1
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Kidder KM, Shell MS, Noid WG. Surveying the energy landscape of coarse-grained mappings. J Chem Phys 2024; 160:054105. [PMID: 38310476 DOI: 10.1063/5.0182524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/28/2023] [Indexed: 02/05/2024] Open
Abstract
Simulations of soft materials often adopt low-resolution coarse-grained (CG) models. However, the CG representation is not unique and its impact upon simulated properties is poorly understood. In this work, we investigate the space of CG representations for ubiquitin, which is a typical globular protein with 72 amino acids. We employ Monte Carlo methods to ergodically sample this space and to characterize its landscape. By adopting the Gaussian network model as an analytically tractable atomistic model for equilibrium fluctuations, we exactly assess the intrinsic quality of each CG representation without introducing any approximations in sampling configurations or in modeling interactions. We focus on two metrics, the spectral quality and the information content, that quantify the extent to which the CG representation preserves low-frequency, large-amplitude motions and configurational information, respectively. The spectral quality and information content are weakly correlated among high-resolution representations but become strongly anticorrelated among low-resolution representations. Representations with maximal spectral quality appear consistent with physical intuition, while low-resolution representations with maximal information content do not. Interestingly, quenching studies indicate that the energy landscape of mapping space is very smooth and highly connected. Moreover, our study suggests a critical resolution below which a "phase transition" qualitatively distinguishes good and bad representations.
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Affiliation(s)
- Katherine M Kidder
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - M Scott Shell
- Department of Chemical Engineering, University of California, Santa Barbara, California 93106, USA
| | - W G Noid
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
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2
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Iljina M, Mazal H, Dayananda A, Zhang Z, Stan G, Riven I, Haran G. Single-molecule FRET probes allosteric effects on protein-translocating pore loops of a AAA+ machine. Biophys J 2024; 123:374-388. [PMID: 38196191 PMCID: PMC10870172 DOI: 10.1016/j.bpj.2024.01.002] [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: 05/02/2023] [Revised: 11/07/2023] [Accepted: 01/02/2024] [Indexed: 01/11/2024] Open
Abstract
AAA+ proteins (ATPases associated with various cellular activities) comprise a family of powerful ring-shaped ATP-dependent translocases that carry out numerous vital substrate-remodeling functions. ClpB is a AAA+ protein disaggregation machine that forms a two-tiered hexameric ring, with flexible pore loops protruding into its center and binding to substrate proteins. It remains unknown whether these pore loops contribute only passively to substrate-protein threading or have a more active role. Recently, we have applied single-molecule FRET spectroscopy to directly measure the dynamics of substrate-binding pore loops in ClpB. We have reported that the three pore loops of ClpB (PL1-3) undergo large-scale fluctuations on the microsecond timescale that are likely to be mechanistically important for disaggregation. Here, using single-molecule FRET, we study the allosteric coupling between the pore loops and the two nucleotide-binding domains of ClpB (NBD1-2). By mutating the conserved Walker B motifs within the NBDs to abolish ATP hydrolysis, we demonstrate how the nucleotide state of each NBD tunes pore-loop dynamics. This effect is surprisingly long-ranged; in particular, PL2 and PL3 respond differentially to a Walker B mutation in either NBD1 or NBD2, as well as to mutations in both. We characterize the conformational dynamics of pore loops and the allosteric paths connecting NBDs to pore loops by molecular dynamics simulations and find that both principal motions and allosteric paths can be altered by changing the ATPase state of ClpB. Remarkably, PL3, which is highly conserved in AAA+ machines, is found to favor an upward conformation when only NBD1 undergoes ATP hydrolysis but a downward conformation when NBD2 is active. These results explicitly demonstrate a significant long-range allosteric effect of ATP hydrolysis sites on pore-loop dynamics. Pore loops are therefore established as active participants that undergo ATP-dependent conformational changes to translocate substrate proteins through the central pores of AAA+ machines.
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Affiliation(s)
- Marija Iljina
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
| | - Hisham Mazal
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
| | - Ashan Dayananda
- Department of Chemistry, University of Cincinnati, Cincinnati, Ohio
| | - Zhaocheng Zhang
- Department of Chemistry, University of Cincinnati, Cincinnati, Ohio
| | - George Stan
- Department of Chemistry, University of Cincinnati, Cincinnati, Ohio.
| | - Inbal Riven
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
| | - Gilad Haran
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel.
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3
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La Sala G, Pfleger C, Käck H, Wissler L, Nevin P, Böhm K, Janet JP, Schimpl M, Stubbs CJ, De Vivo M, Tyrchan C, Hogner A, Gohlke H, Frolov AI. Combining structural and coevolution information to unveil allosteric sites. Chem Sci 2023; 14:7057-7067. [PMID: 37389247 PMCID: PMC10306073 DOI: 10.1039/d2sc06272k] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 06/02/2023] [Indexed: 07/01/2023] Open
Abstract
Understanding allosteric regulation in biomolecules is of great interest to pharmaceutical research and computational methods emerged during the last decades to characterize allosteric coupling. However, the prediction of allosteric sites in a protein structure remains a challenging task. Here, we integrate local binding site information, coevolutionary information, and information on dynamic allostery into a structure-based three-parameter model to identify potentially hidden allosteric sites in ensembles of protein structures with orthosteric ligands. When tested on five allosteric proteins (LFA-1, p38-α, GR, MAT2A, and BCKDK), the model successfully ranked all known allosteric pockets in the top three positions. Finally, we identified a novel druggable site in MAT2A confirmed by X-ray crystallography and SPR and a hitherto unknown druggable allosteric site in BCKDK validated by biochemical and X-ray crystallography analyses. Our model can be applied in drug discovery to identify allosteric pockets.
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Affiliation(s)
- Giuseppina La Sala
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Christopher Pfleger
- Mathematisch-Naturwissenschaftliche Fakultät, Institut für Pharmazeutische und Medizinische Chemie, Heinrich-Heine-Universität Düsseldorf 40225 Düsseldorf Germany
| | - Helena Käck
- Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Lisa Wissler
- Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Philip Nevin
- Discovery Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Kerstin Böhm
- Discovery Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Jon Paul Janet
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Marianne Schimpl
- Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Cambridge UK
| | - Christopher J Stubbs
- Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Cambridge UK
| | - Marco De Vivo
- Laboratory of Molecular Modeling and Drug Design, Istituto Italiano di Tecnologia Via Morego 30 16163 Genoa Italy
| | - Christian Tyrchan
- Medicinal Chemistry, Research and Early Development, Respiratory & Immunology (R&I), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Anders Hogner
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Holger Gohlke
- Mathematisch-Naturwissenschaftliche Fakultät, Institut für Pharmazeutische und Medizinische Chemie, Heinrich-Heine-Universität Düsseldorf 40225 Düsseldorf Germany
- John von Neumann Institute for Computing (NIC), Jülich Supercomputing Centre (JSC), Institute of Biological Information Processing (IBI-7: Structural Biochemistry), Institute of Bio- and Geosciences (IBG-4: Bioinformatics) Forschungszentrum Jülich GmbH 52425 Jülich Germany
| | - Andrey I Frolov
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
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4
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Maschietto F, Morzan UN, Tofoleanu F, Gheeraert A, Chaudhuri A, Kyro GW, Nekrasov P, Brooks B, Loria JP, Rivalta I, Batista VS. Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase. Nat Commun 2023; 14:2239. [PMID: 37076500 PMCID: PMC10115891 DOI: 10.1038/s41467-023-37956-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 04/06/2023] [Indexed: 04/21/2023] Open
Abstract
Allosteric drugs have the potential to revolutionize biomedicine due to their enhanced selectivity and protection against overdosage. However, we need to better understand allosteric mechanisms in order to fully harness their potential in drug discovery. In this study, molecular dynamics simulations and nuclear magnetic resonance spectroscopy are used to investigate how increases in temperature affect allostery in imidazole glycerol phosphate synthase. Results demonstrate that temperature increase triggers a cascade of local amino acid-to-amino acid dynamics that remarkably resembles the allosteric activation that takes place upon effector binding. The differences in the allosteric response elicited by temperature increase as opposed to effector binding are conditional to the alterations of collective motions induced by either mode of activation. This work provides an atomistic picture of temperature-dependent allostery, which could be harnessed to more precisely control enzyme function.
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Affiliation(s)
- Federica Maschietto
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA.
| | - Uriel N Morzan
- International Center for Theoretical Physics, Strada Costiera 11, 34151, Trieste, Italy.
| | - Florentina Tofoleanu
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20852, USA
- Treeline Biosciences, 500 Arsenal Street, Watertown, MA, 02472, USA
| | - Aria Gheeraert
- ENSL, CNRS, Laboratoire de Chimie UMR 5182, 46 allée d'Italie, 69364, Lyon, France
- Dipartimento di Chimica Industriale "Toso Montanari", Alma Mater Studiorum, Università di Bologna, Bologna, Italy
| | - Apala Chaudhuri
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Gregory W Kyro
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA
| | - Peter Nekrasov
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA
| | - Bernard Brooks
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20852, USA
| | - J Patrick Loria
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA.
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA.
| | - Ivan Rivalta
- ENSL, CNRS, Laboratoire de Chimie UMR 5182, 46 allée d'Italie, 69364, Lyon, France.
- Dipartimento di Chimica Industriale "Toso Montanari", Alma Mater Studiorum, Università di Bologna, Bologna, Italy.
| | - Victor S Batista
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA.
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5
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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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6
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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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7
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Ni D, Liu Y, Kong R, Yu Z, Lu S, Zhang J. Computational elucidation of allosteric communication in proteins for allosteric drug design. Drug Discov Today 2022; 27:2226-2234. [DOI: 10.1016/j.drudis.2022.03.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 01/22/2022] [Accepted: 03/17/2022] [Indexed: 02/07/2023]
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8
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Celebi M, Inan T, Kurkcuoglu O, Akten ED. Potential allosteric sites captured in glycolytic enzymes via residue-based network models: Phosphofructokinase, glyceraldehyde-3-phosphate dehydrogenase and pyruvate kinase. Biophys Chem 2021; 280:106701. [PMID: 34736071 DOI: 10.1016/j.bpc.2021.106701] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 10/12/2021] [Accepted: 10/19/2021] [Indexed: 01/05/2023]
Abstract
Likelihood of new allosteric sites for glycolytic enzymes, phosphofructokinase (PFK), glyceraldehyde-3-phosphate dehydrogenase (GADPH) and pyruvate kinase (PK) was evaluated for bacterial, parasitic and human species. Allosteric effect of a ligand binding at a site was revealed on the basis of low-frequency normal modes via Cα-harmonic residue network model. In bacterial PFK, perturbation of the proposed allosteric site outperformed the known allosteric one, producing a high amount of stabilization or reduced dynamics, on all catalytic regions. Another proposed allosteric spot at the dimer interface in parasitic PFK exhibited major stabilization effect on catalytic regions. In parasitic GADPH, the most desired allosteric response was observed upon perturbation of its tunnel region which incorporated key residues for functional regulation. Proposed allosteric site in bacterial PK produced a satisfactory allosteric response on all catalytic regions, whereas in human and parasitic PKs, a partial inhibition was observed. Residue network model based solely on contact topology identified the 'hub residues' with high betweenness tracing plausible allosteric communication pathways between distant functional sites. For both bacterial PFK and PK, proposed sites accommodated hub residues twice as much as the known allosteric site. Tunnel region in parasitic GADPH with the strongest allosteric effect among species, incorporated the highest number of hub residues. These results clearly suggest a one-to-one correspondence between the degree of allosteric effect and the number of hub residues in that perturbation site, which increases the likelihood of its allosteric nature.
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Affiliation(s)
- Metehan Celebi
- Graduate Program of Computational Biology and Bioinformatics, Graduate School of Science and Engineering, Kadir Has University, Istanbul, Turkey
| | - Tugce Inan
- Department of Chemical Engineering, Istanbul Technical University, Istanbul, Turkey
| | - Ozge Kurkcuoglu
- Department of Chemical Engineering, Istanbul Technical University, Istanbul, Turkey
| | - Ebru Demet Akten
- Department of Bioinformatics and Genetics, Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Turkey.
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9
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Aguilar-Pineda GE, Olivares-Quiroz L. Catalytic and binding sites prediction in globular proteins through discrete Markov chains and network centrality measures. Phys Biol 2021; 18. [PMID: 34433159 DOI: 10.1088/1478-3975/ac211b] [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: 04/27/2021] [Accepted: 08/25/2021] [Indexed: 11/11/2022]
Abstract
In this work we use a discrete Markov chain approach combined with network centrality measures to identify and predict the location of active sites in globular proteins. To accomplish this, we use a three-dimensional network of proteinCαatoms as nodes connected through weighted edges which represent the varying interaction degree between protein's atoms. We compute the mean first passage time matrixH= {Hji} for this Markov chain and evaluate the averaged number of steps ⟨Hj⟩ to reach single nodenjin order to identify such residues that, on the average, are at the least distant from every other node. We also carry out a graph theory analysis to evaluate closeness centralityCc, betweenness centralityCband eigenvector centralityCemeasures which provide relevant information about the connectivity structure and topology of theCαprotein networks. Finally we also performed an analysis of equivalent random and regular networks of the same sizeNin terms of the average path lengthLand the average clustering coefficient⟨C⟩comparing these with the corresponding values forCαprotein networks. Our results show that the mean-first passage time matrixHand its related quantity ⟨Hj⟩ together withCc,CbandCecan not only predict with relative high accuracy the location of active sites in globular proteins but also exhibit a high feasibility to use them to predict the existence of new regions in protein's structure to identify new potential binding or catalytic activity or, in some cases, the presence of new allosteric pathways.
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Affiliation(s)
- Gabriel E Aguilar-Pineda
- Departamento de Fisica, Universidad Autónoma de la Ciudad de México (UACM), Campus Centro Histórico, CP 06080, Mexico City, Mexico
| | - L Olivares-Quiroz
- Departamento de Física and Posgrado en Ciencias de la Complejidad, Universidad Autónoma de la Ciudad de México (UACM), CP 09760, Mexico City, Mexico.,Centro de Ciencias de la Complejidad C3 (UNAM), Circuito Centro Cultural S/N Cd. Universitaria, CP 04510, Mexico City, Mexico
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10
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Bheemireddy S, Sandhya S, Srinivasan N. Comparative Analysis of Structural and Dynamical Features of Ribosome Upon Association With mRNA Reveals Potential Role of Ribosomal Proteins. Front Mol Biosci 2021; 8:654164. [PMID: 34409066 PMCID: PMC8365230 DOI: 10.3389/fmolb.2021.654164] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 07/21/2021] [Indexed: 11/24/2022] Open
Abstract
Ribosomes play a critical role in maintaining cellular proteostasis. The binding of messenger RNA (mRNA) to the ribosome regulates kinetics of protein synthesis. To generate an understanding of the structural, mechanistic, and dynamical features of mRNA recognition in the ribosome, we have analysed mRNA-protein interactions through a structural comparison of the ribosomal complex in the presence and absence of mRNA. To do so, we compared the 3-Dimensional (3D) structures of components of the two assembly structures and analysed their structural differences because of mRNA binding, using elastic network models and structural network-based analysis. We observe that the head region of 30S ribosomal subunit undergoes structural displacement and subunit rearrangement to accommodate incoming mRNA. We find that these changes are observed in proteins that lie far from the mRNA-protein interface, implying allostery. Further, through perturbation response scanning, we show that the proteins S13, S19, and S20 act as universal sensors that are sensitive to changes in the inter protein network, upon binding of 30S complex with mRNA and other initiation factors. Our study highlights the significance of mRNA binding in the ribosome complex and identifies putative allosteric sites corresponding to alterations in structure and/or dynamics, in regions away from mRNA binding sites in the complex. Overall, our work provides fresh insights into mRNA association with the ribosome, highlighting changes in the interactions and dynamics of the ribosome assembly because of the binding.
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Affiliation(s)
- Sneha Bheemireddy
- Molecular Biophysics Unit, Indian Institute of Science, Bengaluru, India
| | - Sankaran Sandhya
- Molecular Biophysics Unit, Indian Institute of Science, Bengaluru, India
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11
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Zhang Y, Krieger J, Mikulska-Ruminska K, Kaynak B, Sorzano COS, Carazo JM, Xing J, Bahar I. State-dependent sequential allostery exhibited by chaperonin TRiC/CCT revealed by network analysis of Cryo-EM maps. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2021; 160:104-120. [PMID: 32866476 PMCID: PMC7914283 DOI: 10.1016/j.pbiomolbio.2020.08.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 06/25/2020] [Accepted: 08/16/2020] [Indexed: 12/17/2022]
Abstract
The eukaryotic chaperonin TRiC/CCT plays a major role in assisting the folding of many proteins through an ATP-driven allosteric cycle. Recent structures elucidated by cryo-electron microscopy provide a broad view of the conformations visited at various stages of the chaperonin cycle, including a sequential activation of its subunits in response to nucleotide binding. But we lack a thorough mechanistic understanding of the structure-based dynamics and communication properties that underlie the TRiC/CCT machinery. In this study, we present a computational methodology based on elastic network models adapted to cryo-EM density maps to gain a deeper understanding of the structure-encoded allosteric dynamics of this hexadecameric machine. We have analysed several structures of the chaperonin resolved in different states toward mapping its conformational landscape. Our study indicates that the overall architecture intrinsically favours cooperative movements that comply with the structural variabilities observed in experiments. Furthermore, the individual subunits CCT1-CCT8 exhibit state-dependent sequential events at different states of the allosteric cycle. For example, in the ATP-bound state, subunits CCT5 and CCT4 selectively initiate the lid closure motions favoured by the overall architecture; whereas in the apo form of the heteromer, the subunit CCT7 exhibits the highest predisposition to structural change. The changes then propagate through parallel fluxes of allosteric signals to neighbours on both rings. The predicted state-dependent mechanisms of sequential activation provide new insights into TRiC/CCT intra- and inter-ring signal transduction events.
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Affiliation(s)
- Yan Zhang
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - James Krieger
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Karolina Mikulska-Ruminska
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Burak Kaynak
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | | | - José-María Carazo
- Centro Nacional de Biotecnología (CSIC), Darwin, 3, 28049, Madrid, Spain
| | - Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA.
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12
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Abstract
Allosteric regulation in proteins is fundamental to many important biological processes. Allostery has been employed to control protein functions by regulating protein activity. Engineered allosteric regulation allows controlling protein activity in subsecond time scale and has a broad range of applications, from dissecting spatiotemporal dynamics in biochemical cascades to applications in biotechnology and medicine. Here, we review the concept of allostery in proteins and various approaches to identify allosteric sites and pathways. We then provide an overview of strategies and tools used in allosteric protein regulation and their utility in biological applications. We highlight various classes of proteins, where regulation is achieved through allostery. Finally, we analyze the current problems, critical challenges, and future prospective in achieving allosteric regulation in proteins.
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Affiliation(s)
| | - Jiaxing Chen
- Department of Pharmacology, Penn State College of Medicine, Hershey, Pennsylvania 17033-0850, United States
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, Pennsylvania 17033-0850, United States
- Departments of Biochemistry & Molecular Biology, Penn State College of Medicine, Hershey, Pennsylvania 17033-0850, United States
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, United States
- Department of Biomedical Engineering, Penn State University, University Park, Pennsylvania 16802, United States
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13
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Grindle MP, Carter B, Alao JP, Connors K, Tehver R, Kravats AN. Structural Communication between the E. coli Chaperones DnaK and Hsp90. Int J Mol Sci 2021; 22:ijms22042200. [PMID: 33672263 PMCID: PMC7926864 DOI: 10.3390/ijms22042200] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 02/10/2021] [Accepted: 02/12/2021] [Indexed: 01/03/2023] Open
Abstract
The 70 kDa and 90 kDa heat shock proteins Hsp70 and Hsp90 are two abundant and highly conserved ATP-dependent molecular chaperones that participate in the maintenance of cellular homeostasis. In Escherichia coli, Hsp90 (Hsp90Ec) and Hsp70 (DnaK) directly interact and collaborate in protein remodeling. Previous work has produced a model of the direct interaction of both chaperones. The locations of the residues involved have been confirmed and the model has been validated. In this study, we investigate the allosteric communication between Hsp90Ec and DnaK and how the chaperones couple their conformational cycles. Using elastic network models (ENM), normal mode analysis (NMA), and a structural perturbation method (SPM) of asymmetric and symmetric DnaK-Hsp90Ec, we extract biologically relevant vibrations and identify residues involved in allosteric signaling. When one DnaK is bound, the dominant normal modes favor biological motions that orient a substrate protein bound to DnaK within the substrate/client binding site of Hsp90Ec and release the substrate from the DnaK substrate binding domain. The presence of one DnaK molecule stabilizes the entire Hsp90Ec protomer to which it is bound. Conversely, the symmetric model of DnaK binding results in steric clashes of DnaK molecules and suggests that the Hsp90Ec and DnaK chaperone cycles operate independently. Together, this data supports an asymmetric binding of DnaK to Hsp90Ec.
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Affiliation(s)
- Matthew P. Grindle
- Department of Chemistry & Biochemistry, Miami University, Oxford, OH 45056, USA; (M.P.G.); (J.P.A.); (K.C.)
| | - Ben Carter
- Department of Physics, Denison University, Granville, OH 43023, USA; (B.C.); (R.T.)
| | - John Paul Alao
- Department of Chemistry & Biochemistry, Miami University, Oxford, OH 45056, USA; (M.P.G.); (J.P.A.); (K.C.)
| | - Katherine Connors
- Department of Chemistry & Biochemistry, Miami University, Oxford, OH 45056, USA; (M.P.G.); (J.P.A.); (K.C.)
| | - Riina Tehver
- Department of Physics, Denison University, Granville, OH 43023, USA; (B.C.); (R.T.)
| | - Andrea N. Kravats
- Department of Chemistry & Biochemistry, Miami University, Oxford, OH 45056, USA; (M.P.G.); (J.P.A.); (K.C.)
- Correspondence:
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14
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Abstract
Allostery is a fundamental regulatory mechanism in the majority of biological processes of molecular machines. Allostery is well-known as a dynamic-driven process, and thus, the molecular mechanism of allosteric signal transmission needs to be established. Elastic network models (ENMs) provide efficient methods for investigating the intrinsic dynamics and allosteric communication pathways in proteins. In this chapter, two ENM methods including Gaussian network model (GNM) coupled with Markovian stochastic model, as well as the anisotropic network model (ANM), were introduced to identify allosteric effects in hemoglobins. Techniques on model parameters, scripting and calculation, analysis, and visualization are shown step by step.
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15
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Rocha GV, Bastos LS, Costa MGS. Identification of potential allosteric binding sites in cathepsin K based on intramolecular communication. Proteins 2020; 88:1675-1687. [PMID: 32683717 DOI: 10.1002/prot.25985] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 06/02/2020] [Accepted: 07/12/2020] [Indexed: 12/18/2022]
Abstract
Network theory methods and molecular dynamics (MD) simulations are accepted tools to study allosteric regulation. Indeed, dynamic networks built upon correlation analysis of MD trajectories provide detailed information about communication paths between distant sites. In this context, we aimed to understand whether the efficiency of intramolecular communication could be used to predict the allosteric potential of a given site. To this end, we performed MD simulations and network theory analyses in cathepsin K (catK), whose allosteric sites are well defined. To obtain a quantitative measure of the efficiency of communication, we designed a new protocol that enables the comparison between properties related to ensembles of communication paths obtained from different sites. Further, we applied our strategy to evaluate the allosteric potential of different catK cavities not yet considered for drug design. Our predictions of the allosteric potential based on intramolecular communication correlate well with previous catK experimental and theoretical data. We also discuss the possibility of applying our approach to other proteins from the same family.
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Affiliation(s)
- Gisele V Rocha
- Programa de Computação Científica, Vice-Presidência de Educação, Informação e Comunicação, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.,Laboratoire de Biologie et de Pharmacologie Appliquée, Ecole Normale Supérieure Paris Saclay, Centre National de la Recherche Scientifique, Cachan, France
| | - Leonardo S Bastos
- Programa de Computação Científica, Vice-Presidência de Educação, Informação e Comunicação, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.,Department of Infectious Diseases Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Mauricio G S Costa
- Programa de Computação Científica, Vice-Presidência de Educação, Informação e Comunicação, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.,Laboratoire de Biologie et de Pharmacologie Appliquée, Ecole Normale Supérieure Paris Saclay, Centre National de la Recherche Scientifique, Cachan, France
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16
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Wang J, Jain A, McDonald LR, Gambogi C, Lee AL, Dokholyan NV. Mapping allosteric communications within individual proteins. Nat Commun 2020; 11:3862. [PMID: 32737291 PMCID: PMC7395124 DOI: 10.1038/s41467-020-17618-2] [Citation(s) in RCA: 88] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Accepted: 06/30/2020] [Indexed: 02/05/2023] Open
Abstract
Allostery in proteins influences various biological processes such as regulation of gene transcription and activities of enzymes and cell signaling. Computational approaches for analysis of allosteric coupling provide inexpensive opportunities to predict mutations and to design small-molecule agents to control protein function and cellular activity. We develop a computationally efficient network-based method, Ohm, to identify and characterize allosteric communication networks within proteins. Unlike previously developed simulation-based approaches, Ohm relies solely on the structure of the protein of interest. We use Ohm to map allosteric networks in a dataset composed of 20 proteins experimentally identified to be allosterically regulated. Further, the Ohm allostery prediction for the protein CheY correlates well with NMR CHESCA studies. Our webserver, Ohm.dokhlab.org, automatically determines allosteric network architecture and identifies critical coupled residues within this network.
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Affiliation(s)
- Jian Wang
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA
| | - Abha Jain
- Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7363, USA
| | - Leanna R McDonald
- Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7363, USA
| | - Craig Gambogi
- Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7363, USA
| | - Andrew L Lee
- Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7363, USA
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA.
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Departments of Biochemistry & Molecular Biology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA.
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17
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Verkhivker GM, Agajanian S, Hu G, Tao P. Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning. Front Mol Biosci 2020; 7:136. [PMID: 32733918 PMCID: PMC7363947 DOI: 10.3389/fmolb.2020.00136] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/08/2020] [Indexed: 12/12/2022] Open
Abstract
Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.
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Affiliation(s)
- Gennady M. Verkhivker
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, United States
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA, United States
| | - Steve Agajanian
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, United States
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Peng Tao
- Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, TX, United States
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18
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To Probe Full and Partial Activation of Human Peroxisome Proliferator-Activated Receptors by Pan-Agonist Chiglitazar Using Molecular Dynamics Simulations. PPAR Res 2020; 2020:5314187. [PMID: 32308671 PMCID: PMC7152983 DOI: 10.1155/2020/5314187] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 02/25/2020] [Accepted: 03/03/2020] [Indexed: 02/06/2023] Open
Abstract
Chiglitazar is a promising new-generation insulin sensitizer with low reverse effects for the treatment of type II diabetes mellitus (T2DM) and has shown activity as a nonselective pan-agonist to the human peroxisome proliferator-activated receptors (PPARs) (i.e., full activation of PPARγ and a partial activation of PPARα and PPARβ/δ). Yet, it has no high-resolution complex structure with PPARs and its detailed interactions and activation mechanism remain unclear. In this study, we docked chiglitazar into three experimentally resolved crystal structures of hPPAR subtypes, PPARα, PPARβ/δ, and PPARγ, followed by 3 μs molecular dynamics simulations for each system. Our MM-GBSA binding energy calculation revealed that chiglitazar most favorably bound to hPPARγ (-144.6 kcal/mol), followed by hPPARα (-138.0 kcal/mol) and hPPARβ (-135.9 kcal/mol), and the order is consistent with the experimental data. Through the decomposition of the MM-GBSA binding energy by residue and the use of two-dimensional interaction diagrams, key residues involved in the binding of chiglitazar were identified and characterized for each complex system. Additionally, our detailed dynamics analyses support that the conformation and dynamics of helix 12 play a critical role in determining the activities of the different types of ligands (e.g., full agonist vs. partial agonist). Rather than being bent fully in the direction of the agonist versus antagonist conformation, a partial agonist can adopt a more linear conformation and have a lower degree of flexibility. Our finding may aid in further development of this new generation of medication.
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19
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Sullivan HJ, Tursi A, Moore K, Campbell A, Floyd C, Wu C. Binding Interactions of Ergotamine and Dihydroergotamine to 5-Hydroxytryptamine Receptor 1B (5-HT 1b) Using Molecular Dynamics Simulations and Dynamic Network Analysis. J Chem Inf Model 2020; 60:1749-1765. [PMID: 32078320 DOI: 10.1021/acs.jcim.9b01082] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Ergotamine (ERG) and dihydroergotamine (DHE), common migraine drugs, have small structural differences but lead to clinically important distinctions in their pharmacological profiles. For example, DHE is less potent than ERG by about 10-fold at the 5-hydroxytrptamine receptor 1B (5-HT1B). Although the high-resolution crystal structures of the 5-HT1B receptor with both ligands have been solved, the high similarity between these two complex structures does not sufficiently explain their activity differences and the activation mechanism of the receptor. Hence, an examination of the dynamic motion of both drugs with the receptor is required. In this study, we ran a total of 6.0 μs molecular dynamics simulations on each system. Our simulation data show the subtle variations between the two systems in terms of the ligand-receptor interactions and receptor secondary structures. More importantly, the ligand and protein root-mean-square fluctuations (RMSFs) for the two systems were distinct, with ERG having a trend of lower RMSF values, indicating it to be bound tighter to 5-HT1B with less fluctuations. The molecular mechanism-general born surface area (MM-GBSA) binding energies illustrate this further, proving ERG has an overall stronger MM-GBSA binding energy. Analysis of several different microswitches has shown that the 5-HT1B-ERG complex is in a more active conformation state than 5-HT1B-DHE, which is further supported by the dynamic network model, with reference to mutagenesis data with the critical nodes and the first three low-energy modes from the normal mode analysis. We also identify Trp3276.48 and Phe3316.52 as key residues involved in the active state 5-HT1B for both ligands. Using the detailed dynamic information from our analysis, we made predictions for possible modifications to DHE and ERG that yielded five derivatives that might have more favorable binding energies and reduced structural fluctuations.
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Affiliation(s)
- Holli-Joi Sullivan
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Amanda Tursi
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Kelly Moore
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Alexandra Campbell
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Cecilia Floyd
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Chun Wu
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
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20
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Huang BC, Yang LW. Molecular dynamics simulations and linear response theories jointly describe biphasic responses of myoglobin relaxation and reveal evolutionarily conserved frequent communicators. Biophys Physicobiol 2020; 16:473-484. [PMID: 31984199 PMCID: PMC6975898 DOI: 10.2142/biophysico.16.0_473] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 09/20/2019] [Indexed: 12/01/2022] Open
Abstract
In this study, we provide a time-dependent mechanical model, taking advantage of molecular dynamics simulations, quasiharmonic analysis of molecular dynamics trajectories, and time-dependent linear response theories to describe vibrational energy redistribution within the protein matrix. The theoretical description explained the observed biphasic responses of specific residues in myoglobin to CO-photolysis and photoexcitation on heme. The fast responses were found to be triggered by impulsive forces and propagated mainly by principal modes <40 cm−1. The predicted fast responses for individual atoms were then used to study signal propagation within the protein matrix and signals were found to propagate ~8 times faster across helices (4076 m/s) than within the helices, suggesting the importance of tertiary packing in the sensitivity of proteins to external perturbations. We further developed a method to integrate multiple intramolecular signal pathways and discover frequent “communicators”. These communicators were found to be evolutionarily conserved including those distant from the heme.
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Affiliation(s)
- Bang-Chieh Huang
- Institute of Bioinformatics and Structural Biology, National Tsing-Hua University, Hsinchu 30013, Taiwan
| | - Lee-Wei Yang
- Institute of Bioinformatics and Structural Biology, National Tsing-Hua University, Hsinchu 30013, Taiwan.,Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Sciences, Academia Sinica, Taipei 11529, Taiwan.,Department of Life Science, National Tsing Hua University, Hsinchu 30013, Taiwan.,Physics Division, National Center for Theoretical Sciences, Hsinchu 30013, Taiwan
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21
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Sheik Amamuddy O, Veldman W, Manyumwa C, Khairallah A, Agajanian S, Oluyemi O, Verkhivker GM, Tastan Bishop Ö. Integrated Computational Approaches and Tools forAllosteric Drug Discovery. Int J Mol Sci 2020; 21:E847. [PMID: 32013012 PMCID: PMC7036869 DOI: 10.3390/ijms21030847] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Revised: 01/20/2020] [Accepted: 01/21/2020] [Indexed: 12/16/2022] Open
Abstract
Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.
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Affiliation(s)
- Olivier Sheik Amamuddy
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Wayde Veldman
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Colleen Manyumwa
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Afrah Khairallah
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Steve Agajanian
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA; (S.A.); (O.O.)
| | - Odeyemi Oluyemi
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA; (S.A.); (O.O.)
| | - Gennady M. Verkhivker
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA; (S.A.); (O.O.)
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
| | - Özlem Tastan Bishop
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
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22
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Ahuja LG, Taylor SS, Kornev AP. Tuning the "violin" of protein kinases: The role of dynamics-based allostery. IUBMB Life 2019; 71:685-696. [PMID: 31063633 PMCID: PMC6690483 DOI: 10.1002/iub.2057] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 04/12/2019] [Indexed: 12/17/2022]
Abstract
The intricacies of allosteric regulation of protein kinases continue to engage the research community. Allostery, or control from a distance, is seen as a fundamental biomolecular mechanism for proteins. From the traditional methods of conformational selection and induced fit, the field has grown to include the role of protein motions in defining a dynamics-based allosteric approach. Harnessing of these continuous motions in the protein to exert allosteric effects can be defined by a "violin" model that focuses on distributions of protein vibrations as opposed to concerted pathways. According to this model, binding of an allosteric modifier causes global redistribution of dynamics in the protein kinase domain that leads to changes in its catalytic properties. This model is consistent with the "entropy-driven allostery" mechanism proposed by Cooper and Dryden in 1984 and does not require, but does not exclude, any major structural changes. We provide an overview of practical implementation of the violin model and how it stands amidst the other known models of protein allostery. Protein kinases have been described as the biomolecules of interest. © 2019 IUBMB Life, 71(6):685-696, 2019.
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Affiliation(s)
- Lalima G. Ahuja
- Department of Pharmacology, University of California San Diego, La Jolla, CA, USA
| | - Susan S. Taylor
- Department of Pharmacology, University of California San Diego, La Jolla, CA, USA
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, USA
| | - Alexandr P. Kornev
- Department of Pharmacology, University of California San Diego, La Jolla, CA, USA
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23
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Sengupta U, Strodel B. Markov models for the elucidation of allosteric regulation. Philos Trans R Soc Lond B Biol Sci 2019; 373:rstb.2017.0178. [PMID: 29735732 DOI: 10.1098/rstb.2017.0178] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/14/2018] [Indexed: 11/12/2022] Open
Abstract
Allosteric regulation refers to the process where the effect of binding of a ligand at one site of a protein is transmitted to another, often distant, functional site. In recent years, it has been demonstrated that allosteric mechanisms can be understood by the conformational ensembles of a protein. Molecular dynamics (MD) simulations are often used for the study of protein allostery as they provide an atomistic view of the dynamics of a protein. However, given the wealth of detailed information hidden in MD data, one has to apply a method that allows extraction of the conformational ensembles underlying allosteric regulation from these data. Markov state models are one of the most promising methods for this purpose. We provide a short introduction to the theory of Markov state models and review their application to various examples of protein allostery studied by MD simulations. We also include a discussion of studies where Markov modelling has been employed to analyse experimental data on allosteric regulation. We conclude our review by advertising the wider application of Markov state models to elucidate allosteric mechanisms, especially since in recent years it has become straightforward to construct such models thanks to software programs like PyEMMA and MSMBuilder.This article is part of a discussion meeting issue 'Allostery and molecular machines'.
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Affiliation(s)
- Ushnish Sengupta
- Institute of Complex Systems: Structural Biochemistry (ICS-6), Forschungzentrum Jülich, 52425 Jülich, Germany.,German Research School for Simulation Sciences, RWTH Aachen University, 52062 Aachen, Germany
| | - Birgit Strodel
- Institute of Complex Systems: Structural Biochemistry (ICS-6), Forschungzentrum Jülich, 52425 Jülich, Germany .,Institute of Theoretical and Computational Chemistry, Heinrich Heine University, 40225 Düsseldorf, Germany
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24
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Astl L, Tse A, Verkhivker GM. Interrogating Regulatory Mechanisms in Signaling Proteins by Allosteric Inhibitors and Activators: A Dynamic View Through the Lens of Residue Interaction Networks. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1163:187-223. [DOI: 10.1007/978-981-13-8719-7_9] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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25
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Kürkçüoğlu Ö. Exploring allosteric communication in multiple states of the bacterial ribosome using residue network analysis. Turk J Biol 2018; 42:392-404. [PMID: 30930623 PMCID: PMC6438126 DOI: 10.3906/biy-1802-77] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Antibiotic resistance is one of the most important problems of our era and hence the discovery of new effective therapeutics is urgent. At this point, studying the allosteric communication pathways in the bacterial ribosome and revealing allosteric sites/residues is critical for designing new inhibitors or repurposing readily approved drugs for this enormous machine. To shed light onto molecular details of the allosteric mechanisms, here we construct residue networks of the bacterial ribosomal complex at four different states of translation by using an effective description of the intermolecular interactions. Centrality analysis of these networks highlights the functional roles of structural components and critical residues on the ribosomal complex. High betweenness scores reveal pathways of residues connecting numerous sites on the structure. Interestingly, these pathways assemble highly conserved residues, drug binding sites, and known allosterically linked regions on the same structure. This study proposes a new residue-level model to test how distant sites on the molecular machine may be linked through hub residues that are critically located on the contact topology to inherently form communication pathways. Findings also indicate intersubunit bridges B1b, B3, B5, B7, and B8 as critical targets to design novel antibiotics.
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Affiliation(s)
- Özge Kürkçüoğlu
- Department of Chemical Engineering, Faculty of Chemical-Metallurgical Engineering, İstanbul Technical University , İstanbul , Turkey
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26
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Liang Z, Hu J, Yan W, Jiang H, Hu G, Luo C. Deciphering the role of dimer interface in intrinsic dynamics and allosteric pathways underlying the functional transformation of DNMT3A. Biochim Biophys Acta Gen Subj 2018; 1862:1667-1679. [DOI: 10.1016/j.bbagen.2018.04.015] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Revised: 04/03/2018] [Accepted: 04/13/2018] [Indexed: 01/06/2023]
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27
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Fanelli F, Felline A. Uncovering GPCR and G Protein Function by Protein Structure Network Analysis. COMPUTATIONAL TOOLS FOR CHEMICAL BIOLOGY 2017. [DOI: 10.1039/9781788010139-00198] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used for investigating structural communication in biomolecular systems. Information on the system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM-NMA). This chapter reports on selected applications of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs) and G proteins. Strategies to highlight changes in structural communication caused by mutations, ligand and protein binding are described. Conserved amino acids, sites of misfolding mutations, or ligands acting as functional switches tend to behave as hubs in the native structure networks. Densely linked regions in the protein structure graphs could be identified as playing central roles in protein stability and function. Changes in the communication pathway fingerprints depending on the bound ligand or following amino acid mutation could be highlighted as well. A bridge between misfolding and misrouting could be established in rhodopsin mutants linked to inherited blindness. The analysis of native network perturbations by misfolding mutations served to infer key structural elements of protein responsiveness to small chaperones with implications for drug discovery.
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Affiliation(s)
- Francesca Fanelli
- Department of Life Sciences University of Modena and Reggio Emilia Italy
- Center for Neuroscience and Neurotechnology University of Modena and Reggio Emilia Italy
| | - Angelo Felline
- Department of Life Sciences University of Modena and Reggio Emilia Italy
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28
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Identification of potential allosteric communication pathways between functional sites of the bacterial ribosome by graph and elastic network models. Biochim Biophys Acta Gen Subj 2017; 1861:3131-3141. [PMID: 28917952 DOI: 10.1016/j.bbagen.2017.09.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2017] [Revised: 09/11/2017] [Accepted: 09/12/2017] [Indexed: 12/18/2022]
Abstract
BACKGROUND Accumulated evidence indicates that bacterial ribosome employs allostery throughout its structure for protein synthesis. The nature of the allosteric communication between remote functional sites remains unclear, but the contact topology and dynamics of residues may play role in transmission of a perturbation to distant sites. METHODS/RESULTS We employ two computationally efficient approaches - graph and elastic network modeling to gain insights about the allosteric communication in ribosome. Using graph representation of the structure, we perform k-shortest pathways analysis between peptidyl transferase center-ribosomal tunnel, decoding center-peptidyl transferase center - previously reported functional sites having allosteric communication. Detailed analysis on intact structures points to common and alternative shortest pathways preferred by different states of translation. All shortest pathways capture drug target sites and allosterically important regions. Elastic network model further reveals that residues along all pathways have the ability of quickly establishing pair-wise communication and to help the propagation of a perturbation in long-ranges during functional motions of the complex. CONCLUSIONS Contact topology and inherent dynamics of ribosome configure potential communication pathways between functional sites in different translation states. Inter-subunit bridges B2a, B3 and P-tRNA come forward for their high potential in assisting allostery during translation. Especially B3 emerges as a potential druggable site. GENERAL SIGNIFICANCE This study indicates that the ribosome topology forms a basis for allosteric communication, which can be disrupted by novel drugs to kill drug-resistant bacteria. Our computationally efficient approach not only overlaps with experimental evidence on allosteric regulation in ribosome but also proposes new druggable sites.
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29
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Dissecting intrinsic and ligand-induced structural communication in the β3 headpiece of integrins. Biochim Biophys Acta Gen Subj 2017; 1861:2367-2381. [DOI: 10.1016/j.bbagen.2017.05.018] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Revised: 05/20/2017] [Accepted: 05/22/2017] [Indexed: 12/15/2022]
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30
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Design of Elastic Networks with Evolutionary Optimized Long-Range Communication as Mechanical Models of Allosteric Proteins. Biophys J 2017; 113:558-571. [PMID: 28793211 PMCID: PMC5550307 DOI: 10.1016/j.bpj.2017.06.043] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Revised: 05/25/2017] [Accepted: 06/14/2017] [Indexed: 02/08/2023] Open
Abstract
Allosteric effects often underlie the activity of proteins, and elucidating generic design aspects and functional principles unique to allosteric phenomena represent a major challenge. Here an approach consisting of the in silico design of synthetic structures, which, as the principal element of allostery, encode dynamical long-range coupling among two sites, is presented. The structures are represented by elastic networks, similar to coarse-grained models of real proteins. A strategy of evolutionary optimization was implemented to iteratively improve allosteric coupling. In the designed structures, allosteric interactions were analyzed in terms of strain propagation, and simple pathways that emerged during evolution were identified as signatures through which long-range communication was established. Moreover, robustness of allosteric performance with respect to mutations was demonstrated. As it turned out, the designed prototype structures reveal dynamical properties resembling those found in real allosteric proteins. Hence, they may serve as toy models of complex allosteric systems, such as proteins. Application of the developed modeling scheme to the allosteric transition in the myosin V molecular motor was also demonstrated.
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31
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Directional Force Originating from ATP Hydrolysis Drives the GroEL Conformational Change. Biophys J 2017; 112:1561-1570. [PMID: 28445748 DOI: 10.1016/j.bpj.2017.03.004] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 12/16/2016] [Accepted: 03/01/2017] [Indexed: 11/23/2022] Open
Abstract
Protein functional mechanisms usually require conformational changes, and often there are known structures for the different conformational states. However, usually neither the origin of the driving force nor the underlying pathways for these conformational transitions is known. Exothermic chemical reactions may be an important source of forces that drive conformational changes. Here we investigate this type of force originating from ATP hydrolysis in the chaperonin GroEL, by applying forces originating from the chemical reaction. Specifically, we apply directed forces to drive the GroEL conformational changes and learn that there is a highly specific direction for applied forces to drive the closed form to the open form. For this purpose, we utilize coarse-grained elastic network models. Principal component analysis on 38 GroEL experimental structures yields the most important motions, and these are used in structural interpolation for the construction of a coarse-grained free energy landscape. In addition, we investigate a more random application of forces with a Monte Carlo method and demonstrate pathways for the closed-open conformational transition in both directions by computing trajectories that are shown upon the free energy landscape. Initial root mean square deviation (RMSD) between the open and closed forms of the subunit is 14.7 Å and final forms from our simulations reach an average RMSD of 3.6 Å from the target forms, closely matching the level of resolution of the coarse-grained model.
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32
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Srivastava A, Tracka MB, Uddin S, Casas-Finet J, Livesay DR, Jacobs DJ. Mutations in Antibody Fragments Modulate Allosteric Response Via Hydrogen-Bond Network Fluctuations. Biophys J 2017; 110:1933-42. [PMID: 27166802 DOI: 10.1016/j.bpj.2016.03.033] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Revised: 03/25/2016] [Accepted: 03/28/2016] [Indexed: 11/28/2022] Open
Abstract
A mechanical perturbation method that locally restricts conformational entropy along the protein backbone is used to identify putative allosteric sites in a series of antibody fragments. The method is based on a distance constraint model that integrates mechanical and thermodynamic viewpoints of protein structure wherein mechanical clamps that mimic substrate or cosolute binding are introduced. Across a set of six single chain-Fv fragments of the anti-lymphotoxin-β receptor antibody, statistically significant responses are obtained by averaging over 10 representative structures sampled from a molecular dynamics simulation. As expected, the introduced clamps locally rigidify the protein, but long-ranged increases in both rigidity and flexibility are also frequently observed. Expanding our analysis to every molecular dynamics frame demonstrates that the allosteric responses are modulated by fluctuations within the hydrogen-bond network where the native ensemble is comprised of conformations that both are, and are not, affected by the perturbation in question. Population shifts induced by the mutations alter the allosteric response by adjusting which hydrogen-bond networks are the most probable. These effects are compared using response maps that track changes across each single chain-Fv fragment, thus providing valuable insight into how sensitive allosteric mechanisms are to mutations.
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Affiliation(s)
- Amit Srivastava
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, North Carolina
| | | | - Shahid Uddin
- Formulation Sciences, MedImmune Ltd., Cambridge, UK
| | - Jose Casas-Finet
- Analytical Biochemistry Department, MedImmune LLC, Gaithersburg, Maryland
| | - Dennis R Livesay
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, North Carolina.
| | - Donald J Jacobs
- Department of Physics and Optical Science, University of North Carolina at Charlotte, Charlotte, North Carolina.
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33
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Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case. BIOMED RESEARCH INTERNATIONAL 2017; 2017:2483264. [PMID: 28243596 PMCID: PMC5294226 DOI: 10.1155/2017/2483264] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Revised: 11/17/2016] [Accepted: 12/20/2016] [Indexed: 01/12/2023]
Abstract
The overall topology and interfacial interactions play key roles in understanding structural and functional principles of protein complexes. Elastic Network Model (ENM) and Protein Contact Network (PCN) are two widely used methods for high throughput investigation of structures and interactions within protein complexes. In this work, the comparative analysis of ENM and PCN relative to hemoglobin (Hb) was taken as case study. We examine four types of structural and dynamical paradigms, namely, conformational change between different states of Hbs, modular analysis, allosteric mechanisms studies, and interface characterization of an Hb. The comparative study shows that ENM has an advantage in studying dynamical properties and protein-protein interfaces, while PCN is better for describing protein structures quantitatively both from local and from global levels. We suggest that the integration of ENM and PCN would give a potential but powerful tool in structural systems biology.
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34
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Affiliation(s)
- Changbong Hyeon
- Korea Institute for Advanced Study, Seoul 02455, Republic of Korea
| | - D. Thirumalai
- Department
of Chemistry, University of Texas, Austin, Texas 78712-1224, United States
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35
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Mou L, Cui T, Liu W, Zhang H, Cai Z, Lu S, Gao G. Microsecond molecular dynamics simulations provide insight into the ATP-competitive inhibitor-induced allosteric protection of Akt kinase phosphorylation. Chem Biol Drug Des 2016; 89:723-731. [PMID: 27797456 DOI: 10.1111/cbdd.12895] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 10/02/2016] [Accepted: 10/25/2016] [Indexed: 11/28/2022]
Abstract
Akt is a serine/threonine protein kinase, a critical mediator of growth factor-induced survival in key cellular pathways. Allosteric signaling between protein intramolecular domains requires long-range communication mediated by hotspot residues, often triggered by ligand binding. Here, based on extensive 3 μs explicit solvent molecular dynamics (MD) simulations of Akt1 kinase domain in the unbound (apo) and ATP-competitive inhibitor, GDC-0068-bound states, we propose a molecular mechanism for allosteric regulation of Akt1 kinase phosphorylation by GDC-0068 binding to the ATP-binding site. MD simulations revealed that the apo Akt1 is flexible with two disengaged N- and C-lobes, equilibrated between the open and closed conformations. GDC-0068 occupancy of the ATP-binding site shifts the conformational equilibrium of Akt1 from the open conformation toward the closed conformation and stabilizes the closed state. This effect enables allosteric signal propagation from the GDC-0068 to the phosphorylated T308 (pT308) in the activation loop and restrains phosphatase access to pT308, thereby protecting the pT308 in the GDC-0068-bound Akt1. Importantly, functional hotspots involved in the allosteric communication from the GDC-0068 to the pT308 are identified. Our analysis of GDC-0068-induced allosteric protection of Akt kinase phosphorylation yields important new insights into the molecular mechanism of allosteric regulation of Akt kinase activity.
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Affiliation(s)
- Linkai Mou
- Department of Urology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
| | - Tongwei Cui
- Department of Urology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
| | - Weiguang Liu
- Department of Urology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
| | - Hong Zhang
- Department of Urology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
| | - Zhanxiu Cai
- Department of Electrical and Computer Engineering, College of Bioscience and Technology, Weifang Medical University, Weifang, Shandong, China
| | - Shaoyong Lu
- Department of Pathophysiology, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Guojun Gao
- Department of Urology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
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36
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Wang B, Francis J, Sharma M, Law SM, Predeus AV, Feig M. Long-Range Signaling in MutS and MSH Homologs via Switching of Dynamic Communication Pathways. PLoS Comput Biol 2016; 12:e1005159. [PMID: 27768684 PMCID: PMC5074593 DOI: 10.1371/journal.pcbi.1005159] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Accepted: 09/21/2016] [Indexed: 11/19/2022] Open
Abstract
Allostery is conformation regulation by propagating a signal from one site to another distal site. This study focuses on the long-range communication in DNA mismatch repair proteins MutS and its homologs where intramolecular signaling has to travel over 70 Å to couple lesion detection to ATPase activity and eventual downstream repair. Using dynamic network analysis based on extensive molecular dynamics simulations, multiple preserved communication pathways were identified that would allow such long-range signaling. The pathways appear to depend on the nucleotides bound to the ATPase domain as well as the type of DNA substrate consistent with previously proposed functional cycles of mismatch recognition and repair initiation by MutS and homologs. A mechanism is proposed where pathways are switched without major conformational rearrangements allowing for efficient long-range signaling and allostery.
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Affiliation(s)
- Beibei Wang
- Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States
| | - Joshua Francis
- Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States
| | - Monika Sharma
- Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States
| | - Sean M. Law
- Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States
| | - Alexander V. Predeus
- Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States
| | - Michael Feig
- Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States
- * E-mail:
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37
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Schueler-Furman O, Wodak SJ. Computational approaches to investigating allostery. Curr Opin Struct Biol 2016; 41:159-171. [PMID: 27607077 DOI: 10.1016/j.sbi.2016.06.017] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 06/23/2016] [Indexed: 01/01/2023]
Abstract
Allosteric regulation plays a key role in many biological processes, such as signal transduction, transcriptional regulation, and many more. It is rooted in fundamental thermodynamic and dynamic properties of macromolecular systems that are still poorly understood and are moreover modulated by the cellular context. Here we review the computational approaches used in the investigation of allosteric processes in protein systems. We outline how the models of allostery have evolved from their initial formulation in the sixties to the current views, which more fully account for the roles of the thermodynamic and dynamic properties of the system. We then describe the major classes of computational approaches employed to elucidate the mechanisms of allostery, the insights they have provided, as well as their limitations. We complement this analysis by highlighting the role of computational approaches in promising practical applications, such as the engineering of regulatory modules and identifying allosteric binding sites.
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Affiliation(s)
- Ora Schueler-Furman
- Department of Microbiology and Molecular Genetics, Institute for Medical Research Israel-Canada (IMRIC), Hebrew University, Hadassah Medical School, POB 12272, Jerusalem 91120, Israel
| | - Shoshana J Wodak
- VIB Structural Biology Research Center, VUB, Pleinlaan 2, 1050 Brussels, Belgium.
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38
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Ma X, Qi Y, Lai L. Allosteric sites can be identified based on the residue-residue interaction energy difference. Proteins 2016; 83:1375-84. [PMID: 25185787 DOI: 10.1002/prot.24681] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2014] [Revised: 08/20/2014] [Accepted: 08/22/2014] [Indexed: 11/08/2022]
Abstract
Allosteric drugs act at a distance to regulate protein functions. They have several advantages over conventional orthosteric drugs, including diverse regulation types and fewer side effects. However, the rational design of allosteric ligands remains a challenge, especially when it comes to the identification allosteric binding sites. As the binding of allosteric ligands may induce changes in the pattern of residue-residue interactions, we calculated the residue-residue interaction energies within the allosteric site based on the molecular mechanics generalized Born surface area energy decomposition scheme. Using a dataset of 17 allosteric proteins with structural data for both the apo and the ligand-bound state available, we used conformational ensembles generated by molecular dynamics simulations to compute the differences in the residue-residue interaction energies in known allosteric sites from both states. For all the known sites, distinct interaction energy differences (>25%) were observed. We then used CAVITY, a binding site detection program to identify novel putative allosteric sites in the same proteins. This yielded a total of 31 "druggable binding sites," of which 21 exhibited >25% difference in residue interaction energies, and were hence predicted as novel allosteric sites. Three of the predicted allosteric sites were supported by recent experimental studies. All the predicted sites may serve as novel allosteric sites for allosteric ligand design. Our study provides a computational method for identifying novel allosteric sites for allosteric drug design.
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Affiliation(s)
- Xiaomin Ma
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Yifei Qi
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Luhua Lai
- Center for Quantitative Biology, Peking University, Beijing, 100871, China.,BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, and Peking-Tsinghua Center for Life Sciences at College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
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39
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Clarke D, Sethi A, Li S, Kumar S, Chang RWF, Chen J, Gerstein M. Identifying Allosteric Hotspots with Dynamics: Application to Inter- and Intra-species Conservation. Structure 2016; 24:826-837. [PMID: 27066750 PMCID: PMC4883016 DOI: 10.1016/j.str.2016.03.008] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Revised: 01/01/2016] [Accepted: 03/04/2016] [Indexed: 01/17/2023]
Abstract
The rapidly growing volume of data being produced by next-generation sequencing initiatives is enabling more in-depth analyses of conservation than previously possible. Deep sequencing is uncovering disease loci and regions under selective constraint, despite the fact that intuitive biophysical reasons for such constraint are sometimes absent. Allostery may often provide the missing explanatory link. We use models of protein conformational change to identify allosteric residues by finding essential surface pockets and information-flow bottlenecks, and we develop a software tool that enables users to perform this analysis on their own proteins of interest. Though fundamentally 3D-structural in nature, our analysis is computationally fast, thereby allowing us to run it across the PDB and to evaluate general properties of predicted allosteric residues. We find that these tend to be conserved over diverse evolutionary time scales. Finally, we highlight examples of allosteric residues that help explain poorly understood disease-associated variants.
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Affiliation(s)
- Declan Clarke
- Department of Chemistry, Yale University, 225 Prospect Street, New Haven, CT 06520, USA
| | - Anurag Sethi
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Shantao Li
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Computer Science, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Sushant Kumar
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Richard W F Chang
- Yale College, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Jieming Chen
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Integrated Graduate Program in Physical and Engineering Biology, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Computer Science, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA.
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40
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Abstract
Allosteric transition, defined as conformational changes induced by ligand binding, is one of the fundamental properties of proteins. Allostery has been observed and characterized in many proteins, and has been recently utilized to control protein function via regulation of protein activity. Here, we review the physical and evolutionary origin of protein allostery, as well as its importance to protein regulation, drug discovery, and biological processes in living systems. We describe recently developed approaches to identify allosteric pathways, connected sets of pairwise interactions that are responsible for propagation of conformational change from the ligand-binding site to a distal functional site. We then present experimental and computational protein engineering approaches for control of protein function by modulation of allosteric sites. As an example of application of these approaches, we describe a synergistic computational and experimental approach to rescue the cystic-fibrosis-associated protein cystic fibrosis transmembrane conductance regulator, which upon deletion of a single residue misfolds and causes disease. This example demonstrates the power of allosteric manipulation in proteins to both elucidate mechanisms of molecular function and to develop therapeutic strategies that rescue those functions. Allosteric control of proteins provides a tool to shine a light on the complex cascades of cellular processes and facilitate unprecedented interrogation of biological systems.
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Affiliation(s)
- Nikolay V Dokholyan
- Department of Biochemistry and Biophysics, University of North Carolina , Chapel Hill, North Carolina 27599, United States
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41
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Papaleo E, Saladino G, Lambrughi M, Lindorff-Larsen K, Gervasio FL, Nussinov R. The Role of Protein Loops and Linkers in Conformational Dynamics and Allostery. Chem Rev 2016; 116:6391-423. [DOI: 10.1021/acs.chemrev.5b00623] [Citation(s) in RCA: 239] [Impact Index Per Article: 29.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Elena Papaleo
- Computational
Biology Laboratory, Unit of Statistics, Bioinformatics and Registry, Danish Cancer Society Research Center, Strandboulevarden 49, 2100 Copenhagen, Denmark
- Structural
Biology and NMR Laboratory, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Giorgio Saladino
- Department
of Chemistry, University College London, London WC1E 6BT, United Kingdom
| | - Matteo Lambrughi
- Department
of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza
della Scienza 2, 20126 Milan, Italy
| | - Kresten Lindorff-Larsen
- Structural
Biology and NMR Laboratory, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark
| | | | - Ruth Nussinov
- Cancer
and Inflammation Program, Leidos Biomedical Research, Inc., Frederick
National Laboratory for Cancer Research, National Cancer Institute Frederick, Frederick, Maryland 21702, United States
- Sackler Institute
of Molecular Medicine, Department of Human Genetics and Molecular
Medicine Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
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42
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Abstract
The functions of many proteins are regulated through allostery, whereby effector binding at a distal site changes the functional activity (e.g., substrate binding affinity or catalytic efficiency) at the active site. Most allosteric studies have focused on thermodynamic properties, in particular, substrate binding affinity. Changes in substrate binding affinity by allosteric effectors have generally been thought to be mediated by conformational transitions of the proteins or, alternatively, by changes in the broadness of the free energy basin of the protein conformational state without shifting the basin minimum position. When effector binding changes the free energy landscape of a protein in conformational space, the change affects not only thermodynamic properties but also dynamic properties, including the amplitudes of motions on different time scales and rates of conformational transitions. Here we assess the roles of conformational dynamics in allosteric regulation. Two cases are highlighted where NMR spectroscopy and molecular dynamics simulation have been used as complementary approaches to identify residues possibly involved in allosteric communication. Perspectives on contentious issues, for example, the relationship between picosecond-nanosecond local and microsecond-millisecond conformational exchange dynamics, are presented.
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Affiliation(s)
- Jingjing Guo
- School of Chemistry and Chemical Engineering, Henan Normal University , Xinxiang, Henan 453007, People's Republic of China
| | - Huan-Xiang Zhou
- Department of Physics and Institute of Molecular Biophysics, Florida State University , Tallahassee, Florida 32306, United States
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43
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Affiliation(s)
- Andre A. S. T. Ribeiro
- Department of Chemical Engineering, Columbia University, New York, New York 10027, United States
| | - Vanessa Ortiz
- Department of Chemical Engineering, Columbia University, New York, New York 10027, United States
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44
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Abstract
Chaperonins are nanomachines that facilitate protein folding by undergoing energy (ATP)-dependent movements that are coordinated in time and space owing to complex allosteric regulation. They consist of two back-to-back stacked oligomeric rings with a cavity at each end where protein substrate folding can take place. Here, we focus on the GroEL/GroES chaperonin system from Escherichia coli and, to a lesser extent, on the more poorly characterized eukaryotic chaperonin CCT/TRiC. We describe their various functional (allosteric) states and how they are affected by substrates and allosteric effectors that include ATP, ADP, nonfolded protein substrates, potassium ions, and GroES (in the case of GroEL). We also discuss the pathways of intra- and inter-ring allosteric communication by which they interconvert and the coupling between allosteric transitions and protein folding reactions.
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Affiliation(s)
- Ranit Gruber
- Department of Structural Biology, Weizmann Institute of Science , Rehovot 76100, Israel
| | - Amnon Horovitz
- Department of Structural Biology, Weizmann Institute of Science , Rehovot 76100, Israel
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45
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Schoeler C, Bernardi RC, Malinowska KH, Durner E, Ott W, Bayer EA, Schulten K, Nash MA, Gaub HE. Mapping Mechanical Force Propagation through Biomolecular Complexes. NANO LETTERS 2015; 15:7370-6. [PMID: 26259544 PMCID: PMC4721519 DOI: 10.1021/acs.nanolett.5b02727] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Here we employ single-molecule force spectroscopy with an atomic force microscope (AFM) and steered molecular dynamics (SMD) simulations to reveal force propagation pathways through a mechanically ultrastable multidomain cellulosome protein complex. We demonstrate a new combination of network-based correlation analysis supported by AFM directional pulling experiments, which allowed us to visualize stiff paths through the protein complex along which force is transmitted. The results implicate specific force-propagation routes nonparallel to the pulling axis that are advantageous for achieving high dissociation forces.
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Lu S, Deng R, Jiang H, Song H, Li S, Shen Q, Huang W, Nussinov R, Yu J, Zhang J. The Mechanism of ATP-Dependent Allosteric Protection of Akt Kinase Phosphorylation. Structure 2015; 23:1725-1734. [PMID: 26256536 PMCID: PMC7734571 DOI: 10.1016/j.str.2015.06.027] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2015] [Revised: 05/11/2015] [Accepted: 06/23/2015] [Indexed: 12/11/2022]
Abstract
Kinases use ATP to phosphorylate substrates; recent findings underscore the additional regulatory roles of ATP. Here, we propose a mechanism for allosteric regulation of Akt1 kinase phosphorylation by ATP. Our 4.7-μs molecular dynamics simulations of Akt1 and its mutants in the ATP/ADP bound/unbound states revealed that ATP occupancy of the ATP-binding site stabilizes the closed conformation, allosterically protecting pT308 by restraining phosphatase access and key interconnected residues on the ATP→pT308 allosteric pathway. Following ATP→ADP hydrolysis, pT308 is exposed and readily dephosphorylated. Site-directed mutagenesis validated these predictions and indicated that the mutations do not impair PDK1 and PP2A phosphatase recruitment. We further probed the function of residues around pT308 at the atomic level, and predicted and experimentally confirmed that Akt1(H194R/R273H) double mutant rescues pathology-related Akt1(R273H). Analysis of classical Akt homologs suggests that this mechanism can provide a general model of allosteric kinase regulation by ATP; as such, it offers a potential avenue for allosteric drug discovery.
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Affiliation(s)
- Shaoyong Lu
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai JiaoTong University, School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Rong Deng
- Department of Biochemistry and Molecular Cell Biology & Shanghai Key Laboratory of Tumor Microenvironment and Inflammation, Shanghai JiaoTong University, School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Haiming Jiang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai JiaoTong University, School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Huili Song
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai JiaoTong University, School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Shuai Li
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai JiaoTong University, School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Qiancheng Shen
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai JiaoTong University, School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Wenkang Huang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai JiaoTong University, School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Ruth Nussinov
- Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory, NCI, Frederick, MD 21702, USA; Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Sackler Institute of Molecular Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Jianxiu Yu
- Department of Biochemistry and Molecular Cell Biology & Shanghai Key Laboratory of Tumor Microenvironment and Inflammation, Shanghai JiaoTong University, School of Medicine (SJTU-SM), Shanghai 200025, China.
| | - Jian Zhang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai JiaoTong University, School of Medicine (SJTU-SM), Shanghai 200025, China.
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Kaur Grewal R, Mitra D, Roy S. Mapping networks of light-dark transition in LOV photoreceptors. Bioinformatics 2015. [PMID: 26209799 DOI: 10.1093/bioinformatics/btv429] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION In optogenetics, designing modules of long or short signaling state lifetime is necessary for control over precise cellular events. A critical parameter for designing artificial or synthetic photoreceptors is the signaling state lifetime of photosensor modules. Design and engineering of biologically relevant artificial photoreceptors is based on signaling mechanisms characteristic of naturally occurring photoreceptors. Therefore identifying residues important for light-dark transition is a definite first step towards rational design of synthetic photoreceptors. A thorough grasp of detailed mechanisms of photo induced signaling process would be immensely helpful in understanding the behaviour of organisms. RESULTS Herein, we introduce the technique of differential networks. We identify key biological interactions, using light-oxygen-voltage domains of all organisms whose dark and light state crystal structures are simultaneously available. Even though structural differences between dark and light states are subtle (other than the covalent bond formation between flavin chromophore and active site Cysteine), our results successfully capture functionally relevant residues and are in complete agreement with experimental findings from literature. Additionally, using sequence-structure alignments, we predict functional significance of interactions found to be important from network perspective yet awaiting experimental validation. Our approach would not only help in minimizing extensive photo-cycle kinetics procedure but is also helpful in providing first-hand information on the fundamentals of photo-adaptation and rational design of synthetic photoreceptors in optogenetics. CONTACT devrani.dbs@presiuniv.ac.in or soumen@jcbose.ac.in SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Devrani Mitra
- Department of Biological Sciences, Presidency University, Kolkata 700 073, India
| | - Soumen Roy
- Bose Institute, Kolkata 700 009, India and
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Ponzoni L, Polles G, Carnevale V, Micheletti C. SPECTRUS: A Dimensionality Reduction Approach for Identifying Dynamical Domains in Protein Complexes from Limited Structural Datasets. Structure 2015; 23:1516-1525. [PMID: 26165596 DOI: 10.1016/j.str.2015.05.022] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2015] [Revised: 05/23/2015] [Accepted: 05/29/2015] [Indexed: 02/06/2023]
Abstract
Identifying dynamical, quasi-rigid domains in proteins provides a powerful means for characterizing functionally oriented structural changes via a parsimonious set of degrees of freedom. In fact, the relative displacements of few dynamical domains usually suffice to rationalize the mechanics underpinning biological functionality in proteins and can even be exploited for structure determination or refinement purposes. Here we present SPECTRUS, a general scheme that, by solely using amino acid distance fluctuations, can pinpoint the innate quasi-rigid domains of single proteins or large complexes in a robust way. Consistent domains are usually obtained by using either a pair of representative structures or thousands of conformers. The functional insights offered by the approach are illustrated for biomolecular systems of very different size and complexity such as kinases, ion channels, and viral capsids. The decomposition tool is available as a software package and web server at spectrus.sissa.it.
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Affiliation(s)
- Luca Ponzoni
- Molecular and Statistical Biophysics, Scuola Internazionale Superiore di Studi Avanzati (SISSA), Via Bonomea 265, 34136 Trieste, Italy.
| | - Guido Polles
- Molecular and Statistical Biophysics, Scuola Internazionale Superiore di Studi Avanzati (SISSA), Via Bonomea 265, 34136 Trieste, Italy
| | - Vincenzo Carnevale
- Institute for Computational Molecular Science, College of Science and Technology, Temple University, SERC, 1925 North 12th Street, Philadelphia, PA 19122, USA
| | - Cristian Micheletti
- Molecular and Statistical Biophysics, Scuola Internazionale Superiore di Studi Avanzati (SISSA), Via Bonomea 265, 34136 Trieste, Italy
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Ribeiro AAST, Ortiz V. MDN: A Web Portal for Network Analysis of Molecular Dynamics Simulations. Biophys J 2015; 109:1110-6. [PMID: 26143656 DOI: 10.1016/j.bpj.2015.06.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2015] [Revised: 05/08/2015] [Accepted: 06/03/2015] [Indexed: 01/01/2023] Open
Abstract
We introduce a web portal that employs network theory for the analysis of trajectories from molecular dynamics simulations. Users can create protein energy networks following methodology previously introduced by our group, and can identify residues that are important for signal propagation, as well as measure the efficiency of signal propagation by calculating the network coupling. This tool, called MDN, was used to characterize signal propagation in Escherichia coli heat-shock protein 70-kDa. Two variants of this protein experimentally shown to be allosterically active exhibit higher network coupling relative to that of two inactive variants. In addition, calculations of partial coupling suggest that this quantity could be used as part of the criteria to determine pocket druggability in drug discovery studies.
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Affiliation(s)
| | - Vanessa Ortiz
- Department of Chemical Engineering, Columbia University, New York, New York.
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50
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Ligand-induced protein responses and mechanical signal propagation described by linear response theories. Biophys J 2015; 107:1415-25. [PMID: 25229149 DOI: 10.1016/j.bpj.2014.07.049] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Revised: 06/18/2014] [Accepted: 07/15/2014] [Indexed: 02/04/2023] Open
Abstract
In this study, a general linear response theory (LRT) is formulated to describe time-dependent and -independent protein conformational changes upon CO binding with myoglobin. Using the theory, we are able to monitor protein relaxation in two stages. The slower relaxation is found to occur from 4.4 to 81.2 picoseconds and the time constants characterized for a couple of aromatic residues agree with those observed by UV Resonance Raman (UVRR) spectrometry and time resolved x-ray crystallography. The faster "early responses", triggered as early as 400 femtoseconds, can be best described by the theory when impulse forces are used. The newly formulated theory describes the mechanical propagation following ligand-binding as a function of time, space and types of the perturbation forces. The "disseminators", defined as the residues that propagate signals throughout the molecule the fastest among all the residues in protein when perturbed, are found evolutionarily conserved and the mutations of which have been shown to largely change the CO rebinding kinetics in myoglobin.
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