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Manley LJ, Lin MM. Kinetic and thermodynamic allostery in the Ras protein family. Biophys J 2023; 122:3882-3893. [PMID: 37598291 PMCID: PMC10560677 DOI: 10.1016/j.bpj.2023.08.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 07/20/2023] [Accepted: 08/14/2023] [Indexed: 08/21/2023] Open
Abstract
Allostery, the transfer of information between distant parts of a macromolecule, is a fundamental feature of protein function and regulation. However, allosteric mechanisms are usually not explained by protein structure, requiring information on correlated fluctuations uniquely accessible to molecular simulation. Existing work to extract allosteric pathways from molecular dynamics simulations has focused on thermodynamic correlations. Here, we show how kinetic correlations encode complementary information essential to explain observed variations in allosteric regulation. We applied kinetic and thermodynamic correlation analysis on atomistic simulations of H, K, and NRas isoforms in the apo, GTP, and GDP-bound states of Ras protein, with and without complexing to its downstream effector, Raf. We show that switch I and switch II are the primary components of thermodynamic and kinetic allosteric networks, consistent with the key roles of these two motifs. These networks connect the switches to an allosteric loop recently discovered from a crystal structure of HRas. This allosteric loop is inactive in KRas, but is coupled to the hydrolysis arm switch II in NRas and HRas. We find that the mechanism in the latter two isoforms are thermodynamic and kinetic, respectively. Binding of Raf-RBD further activates thermodynamic allostery in HRas and KRas but has limited effect on NRas. These results indicate that kinetic and thermodynamic correlations are both needed to explain protein function and allostery. These two distinct channels of allosteric regulation, and their combinatorial variability, may explain how subtle mutational differences can lead to diverse regulatory profiles among enzymatic proteins.
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Affiliation(s)
- Leigh J Manley
- Green Center for Systems Biology, Lyda Hill Department of Bioinformatics, Department of Biophysics, Center for Alzheimer's and Neurodegenerative Diseases, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Milo M Lin
- Green Center for Systems Biology, Lyda Hill Department of Bioinformatics, Department of Biophysics, Center for Alzheimer's and Neurodegenerative Diseases, University of Texas Southwestern Medical Center, Dallas, Texas.
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2
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Madan LK, Welsh CL, Kornev AP, Taylor SS. The "violin model": Looking at community networks for dynamic allostery. J Chem Phys 2023; 158:081001. [PMID: 36859094 PMCID: PMC9957607 DOI: 10.1063/5.0138175] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 02/03/2023] [Indexed: 02/09/2023] Open
Abstract
Allosteric regulation of proteins continues to be an engaging research topic for the scientific community. Models describing allosteric communication have evolved from focusing on conformation-based descriptors of protein structural changes to appreciating the role of internal protein dynamics as a mediator of allostery. Here, we explain a "violin model" for allostery as a contemporary method for approaching the Cooper-Dryden model based on redistribution of protein thermal fluctuations. Based on graph theory, the violin model makes use of community network analysis to functionally cluster correlated protein motions obtained from molecular dynamics simulations. This Review provides the theory and workflow of the methodology and explains the application of violin model to unravel the workings of protein kinase A.
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Affiliation(s)
- Lalima K. Madan
- Author to whom correspondence should be addressed: and . Telephone: 843.792.4525. Fax: 843.792.0481
| | - Colin L. Welsh
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, 173 Ashley Ave., Charleston, South Carolina 29425, USA
| | - Alexandr P. Kornev
- Department of Pharmacology, University of California San Diego, 9500 Gilman Drive, San Diego, California, 92093, USA
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3
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Erman B. Mutual information analysis of mutation, nonlinearity, and triple interactions in proteins. Proteins 2023; 91:121-133. [PMID: 36000344 DOI: 10.1002/prot.26415] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 07/16/2022] [Accepted: 07/18/2022] [Indexed: 12/15/2022]
Abstract
Mutations are the cause of several diseases as well as the underlying force of evolution. A thorough understanding of their biophysical consequences is essential. We present a computational framework for evaluating different levels of mutual information (MI) and its dependence on mutation. We used molecular dynamics trajectories of the third PDZ domain and its different mutations. Nonlinear MI between all residue pairs are calculated by tensor Hermite polynomials up to the fifth order and compared with results from multivariate Gaussian distribution of joint probabilities. We show that MI is written as the sum of a Gaussian and a nonlinear component. Results for the PDZ domain show that the Gaussian term gives a sufficiently accurate representation of MI when compared with nonlinear terms up to the fifth order. Changes in MI between residue pairs show the characteristic patterns resulting from specific mutations. Emergence of new peaks in the MI versus residue index plots of mutated PDZ shows how mutation may change allosteric pathways. Triple correlations are characterized by evaluating MI between triplets of residues. We observed that certain triplets are strongly affected by mutation. Susceptibility of residues to perturbation is obtained by MI and discussed in terms of linear response theory.
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Affiliation(s)
- Burak Erman
- Department of Chemical and Biological Engineering, Koc University, Istanbul, Turkey
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4
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Haliloglu T, Hacisuleyman A, Erman B. Prediction of Allosteric Communication Pathways in Proteins. Bioinformatics 2022; 38:3590-3599. [PMID: 35674396 DOI: 10.1093/bioinformatics/btac380] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 04/12/2022] [Accepted: 06/01/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Allostery in proteins is an essential phenomenon in biological processes. In this paper, we present a computational model to predict paths of maximum information transfer between active and allosteric sites. In this information theoretic study, we use mutual information as the measure of information transfer, where transition probability of information from one residue to its contacting neighbors is proportional to the magnitude of mutual information between the two residues. Starting from a given residue and using a Hidden Markov Model, we successively determine the neighboring residues that eventually lead to a path of optimum information transfer. The Gaussian approximation of mutual information between residue pairs is adopted. The limits of validity of this approximation are discussed in terms of a nonlinear theory of mutual information and its reduction to the Gaussian form. RESULTS Predictions of the model are tested on six widely studied cases, CheY Bacterial Chemotaxis, B-cell Lymphoma extra-large Bcl-xL, Human proline isomerase cyclophilin A (CypA), Dihydrofolate reductase DHFR, HRas GTPase, and Caspase-1. The communication transmission rendering the propagation of local fluctuations from the active sites throughout the structure in multiple paths correlate well with the known experimental data. Distinct paths originating from the active site may likely represent a multi functionality such as involving more than one allosteric site and/or preexistence of some other functional states. Our model is computationally fast and simple, and can give allosteric communication pathways, which are crucial for the understanding and control of protein functionality. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Turkan Haliloglu
- Polymer Research Center and Chemical Engineering Department, Bogazici University, 34342, Turkey
| | - Aysima Hacisuleyman
- Institute of Bioengineering, Swiss Federal Institute of Technology (EPFL), 1015, Switzerland
| | - Burak Erman
- Chemical and Biological Engineering, Koc University, 34450, Turkey
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5
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Chatzigoulas A, Cournia Z. Rational design of allosteric modulators: Challenges and successes. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1529] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Alexios Chatzigoulas
- Biomedical Research Foundation Academy of Athens Athens Greece
- Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens Greece
| | - Zoe Cournia
- Biomedical Research Foundation Academy of Athens Athens Greece
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6
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Liu Y, Vashisth H. Allosteric Pathways Originating at Cysteine Residues in Regulators of G-Protein Signaling Proteins. Biophys J 2020; 120:517-526. [PMID: 33347886 PMCID: PMC7895990 DOI: 10.1016/j.bpj.2020.12.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 12/07/2020] [Accepted: 12/14/2020] [Indexed: 12/23/2022] Open
Abstract
Regulators of G-protein signaling (RGS) proteins play a central role in modulating signaling via G-protein coupled receptors (GPCRs). Specifically, RGS proteins bind to activated Gα subunits in G-proteins, accelerate the GTP hydrolysis, and thereby rapidly dampen GPCR signaling. Therefore, covalent molecules targeting conserved cysteine residues among RGS proteins have emerged as potential candidates to inhibit the RGS/Gα protein-protein interaction and enhance GPCR signaling. Although these inhibitors bind to conserved cysteine residues among RGS proteins, we have previously suggested [J. Am. Chem. Soc. 2018;140:3454–3460] that their potencies and specificities are related to differential protein dynamics among RGS proteins. Using data from all-atom molecular dynamics simulations, we reveal these differences in dynamics of RGS proteins by partitioning the protein structural space into a network of communities that allow allosteric signals to propagate along unique pathways originating at inhibitor binding sites and terminating at the RGS/Gα protein-protein interface.
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Affiliation(s)
- Yong Liu
- Department of Chemical Engineering, University of New Hampshire, Durham, New Hampshire
| | - Harish Vashisth
- Department of Chemical Engineering, University of New Hampshire, Durham, New Hampshire.
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7
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Liem SY, Popelier PLA. The influence of water potential in simulation: a catabolite activator protein case study. J Mol Model 2019; 25:216. [PMID: 31292786 PMCID: PMC7406532 DOI: 10.1007/s00894-019-4095-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 06/13/2019] [Indexed: 10/27/2022]
Abstract
We present a rare comparison of structures of the same protein but generated by different potentials. We used four popular water potentials (SPC, TIP3P, TIP4P, TIP5P) in conjunction with the equally popular ff99SB. However, the ff12SB protein potential was used with TI3P only. Simulations (60 ns) were run on the catabolite activator protein (CAP), which is a textbook case of allosteric interaction. Overall, all potentials generated largely similar structures but failed to reproduce a crucial structural feature determined by NMR experiment. This example shows the need to develop next-generation potentials. Graphical abstract Catabolite activator protein.
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Affiliation(s)
- Steven Y Liem
- Manchester Institute of Biotechnology (MIB), University of Manchester, 131 Princess Street, Manchester, M1 7DN, Great Britain.,School of Chemistry, University of Manchester, Oxford Road, Manchester, M13 9PL, Great Britain
| | - Paul L A Popelier
- Manchester Institute of Biotechnology (MIB), University of Manchester, 131 Princess Street, Manchester, M1 7DN, Great Britain. .,School of Chemistry, University of Manchester, Oxford Road, Manchester, M13 9PL, Great Britain.
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8
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Yu M, Chen Y, Wang ZL, Liu Z. Fluctuation correlations as major determinants of structure- and dynamics-driven allosteric effects. Phys Chem Chem Phys 2019; 21:5200-5214. [DOI: 10.1039/c8cp07859a] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Both structure- and dynamics-driven allosteric effects are determined by the correlation of distance fluctuations in proteins.
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Affiliation(s)
- Miao Yu
- College of Chemistry and Molecular Engineering
- Peking University
- Beijing 100871
- China
| | - Yixin Chen
- College of Chemistry and Molecular Engineering
- Peking University
- Beijing 100871
- China
| | - Zi-Le Wang
- Department of Physics
- Tsinghua University
- Beijing 100084
- China
| | - Zhirong Liu
- College of Chemistry and Molecular Engineering
- Peking University
- Beijing 100871
- China
- Center for Quantitative Biology
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9
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Knoverek CR, Amarasinghe GK, Bowman GR. Advanced Methods for Accessing Protein Shape-Shifting Present New Therapeutic Opportunities. Trends Biochem Sci 2018; 44:351-364. [PMID: 30555007 DOI: 10.1016/j.tibs.2018.11.007] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 09/11/2018] [Accepted: 11/20/2018] [Indexed: 12/18/2022]
Abstract
A protein is a dynamic shape-shifter whose function is determined by the set of structures it adopts. Unfortunately, atomically detailed structures are only available for a few conformations of any given protein, and these structures have limited explanatory and predictive power. Here, we provide a brief historical perspective on protein dynamics and introduce recent advances in computational and experimental methods that are providing unprecedented access to protein shape-shifting. Next, we focus on how these tools are revealing the mechanism of allosteric communication and features like cryptic pockets; both of which present new therapeutic opportunities. A major theme is the importance of considering the relative probabilities of different structures and the control one can exert over protein function by modulating this balance.
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Affiliation(s)
- Catherine R Knoverek
- Department of Biochemistry & Molecular Biophysics, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, MO 63110, USA
| | - Gaya K Amarasinghe
- Department of Pathology & Immunology, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, MO 63110, USA
| | - Gregory R Bowman
- Department of Biochemistry & Molecular Biophysics, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, MO 63110, USA.
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10
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Johnson QR, Lindsay RJ, Shen T. CAMERRA: An analysis tool for the computation of conformational dynamics by evaluating residue-residue associations. J Comput Chem 2018; 39:1568-1578. [PMID: 29464733 DOI: 10.1002/jcc.25192] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 01/04/2018] [Accepted: 01/29/2018] [Indexed: 12/20/2022]
Abstract
A computational method which extracts the dominant motions from an ensemble of biomolecular conformations via a correlation analysis of residue-residue contacts is presented. The algorithm first renders the structural information into contact matrices, then constructs the collective modes based on the correlated dynamics of a selected set of dynamic contacts. Associated programs can bridge the results for further visualization using graphics software. The aim of this method is to provide an analysis of conformations of biopolymers from the contact viewpoint. It may assist a systematical uncovering of conformational switching mechanisms existing in proteins and biopolymer systems in general by statistical analysis of simulation snapshots. In contrast to conventional correlation analyses of Cartesian coordinates (such as distance covariance analysis and Cartesian principal component analysis), this program also provides an alternative way to locate essential collective motions in general. Herein, we detail the algorithm in a stepwise manner and comment on the importance of the method as applied to decoding allosteric mechanisms. © 2018 Wiley Periodicals, Inc.
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Affiliation(s)
- Quentin R Johnson
- National Institute for Mathematical and Biological Synthesis, Knoxville, Tennessee, 37996.,Oak Ridge National Laboratory, UT-ORNL Center for Molecular Biophysics, Oak Ridge, Tennessee, 37830
| | - Richard J Lindsay
- Oak Ridge National Laboratory, UT-ORNL Center for Molecular Biophysics, Oak Ridge, Tennessee, 37830.,UT-ORNL Graduate School of Genome Science and Technology, Knoxville, Tennessee, 37996
| | - Tongye Shen
- Oak Ridge National Laboratory, UT-ORNL Center for Molecular Biophysics, Oak Ridge, Tennessee, 37830.,Department of Biochemistry Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee, 37996
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11
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Ettayapuram Ramaprasad AS, Uddin S, Casas-Finet J, Jacobs DJ. Decomposing Dynamical Couplings in Mutated scFv Antibody Fragments into Stabilizing and Destabilizing Effects. J Am Chem Soc 2017; 139:17508-17517. [PMID: 29139290 DOI: 10.1021/jacs.7b09268] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Conformational fluctuations within scFv antibodies are characterized by a novel perturbation-response decomposition of molecular dynamics trajectories. Both perturbation and response profiles are stratified into stabilizing and destabilizing conditions. The linker between the VH and VL domains exhibits the dominant dynamical response by being coupled to nearly the entire protein, responding to both stabilizing and destabilizing perturbations. Perturbations within complementarity-determining regions (CDR) induce rich behavior in dynamic response. Among many effects, stabilizing any CDR loop in the VH domain triggers a destabilizing response in all CDR loops in the VL domain and vice versa. Destabilizing residues within the VL domain are likely to stabilize all CDR loops in the VH domain, and, when these residues are not buried, the CDR loops in the VL domain are also likely to be stabilized. These effects, described by shifts in normal mode characteristics, initiate a propensity for dynamic allostery with possible functional implications in bispecific antibodies.
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Affiliation(s)
| | - Shahid Uddin
- Formulation Sciences, MedImmune Ltd. , Cambridge CB21 6GH, United Kingdom
| | - Jose Casas-Finet
- Analytical Biochemistry Department, MedImmune LLC , Gaithersburg, Maryland 20878, United States
| | - Donald J Jacobs
- Department of Physics and Optical Science, University of North Carolina at Charlotte , Charlotte, North Carolina 28223, United States
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12
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Xiao Y, Shaw GS, Konermann L. Calcium-Mediated Control of S100 Proteins: Allosteric Communication via an Agitator/Signal Blocking Mechanism. J Am Chem Soc 2017; 139:11460-11470. [PMID: 28758397 DOI: 10.1021/jacs.7b04380] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Allosteric proteins possess dynamically coupled residues for the propagation of input signals to distant target binding sites. The input signals usually correspond to "effector is present" or "effector is not present". Many aspects of allosteric regulation remain incompletely understood. This work focused on S100A11, a dimeric EF-hand protein with two hydrophobic target binding sites. An annexin peptide (Ax) served as the target. Target binding is allosterically controlled by Ca2+ over a distance of ∼26 Å. Ca2+ promotes formation of a [Ca4 S100 Ax2] complex, where the Ax peptides are accommodated between helices III/IV and III'/IV'. Without Ca2+ these binding sites are closed, precluding interactions with Ax. The allosteric mechanism was probed by microsecond MD simulations in explicit water, complemented by hydrogen exchange mass spectrometry (HDX/MS). Consistent with experimental data, MD runs in the absence of Ca2+ and Ax culminated in target binding site closure. In simulations on [Ca4 S100] the target binding sites remained open. These results capture the essence of allosteric control, revealing how Ca2+ prevents binding site closure. Both HDX/MS and MD data showed that the metalation sites become more dynamic after Ca2+ loss. However, these enhanced dynamics do not represent the primary trigger of the allosteric cascade. Instead, a labile salt bridge acts as an incessantly active "agitator" that destabilizes the packing of adjacent residues, causing a domino chain of events that culminates in target binding site closure. This agitator represents the starting point of the allosteric signal propagation pathway. Ca2+ binding rigidifies elements along this pathway, thereby blocking signal transmission. This blocking mechanism does not conform to the commonly held view that allosteric communication pathways generally originate at the sites where effectors interact with the protein.
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Affiliation(s)
- Yiming Xiao
- Department of Chemistry, The University of Western Ontario , London, Ontario N6A 5B7, Canada
| | - Gary S Shaw
- Department of Chemistry, The University of Western Ontario , London, Ontario N6A 5B7, Canada
| | - Lars Konermann
- Department of Chemistry, The University of Western Ontario , London, Ontario N6A 5B7, Canada
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13
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Singh S, Bowman GR. Quantifying Allosteric Communication via Both Concerted Structural Changes and Conformational Disorder with CARDS. J Chem Theory Comput 2017; 13:1509-1517. [PMID: 28282132 PMCID: PMC5934993 DOI: 10.1021/acs.jctc.6b01181] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Allosteric (i.e., long-range) communication within proteins is crucial for many biological processes, such as the activation of signaling cascades in response to specific stimuli. However, the physical basis for this communication remains unclear. Existing computational methods for identifying allostery focus on the role of concerted structural changes, but recent experimental work demonstrates that disorder is also an important factor. Here, we introduce the Correlation of All Rotameric and Dynamical States (CARDS) framework for quantifying correlations between both the structure and disorder of different regions of a protein. To quantify disorder, we draw inspiration from methods for quantifying "dynamic heterogeneity" from chemical physics to classify segments of a dihedral's time evolution as being in either ordered or disordered regimes. To demonstrate the utility of this approach, we apply CARDS to the Catabolite Activator Protein (CAP), a transcriptional activator that is regulated by Cyclic Adenosine MonoPhosphate (cAMP) binding. We find that CARDS captures allosteric communication between the two cAMP-Binding Domains (CBDs). Importantly, CARDS reveals that this coupling is dominated by disorder-mediated correlations, consistent with NMR experiments that establish allosteric coupling between the CBDs occurs without a concerted structural change. CARDS also recapitulates an enhanced role for disorder in the communication between the DNA-Binding Domains (DBDs) and CBDs in the S62F variant of CAP. Finally, we demonstrate that using CARDS to find communication hotspots identifies regions of CAP that are in allosteric communication without foreknowledge of their identities. Therefore, we expect CARDS to be of great utility for both understanding and predicting allostery.
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Affiliation(s)
- Sukrit Singh
- Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, MO
| | - Gregory R. Bowman
- Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, MO
- Center for Biological Systems Engineering, Washington University in St. Louis, St. Louis, MO
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