1
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Kamsri B, Kamsri P, Punkvang A, Chimprasit A, Saparpakorn P, Hannongbua S, Spencer J, Oliveira ASF, Mulholland AJ, Pungpo P. Signal Propagation in the ATPase Domain of Mycobacterium tuberculosis DNA Gyrase from Dynamical-Nonequilibrium Molecular Dynamics Simulations. Biochemistry 2024; 63:1493-1504. [PMID: 38742407 PMCID: PMC11154950 DOI: 10.1021/acs.biochem.4c00161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 04/26/2024] [Accepted: 05/01/2024] [Indexed: 05/16/2024]
Abstract
DNA gyrases catalyze negative supercoiling of DNA, are essential for bacterial DNA replication, transcription, and recombination, and are important antibacterial targets in multiple pathogens, including Mycobacterium tuberculosis, which in 2021 caused >1.5 million deaths worldwide. DNA gyrase is a tetrameric (A2B2) protein formed from two subunit types: gyrase A (GyrA) carries the breakage-reunion active site, whereas gyrase B (GyrB) catalyzes ATP hydrolysis required for energy transduction and DNA translocation. The GyrB ATPase domains dimerize in the presence of ATP to trap the translocated DNA (T-DNA) segment as a first step in strand passage, for which hydrolysis of one of the two ATPs and release of the resulting inorganic phosphate is rate-limiting. Here, dynamical-nonequilibrium molecular dynamics (D-NEMD) simulations of the dimeric 43 kDa N-terminal fragment of M. tuberculosis GyrB show how events at the ATPase site (dissociation/hydrolysis of bound nucleotides) are propagated through communication pathways to other functionally important regions of the GyrB ATPase domain. Specifically, our simulations identify two distinct pathways that respectively connect the GyrB ATPase site to the corynebacteria-specific C-loop, thought to interact with GyrA prior to DNA capture, and to the C-terminus of the GyrB transduction domain, which in turn contacts the C-terminal GyrB topoisomerase-primase (TOPRIM) domain responsible for interactions with GyrA and the centrally bound G-segment DNA. The connection between the ATPase site and the C-loop of dimeric GyrB is consistent with the unusual properties of M. tuberculosis DNA gyrase relative to those from other bacterial species.
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Affiliation(s)
- Bundit Kamsri
- Department
of Chemistry and Center of Excellence for Innovation in Chemistry,
Faculty of Science, Ubon Ratchathani University, Ubon Ratchathani 34190, Thailand
| | - Pharit Kamsri
- Division
of Chemistry, Faculty of Science, Nakhon
Phanom University, Nakhon
Phanom 48000, Thailand
| | - Auradee Punkvang
- Division
of Chemistry, Faculty of Science, Nakhon
Phanom University, Nakhon
Phanom 48000, Thailand
| | - Aunlika Chimprasit
- Department
of Chemistry, Faculty of Science, Kasetsart
University, Bangkok 10900, Thailand
| | | | - Supa Hannongbua
- Department
of Chemistry, Faculty of Science, Kasetsart
University, Bangkok 10900, Thailand
| | - James Spencer
- School
of Cellular and Molecular Medicine, Biomedical Sciences Building, University of Bristol, Bristol BS8 1TD, U.K.
| | - A. Sofia F. Oliveira
- Centre
for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.
| | - Adrian J. Mulholland
- Centre
for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.
| | - Pornpan Pungpo
- Department
of Chemistry and Center of Excellence for Innovation in Chemistry,
Faculty of Science, Ubon Ratchathani University, Ubon Ratchathani 34190, Thailand
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2
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Astore MA, Pradhan AS, Thiede EH, Hanson SM. Protein dynamics underlying allosteric regulation. Curr Opin Struct Biol 2024; 84:102768. [PMID: 38215528 DOI: 10.1016/j.sbi.2023.102768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/16/2023] [Accepted: 12/18/2023] [Indexed: 01/14/2024]
Abstract
Allostery is the mechanism by which information and control are propagated in biomolecules. It regulates ligand binding, chemical reactions, and conformational changes. An increasing level of experimental resolution and control over allosteric mechanisms promises a deeper understanding of the molecular basis for life and powerful new therapeutics. In this review, we survey the literature for an up-to-date biological and theoretical understanding of protein allostery. By delineating five ways in which the energy landscape or the kinetics of a system may change to give rise to allostery, we aim to help the reader grasp its physical origins. To illustrate this framework, we examine three systems that display these forms of allostery: allosteric inhibitors of beta-lactamases, thermosensation of TRP channels, and the role of kinetic allostery in the function of kinases. Finally, we summarize the growing power of computational tools available to investigate the different forms of allostery presented in this review.
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Affiliation(s)
- Miro A Astore
- Center for Computational Biology, Flatiron Institute, New York, NY, USA; Center for Computational Mathematics, Flatiron Institute, New York, NY, USA. https://twitter.com/@miroastore
| | - Akshada S Pradhan
- Center for Computational Biology, Flatiron Institute, New York, NY, USA
| | - Erik H Thiede
- Center for Computational Biology, Flatiron Institute, New York, NY, USA; Center for Computational Mathematics, Flatiron Institute, New York, NY, USA; Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA
| | - Sonya M Hanson
- Center for Computational Biology, Flatiron Institute, New York, NY, USA; Center for Computational Mathematics, Flatiron Institute, New York, NY, USA.
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3
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Castelli M, Marchetti F, Osuna S, F. Oliveira AS, Mulholland AJ, Serapian SA, Colombo G. Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations. J Am Chem Soc 2024; 146:901-919. [PMID: 38116743 PMCID: PMC10785808 DOI: 10.1021/jacs.3c11396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/06/2023] [Accepted: 12/07/2023] [Indexed: 12/21/2023]
Abstract
Protein functions are dynamically regulated by allostery, which enables conformational communication even between faraway residues, and expresses itself in many forms, akin to different "languages": allosteric control pathways predominating in an unperturbed protein are often unintuitively reshaped whenever biochemical perturbations arise (e.g., mutations). To accurately model allostery, unbiased molecular dynamics (MD) simulations require integration with a reliable method able to, e.g., detect incipient allosteric changes or likely perturbation pathways; this is because allostery can operate at longer time scales than those accessible by plain MD. Such methods are typically applied singularly, but we here argue their joint application─as a "multilingual" approach─could work significantly better. We successfully prove this through unbiased MD simulations (∼100 μs) of the widely studied, allosterically active oncotarget K-Ras4B, solvated and embedded in a phospholipid membrane, from which we decrypt allostery using four showcase "languages": Distance Fluctuation analysis and the Shortest Path Map capture allosteric hotspots at equilibrium; Anisotropic Thermal Diffusion and Dynamical Non-Equilibrium MD simulations assess perturbations upon, respectively, either superheating or hydrolyzing the GTP that oncogenically activates K-Ras4B. Chosen "languages" work synergistically, providing an articulate, mutually coherent, experimentally consistent picture of K-Ras4B allostery, whereby distinct traits emerge at equilibrium and upon GTP cleavage. At equilibrium, combined evidence confirms prominent allosteric communication from the membrane-embedded hypervariable region, through a hub comprising helix α5 and sheet β5, and up to the active site, encompassing allosteric "switches" I and II (marginally), and two proposed pockets. Upon GTP cleavage, allosteric perturbations mostly accumulate on the switches and documented interfaces.
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Affiliation(s)
- Matteo Castelli
- Department
of Chemistry, University of Pavia, viale T. Taramelli 12, 27100 Pavia, Italy
| | - Filippo Marchetti
- Department
of Chemistry, University of Pavia, viale T. Taramelli 12, 27100 Pavia, Italy
- INSTM, via G. Giusti 9, 50121 Florence, Italy
- E4
Computer Engineering, via Martiri delle libertà 66, 42019 Scandiano (RE), Italy
| | - Sílvia Osuna
- Institut
de Química Computacional i Catàlisi (IQCC) and Departament
de Química, Universitat de Girona, Girona, Catalonia E-17071, Spain
- ICREA, Barcelona, Catalonia E-08010, Spain
| | - A. Sofia F. Oliveira
- Centre for
Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.
| | - Adrian J. Mulholland
- Centre for
Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.
| | - Stefano A. Serapian
- Department
of Chemistry, University of Pavia, viale T. Taramelli 12, 27100 Pavia, Italy
| | - Giorgio Colombo
- Department
of Chemistry, University of Pavia, viale T. Taramelli 12, 27100 Pavia, Italy
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4
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Oliveira AS, Rubio J, Noble CEM, Anderson JLR, Anders J, Mulholland AJ. Fluctuation Relations to Calculate Protein Redox Potentials from Molecular Dynamics Simulations. J Chem Theory Comput 2024; 20:385-395. [PMID: 38150288 PMCID: PMC10782445 DOI: 10.1021/acs.jctc.3c00785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 12/05/2023] [Accepted: 12/05/2023] [Indexed: 12/28/2023]
Abstract
The tunable design of protein redox potentials promises to open a range of applications in biotechnology and catalysis. Here, we introduce a method to calculate redox potential changes by combining fluctuation relations with molecular dynamics simulations. It involves the simulation of reduced and oxidized states, followed by the instantaneous conversion between them. Energy differences introduced by the perturbations are obtained using the Kubo-Onsager approach. Using a detailed fluctuation relation coupled with Bayesian inference, these are postprocessed into estimates for the redox potentials in an efficient manner. This new method, denoted MD + CB, is tested on a de novo four-helix bundle heme protein (the m4D2 "maquette") and five designed mutants, including some mutants characterized experimentally in this work. The MD + CB approach is found to perform reliably, giving redox potential shifts with reasonably good correlation (0.85) to the experimental values for the mutants. The MD + CB approach also compares well with redox potential shift predictions using a continuum electrostatic method. The estimation method employed within the MD + CB approach is straightforwardly transferable to standard equilibrium MD simulations and holds promise for redox protein engineering and design applications.
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Affiliation(s)
- A. S.
F. Oliveira
- Centre
for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.
- School
of Biochemistry, University of Bristol, Bristol BS8 1DT, U.K.
- BrisSynBio
Synthetic Biology Research Centre, University
of Bristol, Bristol BS8 1TQ, U.K.
| | - J. Rubio
- School
of Mathematics and Physics, University of
Surrey, Guildford GU2 7XH, U.K.
- Department
of Physics and Astronomy, University of
Exeter, Stocker Road, Exeter EX4
4QL, U.K.
| | - C. E. M. Noble
- School
of Biochemistry, University of Bristol, Bristol BS8 1DT, U.K.
- BrisSynBio
Synthetic Biology Research Centre, University
of Bristol, Bristol BS8 1TQ, U.K.
| | - J. L. R. Anderson
- School
of Biochemistry, University of Bristol, Bristol BS8 1DT, U.K.
- BrisSynBio
Synthetic Biology Research Centre, University
of Bristol, Bristol BS8 1TQ, U.K.
| | - J. Anders
- Department
of Physics and Astronomy, University of
Exeter, Stocker Road, Exeter EX4
4QL, U.K.
- Institute
of Physics and Astronomy, University of
Potsdam, Potsdam 14476, Germany
| | - A. J. Mulholland
- Centre
for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.
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5
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Castelli M, Magni A, Bonollo G, Pavoni S, Frigerio F, Oliveira ASF, Cinquini F, Serapian SA, Colombo G. Molecular mechanisms of chaperone-directed protein folding: Insights from atomistic simulations. Protein Sci 2023; 33:e4880. [PMID: 38145386 PMCID: PMC10895457 DOI: 10.1002/pro.4880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/06/2023] [Accepted: 12/19/2023] [Indexed: 12/26/2023]
Abstract
Molecular chaperones, a family of proteins of which Hsp90 and Hsp70 are integral members, form an essential machinery to maintain healthy proteomes by controlling the folding and activation of a plethora of substrate client proteins. This is achieved through cycles in which Hsp90 and Hsp70, regulated by task-specific co-chaperones, process ATP and become part of a complex network that undergoes extensive compositional and conformational variations. Despite impressive advances in structural knowledge, the mechanisms that regulate the dynamics of functional assemblies, their response to nucleotides, and their relevance for client remodeling are still elusive. Here, we focus on the glucocorticoid receptor (GR):Hsp90:Hsp70:co-chaperone Hop client-loading and the GR:Hsp90:co-chaperone p23 client-maturation complexes, key assemblies in the folding cycle of glucocorticoid receptor (GR), a client strictly dependent upon Hsp90/Hsp70 for activity. Using a combination of molecular dynamics simulation approaches, we unveil with unprecedented detail the mechanisms that underpin function in these chaperone machineries. Specifically, we dissect the processes by which the nucleotide-encoded message is relayed to the client and how the distinct partners of the assemblies cooperate to (pre)organize partially folded GR during Loading and Maturation. We show how different ligand states determine distinct dynamic profiles for the functional interfaces defining the interactions in the complexes and modulate their overall flexibility to facilitate progress along the chaperone cycle. Finally, we also show that the GR regions engaged by the chaperone machinery display peculiar energetic signatures in the folded state, which enhance the probability of partial unfolding fluctuations. From these results, we propose a model where a dynamic cross-talk emerges between the chaperone dynamics states and remodeling of client-interacting regions. This factor, coupled to the highly dynamic nature of the assemblies and the conformational heterogeneity of their interactions, provides the basis for regulating the functions of distinct assemblies during the chaperoning cycle.
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Affiliation(s)
| | - Andrea Magni
- Dipartimento di Chimica, Università di Pavia, Pavia, Italy
| | | | - Silvia Pavoni
- Department of Physical Chemistry, R&D Eni SpA, San Donato Milanese, Italy
| | - Francesco Frigerio
- Department of Physical Chemistry, R&D Eni SpA, San Donato Milanese, Italy
| | - A Sofia F Oliveira
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, UK
| | - Fabrizio Cinquini
- Upstream & Technical Services - TECS/STES - Eni Spa, San Donato Milanese, Italy
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6
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Oliveira ASF, Shoemark DK, Davidson AD, Berger I, Schaffitzel C, Mulholland AJ. SARS-CoV-2 spike variants differ in their allosteric responses to linoleic acid. J Mol Cell Biol 2023; 15:mjad021. [PMID: 36990513 PMCID: PMC10563148 DOI: 10.1093/jmcb/mjad021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 11/07/2022] [Accepted: 03/28/2023] [Indexed: 03/31/2023] Open
Abstract
The SARS-CoV-2 spike protein contains a functionally important fatty acid (FA) binding site, which is also found in some other coronaviruses, e.g. SARS-CoV and MERS-CoV. The occupancy of the FA site by linoleic acid (LA) reduces infectivity by 'locking' the spike in a less infectious conformation. Here, we use dynamical-nonequilibrium molecular dynamics (D-NEMD) simulations to compare the allosteric responses of spike variants to LA removal. D-NEMD simulations show that the FA site is coupled to other functional regions of the protein, e.g. the receptor-binding motif (RBM), N-terminal domain (NTD), furin cleavage site, and regions surrounding the fusion peptide. D-NEMD simulations also identify the allosteric networks connecting the FA site to these functional regions. The comparison between the wild-type spike and four variants (Alpha, Delta, Delta plus, and Omicron BA.1) shows that the variants differ significantly in their responses to LA removal. The allosteric connections to the FA site on Alpha are generally similar to those on the wild-type protein, with the exception of the RBM and the S71-R78 region, which show a weaker link to the FA site. In contrast, Omicron is the most different variant, exhibiting significant differences in the RBM, NTD, V622-L629, and furin cleavage site. These differences in the allosteric modulation may be of functional relevance, potentially affecting transmissibility and virulence. Experimental comparison of the effects of LA on SARS-CoV-2 variants, including emerging variants, is warranted.
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Affiliation(s)
- A Sofia F Oliveira
- School of Chemistry, Centre for Computational Chemistry, University of Bristol, Bristol BS8 1TS, UK
- School of Chemistry, University of Bristol, Bristol BS8 1TS, UK
- School of Biochemistry, University of Bristol, Bristol BS8 1TD, UK
| | | | - Andrew D Davidson
- School of Cellular and Molecular Medicine, University of Bristol, University Walk, Bristol BS8 1TD, UK
| | - Imre Berger
- School of Chemistry, University of Bristol, Bristol BS8 1TS, UK
- School of Biochemistry, University of Bristol, Bristol BS8 1TD, UK
- School of Chemistry, Max Planck Bristol Centre for Minimal Biology, Bristol BS8 1TS, UK
| | | | - Adrian J Mulholland
- School of Chemistry, Centre for Computational Chemistry, University of Bristol, Bristol BS8 1TS, UK
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7
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Chan HT, Oliveira ASF, Schofield CJ, Mulholland AJ, Duarte F. Dynamical Nonequilibrium Molecular Dynamics Simulations Identify Allosteric Sites and Positions Associated with Drug Resistance in the SARS-CoV-2 Main Protease. JACS AU 2023; 3:1767-1774. [PMID: 37384148 PMCID: PMC10262681 DOI: 10.1021/jacsau.3c00185] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/19/2023] [Accepted: 05/19/2023] [Indexed: 06/30/2023]
Abstract
The SARS-CoV-2 main protease (Mpro) plays an essential role in the coronavirus lifecycle by catalyzing hydrolysis of the viral polyproteins at specific sites. Mpro is the target of drugs, such as nirmatrelvir, though resistant mutants have emerged that threaten drug efficacy. Despite its importance, questions remain on the mechanism of how Mpro binds its substrates. Here, we apply dynamical nonequilibrium molecular dynamics (D-NEMD) simulations to evaluate structural and dynamical responses of Mpro to the presence and absence of a substrate. The results highlight communication between the Mpro dimer subunits and identify networks, including some far from the active site, that link the active site with a known allosteric inhibition site, or which are associated with nirmatrelvir resistance. They imply that some mutations enable resistance by altering the allosteric behavior of Mpro. More generally, the results show the utility of the D-NEMD technique for identifying functionally relevant allosteric sites and networks including those relevant to resistance.
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Affiliation(s)
- H. T.
Henry Chan
- Chemistry
Research Laboratory, Department of Chemistry and the Ineos Oxford
Institute for Antimicrobial Research, University
of Oxford, 12 Mansfield Road, Oxford OX1 3TA, UK
| | - A. Sofia F. Oliveira
- Centre
for Computational Chemistry, School of Chemistry, University of Bristol, Cantock’s Close, Bristol BS8 1TS, UK
- School
of Biochemistry, University of Bristol, Bristol BS8 1TD, UK
| | - Christopher J. Schofield
- Chemistry
Research Laboratory, Department of Chemistry and the Ineos Oxford
Institute for Antimicrobial Research, University
of Oxford, 12 Mansfield Road, Oxford OX1 3TA, UK
| | - Adrian J. Mulholland
- Centre
for Computational Chemistry, School of Chemistry, University of Bristol, Cantock’s Close, Bristol BS8 1TS, UK
| | - Fernanda Duarte
- Chemistry
Research Laboratory, Department of Chemistry and the Ineos Oxford
Institute for Antimicrobial Research, University
of Oxford, 12 Mansfield Road, Oxford OX1 3TA, UK
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8
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Agajanian S, Alshahrani M, Bai F, Tao P, Verkhivker GM. Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches. J Chem Inf Model 2023; 63:1413-1428. [PMID: 36827465 PMCID: PMC11162550 DOI: 10.1021/acs.jcim.2c01634] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
Abstract
Allosteric mechanisms are commonly employed regulatory tools used by proteins to orchestrate complex biochemical processes and control communications in cells. The quantitative understanding and characterization of allosteric molecular events are among major challenges in modern biology and require integration of innovative computational experimental approaches to obtain atomistic-level knowledge of the allosteric states, interactions, and dynamic conformational landscapes. The growing body of computational and experimental studies empowered by emerging artificial intelligence (AI) technologies has opened up new paradigms for exploring and learning the universe of protein allostery from first principles. In this review we analyze recent developments in high-throughput deep mutational scanning of allosteric protein functions; applications and latest adaptations of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems. We also highlight recent computational and experimental studies of the SARS-CoV-2 spike (S) proteins revealing an important and often hidden role of allosteric regulation driving functional conformational changes, binding interactions with the host receptor, and mutational escape mechanisms of S proteins which are critical for viral infection. We conclude with a summary and outlook of future directions suggesting that AI-augmented biophysical and computer simulation approaches are beginning to transform studies of protein allostery toward systematic characterization of allosteric landscapes, hidden allosteric states, and mechanisms which may bring about a new revolution in molecular biology and drug discovery.
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Affiliation(s)
- Steve Agajanian
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
| | - Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
| | - Fang Bai
- Shanghai Institute for Advanced Immunochemical Studies, School of Life Science and Technology and Information Science and Technology, Shanghai Tech University, 393 Middle Huaxia Road, Shanghai 201210, China
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas 75205, United States
| | - Gennady M Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California 92618, United States
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9
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Dommer A, Casalino L, Kearns F, Rosenfeld M, Wauer N, Ahn SH, Russo J, Oliveira S, Morris C, Bogetti A, Trifan A, Brace A, Sztain T, Clyde A, Ma H, Chennubhotla C, Lee H, Turilli M, Khalid S, Tamayo-Mendoza T, Welborn M, Christensen A, Smith DG, Qiao Z, Sirumalla SK, O'Connor M, Manby F, Anandkumar A, Hardy D, Phillips J, Stern A, Romero J, Clark D, Dorrell M, Maiden T, Huang L, McCalpin J, Woods C, Gray A, Williams M, Barker B, Rajapaksha H, Pitts R, Gibbs T, Stone J, Zuckerman DM, Mulholland AJ, Miller T, Jha S, Ramanathan A, Chong L, Amaro RE. #COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. THE INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2023; 37:28-44. [PMID: 36647365 PMCID: PMC9527558 DOI: 10.1177/10943420221128233] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus obscure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.
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Affiliation(s)
| | | | | | | | | | | | - John Russo
- Oregon Health & Science University, Portland, OR, USA
| | | | | | | | - Anda Trifan
- Argonne National Laboratory, Lemont, IL, USA
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Alexander Brace
- Argonne National Laboratory, Lemont, IL, USA
- University of Chicago, Chicago, IL, USA
| | - Terra Sztain
- UC San Diego, La Jolla, CA, USA
- Freie Universitat Berlin
| | - Austin Clyde
- Argonne National Laboratory, Lemont, IL, USA
- University of Chicago, Chicago, IL, USA
| | - Heng Ma
- Argonne National Laboratory, Lemont, IL, USA
| | | | - Hyungro Lee
- Brookhaven National Lab and Rutgers University
| | | | | | | | | | | | | | - Zhuoran Qiao
- California Institute of Technology, Pasadena, CA, USA
| | | | | | | | - Anima Anandkumar
- California Institute of Technology, Pasadena, CA, USA
- NVIDIA Corp, Santa Clara, CA, USA
| | - David Hardy
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - James Phillips
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | | | | | - Tom Maiden
- Pittsburgh Supercomputing Center, Pittsburgh, PA, USA
| | - Lei Huang
- Texas Advanced Computing Center, Austin, TX, USA
| | | | | | | | | | | | | | | | | | - John Stone
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
- NVIDIA Corp, Santa Clara, CA, USA
| | | | | | - Thomas Miller
- Entos, Inc., San Diego, CA, USA
- California Institute of Technology, Pasadena, CA, USA
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10
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Liu H, Zhou Y, Song Y, Zhang Q, Kan Y, Tang X, Xiao Q, Xiang Q, Liu H, Luo Y, Bao R. Structural and Dynamics Studies of the Spcas9 Variant Provide Insights into the Regulatory Role of the REC1 Domain. ACS Catal 2022. [DOI: 10.1021/acscatal.2c01804] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Huayi Liu
- Frontiers Science Center of Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
| | - Yi Zhou
- Center of Infectious Diseases, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yingjie Song
- Center of Infectious Diseases, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Qianqian Zhang
- School of Pharmacy, Lanzhou University, Lanzhou 730000, China
| | - Yeyi Kan
- Center of Infectious Diseases, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Xinyue Tang
- Center of Infectious Diseases, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Qingjie Xiao
- National Facility for Protein Science in Shanghai, Shanghai Advanced Research Institute (Zhangjiang Laboratory), Chinese Academy of Sciences, Shanghai 200135, China
| | - Qianyin Xiang
- Center of Infectious Diseases, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Huanxiang Liu
- Faculty of Applied Science, Macao Polytechnic University, Macao, SAR 999078, China
| | - Yunzi Luo
- Center of Infectious Diseases, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
- Frontiers Science Center of Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
| | - Rui Bao
- Center of Infectious Diseases, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
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11
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Structural insights in cell-type specific evolution of intra-host diversity by SARS-CoV-2. Nat Commun 2022; 13:222. [PMID: 35017512 PMCID: PMC8752678 DOI: 10.1038/s41467-021-27881-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 12/16/2021] [Indexed: 11/08/2022] Open
Abstract
As the global burden of SARS-CoV-2 infections escalates, so does the evolution of viral variants with increased transmissibility and pathology. In addition to this entrenched diversity, RNA viruses can also display genetic diversity within single infected hosts with co-existing viral variants evolving differently in distinct cell types. The BriSΔ variant, originally identified as a viral subpopulation from SARS-CoV-2 isolate hCoV-19/England/02/2020, comprises in the spike an eight amino-acid deletion encompassing a furin recognition motif and S1/S2 cleavage site. We elucidate the structure, function and molecular dynamics of this spike providing mechanistic insight into how the deletion correlates to viral cell tropism, ACE2 receptor binding and infectivity of this SARS-CoV-2 variant. Our results reveal long-range allosteric communication between functional domains that differ in the wild-type and the deletion variant and support a view of SARS-CoV-2 probing multiple evolutionary trajectories in distinct cell types within the same infected host.
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12
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Sofia F. Oliveira A, Shoemark DK, Avila Ibarra A, Davidson AD, Berger I, Schaffitzel C, Mulholland AJ. The fatty acid site is coupled to functional motifs in the SARS-CoV-2 spike protein and modulates spike allosteric behaviour. Comput Struct Biotechnol J 2021; 20:139-147. [PMID: 34934478 PMCID: PMC8670790 DOI: 10.1016/j.csbj.2021.12.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 12/08/2021] [Accepted: 12/08/2021] [Indexed: 12/12/2022] Open
Abstract
The SARS-CoV-2 spike protein is the first contact point between the SARS-CoV-2 virus and host cells and mediates membrane fusion. Recently, a fatty acid binding site was identified in the spike (Toelzer et al. Science 2020). The presence of linoleic acid at this site modulates binding of the spike to the human ACE2 receptor, stabilizing a locked conformation of the protein. Here, dynamical-nonequilibrium molecular dynamics simulations reveal that this fatty acid site is coupled to functionally relevant regions of the spike, some of them far from the fatty acid binding pocket. Removal of a ligand from the fatty acid binding site significantly affects the dynamics of distant, functionally important regions of the spike, including the receptor-binding motif, furin cleavage site and fusion-peptide-adjacent regions. Simulations of the D614G mutant show differences in behaviour between these clinical variants of the spike: the D614G mutant shows a significantly different conformational response for some structural motifs relevant for binding and fusion. The simulations identify structural networks through which changes at the fatty acid binding site are transmitted within the protein. These communication networks significantly involve positions that are prone to mutation, indicating that observed genetic variation in the spike may alter its response to linoleate binding and associated allosteric communication.
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Key Words
- ACE2, angiotensin-converting 2 enzyme
- CD, connector domain
- CH, central helix
- FA, fatty acid
- FP, fusion peptide
- FPPR, fusion-peptide proximal region
- HR1, heptad repeat 1
- LA, Linoleic acid
- MD, Molecular dynamics
- MERS, middle east respiratory syndrome
- NTD, N-terminal domain
- RBD, receptor binding domain
- RBM, receptor-binding motif
- RMB, receptor binding motif
- SARS, severe acute respiratory syndrome
- SARS-CoV-2, severe acute respiratory syndrome 2
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Affiliation(s)
- A. Sofia F. Oliveira
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, UK
- BrisSynBio, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, UK
| | - Deborah K. Shoemark
- BrisSynBio, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, UK
- School of Biochemistry, University of Bristol, Bristol BS8 1TD, UK
| | - Amaurys Avila Ibarra
- Research Software Engineering, Advanced Computing Research Centre, University of Bristol, Bristol BS1 5QD, UK
| | - Andrew D. Davidson
- School of Cellular and Molecular Medicine, University of Bristol, University Walk, Bristol BS8 1TD, UK
| | - Imre Berger
- BrisSynBio, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, UK
- School of Biochemistry, University of Bristol, Bristol BS8 1TD, UK
- Max Planck Bristol Centre for Minimal Biology, Cantock's Close, Bristol BS8 1TS, UK
| | - Christiane Schaffitzel
- BrisSynBio, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, UK
- School of Biochemistry, University of Bristol, Bristol BS8 1TD, UK
| | - Adrian J. Mulholland
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, UK
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13
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Dommer A, Casalino L, Kearns F, Rosenfeld M, Wauer N, Ahn SH, Russo J, Oliveira S, Morris C, Bogetti A, Trifan A, Brace A, Sztain T, Clyde A, Ma H, Chennubhotla C, Lee H, Turilli M, Khalid S, Tamayo-Mendoza T, Welborn M, Christensen A, Smith DGA, Qiao Z, Sirumalla SK, O'Connor M, Manby F, Anandkumar A, Hardy D, Phillips J, Stern A, Romero J, Clark D, Dorrell M, Maiden T, Huang L, McCalpin J, Woods C, Gray A, Williams M, Barker B, Rajapaksha H, Pitts R, Gibbs T, Stone J, Zuckerman D, Mulholland A, Miller T, Jha S, Ramanathan A, Chong L, Amaro R. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.11.12.468428. [PMID: 34816263 PMCID: PMC8609898 DOI: 10.1101/2021.11.12.468428] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus ob-scure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized. ACM REFERENCE FORMAT Abigail Dommer 1† , Lorenzo Casalino 1† , Fiona Kearns 1† , Mia Rosenfeld 1 , Nicholas Wauer 1 , Surl-Hee Ahn 1 , John Russo, 2 Sofia Oliveira 3 , Clare Morris 1 , AnthonyBogetti 4 , AndaTrifan 5,6 , Alexander Brace 5,7 , TerraSztain 1,8 , Austin Clyde 5,7 , Heng Ma 5 , Chakra Chennubhotla 4 , Hyungro Lee 9 , Matteo Turilli 9 , Syma Khalid 10 , Teresa Tamayo-Mendoza 11 , Matthew Welborn 11 , Anders Christensen 11 , Daniel G. A. Smith 11 , Zhuoran Qiao 12 , Sai Krishna Sirumalla 11 , Michael O'Connor 11 , Frederick Manby 11 , Anima Anandkumar 12,13 , David Hardy 6 , James Phillips 6 , Abraham Stern 13 , Josh Romero 13 , David Clark 13 , Mitchell Dorrell 14 , Tom Maiden 14 , Lei Huang 15 , John McCalpin 15 , Christo- pherWoods 3 , Alan Gray 13 , MattWilliams 3 , Bryan Barker 16 , HarindaRajapaksha 16 , Richard Pitts 16 , Tom Gibbs 13 , John Stone 6 , Daniel Zuckerman 2 *, Adrian Mulholland 3 *, Thomas MillerIII 11,12 *, ShantenuJha 9 *, Arvind Ramanathan 5 *, Lillian Chong 4 *, Rommie Amaro 1 *. 2021. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In Supercomputing '21: International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis . ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Anda Trifan
- Argonne National Laboratory
- University of Illinois at Urbana-Champaign
| | | | | | - Austin Clyde
- Argonne National Laboratory
- University of Chicago
| | | | | | - Hyungro Lee
- Brookhaven National Lab & Rutgers University
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - John Stone
- University of Illinois at Urbana-Champaign
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