1
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Burns D, Venditti V, Potoyan DA. Illuminating Protein Allostery by Chemically Accurate Contact Response Analysis (ChACRA). J Chem Theory Comput 2024. [PMID: 39038177 DOI: 10.1021/acs.jctc.4c00414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
Decoding allostery at the atomic level is essential for understanding the relationship between a protein's sequence, structure, and dynamics. Recently, we have shown that decomposing temperature responses of inter-residue contacts can reveal allosteric couplings and provide useful insight into the functional dynamics of proteins. The details of this Chemically Accurate Contact Response Analysis (ChACRA) are presented here along with its application to two well-known allosteric proteins. The first protein, IGPS, is a model of ensemble allostery that lacks clear structural differences between the active and inactive states. We show that the application of ChACRA reveals the experimentally identified allosteric coupling between effector and active sites of IGPS. The second protein, ATCase, is a classic example of allostery with distinct active and inactive structural states. Using ChACRA, we directly identify the most significant residue level interactions underlying the enzyme's cooperative behavior. Both test cases demonstrate the utility of ChACRA's unsupervised machine learning approach for dissecting allostery at the residue level.
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Affiliation(s)
- Daniel Burns
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
| | - Vincenzo Venditti
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
| | - Davit A Potoyan
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
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2
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Evoli S, Kariyawasam NL, Nitiss KC, Nitiss JL, Wereszczynski J. Modeling allosteric mechanisms of eukaryotic type II topoisomerases. Biophys J 2024; 123:1620-1634. [PMID: 38720465 PMCID: PMC11213992 DOI: 10.1016/j.bpj.2024.05.004] [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: 08/10/2023] [Revised: 03/24/2024] [Accepted: 05/03/2024] [Indexed: 05/21/2024] Open
Abstract
Type II topoisomerases (TopoIIs) are ubiquitous enzymes that are involved in crucial nuclear processes such as genome organization, chromosome segregation, and other DNA metabolic processes. These enzymes function as large, homodimeric complexes that undergo a complex cycle of binding and hydrolysis of two ATP molecules in their ATPase domains, which regulates the capture and passage of one DNA double-helix through a second, cleaved DNA molecule. This process requires the transmission of information about the state of the bound nucleotide over vast ranges in the TopoII complex. How this information is transmitted at the molecular level to regulate TopoII functions and how protein substitutions disrupt these mechanisms remains largely unknown. Here, we employed extensive microsecond-scale molecular dynamics simulations of the yeast TopoII enzyme in multiple nucleotide-bound states and with amino acid substitutions near both the N and C termini of the complex. Simulation results indicate that the ATPase domains are remarkably flexible on the sub-microsecond timescale and that these dynamics are modulated by the identity of the bound nucleotides and both local and distant amino acid substitutions. Network analyses point toward specific allosteric networks that transmit information about the hydrolysis cycle throughout the complex, which include residues in both the protein and the bound DNA molecule. Amino acid substitutions weaken many of these pathways. Together, our results provide molecular level details on how the TopoII catalytic cycle is controlled through nucleotide binding and hydrolysis and how mutations may disrupt this process.
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Affiliation(s)
- Stefania Evoli
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois; Center for Molecular Study of Condensed Soft Matter, Illinois Institute of Technology, Chicago, Illinois
| | - Nilusha L Kariyawasam
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois; Center for Molecular Study of Condensed Soft Matter, Illinois Institute of Technology, Chicago, Illinois
| | - Karin C Nitiss
- Pharmaceutical Sciences Department, University of Illinois at Chicago, Rockford, Illinois
| | - John L Nitiss
- Pharmaceutical Sciences Department, University of Illinois at Chicago, Rockford, Illinois
| | - Jeff Wereszczynski
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois; Center for Molecular Study of Condensed Soft Matter, Illinois Institute of Technology, Chicago, Illinois; Department of Biology, Illinois Institute of Technology, Chicago, Illinois.
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3
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Amisaki T. Multilevel superposition for deciphering the conformational variability of protein ensembles. Brief Bioinform 2024; 25:bbae137. [PMID: 38557679 PMCID: PMC10983786 DOI: 10.1093/bib/bbae137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 02/14/2024] [Accepted: 03/10/2024] [Indexed: 04/04/2024] Open
Abstract
The dynamics and variability of protein conformations are directly linked to their functions. Many comparative studies of X-ray protein structures have been conducted to elucidate the relevant conformational changes, dynamics and heterogeneity. The rapid increase in the number of experimentally determined structures has made comparison an effective tool for investigating protein structures. For example, it is now possible to compare structural ensembles formed by enzyme species, variants or the type of ligands bound to them. In this study, the author developed a multilevel model for estimating two covariance matrices that represent inter- and intra-ensemble variability in the Cartesian coordinate space. Principal component analysis using the two estimated covariance matrices identified the inter-/intra-enzyme variabilities, which seemed to be important for the enzyme functions, with the illustrative examples of cytochrome P450 family 2 enzymes and class A $\beta$-lactamases. In P450, in which each enzyme has its own active site of a distinct size, an active-site motion shared universally between the enzymes was captured as the first principal mode of the intra-enzyme covariance matrix. In this case, the method was useful for understanding the conformational variability after adjusting for the differences between enzyme sizes. The developed method is advantageous in small ensemble-size problems and hence promising for use in comparative studies on experimentally determined structures where ensemble sizes are smaller than those generated, for example, by molecular dynamics simulations.
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Affiliation(s)
- Takashi Amisaki
- Department of Biological Regulation, Faculty of Medicine, Tottori University, Yonago, Tottori 683-8503, Japan
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4
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Evoli S, Kariyawasam NL, Nitiss KC, Nitiss JL, Wereszczynski J. Modeling Allosteric Mechanisms of Eukaryotic Type II Topoisomerases. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.02.551689. [PMID: 37577673 PMCID: PMC10418245 DOI: 10.1101/2023.08.02.551689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Type II topoisomerases (TopoIIs) are ubiquitous enzymes that are involved in crucial nuclear processes such as genome organization, chromosome segregation, and other DNA metabolic processes. These enzymes function as large, homodimeric complexes that undergo a complex cycle of binding and hydrolysis of two ATP molecules in their ATPase domains, which regulates the capture and passage of one DNA double-helix through a second, cleaved DNA molecule. This process requires the transmission of information about the state of the bound nucleotide over vast ranges in the TopoII complex. How this information is transmitted at the molecular level to regulate TopoII functions and how protein substitutions disrupt these mechanisms remains largely unknown. Here, we employed extensive microsecond scale molecular dynamics simulations of the yeast TopoII enzyme in multiple nucleotide-bound states and with amino acid substitutions near both the N- and C-terminals of the complex. Simulation results indicate that the ATPase domains are remarkably flexible on the sub-microsecond timescale and that these dynamics are modulated by the identity of the bound nucleotides and both local and distant amino acid substitutions. Network analyses point towards specific allosteric networks that transmit information about the hydrolysis cycle throughout the complex, which include residues in both the protein and the bound DNA molecule. Amino acid substitutions weaken many of these pathways. Together, our results provide molecular-level details on how the TopoII catalytic cycle is controlled through nucleotide binding and hydrolysis and how mutations may disrupt this process.
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Affiliation(s)
- Stefania Evoli
- Department of Physics, Illinois Institute of Technology, Chicago, USA
- Center for Molecular Study of Condensed Soft Matter, Illinois Institute of Technology, Chicago, USA
- these authors contributed equally to this work
| | - Nilusha L. Kariyawasam
- Department of Physics, Illinois Institute of Technology, Chicago, USA
- Center for Molecular Study of Condensed Soft Matter, Illinois Institute of Technology, Chicago, USA
- these authors contributed equally to this work
| | - Karin C. Nitiss
- Pharmaceutical Sciences Department, University of Illinois at Chicago, Rockford, IL
| | - John L. Nitiss
- Pharmaceutical Sciences Department, University of Illinois at Chicago, Rockford, IL
| | - Jeff Wereszczynski
- Department of Physics, Illinois Institute of Technology, Chicago, USA
- Center for Molecular Study of Condensed Soft Matter, Illinois Institute of Technology, Chicago, USA
- Department of Biology, Illinois Institute of Technology, Chicago, USA
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5
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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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6
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Moosavi-Movahedi Z, Salehi N, Habibi-Rezaei M, Qassemi F, Karimi-Jafari MH. Intermediate-aided allostery mechanism for α-glucosidase by Xanthene-11v as an inhibitor using residue interaction network analysis. J Mol Graph Model 2023; 122:108495. [PMID: 37116337 DOI: 10.1016/j.jmgm.2023.108495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 04/04/2023] [Accepted: 04/12/2023] [Indexed: 04/30/2023]
Abstract
Exploring allosteric inhibition and the discovery of new inhibitor binding sites are important studies in protein regulation mechanisms and drug discovery. Structural and network-based analyses of trajectories resulting from molecular dynamics (MD) simulations have been developed to discover protein dynamics, landscape, functions, and allosteric regions. Here, an experimentally suggested non-competitive inhibitor, xanthene-11v, was considered to explore its allosteric inhibition mechanism in α-glucosidase MAL12. Comparative structural and network analyses were applied to eight 250 ns independent MD simulations, four of which were performed in the free state and four of which were performed in ligand-bound forms. Projected two-dimensional free energy landscapes (FEL) were constructed from the probabilistic distribution of conformations along the first two principal components. The post-simulation analyses of the coordinates, side-chain torsion angles, non-covalent interaction networks, network communities, and their centralities were performed on α-glucosidase conformations and the intermediate sub-states. Important communities of residues have been found that connect the allosteric site to the active site. Some of these residues like Thr307, Arg312, TYR344, ILE345, Phe357, Asp406, Val407, Asp408, and Leu436 are the key messengers in the transition pathway between allosteric and active sites. Evaluating the probability distribution of distances between gate residues including Val407 in one community and Phe158, and Pro65 in another community depicted the closure of this gate due to the inhibitor binding. Six macro states of protein were deduced from the topology of FEL and analysis of conformational preference of free and ligand-bound systems to these macro states shows a combination of lock-and-key, conformational selection, and induced fit mechanisms are effective in ligand binding. All these results reveal structural states, allosteric mechanisms, and key players in the inhibition pathway of α-glucosidase by xanthene-11v.
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Affiliation(s)
- Zahra Moosavi-Movahedi
- Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Najmeh Salehi
- School of Biological Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | | | | | - Mohammad Hossein Karimi-Jafari
- Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran; School of Biological Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
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7
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Ouedraogo D, Souffrant M, Yao XQ, Hamelberg D, Gadda G. Non-active Site Residue in Loop L4 Alters Substrate Capture and Product Release in d-Arginine Dehydrogenase. Biochemistry 2023; 62:1070-1081. [PMID: 36795942 PMCID: PMC9996824 DOI: 10.1021/acs.biochem.2c00697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
Numerous studies demonstrate that enzymes undergo multiple conformational changes during catalysis. The malleability of enzymes forms the basis for allosteric regulation: residues located far from the active site can exert long-range dynamical effects on the active site residues to modulate catalysis. The structure of Pseudomonas aeruginosa d-arginine dehydrogenase (PaDADH) shows four loops (L1, L2, L3, and L4) that span the substrate and the FAD-binding domains. Loop L4 comprises residues 329-336, spanning over the flavin cofactor. The I335 residue on loop L4 is ∼10 Å away from the active site and ∼3.8 Å from N(1)-C(2)═O atoms of the flavin. In this study, we used molecular dynamics and biochemical techniques to investigate the effect of the mutation of I335 to histidine on the catalytic function of PaDADH. Molecular dynamics showed that the conformational dynamics of PaDADH are shifted to a more closed conformation in the I335H variant. In agreement with an enzyme that samples more in a closed conformation, the kinetic data of the I335H variant showed a 40-fold decrease in the rate constant of substrate association (k1), a 340-fold reduction in the rate constant of substrate dissociation from the enzyme-substrate complex (k2), and a 24-fold decrease in the rate constant of product release (k5), compared to that of the wild-type. Surprisingly, the kinetic data are consistent with the mutation having a negligible effect on the reactivity of the flavin. Altogether, the data indicate that the residue at position 335 has a long-range dynamical effect on the catalytic function in PaDADH.
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Affiliation(s)
- Daniel Ouedraogo
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302, United States
| | - Michael Souffrant
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302, United States
| | - Xin-Qiu Yao
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302, United States
| | - Donald Hamelberg
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302, United States.,Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30302, United States.,Center for Biotechnology and Drug Design, Georgia State University, Atlanta, Georgia 30302, United States
| | - Giovanni Gadda
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302, United States.,Department of Biology, Georgia State University, Atlanta, Georgia 30302, United States.,Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30302, United States.,Center for Biotechnology and Drug Design, Georgia State University, Atlanta, Georgia 30302, United States
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8
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Cao Y, Qiao Y, Cui S, Ge J. Origin of Metal Cluster Tuning Enzyme Activity at the Bio-Nano Interface. JACS AU 2022; 2:961-971. [PMID: 35557767 PMCID: PMC9088776 DOI: 10.1021/jacsau.2c00077] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 03/29/2022] [Accepted: 03/30/2022] [Indexed: 06/15/2023]
Abstract
Detailed understanding of how the bio-nano interface orchestrates the function of both biological components and nanomaterials remains ambiguous. Here, through a combination of experiments and molecular dynamics simulations, we investigated how the interface between Candida Antarctic lipase B and palladium (Pd) nanoparticles (NPs) tunes the structure, dynamics, and catalysis of the enzyme. Our simulations show that the metal binding to protein is a shape matching behavior and there is a transition from saturated binding to unsaturated binding along with the increase in the size of metal NPs. When we engineered the interface with the polymer, not only did the critical size of saturated binding of metal NPs become larger, but also the disturbance of the metal NPs to the enzyme function was reduced. In addition, we found that an enzyme-metal interface engineered with the polymer can boost bio-metal cascade reactions via substrate channeling. Understanding and control of the bio-nano interface at the molecular level enable us to rationally design bio-nanocomposites with prospective properties.
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Affiliation(s)
- Yufei Cao
- Key
Lab for Industrial Biocatalysis, Ministry of Education, Department
of Chemical Engineering, Tsinghua University, Beijing 100084, China
| | - Yida Qiao
- Key
Lab for Industrial Biocatalysis, Ministry of Education, Department
of Chemical Engineering, Tsinghua University, Beijing 100084, China
| | - Shitong Cui
- Key
Lab for Industrial Biocatalysis, Ministry of Education, Department
of Chemical Engineering, Tsinghua University, Beijing 100084, China
| | - Jun Ge
- Key
Lab for Industrial Biocatalysis, Ministry of Education, Department
of Chemical Engineering, Tsinghua University, Beijing 100084, China
- Institute
of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China
- Institute
of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen 518107, China
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9
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Yao XQ, Hamelberg D. From Distinct to Differential Conformational Dynamics to Map Allosteric Communication Pathways in Proteins. J Phys Chem B 2022; 126:2612-2620. [PMID: 35319195 DOI: 10.1021/acs.jpcb.2c00199] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Initiation of biological processes involving protein-ligand binding, transient protein-protein interactions, or amino acid modifications alters the conformational dynamics of proteins. Accompanying these biological processes are ensuing coupled atomic level conformational changes within the proteins. These conformational changes collectively connect multiple amino acid residues at distal allosteric, binding, and/or active sites. Local changes due to, for example, binding of a regulatory ligand at an allosteric site initiate the allosteric regulation. The allosteric signal propagates throughout the protein structure, causing changes at distal sites, activating, deactivating, or modifying the function of the protein. Hence, dynamical responses within protein structures to stimuli contain critical information on protein function. In this Perspective, we examine the description of allosteric regulation from protein dynamical responses and associated alternative and emerging computational approaches to map allosteric communication pathways between distal sites in proteins at the atomic level.
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Affiliation(s)
- Xin-Qiu Yao
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
| | - Donald Hamelberg
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
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10
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Yao XQ, Hamelberg D. Residue–Residue Contact Changes during Functional Processes Define Allosteric Communication Pathways. J Chem Theory Comput 2022; 18:1173-1187. [DOI: 10.1021/acs.jctc.1c00669] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Xin-Qiu Yao
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
| | - Donald Hamelberg
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
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11
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Sladek V, Yamamoto Y, Harada R, Shoji M, Shigeta Y, Sladek V. pyProGA-A PyMOL plugin for protein residue network analysis. PLoS One 2021; 16:e0255167. [PMID: 34329304 PMCID: PMC8323899 DOI: 10.1371/journal.pone.0255167] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 07/11/2021] [Indexed: 11/18/2022] Open
Abstract
The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software which collects an ensemble of (network) methods tailored towards the analysis of protein-protein interactions (PPI) and/or interactions of proteins with ligands of other type, e.g. nucleic acids, oligosaccharides etc. In parallel, we propose the use of the network differential analysis as a method to identify residues mediating key interactions between proteins. We use a model system, to show that in combination with other, already published methods, also included in pyProGA, it can be used to make such predictions. Such extended repertoire of methods allows to cross-check predictions with other methods as well, as we show here. In addition, the possibility to construct PRN models from various kinds of input is so far a unique asset of our code. One can use structural data as defined in PDB files and/or from data on residue pair interaction energies, either from force-field parameters or fragment molecular orbital (FMO) calculations. pyProGA is a free open-source software available from https://gitlab.com/Vlado_S/pyproga.
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Affiliation(s)
- Vladimir Sladek
- Institute of Chemistry, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Yuta Yamamoto
- Department of Chemistry, Rikkyo University, Nishi-Ikebukuro, Tokyo, Japan
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Mitsuo Shoji
- Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Vladimir Sladek
- Institute of Construction and Architecture, Slovak Academy of Sciences, Bratislava, Slovakia
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12
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Chatzigoulas A, Cournia Z. Rational design of allosteric modulators: Challenges and successes. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1529] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Alexios Chatzigoulas
- Biomedical Research Foundation Academy of Athens Athens Greece
- Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens Greece
| | - Zoe Cournia
- Biomedical Research Foundation Academy of Athens Athens Greece
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13
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Nierzwicki Ł, Arantes PR, Saha A, Palermo G. Establishing the allosteric mechanism in CRISPR-Cas9. WILEY INTERDISCIPLINARY REVIEWS. COMPUTATIONAL MOLECULAR SCIENCE 2021; 11:e1503. [PMID: 34322166 PMCID: PMC8315640 DOI: 10.1002/wcms.1503] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 08/26/2020] [Indexed: 12/18/2022]
Abstract
Allostery is a fundamental property of proteins, which regulates biochemical information transfer between spatially distant sites. Here, we report on the critical role of molecular dynamics (MD) simulations in discovering the mechanism of allosteric communication within CRISPR-Cas9, a leading genome editing machinery with enormous promises for medicine and biotechnology. MD revealed how allostery intervenes during at least three steps of the CRISPR-Cas9 function: affecting DNA recognition, mediating the cleavage and interfering with the off-target activity. An allosteric communication that activates concerted DNA cleavages was found to led through the L1/L2 loops, which connect the HNH and RuvC catalytic domains. The identification of these "allosteric transducers" inspired the development of novel variants of the Cas9 protein with improved specificity, opening a new avenue for controlling the CRISPR-Cas9 activity. Discussed studies also highlight the critical role of the recognition lobe in the conformational activation of the catalytic HNH domain. Specifically, the REC3 region was found to modulate the dynamics of HNH by sensing the formation of the RNA:DNA hybrid. The role of REC3 was revealed to be particularly relevant in the presence of DNA mismatches. Indeed, interference of REC3 with the RNA:DNA hybrid containing mismatched pairs at specific positions resulted in locking HNH in an inactive "conformational checkpoint" conformation, thereby hampering off-target cleavages. Overall, MD simulations established the fundamental mechanisms underlying the allosterism of CRISPR-Cas9, aiding engineering strategies to develop new CRISPR-Cas9 variants for improved genome editing.
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Affiliation(s)
- Łukasz Nierzwicki
- Department of Bioengineering, University of California Riverside, Riverside, California
| | - Pablo Ricardo Arantes
- Department of Bioengineering, University of California Riverside, Riverside, California
| | - Aakash Saha
- Department of Bioengineering, University of California Riverside, Riverside, California
| | - Giulia Palermo
- Department of Bioengineering and Department of Chemistry, University of California Riverside, Riverside, California
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14
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Ferraro M, Moroni E, Ippoliti E, Rinaldi S, Sanchez-Martin C, Rasola A, Pavarino LF, Colombo G. Machine Learning of Allosteric Effects: The Analysis of Ligand-Induced Dynamics to Predict Functional Effects in TRAP1. J Phys Chem B 2020; 125:101-114. [PMID: 33369425 PMCID: PMC8016192 DOI: 10.1021/acs.jpcb.0c09742] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
![]()
Allosteric
molecules provide a powerful means to modulate protein
function. However, the effect of such ligands on distal orthosteric
sites cannot be easily described by classical docking methods. Here,
we applied machine learning (ML) approaches to expose the links between
local dynamic patterns and different degrees of allosteric inhibition
of the ATPase function in the molecular chaperone TRAP1. We focused
on 11 novel allosteric modulators with similar affinities to the target
but with inhibitory efficacy between the 26.3 and 76%. Using a set
of experimentally related local descriptors, ML enabled us to connect
the molecular dynamics (MD) accessible to ligand-bound (perturbed)
and unbound (unperturbed) systems to the degree of ATPase allosteric
inhibition. The ML analysis of the comparative perturbed ensembles
revealed a redistribution of dynamic states in the inhibitor-bound
versus inhibitor-free systems following allosteric binding. Linear
regression models were built to quantify the percentage of experimental
variance explained by the predicted inhibitor-bound TRAP1 states.
Our strategy provides a comparative MD–ML framework to infer
allosteric ligand functionality. Alleviating the time scale issues
which prevent the routine use of MD, a combination of MD and ML represents
a promising strategy to support in silico mechanistic
studies and drug design.
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Affiliation(s)
- Mariarosaria Ferraro
- Istituto di Scienze e Tecnologie Chimiche "Giulio Natta"- SCITEC, Via Mario Bianco 9, 20131 Milano, Italy
| | - Elisabetta Moroni
- Istituto di Scienze e Tecnologie Chimiche "Giulio Natta"- SCITEC, Via Mario Bianco 9, 20131 Milano, Italy
| | - Emiliano Ippoliti
- Institute for Advanced Simulation (IAS-5) and Institute of Neuroscience and Medicine (INM-9), Computational Biomedicine, Forschungszentrum Jülich, 52425 Jülich, Germany.,JARA-HPC, Forschungszentrum Jülich, D-54245 Jülich, Germany
| | - Silvia Rinaldi
- Istituto di Scienze e Tecnologie Chimiche "Giulio Natta"- SCITEC, Via Mario Bianco 9, 20131 Milano, Italy
| | - Carlos Sanchez-Martin
- Dipartimento di Scienze Biomediche, Università di Padova, viale G. Colombo 3, 35131 Padova, Italy
| | - Andrea Rasola
- Dipartimento di Scienze Biomediche, Università di Padova, viale G. Colombo 3, 35131 Padova, Italy
| | - Luca F Pavarino
- Dipartimento di Matematica "F. Casorati", Università di Pavia, Via Ferrata 5, 27100 Pavia Italy
| | - Giorgio Colombo
- Istituto di Scienze e Tecnologie Chimiche "Giulio Natta"- SCITEC, Via Mario Bianco 9, 20131 Milano, Italy.,Dipartimento di Chimica, Università di Pavia, via Taramelli 12, 27100 Pavia, Italy
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15
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D'Amico RN, Murray AM, Boehr DD. Driving Protein Conformational Cycles in Physiology and Disease: "Frustrated" Amino Acid Interaction Networks Define Dynamic Energy Landscapes: Amino Acid Interaction Networks Change Progressively Along Alpha Tryptophan Synthase's Catalytic Cycle. Bioessays 2020; 42:e2000092. [PMID: 32720327 DOI: 10.1002/bies.202000092] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 06/09/2020] [Indexed: 12/22/2022]
Abstract
A general framework by which dynamic interactions within a protein will promote the necessary series of structural changes, or "conformational cycle," required for function is proposed. It is suggested that the free-energy landscape of a protein is biased toward this conformational cycle. Fluctuations into higher energy, although thermally accessible, conformations drive the conformational cycle forward. The amino acid interaction network is defined as those intraprotein interactions that contribute most to the free-energy landscape. Some network connections are consistent in every structural state, while others periodically change their interaction strength according to the conformational cycle. It is reviewed here that structural transitions change these periodic network connections, which then predisposes the protein toward the next set of network changes, and hence the next structural change. These concepts are illustrated by recent work on tryptophan synthase. Disruption of these dynamic connections may lead to aberrant protein function and disease states.
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Affiliation(s)
- Rebecca N D'Amico
- Department of Chemistry, The Pennsylvania State University, 107 Chemistry Building, University Park, PA, 16802, USA
| | - Alec M Murray
- Department of Chemistry, The Pennsylvania State University, 107 Chemistry Building, University Park, PA, 16802, USA
| | - David D Boehr
- Department of Chemistry, The Pennsylvania State University, 107 Chemistry Building, University Park, PA, 16802, USA
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16
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Souffrant MG, Yao XQ, Momin M, Hamelberg D. N-Glycosylation and Gaucher Disease Mutation Allosterically Alter Active-Site Dynamics of Acid-β-Glucosidase. ACS Catal 2020. [DOI: 10.1021/acscatal.9b04404] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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