of orthologous DHFR proteins had minimal effect on all levels of cellular organization - molecular, systems, and phenotypic, in sharp contrast to E. coli DHFR. Dramatic difference of GDT between 'E. coli's self' and 'foreign' proteins suggests the crucial role of evolutionary selection in shaping protein-protein interaction (PPI) networks at the whole proteome level. This study shows how protein overexpression perturbs a dynamic metabolon of weak yet potentially functional PPI, with consequences for the metabolic state of cells and their fitness.
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Affiliation(s)
- Sanchari Bhattacharyya
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Shimon Bershtein
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Jin Yan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States.,College of Chemical Engineering, Sichuan University, Chengdu, China
| | - Tijda Argun
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Amy I Gilson
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Sunia A Trauger
- Small Molecule Mass Spectrometry, Northwest Laboratories, Harvard University, Cambridge, United States
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
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44
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Bershtein S, Serohijos AW, Shakhnovich EI. Bridging the physical scales in evolutionary biology: from protein sequence space to fitness of organisms and populations. Curr Opin Struct Biol 2016; 42:31-40. [PMID: 27810574 DOI: 10.1016/j.sbi.2016.10.013] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 10/14/2016] [Indexed: 01/11/2023]
Abstract
Bridging the gap between the molecular properties of proteins and organismal/population fitness is essential for understanding evolutionary processes. This task requires the integration of the several physical scales of biological organization, each defined by a distinct set of mechanisms and constraints, into a single unifying model. The molecular scale is dominated by the constraints imposed by the physico-chemical properties of proteins and their substrates, which give rise to trade-offs and epistatic (non-additive) effects of mutations. At the systems scale, biological networks modulate protein expression and can either buffer or enhance the fitness effects of mutations. The population scale is influenced by the mutational input, selection regimes, and stochastic changes affecting the size and structure of populations, which eventually determine the evolutionary fate of mutations. Here, we summarize the recent advances in theory, computer simulations, and experiments that advance our understanding of the links between various physical scales in biology.
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Affiliation(s)
- Shimon Bershtein
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84501, Israel
| | - Adrian Wr Serohijos
- Département de Biochimie, Centre Robert-Cedergren en Bioinformatique & Génomique, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, United States.
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45
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Serebryany E, Woodard JC, Adkar BV, Shabab M, King JA, Shakhnovich EI. An Internal Disulfide Locks a Misfolded Aggregation-prone Intermediate in Cataract-linked Mutants of Human γD-Crystallin. J Biol Chem 2016; 291:19172-83. [PMID: 27417136 DOI: 10.1074/jbc.m116.735977] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Indexed: 11/06/2022] Open
Abstract
Considerable mechanistic insight has been gained into amyloid aggregation; however, a large number of non-amyloid protein aggregates are considered "amorphous," and in most cases, little is known about their mechanisms. Amorphous aggregation of γ-crystallins in the eye lens causes cataract, a widespread disease of aging. We combined simulations and experiments to study the mechanism of aggregation of two γD-crystallin mutants, W42R and W42Q: the former a congenital cataract mutation, and the latter a mimic of age-related oxidative damage. We found that formation of an internal disulfide was necessary and sufficient for aggregation under physiological conditions. Two-chain all-atom simulations predicted that one non-native disulfide in particular, between Cys(32) and Cys(41), was likely to stabilize an unfolding intermediate prone to intermolecular interactions. Mass spectrometry and mutagenesis experiments confirmed the presence of this bond in the aggregates and its necessity for oxidative aggregation under physiological conditions in vitro Mining the simulation data linked formation of this disulfide to extrusion of the N-terminal β-hairpin and rearrangement of the native β-sheet topology. Specific binding between the extruded hairpin and a distal β-sheet, in an intermolecular chain reaction similar to domain swapping, is the most probable mechanism of aggregate propagation.
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Affiliation(s)
- Eugene Serebryany
- From the Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 and
| | - Jaie C Woodard
- the Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138
| | - Bharat V Adkar
- the Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138
| | - Mohammed Shabab
- From the Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 and
| | - Jonathan A King
- From the Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 and
| | - Eugene I Shakhnovich
- the Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138
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46
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Chéron N, Serohijos AWR, Choi JM, Shakhnovich EI. Evolutionary dynamics of viral escape under antibodies stress: A biophysical model. Protein Sci 2016; 25:1332-40. [PMID: 26939576 PMCID: PMC4918420 DOI: 10.1002/pro.2915] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Revised: 02/23/2016] [Accepted: 03/02/2016] [Indexed: 12/12/2022]
Abstract
Viruses constantly face the selection pressure of antibodies, either from innate immune response of the host or from administered antibodies for treatment. We explore the interplay between the biophysical properties of viral proteins and the population and demographic variables in the viral escape. The demographic and population genetics aspect of the viral escape have been explored before; however one important assumption was the a priori distribution of fitness effects (DFE). Here, we relax this assumption by instead considering a realistic biophysics-based genotype-phenotype relationship for RNA viruses escaping antibodies stress. In this model the DFE is itself an evolvable property that depends on the genetic background (epistasis) and the distribution of biophysical effects of mutations, which is informed by biochemical experiments and theoretical calculations in protein engineering. We quantitatively explore in silico the viability of viral populations under antibodies pressure and derive the phase diagram that defines the fate of the virus population (extinction or escape from stress) in a range of viral mutation rates and antibodies concentrations. We find that viruses are most resistant to stress at an optimal mutation rate (OMR) determined by the competition between supply of beneficial mutation to facilitate escape from stressors and lethal mutagenesis caused by excess of destabilizing mutations. We then show the quantitative dependence of the OMR on genome length and viral burst size. We also recapitulate the experimental observation that viruses with longer genomes have smaller mutation rate per nucleotide.
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Affiliation(s)
- Nicolas Chéron
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, 02138
- Département de Biochimie et Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, Montréal, Quebec, Canada, H3T 1J4
| | - Adrian W R Serohijos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, 02138
| | - Jeong-Mo Choi
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, 02138
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, 02138
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47
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Woodard JC, Dunatunga S, Shakhnovich EI. A Simple Model of Protein Domain Swapping in Crowded Cellular Environments. Biophys J 2016; 110:2367-2376. [PMID: 27276255 DOI: 10.1016/j.bpj.2016.04.033] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Revised: 04/07/2016] [Accepted: 04/20/2016] [Indexed: 11/25/2022] Open
Abstract
Domain swapping in proteins is an important mechanism of functional and structural innovation. However, despite its ubiquity and importance, the physical mechanisms that lead to domain swapping are poorly understood. Here, we present a simple two-dimensional coarse-grained model of protein domain swapping in the cytoplasm. In our model, two-domain proteins partially unfold and diffuse in continuous space. Monte Carlo multiprotein simulations of the model reveal that domain swapping occurs at intermediate temperatures, whereas folded dimers and folded monomers prevail at low temperatures, and partially unfolded monomers predominate at high temperatures. We use a simplified amino acid alphabet consisting of four residue types, and find that the oligomeric state at a given temperature depends on the sequence of the protein. We also show that hinge strain between domains can promote domain swapping, consistent with experimental observations for real proteins. Domain swapping depends nonmonotonically on the protein concentration, with domain-swapped dimers occurring at intermediate concentrations and nonspecific interactions between partially unfolded proteins occurring at high concentrations. For folded proteins, we recover the result obtained in three-dimensional lattice simulations, i.e., that functional dimerization is most prevalent at intermediate temperatures and nonspecific interactions increase at low temperatures.
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Affiliation(s)
- Jaie C Woodard
- Graduate Program in Biophysics, Harvard University, Cambridge, Massachusetts; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Sachith Dunatunga
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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48
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Choi JM, Serohijos AWR, Murphy S, Lucarelli D, Lofranco LL, Feldman A, Shakhnovich EI. Minimalistic predictor of protein binding energy: contribution of solvation factor to protein binding. Biophys J 2015; 108:795-798. [PMID: 25692584 DOI: 10.1016/j.bpj.2015.01.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2014] [Revised: 12/28/2014] [Accepted: 01/05/2015] [Indexed: 01/20/2023] Open
Abstract
It has long been known that solvation plays an important role in protein-protein interactions. Here, we use a minimalistic solvation-based model for predicting protein binding energy to estimate quantitatively the contribution of the solvation factor in protein binding. The factor is described by a simple linear combination of buried surface areas according to amino-acid types. Even without structural optimization, our minimalistic model demonstrates a predictive power comparable to more complex methods, making the proposed approach the basis for high throughput applications. Application of the model to a proteomic database shows that receptor-substrate complexes involved in signaling have lower affinities than enzyme-inhibitor and antibody-antigen complexes, and they differ by chemical compositions on interfaces. Also, we found that protein complexes with components that come from the same genes generally have lower affinities than complexes formed by proteins from different genes, but in this case the difference originates from different interface areas. The model was implemented in the software PYTHON, and the source code can be found on the Shakhnovich group webpage: http://faculty.chemistry.harvard.edu/shakhnovich/software.
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Affiliation(s)
- Jeong-Mo Choi
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Adrian W R Serohijos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Sean Murphy
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | - Dennis Lucarelli
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | - Leo L Lofranco
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Andrew Feldman
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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49
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Affiliation(s)
- Nicolas Chéron
- Department of Chemistry and
Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Naveen Jasty
- Department of Chemistry and
Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Eugene I. Shakhnovich
- Department of Chemistry and
Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
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50
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Çetinbaş M, Shakhnovich EI. Is catalytic activity of chaperones a selectable trait for the emergence of heat shock response? Biophys J 2015; 108:438-48. [PMID: 25606691 DOI: 10.1016/j.bpj.2014.11.3468] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Revised: 10/28/2014] [Accepted: 11/24/2014] [Indexed: 10/24/2022] Open
Abstract
Although heat shock response is ubiquitous in bacterial cells, the underlying physical chemistry behind heat shock response remains poorly understood. To study the response of cell populations to heat shock we employ a physics-based ab initio model of living cells where protein biophysics (i.e., folding and protein-protein interactions in crowded cellular environments) and important aspects of proteins homeostasis are coupled with realistic population dynamics simulations. By postulating a genotype-phenotype relationship we define a cell division rate in terms of functional concentrations of proteins and protein complexes, whose Boltzmann stabilities of folding and strengths of their functional interactions are exactly evaluated from their sequence information. We compare and contrast evolutionary dynamics for two models of chaperon action. In the active model, foldase chaperones function as nonequilibrium machines to accelerate the rate of protein folding. In the passive model, holdase chaperones form reversible complexes with proteins in their misfolded conformations to maintain their solubility. We find that only cells expressing foldase chaperones are capable of genuine heat shock response to the increase in the amount of unfolded proteins at elevated temperatures. In response to heat shock, cells' limited resources are redistributed differently for active and passive models. For the active model, foldase chaperones are overexpressed at the expense of downregulation of high abundance proteins, whereas for the passive model; cells react to heat shock by downregulating their high abundance proteins, as their low abundance proteins are upregulated.
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Affiliation(s)
- Murat Çetinbaş
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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