1
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Inan T, Flinko R, Lewis GK, MacKerell AD, Kurkcuoglu O. Identifying and Assessing Putative Allosteric Sites and Modulators for CXCR4 Predicted through Network Modeling and Site Identification by Ligand Competitive Saturation. J Phys Chem B 2024; 128:5157-5174. [PMID: 38647430 PMCID: PMC11139592 DOI: 10.1021/acs.jpcb.4c00925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/25/2024]
Abstract
The chemokine receptor CXCR4 is a critical target for the treatment of several cancer types and HIV-1 infections. While orthosteric and allosteric modulators have been developed targeting its extracellular or transmembrane regions, the intramembrane region of CXCR4 may also include allosteric binding sites suitable for the development of allosteric drugs. To investigate this, we apply the Gaussian Network Model (GNM) to the monomeric and dimeric forms of CXCR4 to identify residues essential for its local and global motions located in the hinge regions of the protein. Residue interaction network (RIN) analysis suggests hub residues that participate in allosteric communication throughout the receptor. Mutual residues from the network models reside in regions with a high capacity to alter receptor dynamics upon ligand binding. We then investigate the druggability of these potential allosteric regions using the site identification by ligand competitive saturation (SILCS) approach, revealing two putative allosteric sites on the monomer and three on the homodimer. Two screening campaigns with Glide and SILCS-Monte Carlo docking using FDA-approved drugs suggest 20 putative hit compounds including antifungal drugs, anticancer agents, HIV protease inhibitors, and antimalarial drugs. In vitro assays considering mAB 12G5 and CXCL12 demonstrate both positive and negative allosteric activities of these compounds, supporting our computational approach. However, in vivo functional assays based on the recruitment of β-arrestin to CXCR4 do not show significant agonism and antagonism at a single compound concentration. The present computational pipeline brings a new perspective to computer-aided drug design by combining conformational dynamics based on network analysis and cosolvent analysis based on the SILCS technology to identify putative allosteric binding sites using CXCR4 as a showcase.
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Affiliation(s)
- Tugce Inan
- Department
of Chemical Engineering, Istanbul Technical
University, Istanbul 34469, Turkey
| | - Robin Flinko
- Institute
of Human Virology, University of Maryland
School of Medicine, Baltimore, Maryland 21201, United States
| | - George K. Lewis
- Institute
of Human Virology, University of Maryland
School of Medicine, Baltimore, Maryland 21201, United States
| | - Alexander D. MacKerell
- University
of Maryland Computer-Aided Drug Design Center, Department of Pharmaceutical
Sciences, School of Pharmacy, University
of Maryland, Baltimore, Maryland 21201, United States
| | - Ozge Kurkcuoglu
- Department
of Chemical Engineering, Istanbul Technical
University, Istanbul 34469, Turkey
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2
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Gupta S, Azadvari N, Hosseinzadeh P. Design of Protein Segments and Peptides for Binding to Protein Targets. BIODESIGN RESEARCH 2022; 2022:9783197. [PMID: 37850124 PMCID: PMC10521657 DOI: 10.34133/2022/9783197] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 03/16/2022] [Indexed: 10/19/2023] Open
Abstract
Recent years have witnessed a rise in methods for accurate prediction of structure and design of novel functional proteins. Design of functional protein fragments and peptides occupy a small, albeit unique, space within the general field of protein design. While the smaller size of these peptides allows for more exhaustive computational methods, flexibility in their structure and sparsity of data compared to proteins, as well as presence of noncanonical building blocks, add additional challenges to their design. This review summarizes the current advances in the design of protein fragments and peptides for binding to targets and discusses the challenges in the field, with an eye toward future directions.
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Affiliation(s)
- Suchetana Gupta
- Knight Campus Center for Accelerating Scientific Impact, University of Oregon, Eugene OR 97403, USA
| | - Noora Azadvari
- Knight Campus Center for Accelerating Scientific Impact, University of Oregon, Eugene OR 97403, USA
| | - Parisa Hosseinzadeh
- Knight Campus Center for Accelerating Scientific Impact, University of Oregon, Eugene OR 97403, USA
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3
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Tang QY, Kaneko K. Dynamics-Evolution Correspondence in Protein Structures. PHYSICAL REVIEW LETTERS 2021; 127:098103. [PMID: 34506164 DOI: 10.1103/physrevlett.127.098103] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 07/28/2021] [Indexed: 06/13/2023]
Abstract
The genotype-phenotype mapping of proteins is a fundamental question in structural biology. In this Letter, with the analysis of a large dataset of proteins from hundreds of protein families, we quantitatively demonstrate the correlations between the noise-induced protein dynamics and mutation-induced variations of native structures, indicating the dynamics-evolution correspondence of proteins. Based on the investigations of the linear responses of native proteins, the origin of such a correspondence is elucidated. It is essential that the noise- and mutation-induced deformations of the proteins are restricted on a common low-dimensional subspace, as confirmed from the data. These results suggest an evolutionary mechanism of the proteins gaining both dynamical flexibility and evolutionary structural variability.
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Affiliation(s)
- Qian-Yuan Tang
- Center for Complex Systems Biology, Universal Biology Institute, University of Tokyo, Komaba 3-8-1, Meguro-ku, Tokyo 153-8902, Japan
- Lab for Neural Computation and Adaptation, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Kunihiko Kaneko
- Center for Complex Systems Biology, Universal Biology Institute, University of Tokyo, Komaba 3-8-1, Meguro-ku, Tokyo 153-8902, Japan
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4
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Kurkcuoglu O, Gunes MU, Haliloglu T. Local and Global Motions Underlying Antibiotic Binding in Bacterial Ribosome. J Chem Inf Model 2020; 60:6447-6461. [PMID: 33231066 DOI: 10.1021/acs.jcim.0c00967] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The bacterial ribosome is one of the most important targets in the treatment of infectious diseases. As antibiotic resistance in bacteria poses a growing threat, a significant amount of effort is concentrated on exploring new drug-binding sites where testable predictions are of significance. Here, we study the dynamics of a ribosomal complex and 67 small and large subunits of the ribosomal crystal structures (64 antibiotic-bound, 3 antibiotic-free) from Deinococcus radiodurans, Escherichia coli, Haloarcula marismortui, and Thermus thermophilus by the Gaussian network model. Interestingly, a network of nucleotides coupled in high-frequency fluctuations reveals known antibiotic-binding sites. These sites are seen to locate at the interface of dynamic domains that have an intrinsic dynamic capacity to interfere with functional globular motions. The nucleotides and the residues fluctuating in the fast and slow modes of motion thus have promise for plausible antibiotic-binding and allosteric sites that can alter antibiotic binding and resistance. Overall, the present analysis brings a new dynamic perspective to the long-discussed link between small-molecule binding and large conformational changes of the supramolecule.
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Affiliation(s)
- Ozge Kurkcuoglu
- Department of Chemical Engineering, Istanbul Technical University, Istanbul 34469, Turkey
| | - M Unal Gunes
- Polymer Research Center, Bogazici University, Istanbul 34342, Turkey
| | - Turkan Haliloglu
- Polymer Research Center, Bogazici University, Istanbul 34342, Turkey
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5
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Tang QY, Kaneko K. Long-range correlation in protein dynamics: Confirmation by structural data and normal mode analysis. PLoS Comput Biol 2020; 16:e1007670. [PMID: 32053592 PMCID: PMC7043781 DOI: 10.1371/journal.pcbi.1007670] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Revised: 02/26/2020] [Accepted: 01/21/2020] [Indexed: 11/18/2022] Open
Abstract
Proteins in cellular environments are highly susceptible. Local perturbations to any residue can be sensed by other spatially distal residues in the protein molecule, showing long-range correlations in the native dynamics of proteins. The long-range correlations of proteins contribute to many biological processes such as allostery, catalysis, and transportation. Revealing the structural origin of such long-range correlations is of great significance in understanding the design principle of biologically functional proteins. In this work, based on a large set of globular proteins determined by X-ray crystallography, by conducting normal mode analysis with the elastic network models, we demonstrate that such long-range correlations are encoded in the native topology of the proteins. To understand how native topology defines the structure and the dynamics of the proteins, we conduct scaling analysis on the size dependence of the slowest vibration mode, average path length, and modularity. Our results quantitatively describe how native proteins balance between order and disorder, showing both dense packing and fractal topology. It is suggested that the balance between stability and flexibility acts as an evolutionary constraint for proteins at different sizes. Overall, our result not only gives a new perspective bridging the protein structure and its dynamics but also reveals a universal principle in the evolution of proteins at all different sizes. The long-range correlated fluctuations are closely related to many biological processes of the proteins, such as catalysis, ligand binding, biomolecular recognition, and transportation. In this paper, we elucidate the structural origin of the long-range correlation and describe how native contact topology defines the slow-mode dynamics of the native proteins. Our result suggests an evolutionary constraint for proteins at different sizes, which may shed light on solving many biophysical problems such as structure prediction, multi-scale molecular simulations, and the design of molecular machines. Moreover, in statistical physics, as the long-range correlations are notable signs of the critical point, unveiling the origin of such criticality can extend our understanding of the organizing principle of a large variety of complex systems.
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Affiliation(s)
- Qian-Yuan Tang
- Center for Complex Systems Biology, Universal Biology Institute, University of Tokyo, Tokyo, Japan
- * E-mail:
| | - Kunihiko Kaneko
- Center for Complex Systems Biology, Universal Biology Institute, University of Tokyo, Tokyo, Japan
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6
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Gaussian network model can be enhanced by combining solvent accessibility in proteins. Sci Rep 2017; 7:7486. [PMID: 28790346 PMCID: PMC5548781 DOI: 10.1038/s41598-017-07677-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Accepted: 06/29/2017] [Indexed: 01/03/2023] Open
Abstract
Gaussian network model (GNM), regarded as the simplest and most representative coarse-grained model, has been widely adopted to analyze and reveal protein dynamics and functions. Designing a variation of the classical GNM, by defining a new Kirchhoff matrix, is the way to improve the residue flexibility modeling. We combined information arising from local relative solvent accessibility (RSA) between two residues into the Kirchhoff matrix of the parameter-free GNM. The undetermined parameters in the new Kirchhoff matrix were estimated by using particle swarm optimization. The usage of RSA was motivated by the fact that our previous work using RSA based linear regression model resulted out higher prediction quality of the residue flexibility when compared with the classical GNM and the parameter free GNM. Computational experiments, conducted based on one training dataset, two independent datasets and one additional small set derived by molecular dynamics simulations, demonstrated that the average correlation coefficients of the proposed RSA based parameter-free GNM, called RpfGNM, were significantly increased when compared with the parameter-free GNM. Our empirical results indicated that a variation of the classical GNMs by combining other protein structural properties is an attractive way to improve the quality of flexibility modeling.
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7
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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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8
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Onel M, Sumbul F, Liu J, Nussinov R, Haliloglu T. Cullin neddylation may allosterically tune polyubiquitin chain length and topology. Biochem J 2017; 474:781-795. [PMID: 28082425 PMCID: PMC7900908 DOI: 10.1042/bcj20160748] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 01/09/2017] [Accepted: 01/12/2017] [Indexed: 12/13/2022]
Abstract
Conjugation of Nedd8 (neddylation) to Cullins (Cul) in Cul-RING E3 ligases (CRLs) stimulates ubiquitination and polyubiquitination of protein substrates. CRL is made up of two Cul-flanked arms: one consists of the substrate-binding and adaptor proteins and the other consists of E2 and Ring-box protein (Rbx). Polyubiquitin chain length and topology determine the substrate fate. Here, we ask how polyubiquitin chains are accommodated in the limited space available between the two arms and what determines the polyubiquitin linkage topology. We focus on Cul5 and Rbx1 in three states: before Cul5 neddylation (closed state), after neddylation (open state), and after deneddylation, exploiting molecular dynamics simulations and the Gaussian Network Model. We observe that regulation of substrate ubiquitination and polyubiquitination takes place through Rbx1 rotations, which are controlled by Nedd8-Rbx1 allosteric communication. Allosteric propagation proceeds from Nedd8 via Cul5 dynamic hinges and hydrogen bonds between the C-terminal domain of Cul5 (Cul5CTD) and Rbx1 (Cul5CTD residues R538/R569 and Rbx1 residue E67, or Cul5CTD E474/E478/N491 and Rbx1 K105). Importantly, at each ubiquitination step (homogeneous or heterogeneous, linear or branched), the polyubiquitin linkages fit into the distances between the two arms, and these match the inherent CRL conformational tendencies. Hinge sites may constitute drug targets.
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Affiliation(s)
- Melis Onel
- Polymer Research Center and Chemical Engineering Department, Bogazici University, Istanbul, Turkey
| | - Fidan Sumbul
- Polymer Research Center and Chemical Engineering Department, Bogazici University, Istanbul, Turkey
| | - Jin Liu
- Department of Pharmaceutical Sciences, University of North Texas System College of Pharmacy, University of North Texas Health Science Center, Fort Worth, TX, U.S.A
| | - Ruth Nussinov
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, MD, U.S.A.
- Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Turkan Haliloglu
- Polymer Research Center and Chemical Engineering Department, Bogazici University, Istanbul, Turkey
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9
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Lu C, Nakajima N, Maruyama H. Observation of the flexoelectricity of a SrTiO 3 single crystal by x-ray absorption and emission spectroscopies. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2017; 29:045702. [PMID: 27882902 DOI: 10.1088/1361-648x/29/4/045702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Flexoelectricity, defined as the spontaneous electric polarization in a dielectric material induced by a strain gradient, is investigated from the microscopic viewpoint by x-ray spectroscopy. A single crystal SrTiO3 sample was used as a test system in order to reveal the appearance of the electric dipole moment by simple bending of the crystal. The spectral change characteristic of ferroelectric transition in SrTiO3 was not observed in the Ti K-edge absorption spectra. Instead, the gradual decrease (increase) of the post-edge feature (pre-edge structure) by bending was qualitatively explained using theoretical calculations that assumed the presence of oxygen vacancies and a slight crystal distortion. This assumption is also supported by the broadening of a tiny charge-transfer peak in the Ti Kβ resonant emission spectra. Therefore, it was revealed that the flexoelectric effect in SrTiO3 is easily drowned out through local imperfection induced by crystal deformations and cracks.
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Affiliation(s)
- C Lu
- Graduate School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8526, Japan
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10
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Identification of Hot Spots in Protein Structures Using Gaussian Network Model and Gaussian Naive Bayes. BIOMED RESEARCH INTERNATIONAL 2016; 2016:4354901. [PMID: 27882325 PMCID: PMC5110947 DOI: 10.1155/2016/4354901] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2016] [Revised: 10/02/2016] [Accepted: 10/11/2016] [Indexed: 01/21/2023]
Abstract
Residue fluctuations in protein structures have been shown to be highly associated with various protein functions. Gaussian network model (GNM), a simple representative coarse-grained model, was widely adopted to reveal function-related protein dynamics. We directly utilized the high frequency modes generated by GNM and further performed Gaussian Naive Bayes (GNB) to identify hot spot residues. Two coding schemes about the feature vectors were implemented with varying distance cutoffs for GNM and sliding window sizes for GNB based on tenfold cross validations: one by using only a single high mode and the other by combining multiple modes with the highest frequency. Our proposed methods outperformed the previous work that did not directly utilize the high frequency modes generated by GNM, with regard to overall performance evaluated using F1 measure. Moreover, we found that inclusion of more high frequency modes for a GNB classifier can significantly improve the sensitivity. The present study provided additional valuable insights into the relation between the hot spots and the residue fluctuations.
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11
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Wei G, Xi W, Nussinov R, Ma B. Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell. Chem Rev 2016; 116:6516-51. [PMID: 26807783 PMCID: PMC6407618 DOI: 10.1021/acs.chemrev.5b00562] [Citation(s) in RCA: 253] [Impact Index Per Article: 31.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation.
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Affiliation(s)
- Guanghong Wei
- State Key Laboratory of Surface Physics, Key Laboratory for Computational Physical Sciences (MOE), and Department of Physics, Fudan University, Shanghai, P. R. China
| | - Wenhui Xi
- State Key Laboratory of Surface Physics, Key Laboratory for Computational Physical Sciences (MOE), and Department of Physics, Fudan University, Shanghai, P. R. China
| | - Ruth Nussinov
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland 21702, USA
- Sackler Inst. of Molecular Medicine Department of Human Genetics and Molecular Medicine Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Buyong Ma
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland 21702, USA
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12
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Isaac AE, Sinha S. Analysis of core-periphery organization in protein contact networks reveals groups of structurally and functionally critical residues. J Biosci 2015; 40:683-99. [PMID: 26564971 DOI: 10.1007/s12038-015-9554-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks corresponding to the native states of 66 proteins (belonging to different families) in terms of their core-periphery organization. The resulting hierarchical classification of the amino acid constituents of a protein arranges the residues into successive layers - having higher core order - with increasing connection density, ranging from a sparsely linked periphery to a densely intra-connected core (distinct from the earlier concept of protein core defined in terms of the three-dimensional geometry of the native state, which has least solvent accessibility). Our results show that residues in the inner cores are more conserved than those at the periphery. Underlining the functional importance of the network core, we see that the receptor sites for known ligand molecules of most proteins occur in the innermost core. Furthermore, the association of residues with structural pockets and cavities in binding or active sites increases with the core order. From mutation sensitivity analysis, we show that the probability of deleterious or intolerant mutations also increases with the core order. We also show that stabilization centre residues are in the innermost cores, suggesting that the network core is critically important in maintaining the structural stability of the protein. A publicly available Web resource for performing core-periphery analysis of any protein whose native state is known has been made available by us at http://www.imsc.res.in/ ~sitabhra/proteinKcore/index.html.
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Affiliation(s)
- Arnold Emerson Isaac
- Bioinformatics Division, School of Bio Sciences and Technology, VIT University, Vellore, India
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13
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Cao P, Yoon G, Tao W, Eom K, Park HS. The role of binding site on the mechanical unfolding mechanism of ubiquitin. Sci Rep 2015; 5:8757. [PMID: 25736913 PMCID: PMC4348633 DOI: 10.1038/srep08757] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2014] [Accepted: 02/03/2015] [Indexed: 12/16/2022] Open
Abstract
We apply novel atomistic simulations based on potential energy surface exploration to investigate the constant force-induced unfolding of ubiquitin. At the experimentally-studied force clamping level of 100 pN, we find a new unfolding mechanism starting with the detachment between β5 and β3 involving the binding site of ubiquitin, the Ile44 residue. This new unfolding pathway leads to the discovery of new intermediate configurations, which correspond to the end-to-end extensions previously seen experimentally. More importantly, it demonstrates the novel finding that the binding site of ubiquitin can be responsible not only for its biological functions, but also its unfolding dynamics. We also report in contrast to previous single molecule constant force experiments that when the clamping force becomes smaller than about 300 pN, the number of intermediate configurations increases dramatically, where almost all unfolding events at 100 pN involve an intermediate configuration. By directly calculating the life times of the intermediate configurations from the height of the barriers that were crossed on the potential energy surface, we demonstrate that these intermediate states were likely not observed experimentally due to their lifetimes typically being about two orders of magnitude smaller than the experimental temporal resolution.
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Affiliation(s)
- Penghui Cao
- Department of Mechanical Engineering, Boston University, Boston, MA 02215
| | - Gwonchan Yoon
- 1] Department of Mechanical Engineering, Boston University, Boston, MA 02215 [2] Department of Mechanical Engineering, Korea University, Seoul 136-701, South Korea
| | - Weiwei Tao
- Department of Mechanical Engineering, Boston University, Boston, MA 02215
| | - Kilho Eom
- Biomechanics Laboratory, College of Sport Science, Sungkyunkwan University, Suwon 440-746, South Korea
| | - Harold S Park
- Department of Mechanical Engineering, Boston University, Boston, MA 02215
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14
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Walpoth BN, Erman B. Regulation of ryanodine receptor RyR2 by protein-protein interactions: prediction of a PKA binding site on the N-terminal domain of RyR2 and its relation to disease causing mutations. F1000Res 2015; 4:29. [PMID: 25901278 PMCID: PMC4392826 DOI: 10.12688/f1000research.5858.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/15/2015] [Indexed: 01/28/2023] Open
Abstract
Protein-protein interactions are the key processes responsible for signaling and function in complex networks. Determining the correct binding partners and predicting the ligand binding sites in the absence of experimental data require predictive models. Hybrid models that combine quantitative atomistic calculations with statistical thermodynamics formulations are valuable tools for bioinformatics predictions. We present a hybrid prediction and analysis model for determining putative binding partners and interpreting the resulting correlations in the yet functionally uncharacterized interactions of the ryanodine RyR2 N-terminal domain. Using extensive docking calculations and libraries of hexameric peptides generated from regulator proteins of the RyR2 channel, we show that the residues 318-323 of protein kinase A, PKA, have a very high affinity for the N-terminal of RyR2. Using a coarse grained Elastic Net Model, we show that the binding site lies at the end of a pathway of evolutionarily conserved residues in RyR2. The two disease causing mutations are also on this path. The program for the prediction of the energetically responsive residues by the Elastic Net Model is freely available on request from the corresponding author.
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Affiliation(s)
- Belinda Nazan Walpoth
- Swiss Cardiovascular Center, University of Bern, Inselspital, Cardiology, Bern, CH-3012, Switzerland
| | - Burak Erman
- Department of Chemical and Biological Engineering, Koc University, Instanbul, 34450 S, Turkey
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15
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Sahillioglu AC, Sumbul F, Ozoren N, Haliloglu T. Structural and dynamics aspects of ASC speck assembly. Structure 2014; 22:1722-1734. [PMID: 25458835 DOI: 10.1016/j.str.2014.09.011] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2014] [Revised: 09/17/2014] [Accepted: 09/17/2014] [Indexed: 10/24/2022]
Abstract
Activation of the inflammasome is accompanied by rapid formation of a micrometer-sized perinuclear structure called the ASC speck, a platform for caspase-1 activity. The ASC speck is often referred to as an aggregate and shares certain features with aggresomes. It is thus an open question whether the ASC speck formation takes place via nonspecific aggregation of hydrophobic patches or specific interactions of its domains; PYD and CARD, which belong to the death fold superfamily. Bringing together structure and dynamics studies using the Gaussian network model of PYD and CARD, and molecular dynamics simulations of the wild-type and in silico mutated PYD, with the mutational analysis on the ASC structure and its separate domains in human cells, we show that the ASC speck is an organized structure with at least two levels of distinct compaction mechanisms based on the specific interactions of PYD and CARD.
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Affiliation(s)
- Ali Can Sahillioglu
- Department of Molecular Biology and Genetics, Apoptosis and Cancer Immunology Laboratory (AKIL), Bogazici University, 34470 Istanbul, Turkey
| | - Fidan Sumbul
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, 34470 Istanbul, Turkey
| | - Nesrin Ozoren
- Department of Molecular Biology and Genetics, Apoptosis and Cancer Immunology Laboratory (AKIL), Bogazici University, 34470 Istanbul, Turkey; Center for Life Sciences and Technologies, Bogazici University, 34470 Istanbul, Turkey.
| | - Turkan Haliloglu
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, 34470 Istanbul, Turkey; Center for Life Sciences and Technologies, Bogazici University, 34470 Istanbul, Turkey.
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16
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Cukuroglu E, Engin HB, Gursoy A, Keskin O. Hot spots in protein–protein interfaces: Towards drug discovery. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2014; 116:165-73. [DOI: 10.1016/j.pbiomolbio.2014.06.003] [Citation(s) in RCA: 113] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2014] [Revised: 05/30/2014] [Accepted: 06/12/2014] [Indexed: 11/16/2022]
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17
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Su JG, Qi LS, Li CH, Zhu YY, Du HJ, Hou YX, Hao R, Wang JH. Prediction of allosteric sites on protein surfaces with an elastic-network-model-based thermodynamic method. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2014; 90:022719. [PMID: 25215770 DOI: 10.1103/physreve.90.022719] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2014] [Indexed: 06/03/2023]
Abstract
Allostery is a rapid and efficient way in many biological processes to regulate protein functions, where binding of an effector at the allosteric site alters the activity and function at a distant active site. Allosteric regulation of protein biological functions provides a promising strategy for novel drug design. However, how to effectively identify the allosteric sites remains one of the major challenges for allosteric drug design. In the present work, a thermodynamic method based on the elastic network model was proposed to predict the allosteric sites on the protein surface. In our method, the thermodynamic coupling between the allosteric and active sites was considered, and then the allosteric sites were identified as those where the binding of an effector molecule induces a large change in the binding free energy of the protein with its ligand. Using the proposed method, two proteins, i.e., the 70 kD heat shock protein (Hsp70) and GluA2 alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor, were studied and the allosteric sites on the protein surface were successfully identified. The predicted results are consistent with the available experimental data, which indicates that our method is a simple yet effective approach for the identification of allosteric sites on proteins.
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Affiliation(s)
- Ji Guo Su
- College of Science, Yanshan University, Qinhuangdao 066004, China
| | - Li Sheng Qi
- Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China
| | - Chun Hua Li
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100022, China
| | - Yan Ying Zhu
- College of Science, Yanshan University, Qinhuangdao 066004, China
| | - Hui Jing Du
- College of Science, Yanshan University, Qinhuangdao 066004, China
| | - Yan Xue Hou
- College of Science, Yanshan University, Qinhuangdao 066004, China
| | - Rui Hao
- College of Science, Yanshan University, Qinhuangdao 066004, China
| | - Ji Hua Wang
- Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China
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18
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Abstract
Motivation: Gaussian network model (GNM) is widely adopted to analyze and understand protein dynamics, function and conformational changes. The existing GNM-based approaches require atomic coordinates of the corresponding protein and cannot be used when only the sequence is known. Results: We report, first of its kind, GNM model that allows modeling using the sequence. Our linear regression-based, parameter-free, sequence-derived GNM (L-pfSeqGNM) uses contact maps predicted from the sequence and models local, in the sequence, contact neighborhoods with the linear regression. Empirical benchmarking shows relatively high correlations between the native and the predicted with L-pfSeqGNM B-factors and between the cross-correlations of residue fluctuations derived from the structure- and the sequence-based GNM models. Our results demonstrate that L-pfSeqGNM is an attractive platform to explore protein dynamics. In contrast to the highly used GNMs that require protein structures that number in thousands, our model can be used to study motions for the millions of the readily available sequences, which finds applications in modeling conformational changes, protein–protein interactions and protein functions. Contact:zerozhua@126.com Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Hua Zhang
- School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, P.R. China and Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada
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19
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Fornili A, Pandini A, Lu HC, Fraternali F. Specialized Dynamical Properties of Promiscuous Residues Revealed by Simulated Conformational Ensembles. J Chem Theory Comput 2013; 9:5127-5147. [PMID: 24250278 PMCID: PMC3827836 DOI: 10.1021/ct400486p] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2013] [Indexed: 12/13/2022]
Abstract
![]()
The
ability to interact with different partners is one of the most
important features in proteins. Proteins that bind a large number
of partners (hubs) have been often associated with intrinsic disorder.
However, many examples exist of hubs with an ordered structure, and
evidence of a general mechanism promoting promiscuity in ordered proteins
is still elusive. An intriguing hypothesis is that promiscuous binding
sites have specific dynamical properties, distinct from the rest of
the interface and pre-existing in the protein isolated state. Here,
we present the first comprehensive study of the intrinsic dynamics
of promiscuous residues in a large protein data set. Different computational
methods, from coarse-grained elastic models to geometry-based sampling
methods and to full-atom Molecular Dynamics simulations, were used
to generate conformational ensembles for the isolated proteins. The
flexibility and dynamic correlations of interface residues with a
different degree of binding promiscuity were calculated and compared
considering side chain and backbone motions, the latter both on a
local and on a global scale. The study revealed that (a) promiscuous
residues tend to be more flexible than nonpromiscuous ones, (b) this
additional flexibility has a higher degree of organization, and (c)
evolutionary conservation and binding promiscuity have opposite effects
on intrinsic dynamics. Findings on simulated ensembles were also validated
on ensembles of experimental structures extracted from the Protein
Data Bank (PDB). Additionally, the low occurrence of single nucleotide
polymorphisms observed for promiscuous residues indicated a tendency
to preserve binding diversity at these positions. A case study on
two ubiquitin-like proteins exemplifies how binding promiscuity in
evolutionary related proteins can be modulated by the fine-tuning
of the interface dynamics. The interplay between promiscuity and flexibility
highlighted here can inspire new directions in protein–protein
interaction prediction and design methods.
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Affiliation(s)
- Arianna Fornili
- Randall Division of Cell and Molecular Biophysics, King's College London , New Hunt's House, London SE1 1UL, United Kingdom
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20
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Ozbek P, Soner S, Haliloglu T. Hot spots in a network of functional sites. PLoS One 2013; 8:e74320. [PMID: 24023934 PMCID: PMC3759471 DOI: 10.1371/journal.pone.0074320] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2012] [Accepted: 08/02/2013] [Indexed: 12/05/2022] Open
Abstract
It is of significant interest to understand how proteins interact, which holds the key phenomenon in biological functions. Using dynamic fluctuations in high frequency modes, we show that the Gaussian Network Model (GNM) predicts hot spot residues with success rates ranging between S 8–58%, C 84–95%, P 5–19% and A 81–92% on unbound structures and S 8–51%, C 97–99%, P 14–50%, A 94–97% on complex structures for sensitivity, specificity, precision and accuracy, respectively. High specificity and accuracy rates with a single property on unbound protein structures suggest that hot spots are predefined in the dynamics of unbound structures and forming the binding core of interfaces, whereas the prediction of other functional residues with similar dynamic behavior explains the lower precision values. The latter is demonstrated with the case studies; ubiquitin, hen egg-white lysozyme and M2 proton channel. The dynamic fluctuations suggest a pseudo network of residues with high frequency fluctuations, which could be plausible for the mechanism of biological interactions and allosteric regulation.
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Affiliation(s)
- Pemra Ozbek
- Department of Bioengineering, Marmara University, Goztepe, Istanbul, Turkey
| | - Seren Soner
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, Bebek, Turkey
| | - Turkan Haliloglu
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, Bebek, Turkey
- * E-mail:
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21
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Su JG, Du HJ, Hao R, Xu XJ, Li CH, Chen WZ, Wang CX. Identification of functionally key residues in AMPA receptor with a thermodynamic method. J Phys Chem B 2013; 117:8689-96. [PMID: 23822189 DOI: 10.1021/jp402290t] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
AMPA receptor mediates the fast excitatory synaptic transmission in the central nervous system, and it is activated by the binding of glutamate that results in the opening of the transmembrane ion channel. In the present work, the thermodynamic method developed by our group was improved and then applied to identify the functionally key residues that regulate the glutamate-binding affinity of AMPA receptor. In our method, the key residues are identified as those whose perturbation largely changes the ligand binding free energy of the protein. It is found that besides the ligand binding sites, other residues distant from the binding cleft can also influence the glutamate binding affinity through a long-range allosteric regulation. These allosteric sites include the hinge region of the ligand binding cleft, the dimer interface of the ligand binding domain, the linkers between the ligand binding domain and the transmembrane domain, and the interface between the N-terminal domain and the ligand binding domain. Our calculation results are consistent with the available experimental data. The results are helpful for our understanding of the mechanism of long-range allosteric communication in the AMPA receptor and the mechanism of channel opening triggered by glutamate binding.
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Affiliation(s)
- Ji Guo Su
- College of Science, Yanshan University, Qinhuangdao, China
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22
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Identification of key residues for protein conformational transition using elastic network model. J Chem Phys 2011; 135:174101. [DOI: 10.1063/1.3651480] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
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23
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Erman B. Relationships between ligand binding sites, protein architecture and correlated paths of energy and conformational fluctuations. Phys Biol 2011; 8:056003. [DOI: 10.1088/1478-3975/8/5/056003] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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24
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Ma B, Tsai CJ, Haliloğlu T, Nussinov R. Dynamic allostery: linkers are not merely flexible. Structure 2011; 19:907-17. [PMID: 21742258 PMCID: PMC6361528 DOI: 10.1016/j.str.2011.06.002] [Citation(s) in RCA: 180] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2011] [Revised: 06/05/2011] [Accepted: 06/07/2011] [Indexed: 12/19/2022]
Abstract
Most proteins consist of multiple domains. How do linkers efficiently transfer information between sites that are on different domains to activate the protein? Mere flexibility only implies that the conformations would be sampled. For fast timescales between triggering events and cellular response, which often involves large conformational change, flexibility on its own may not constitute a good solution. We posit that successive conformational states along major allosteric propagation pathways are pre-encoded in linker sequences where each state is encoded by the previous one. The barriers between these states that are hierarchically populated are lower, achieving faster timescales even for large conformational changes. We further propose that evolution has optimized the linker sequences and lengths for efficiency, which explains why mutations in linkers may affect protein function and review the literature in this light.
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Affiliation(s)
- Buyong Ma
- Basic Science Program, SAIC-Frederick, Inc., Center for Cancer Research Nanobiology Program, NCI-Frederick, Frederick, MD 21702, USA
| | - Chung-Jung Tsai
- Basic Science Program, SAIC-Frederick, Inc., Center for Cancer Research Nanobiology Program, NCI-Frederick, Frederick, MD 21702, USA
| | - Türkan Haliloğlu
- Polymer Research Center and Chemical Engineering Department, Bogazici University, Bebek-Istanbul 34342, Turkey
| | - Ruth Nussinov
- Basic Science Program, SAIC-Frederick, Inc., Center for Cancer Research Nanobiology Program, NCI-Frederick, Frederick, MD 21702, USA
- 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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25
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Vanhee P, van der Sloot AM, Verschueren E, Serrano L, Rousseau F, Schymkowitz J. Computational design of peptide ligands. Trends Biotechnol 2011; 29:231-9. [PMID: 21316780 DOI: 10.1016/j.tibtech.2011.01.004] [Citation(s) in RCA: 118] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2010] [Revised: 01/11/2011] [Accepted: 01/12/2011] [Indexed: 12/19/2022]
Abstract
Peptides possess several attractive features when compared to small molecule and protein therapeutics, such as high structural compatibility with target proteins, the ability to disrupt protein-protein interfaces, and small size. Efficient design of high-affinity peptide ligands via rational methods has been a major obstacle to the development of this potential drug class. However, structural insights into the architecture of protein-peptide interfaces have recently culminated in several computational approaches for the rational design of peptides that target proteins. These methods provide a valuable alternative to experimental high-resolution structures of target protein-peptide complexes, bringing closer the dream of in silico designed peptides for therapeutic applications.
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Affiliation(s)
- Peter Vanhee
- VIB SWITCH Laboratory, Flanders Institute of Biotechnology (VIB), Pleinlaan 2, 1050 Brussels, Belgium
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26
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Tuzmen C, Erman B. Identification of ligand binding sites of proteins using the Gaussian Network Model. PLoS One 2011; 6:e16474. [PMID: 21283550 PMCID: PMC3026835 DOI: 10.1371/journal.pone.0016474] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2010] [Accepted: 12/31/2010] [Indexed: 12/03/2022] Open
Abstract
The nonlocal nature of the protein-ligand binding problem is investigated via the Gaussian Network Model with which the residues lying along interaction pathways in a protein and the residues at the binding site are predicted. The predictions of the binding site residues are verified by using several benchmark systems where the topology of the unbound protein and the bound protein-ligand complex are known. Predictions are made on the unbound protein. Agreement of results with the bound complexes indicates that the information for binding resides in the unbound protein. Cliques that consist of three or more residues that are far apart along the primary structure but are in contact in the folded structure are shown to be important determinants of the binding problem. Comparison with known structures shows that the predictive capability of the method is significant.
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Affiliation(s)
- Ceren Tuzmen
- Center for Computational Biology and Bioinformatics, Koc University, Istanbul Turkey
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27
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Haliloglu T, Gul A, Erman B. Predicting important residues and interaction pathways in proteins using Gaussian Network Model: binding and stability of HLA proteins. PLoS Comput Biol 2010; 6:e1000845. [PMID: 20628622 PMCID: PMC2900293 DOI: 10.1371/journal.pcbi.1000845] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2010] [Accepted: 06/02/2010] [Indexed: 01/07/2023] Open
Abstract
A statistical thermodynamics approach is proposed to determine structurally and functionally important residues in native proteins that are involved in energy exchange with a ligand and other residues along an interaction pathway. The structure-function relationships, ligand binding and allosteric activities of ten structures of HLA Class I proteins of the immune system are studied by the Gaussian Network Model. Five of these models are associated with inflammatory rheumatic disease and the remaining five are properly functioning. In the Gaussian Network Model, the protein structures are modeled as an elastic network where the inter-residue interactions are harmonic. Important residues and the interaction pathways in the proteins are identified by focusing on the largest eigenvalue of the residue interaction matrix. Predicted important residues match those known from previous experimental and clinical work. Graph perturbation is used to determine the response of the important residues along the interaction pathway. Differences in response patterns of the two sets of proteins are identified and their relations to disease are discussed. We propose a statistical thermodynamics model for determining structurally and functionally important residues in ligand-protein interactions. Our method identifies the path that the protein uses in transferring information from one point to the other. We show that a few energetically active residues are most efficient in energy exchange with the surroundings acting as ‘energy gates’. The remaining important residues that we identify are situated along the interaction path. These are the hub residues. Strong correlations exist between energy gates and hub residues along the interaction path, thus relating to allostery and cooperative binding. We studied the structure-function, ligand binding and allosteric activities of ten models of HLA Class I proteins of the immune system. Five of these models belong to the HLA-B*2705 allele and are strongly associated with a chronic inflammatory rheumatic disease. The remaining five from the HLA-B*2709 allele of the same protein are the corresponding properly functioning ones. We show that differences in the contact maps of the two types lead to significant and consistent changes in the fluctuation profile, making the HLA-B*2705 alleles respond too strongly to perturbation.
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Affiliation(s)
- Turkan Haliloglu
- Polymer Research Center, Bogazici University, Bebek, Istanbul, Turkey
- * E-mail: (TH); (BE)
| | - Ahmet Gul
- Division of Rheumatology, Department of Internal Medicine, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Burak Erman
- Center for Computational Biology and Bioinformatics, Koc University, Istanbul, Turkey
- * E-mail: (TH); (BE)
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28
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Unal EB, Gursoy A, Erman B. VitAL: Viterbi algorithm for de novo peptide design. PLoS One 2010; 5:e10926. [PMID: 20532195 PMCID: PMC2880006 DOI: 10.1371/journal.pone.0010926] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2010] [Accepted: 05/07/2010] [Indexed: 01/18/2023] Open
Abstract
Background Drug design against proteins to cure various diseases has been studied for several years. Numerous design techniques were discovered for small organic molecules for specific protein targets. The specificity, toxicity and selectivity of small molecules are hard problems to solve. The use of peptide drugs enables a partial solution to the toxicity problem. There has been a wide interest in peptide design, but the design techniques of a specific and selective peptide inhibitor against a protein target have not yet been established. Methodology/Principal Findings A novel de novo peptide design approach is developed to block activities of disease related protein targets. No prior training, based on known peptides, is necessary. The method sequentially generates the peptide by docking its residues pair by pair along a chosen path on a protein. The binding site on the protein is determined via the coarse grained Gaussian Network Model. A binding path is determined. The best fitting peptide is constructed by generating all possible peptide pairs at each point along the path and determining the binding energies between these pairs and the specific location on the protein using AutoDock. The Markov based partition function for all possible choices of the peptides along the path is generated by a matrix multiplication scheme. The best fitting peptide for the given surface is obtained by a Hidden Markov model using Viterbi decoding. The suitability of the conformations of the peptides that result upon binding on the surface are included in the algorithm by considering the intrinsic Ramachandran potentials. Conclusions/Significance The model is tested on known protein-peptide inhibitor complexes. The present algorithm predicts peptides that have better binding energies than those of the existing ones. Finally, a heptapeptide is designed for a protein that has excellent binding affinity according to AutoDock results.
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Affiliation(s)
- E. Besray Unal
- Center for Computational Biology and Bioinformatics, Koc University, Istanbul, Turkey
| | - Attila Gursoy
- Center for Computational Biology and Bioinformatics, Koc University, Istanbul, Turkey
| | - Burak Erman
- Center for Computational Biology and Bioinformatics, Koc University, Istanbul, Turkey
- * E-mail:
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29
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Ozbek P, Soner S, Erman B, Haliloglu T. DNABINDPROT: fluctuation-based predictor of DNA-binding residues within a network of interacting residues. Nucleic Acids Res 2010; 38:W417-23. [PMID: 20478828 PMCID: PMC2896127 DOI: 10.1093/nar/gkq396] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
DNABINDPROT is designed to predict DNA-binding residues, based on the fluctuations of residues in high-frequency modes by the Gaussian network model. The residue pairs that display high mean-square distance fluctuations are analyzed with respect to DNA binding, which are then filtered with their evolutionary conservation profiles and ranked according to their DNA-binding propensities. If the analyses are based on the exact outcome of fluctuations in the highest mode, using a conservation threshold of 5, the results have a sensitivity, specificity, precision and accuracy of 9.3%, 90.5%, 18.1% and 78.6%, respectively, on a dataset of 36 unbound–bound protein structure pairs. These values increase up to 24.3%, 93.4%, 45.3% and 83.3% for the respective cases, when the neighboring two residues are considered. The relatively low sensitivity appears with the identified residues being selective and susceptible more for the binding core residues rather than all DNA-binding residues. The predicted residues that are not tagged as DNA-binding residues are those whose fluctuations are coupled with DNA-binding sites. They are in close proximity as well as plausible for other functional residues, such as ligand and protein–protein interaction sites. DNABINDPROT is free and open to all users without login requirement available at: http://www.prc.boun.edu.tr/appserv/prc/dnabindprot/.
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Affiliation(s)
- Pemra Ozbek
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, Bebek, 34342 Istanbul
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30
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Abstract
Protein dynamics is essential for gaining insight into biological functions of proteins. Although protein dynamics is well delineated by molecular model, the molecular model is computationally prohibited for simulating large protein structures. In this work, we provide a multiscale network model (MNM) that allows the efficient computation on low-frequency normal modes related to structural deformation of proteins as well as dynamic behavior of functional sites. Specifically, MNM consists of two regions, one of which is described as a low-resolution structure, while the other is dictated by a high-resolution structure. The high-resolution regions using all alpha carbons of the protein are mainly binding site parts, which play a critical function in molecules, while the low-resolution parts are constructed from a further coarse-grained model (not using all alpha carbons). The feasibility of MNM to observe the cooperative motion of a protein structure was validated. It was shown that the MNM enables us to understand functional motion of proteins with computational efficiency.
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Affiliation(s)
- Hyoseon Jang
- Department of Mechanical Engineering, Korea University, Seoul 136-701, Republic of Korea
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31
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Abstract
Proteins are large and complex molecular machines. In order to perform their function, most of them need energy, e.g. either in the form of a photon, as in the case of the visual pigment rhodopsin, or through the breaking of a chemical bond, as in the presence of adenosine triphosphate (ATP). Such energy, in turn, has to be transmitted to specific locations, often several tens of A away from where it is initially released. Here we show, within the framework of a coarse-grained nonlinear network model, that energy in a protein can jump from site to site with high yields, covering in many instances remarkably large distances. Following single-site excitations, few specific sites are targeted, systematically within the stiffest regions. Such energy transfers mark the spontaneous formation of a localized mode of nonlinear origin at the destination site, which acts as an efficient energy-accumulating center. Interestingly, yields are found to be optimum for excitation energies in the range of biologically relevant ones.
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Affiliation(s)
- Francesco Piazza
- Ecole Polytechnique Fédérale de Lausanne, Laboratoire de Biophysique Statistique, ITP-SB, BSP-720, CH-1015 Lausanne, Switzerland.
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