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Kumar A, Kaynak BT, Dorman KS, Doruker P, Jernigan RL. Predicting allosteric pockets in protein biological assemblages. Bioinformatics 2023; 39:btad275. [PMID: 37115636 PMCID: PMC10185404 DOI: 10.1093/bioinformatics/btad275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 02/06/2023] [Accepted: 03/09/2023] [Indexed: 04/29/2023] Open
Abstract
MOTIVATION Allostery enables changes to the dynamic behavior of a protein at distant positions induced by binding. Here, we present APOP, a new allosteric pocket prediction method, which perturbs the pockets formed in the structure by stiffening pairwise interactions in the elastic network across the pocket, to emulate ligand binding. Ranking the pockets based on the shifts in the global mode frequencies, as well as their mean local hydrophobicities, leads to high prediction success when tested on a dataset of allosteric proteins, composed of both monomers and multimeric assemblages. RESULTS Out of the 104 test cases, APOP predicts known allosteric pockets for 92 within the top 3 rank out of multiple pockets available in the protein. In addition, we demonstrate that APOP can also find new alternative allosteric pockets in proteins. Particularly interesting findings are the discovery of previously overlooked large pockets located in the centers of many protein biological assemblages; binding of ligands at these sites would likely be particularly effective in changing the protein's global dynamics. AVAILABILITY AND IMPLEMENTATION APOP is freely available as an open-source code (https://github.com/Ambuj-UF/APOP) and as a web server at https://apop.bb.iastate.edu/.
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Affiliation(s)
- Ambuj Kumar
- Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, United States
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, United States
| | - Burak T Kaynak
- Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, United States
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15232, United States
| | - Karin S Dorman
- Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, United States
- Department of Statistics, Iowa State University, Ames, IA 50011, United States
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15232, United States
| | - Robert L Jernigan
- Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, United States
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, United States
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2
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Wah Tan Z, Tee WV, Berezovsky IN. Learning about allosteric drugs and ways to design them. J Mol Biol 2022; 434:167692. [PMID: 35738428 DOI: 10.1016/j.jmb.2022.167692] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 05/23/2022] [Accepted: 06/15/2022] [Indexed: 11/16/2022]
Abstract
While the accelerating quest for precision medicine requires new individually targeting and selective drugs, and the ability to work with so-called undruggable targets, the realm of allosteric drugs meeting this need remains largely uncharted. Generalizing the observations on two major drug targets with widely observed inherent allostery, GPCRs and kinases, we describe and discuss basic allosteric modes of action that are universally applicable in all types of structures and functions. Using examples of Class A GPCRs and CMGC protein kinases, we show how Allosteric Signalling and Probing Fingerprints can be used to identify potential allosteric sites and reveal effector-leads that may serve as a starting point for the development of allosteric drugs targeting these regulatory sites. A set of distinct characteristics of allosteric ligands was established, which highlights the versatility of their design and make them advantageous before their orthosteric counterparts in personalized medicine. We argue that rational design of allosteric drugs should begin with the search for latent sites or design of non-natural binding sites followed by fragment-based design of allosteric ligands and by the mutual adjustment of the site-ligand pair in order to achieve required effects. On the basis of the perturbative nature and reversibility of allosteric communication, we propose a generic protocol for computational design of allosteric effectors, enabling also the allosteric tuning of biologics, in obtaining allosteric control over protein functions.
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Affiliation(s)
- Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore.
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3
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Ni D, Liu Y, Kong R, Yu Z, Lu S, Zhang J. Computational elucidation of allosteric communication in proteins for allosteric drug design. Drug Discov Today 2022; 27:2226-2234. [DOI: 10.1016/j.drudis.2022.03.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 01/22/2022] [Accepted: 03/17/2022] [Indexed: 02/07/2023]
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4
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Rehman AU, Lu S, Khan AA, Khurshid B, Rasheed S, Wadood A, Zhang J. Hidden allosteric sites and De-Novo drug design. Expert Opin Drug Discov 2021; 17:283-295. [PMID: 34933653 DOI: 10.1080/17460441.2022.2017876] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Hidden allosteric sites are not visible in apo-crystal structures, but they may be visible in holo-structures when a certain ligand binds and maintains the ligand intended conformation. Several computational and experimental techniques have been used to investigate these hidden sites but identifying them remains a challenge. AREAS COVERED This review provides a summary of the many theoretical approaches for predicting hidden allosteric sites in disease-related proteins. Furthermore, promising cases have been thoroughly examined to reveal the hidden allosteric site and its modulator. EXPERT OPINION In the recent past, with the development in scientific techniques and bioinformatics tools, the number of drug targets for complex human diseases has significantly increased but unfortunately most of these targets are undruggable due to several reasons. Alternative strategies such as finding cryptic (hidden) allosteric sites are an attractive approach for exploitation of the discovery of new targets. These hidden sites are difficult to recognize compared to allosteric sites, mainly due to a lack of visibility in the crystal structure. In our opinion, after many years of development, MD simulations are finally becoming successful for obtaining a detailed molecular description of drug-target interaction.
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Affiliation(s)
- Ashfaq Ur Rehman
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Shaoyong Lu
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Abdul Aziz Khan
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, China
| | - Beenish Khurshid
- Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan
| | - Salman Rasheed
- National Center for Bioinformatics, Quaid-e-Azam University, Islamabad, Pakistan
| | - Abdul Wadood
- Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan
| | - Jian Zhang
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China.,School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
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5
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Muchiri RN, van Breemen RB. Drug discovery from natural products using affinity selection-mass spectrometry. DRUG DISCOVERY TODAY. TECHNOLOGIES 2021; 40:59-63. [PMID: 34916024 DOI: 10.1016/j.ddtec.2021.10.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 10/08/2021] [Accepted: 10/11/2021] [Indexed: 12/22/2022]
Abstract
As a starting point for drug discovery, affinity selection-mass spectrometry (AS-MS) is ideal for the discovery of lead compounds from chemically diverse sources such as botanical, fungal and microbial extracts. Based on binding interactions between macromolecular receptors and ligands of low molecular mass, AS-MS enables the rapid isolation of pharmacologically active small molecules from complex mixtures for mass spectrometric characterization and identification. Unlike conventional high-throughput screening, AS-MS requires no radiolabels, no UV or fluorescent chromophores, and is compatible with all classes of receptors, enzymes, incubation buffers, cofactors, and ligands. The most successful types of AS-MS include pulsed ultrafiltration (PUF) AS-MS, size exclusion chromatography (SEC) AS-MS, and magnetic microbead affinity selection screening (MagMASS), which differ in their approaches for separating the ligand-receptor complexes from the non-binding compounds in mixtures. After affinity isolation, the ligand(s) from the mixture are characterized using high resolution UHPLC-MS and tandem mass spectrometry. Based on these elemental composition and structural data, the identities of the lead compounds are determined by searching on-line databases for known natural products and by comparison with standards. The structures of novel natural products are determined using a combination of spectroscopic techniques including two-dimensional NMR and MS.
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Affiliation(s)
- Ruth N Muchiri
- Linus Pauling Institute, Oregon State University, Corvallis, OR 97331, United States; College of Pharmacy, Oregon State University, Corvallis, OR 97331, United States
| | - Richard B van Breemen
- Linus Pauling Institute, Oregon State University, Corvallis, OR 97331, United States; College of Pharmacy, Oregon State University, Corvallis, OR 97331, United States
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6
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Chan WKB, DasGupta D, Carlson HA, Traynor JR. Mixed-solvent molecular dynamics simulation-based discovery of a putative allosteric site on regulator of G protein signaling 4. J Comput Chem 2021; 42:2170-2180. [PMID: 34494289 DOI: 10.1002/jcc.26747] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 06/19/2021] [Accepted: 07/25/2021] [Indexed: 11/07/2022]
Abstract
Regulator of G protein signaling 4 (RGS4) is an intracellular protein that binds to the Gα subunit ofheterotrimeric G proteins and aids in terminating G protein coupled receptor signaling. RGS4 has been implicated in pain, schizophrenia, and the control of cardiac contractility. Inhibitors of RGS4 have been developed but bind covalently to cysteine residues on the protein. Therefore, we sought to identify alternative druggable sites on RGS4 using mixed-solvent molecular dynamics simulations, which employ low concentrations of organic probes to identify druggable hotspots on the protein. Pseudo-ligands were placed in consensus hotspots, and perturbation with normal mode analysis led to the identification and characterization of a putative allosteric site, which would be invaluable for structure-based drug design of non-covalent, small molecule inhibitors. Future studies on the mechanism of this allostery will aid in the development of novel therapeutics targeting RGS4.
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Affiliation(s)
- Wallace K B Chan
- Department of Pharmacology, Edward F Domino Research Center, University of Michigan, Ann Arbor, Michigan, USA
| | - Debarati DasGupta
- Department of Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan, USA
| | - Heather A Carlson
- Department of Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan, USA
| | - John R Traynor
- Department of Pharmacology, Edward F Domino Research Center, University of Michigan, Ann Arbor, Michigan, USA
- Department of Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan, USA
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7
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Celebi M, Inan T, Kurkcuoglu O, Akten ED. Potential allosteric sites captured in glycolytic enzymes via residue-based network models: Phosphofructokinase, glyceraldehyde-3-phosphate dehydrogenase and pyruvate kinase. Biophys Chem 2021; 280:106701. [PMID: 34736071 DOI: 10.1016/j.bpc.2021.106701] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 10/12/2021] [Accepted: 10/19/2021] [Indexed: 01/05/2023]
Abstract
Likelihood of new allosteric sites for glycolytic enzymes, phosphofructokinase (PFK), glyceraldehyde-3-phosphate dehydrogenase (GADPH) and pyruvate kinase (PK) was evaluated for bacterial, parasitic and human species. Allosteric effect of a ligand binding at a site was revealed on the basis of low-frequency normal modes via Cα-harmonic residue network model. In bacterial PFK, perturbation of the proposed allosteric site outperformed the known allosteric one, producing a high amount of stabilization or reduced dynamics, on all catalytic regions. Another proposed allosteric spot at the dimer interface in parasitic PFK exhibited major stabilization effect on catalytic regions. In parasitic GADPH, the most desired allosteric response was observed upon perturbation of its tunnel region which incorporated key residues for functional regulation. Proposed allosteric site in bacterial PK produced a satisfactory allosteric response on all catalytic regions, whereas in human and parasitic PKs, a partial inhibition was observed. Residue network model based solely on contact topology identified the 'hub residues' with high betweenness tracing plausible allosteric communication pathways between distant functional sites. For both bacterial PFK and PK, proposed sites accommodated hub residues twice as much as the known allosteric site. Tunnel region in parasitic GADPH with the strongest allosteric effect among species, incorporated the highest number of hub residues. These results clearly suggest a one-to-one correspondence between the degree of allosteric effect and the number of hub residues in that perturbation site, which increases the likelihood of its allosteric nature.
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Affiliation(s)
- Metehan Celebi
- Graduate Program of Computational Biology and Bioinformatics, Graduate School of Science and Engineering, Kadir Has University, Istanbul, Turkey
| | - Tugce Inan
- Department of Chemical Engineering, Istanbul Technical University, Istanbul, Turkey
| | - Ozge Kurkcuoglu
- Department of Chemical Engineering, Istanbul Technical University, Istanbul, Turkey
| | - Ebru Demet Akten
- Department of Bioinformatics and Genetics, Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Turkey.
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8
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Ni D, Chai Z, Wang Y, Li M, Yu Z, Liu Y, Lu S, Zhang J. Along the allostery stream: Recent advances in computational methods for allosteric drug discovery. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1585] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Duan Ni
- College of Pharmacy Ningxia Medical University Yinchuan China
- The Charles Perkins Centre University of Sydney Sydney New South Wales Australia
| | - Zongtao Chai
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital Second Military Medical University Shanghai China
| | - Ying Wang
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Mingyu Li
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
| | | | - Yaqin Liu
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Shaoyong Lu
- College of Pharmacy Ningxia Medical University Yinchuan China
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Jian Zhang
- College of Pharmacy Ningxia Medical University Yinchuan China
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
- School of Pharmaceutical Sciences Zhengzhou University Zhengzhou China
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9
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Civera M, Moroni E, Sorrentino L, Vasile F, Sattin S. Chemical and Biophysical Approaches to Allosteric Modulation. European J Org Chem 2021. [DOI: 10.1002/ejoc.202100506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Monica Civera
- Department of Chemistry Università degli Studi di Milano via C. Golgi, 19 20133 Milan Italy
| | - Elisabetta Moroni
- Istituto di Scienze e Tecnologie Chimiche Giulio Natta, SCITEC Via Mario Bianco 9 20131 Milan Italy
| | - Luca Sorrentino
- Department of Chemistry Università degli Studi di Milano via C. Golgi, 19 20133 Milan Italy
| | - Francesca Vasile
- Department of Chemistry Università degli Studi di Milano via C. Golgi, 19 20133 Milan Italy
| | - Sara Sattin
- Department of Chemistry Università degli Studi di Milano via C. Golgi, 19 20133 Milan Italy
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10
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Sequeiros-Borja CE, Surpeta B, Brezovsky J. Recent advances in user-friendly computational tools to engineer protein function. Brief Bioinform 2021; 22:bbaa150. [PMID: 32743637 PMCID: PMC8138880 DOI: 10.1093/bib/bbaa150] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/03/2020] [Accepted: 06/16/2020] [Indexed: 12/14/2022] Open
Abstract
Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein-protein and protein-nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.
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Affiliation(s)
- Carlos Eduardo Sequeiros-Borja
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Bartłomiej Surpeta
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Jan Brezovsky
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw
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11
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Tee WV, Tan ZW, Lee K, Guarnera E, Berezovsky IN. Exploring the Allosteric Territory of Protein Function. J Phys Chem B 2021; 125:3763-3780. [PMID: 33844527 DOI: 10.1021/acs.jpcb.1c00540] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
While the pervasiveness of allostery in proteins is commonly accepted, we further show the generic nature of allosteric mechanisms by analyzing here transmembrane ion-channel viroporin 3a and RNA-dependent RNA polymerase (RdRp) from SARS-CoV-2 along with metabolic enzymes isocitrate dehydrogenase 1 (IDH1) and fumarate hydratase (FH) implicated in cancers. Using the previously developed structure-based statistical mechanical model of allostery (SBSMMA), we share our experience in analyzing the allosteric signaling, predicting latent allosteric sites, inducing and tuning targeted allosteric response, and exploring the allosteric effects of mutations. This, yet incomplete list of phenomenology, forms a complex and unique allosteric territory of protein function, which should be thoroughly explored. We propose a generic computational framework, which not only allows one to obtain a comprehensive allosteric control over proteins but also provides an opportunity to approach the fragment-based design of allosteric effectors and drug candidates. The advantages of allosteric drugs over traditional orthosteric compounds, complemented by the emerging role of the allosteric effects of mutations in the expansion of the cancer mutational landscape and in the increased mutability of viral proteins, leave no choice besides further extensive studies of allosteric mechanisms and their biomedical implications.
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Affiliation(s)
- Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117597, Singapore
| | - Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Keene Lee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117597, Singapore
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12
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Prabantu VM, Naveenkumar N, Srinivasan N. Influence of Disease-Causing Mutations on Protein Structural Networks. Front Mol Biosci 2021; 7:620554. [PMID: 33778000 PMCID: PMC7987782 DOI: 10.3389/fmolb.2020.620554] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 12/17/2020] [Indexed: 01/18/2023] Open
Abstract
The interactions between residues in a protein tertiary structure can be studied effectively using the approach of protein structure network (PSN). A PSN is a node-edge representation of the structure with nodes representing residues and interactions between residues represented by edges. In this study, we have employed weighted PSNs to understand the influence of disease-causing mutations on proteins of known 3D structures. We have used manually curated information on disease mutations from UniProtKB/Swiss-Prot and their corresponding protein structures of wildtype and disease variant from the protein data bank. The PSNs of the wildtype and disease-causing mutant are compared to analyse variation of global and local dissimilarity in the overall network and at specific sites. We study how a mutation at a given site can affect the structural network at a distant site which may be involved in the function of the protein. We have discussed specific examples of the disease cases where the protein structure undergoes limited structural divergence in their backbone but have large dissimilarity in their all atom networks and vice versa, wherein large conformational alterations are observed while retaining overall network. We analyse the effect of variation of network parameters that characterize alteration of function or stability.
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Affiliation(s)
| | - Nagarajan Naveenkumar
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.,National Centre for Biological Sciences, TIFR, Bangalore, India.,Bharathidasan University, Tiruchirappalli, India
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13
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Pitard I, Monet D, Goossens PL, Blondel A, Malliavin TE. Analyzing In Silico the Relationship Between the Activation of the Edema Factor and Its Interaction With Calmodulin. Front Mol Biosci 2020; 7:586544. [PMID: 33344505 PMCID: PMC7746812 DOI: 10.3389/fmolb.2020.586544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 11/02/2020] [Indexed: 11/25/2022] Open
Abstract
Molecular dynamics (MD) simulations have been recorded on the complex between the edema factor (EF) of Bacilllus anthracis and calmodulin (CaM), starting from a structure with the orthosteric inhibitor adefovir bound in the EF catalytic site. The starting structure has been destabilized by alternately suppressing different co-factors, such as adefovir ligand or ions, revealing several long-distance correlations between the conformation of CaM, the geometry of the CaM/EF interface, the enzymatic site and the overall organization of the complex. An allosteric communication between CaM/EF interface and the EF catalytic site, highlighted by these correlations, was confirmed by several bioinformatics approaches from the literature. A network of hydrogen bonds and stacking interactions extending from the helix V of of CaM, and the residues of the switches A, B and C, and connecting to catalytic site residues, is a plausible candidate for the mediation of allosteric communication. The greatest variability in volume between the different MD conditions was also found for cavities present at the EF/CaM interface and in the EF catalytic site. The similarity between the predictions from literature and the volume variability might introduce the volume variability as new descriptor of allostery.
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Affiliation(s)
- Irène Pitard
- Unité de Bioinformatique Structurale, Institut Pasteur and CNRS UMR 3528, Paris, France.,Center de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur and CNRS USR 3756, Paris, France.,Ecole Doctorale Université Paris Sorbonne, Paris, France
| | - Damien Monet
- Unité de Bioinformatique Structurale, Institut Pasteur and CNRS UMR 3528, Paris, France.,Center de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur and CNRS USR 3756, Paris, France.,Ecole Doctorale Université Paris Sorbonne, Paris, France
| | | | - Arnaud Blondel
- Unité de Bioinformatique Structurale, Institut Pasteur and CNRS UMR 3528, Paris, France.,Center de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur and CNRS USR 3756, Paris, France
| | - Thérèse E Malliavin
- Unité de Bioinformatique Structurale, Institut Pasteur and CNRS UMR 3528, Paris, France.,Center de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur and CNRS USR 3756, Paris, France
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14
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Prabhakant A, Panigrahi A, Krishnan M. Allosteric Response of DNA Recognition Helices of Catabolite Activator Protein to cAMP and DNA Binding. J Chem Inf Model 2020; 60:6366-6376. [PMID: 33108170 DOI: 10.1021/acs.jcim.0c00617] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The homodimeric catabolite activator protein (CAP) regulates the transcription of several bacterial genes based on the cellular concentration of cyclic adenosine monophosphate (cAMP). The binding of cAMP to CAP triggers allosteric communication between the cAMP binding domains (CBD) and DNA binding domains (DBD) of CAP, which entails repositioning of DNA recognition helices (F-helices) in the DBD to dock favorably to the target DNA. Despite considerable progress, much remains to be understood about the mechanistic details of DNA recognition by CAP and about the map of allosteric pathways involved in CAP-mediated gene transcription. The present study uses molecular dynamics and umbrella sampling simulations to investigate the mechanism of cAMP- and DNA-induced changes in the conformation and energetics of F-helices observed during the allosteric regulation of CAP by cAMP and the subsequent binding to the DNA promoter region. Using novel collective variables, the free energy profiles associated with the orientation and dynamics of F-helices in the unliganded, cAMP-bound, and cAMP-DNA-bound states of CAP are calculated and compared. The binding-induced alterations in the resultant free energy profiles reveal important flexibility constraints imposed on DBD upon cAMP and DNA binding. A comprehensive analysis of residue-wise interaction maps reveals potential allosteric pathways between CBD and DBD that facilitate the allosteric transduction of regulatory signals in CAP. The revelation that the predicted allosteric pathways crisscross the intersubunit interface offers important clues on the microscopic origin of the intersubunit cooperativity and dimer stability of CAP.
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Affiliation(s)
- Akshay Prabhakant
- Center for Computational Natural Sciences and Bioinformatics (CCNSB), International Institute of Information Technology, Gachibowli, Hyderabad, Telangana 500032, India
| | - Abhinandan Panigrahi
- Center for Computational Natural Sciences and Bioinformatics (CCNSB), International Institute of Information Technology, Gachibowli, Hyderabad, Telangana 500032, India
| | - Marimuthu Krishnan
- Center for Computational Natural Sciences and Bioinformatics (CCNSB), International Institute of Information Technology, Gachibowli, Hyderabad, Telangana 500032, India
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15
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Tan ZW, Guarnera E, Tee WV, Berezovsky IN. AlloSigMA 2: paving the way to designing allosteric effectors and to exploring allosteric effects of mutations. Nucleic Acids Res 2020; 48:W116-W124. [PMID: 32392302 PMCID: PMC7319554 DOI: 10.1093/nar/gkaa338] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/09/2020] [Accepted: 04/22/2020] [Indexed: 12/21/2022] Open
Abstract
The AlloSigMA 2 server provides an interactive platform for exploring the allosteric signaling caused by ligand binding and/or mutations, for analyzing the allosteric effects of mutations and for detecting potential cancer drivers and pathogenic nsSNPs. It can also be used for searching latent allosteric sites and for computationally designing allosteric effectors for these sites with required agonist/antagonist activity. The server is based on the implementation of the Structure-Based Statistical Mechanical Model of Allostery (SBSMMA), which allows one to evaluate the allosteric free energy as a result of the perturbation at per-residue resolution. The Allosteric Signaling Map (ASM) providing a comprehensive residue-by-residue allosteric control over the protein activity can be obtained for any structure of interest. The Allosteric Probing Map (APM), in turn, allows one to perform the fragment-based-like computational design experiment aimed at finding leads for potential allosteric effectors. The server can be instrumental in elucidating of allosteric mechanisms and actions of allosteric mutations, and in the efforts on design of new elements of allosteric control. The server is freely available at: http://allosigma.bii.a-star.edu.sg.
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Affiliation(s)
- Zhen Wah Tan
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Enrico Guarnera
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Wei-Ven Tee
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore
| | - Igor N Berezovsky
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore
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16
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Tee WV, Guarnera E, Berezovsky IN. Disorder driven allosteric control of protein activity. Curr Res Struct Biol 2020; 2:191-203. [PMID: 34235479 PMCID: PMC8244471 DOI: 10.1016/j.crstbi.2020.09.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 08/27/2020] [Accepted: 09/02/2020] [Indexed: 12/23/2022] Open
Abstract
Studies of protein allostery increasingly reveal an involvement of the back and forth order-disorder transitions in this mechanism of protein activity regulation. Here, we investigate the allosteric mechanisms mediated by structural disorder using the structure-based statistical mechanical model of allostery (SBSMMA) that we have previously developed. We show that SBSMMA accounts for the energetics and causality of allosteric communication underlying dimerization of the BirA biotin repressor, activation of the sortase A enzyme, and inhibition of the Rac1 GTPase. Using the SBSMMA, we also show that introducing structural order or disorder in various regions of esterases can originate tunable allosteric modulation of the catalytic triad. On the basis of obtained results, we propose that operating with the order-disorder continuum allows one to establish an allosteric control scale for achieving desired modulation of the protein activity. Back and forth order-disorder transitions can induce allosteric signaling. Allosteric signaling originated by order/disorder follow universal rules. Allosteric control scale facilitates engineering of the protein activity regulation.
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Affiliation(s)
- Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive 117597, Singapore
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix 138671, Singapore
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive 117597, Singapore
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17
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Sequence-Based Prediction of Metamorphic Behavior in Proteins. Biophys J 2020; 119:1380-1390. [PMID: 32937108 PMCID: PMC7567988 DOI: 10.1016/j.bpj.2020.07.034] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 07/07/2020] [Accepted: 07/23/2020] [Indexed: 12/24/2022] Open
Abstract
An increasing number of proteins have been demonstrated in recent years to adopt multiple three-dimensional folds with different functions. These metamorphic proteins are characterized by having two or more folds with significant differences in their secondary structure, in which each fold is stabilized by a distinct local environment. So far, ∼90 metamorphic proteins have been identified in the Protein Databank, but we and others hypothesize that a far greater number of metamorphic proteins remain undiscovered. In this work, we introduce a computational model to predict metamorphic behavior in proteins using only knowledge of the sequence. In this model, secondary structure prediction programs are used to calculate diversity indices, which are measures of uncertainty in predicted secondary structure at each position in the sequence; these are then used to assign protein sequences as likely to be metamorphic versus monomorphic (i.e., having just one fold). We constructed a reference data set to train our classification method, which includes a novel compilation of 136 likely monomorphic proteins and a set of 201 metamorphic protein structures taken from the literature. Our model is able to classify proteins as metamorphic versus monomorphic with a Matthews correlation coefficient of ∼0.36 and true positive/true negative rates of ∼65%/80%, suggesting that it is possible to predict metamorphic behavior in proteins using only sequence information.
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18
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Zinc-mediated conformational preselection mechanism in the allosteric control of DNA binding to the zinc transcriptional regulator (ZitR). Sci Rep 2020; 10:13276. [PMID: 32764589 PMCID: PMC7413533 DOI: 10.1038/s41598-020-70381-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 07/23/2020] [Indexed: 12/13/2022] Open
Abstract
The zinc transcriptional regulator (ZitR) functions as a metalloregulator that fine tunes transcriptional regulation through zinc-dependent DNA binding. However, the molecular mechanism of zinc-driven allosteric control of the DNA binding to ZitR remains elusive. Here, we performed enhanced sampling accelerated molecular dynamics simulations to figure out the mechanism, revealing the role of protein dynamics in the zinc-induced allosteric control of DNA binding to ZitR. The results suggest that zinc-free ZitR samples distinct conformational states, only a handful of which are compatible with DNA binding. Remarkably, zinc binding reduces the conformational plasticity of the DNA-binding domain of ZitR, promoting the population shift in the ZitR conformational ensemble towards the DNA binding-competent conformation. Further co-binding of DNA to the zinc–ZitR complex stabilizes this competent conformation. These findings suggest that ZitR–DNA interactions are allosterically regulated in a zinc-mediated conformational preselection manner, highlighting the importance of conformational dynamics in the regulation of transcription factor family.
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19
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Verkhivker GM, Agajanian S, Hu G, Tao P. Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning. Front Mol Biosci 2020; 7:136. [PMID: 32733918 PMCID: PMC7363947 DOI: 10.3389/fmolb.2020.00136] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/08/2020] [Indexed: 12/12/2022] Open
Abstract
Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.
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Affiliation(s)
- Gennady M. Verkhivker
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, United States
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA, United States
| | - Steve Agajanian
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, United States
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Peng Tao
- Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, TX, United States
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20
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Alfayate A, Rodriguez Caceres C, Gomes Dos Santos H, Bastolla U. Predicted dynamical couplings of protein residues characterize catalysis, transport and allostery. Bioinformatics 2020; 35:4971-4978. [PMID: 31038697 DOI: 10.1093/bioinformatics/btz301] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 03/21/2019] [Accepted: 04/19/2019] [Indexed: 02/06/2023] Open
Abstract
MOTIVATION Protein function is intrinsically linked to native dynamics, but the systematic characterization of functionally relevant dynamics remains elusive besides specific examples. Here we exhaustively characterize three types of dynamical couplings between protein residues: co-directionality (moving along collinear directions), coordination (small fluctuations of the interatomic distance) and deformation (the extent by which perturbations applied at one residue modify the local structure of the other one), which we analytically compute through the torsional network model. RESULTS We find that ligand binding sites are characterized by large within-site coordination and co-directionality, much larger than expected for generic sets of residues with equivalent sequence distances. In addition, catalytic sites are characterized by high coordination couplings with other residues in the protein, supporting the view that the overall protein structure facilitates the catalytic dynamics. The binding sites of allosteric effectors are characterized by comparably smaller coordination and higher within-site deformation than other ligands, which supports their dynamic nature. Allosteric inhibitors are coupled to the active site more frequently through deformation than through coordination, while the contrary holds for activators. We characterize the dynamical couplings of the sodium-dependent Leucine transporter protein (LeuT). The couplings between and within sites progress consistently along the transport cycle, providing a mechanistic description of the coupling between the uptake and release of ions and substrate, and they highlight qualitative differences between the wild-type and a mutant for which chloride is necessary for transport. AVAILABILITY AND IMPLEMENTATION The program tnm is freely available at https://github.com/ugobas/tnm. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Alvaro Alfayate
- Centro de Biologia Molecular "Severo Ochoa" CSIC-UAM Cantoblanco, Madrid, Spain
| | | | | | - Ugo Bastolla
- Centro de Biologia Molecular "Severo Ochoa" CSIC-UAM Cantoblanco, Madrid, Spain
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21
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Allosteric drugs and mutations: chances, challenges, and necessity. Curr Opin Struct Biol 2020; 62:149-157. [DOI: 10.1016/j.sbi.2020.01.010] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 01/16/2020] [Indexed: 12/22/2022]
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22
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Ayyildiz M, Celiker S, Ozhelvaci F, Akten ED. Identification of Alternative Allosteric Sites in Glycolytic Enzymes for Potential Use as Species-Specific Drug Targets. Front Mol Biosci 2020; 7:88. [PMID: 32478093 PMCID: PMC7240002 DOI: 10.3389/fmolb.2020.00088] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 04/16/2020] [Indexed: 12/22/2022] Open
Abstract
Three allosteric glycolytic enzymes, phosphofructokinase, glyceraldehyde-3 phosphate dehydrogenase and pyruvate kinase, associated with bacterial, parasitic and human species, were explored to identify potential allosteric sites that would be used as prime targets for species-specific drug design purposes using a newly developed approach which incorporates solvent mapping, elastic network modeling, sequence and structural alignments. The majority of binding sites detected by solvent mapping overlapped with the interface regions connecting the subunits, thus appeared as promising target sites for allosteric regulation. Each binding site was then evaluated by its ability to alter the global dynamics of the receptor defined by the percentage change in the frequencies of the lowest-frequency modes most significantly and as anticipated, the most effective ones were detected in the vicinity of the well-reported catalytic and allosteric sites. Furthermore, some of our proposed regions intersected with experimentally resolved sites which are known to be critical for activity regulation, which further validated our approach. Despite the high degree of structural conservation encountered between bacterial/parasitic and human glycolytic enzymes, the majority of the newly presented allosteric sites exhibited a low degree of sequence conservation which further increased their likelihood to be used as species-specific target regions for drug design studies.
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Affiliation(s)
- Merve Ayyildiz
- Graduate Program of Computational Biology and Bioinformatics, Graduate School of Science and Engineering, Kadir Has University, Istanbul, Turkey
| | - Serkan Celiker
- Graduate Program of Computational Biology and Bioinformatics, Graduate School of Science and Engineering, Kadir Has University, Istanbul, Turkey
| | - Fatih Ozhelvaci
- Graduate Program of Computational Science and Engineering, Graduate School of Science and Engineering, Bogazici University, Istanbul, Turkey
| | - E. Demet Akten
- Department of Bioinformatics and Genetics, Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Turkey
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23
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Tan ZW, Tee WV, Guarnera E, Booth L, Berezovsky IN. AlloMAPS: allosteric mutation analysis and polymorphism of signaling database. Nucleic Acids Res 2020; 47:D265-D270. [PMID: 30365033 PMCID: PMC6323965 DOI: 10.1093/nar/gky1028] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 10/16/2018] [Indexed: 01/06/2023] Open
Abstract
AlloMAPS database provides data on the causality and energetics of allosteric communication obtained with the structure-based statistical mechanical model of allostery (SBSMMA). The database contains data on allosteric signaling in three sets of proteins and protein chains: (i) 46 proteins with comprehensively annotated functional and allosteric sites; (ii) 1908 protein chains from PDBselect set of chains with low (<25%) sequence identity; (iii) 33 proteins with more than 50 known pathological SNPs in each molecule. In addition to energetics of allosteric signaling between known functional and regulatory sites, allosteric modulation caused by the binding to these sites, by SNPs, and by mutations designated by the user can be explored. Allosteric Signaling Maps (ASMs), which are produced via the exhaustive computational scanning for stabilizing and destabilizing mutations and for the modulation range caused by the sequence position are available for each protein/protein chain in the database. We propose to use this database for evaluating the effects of allosteric signaling in the search for latent regulatory sites and in the design of allosteric sites and effectors. The database is freely available at: http://allomaps.bii.a-star.edu.sg.
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Affiliation(s)
- Zhen Wah Tan
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671 Singapore
| | - Wei-Ven Tee
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671 Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579 Singapore
| | - Enrico Guarnera
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671 Singapore
| | - Lauren Booth
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671 Singapore.,Research School of Chemistry, The Australian National University, Canberra, ACT 2601, Australia
| | - Igor N Berezovsky
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671 Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579 Singapore
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24
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The past, present and future perspectives of matrix metalloproteinase inhibitors. Pharmacol Ther 2020; 207:107465. [DOI: 10.1016/j.pharmthera.2019.107465] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 12/13/2019] [Indexed: 12/12/2022]
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25
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Sheik Amamuddy O, Veldman W, Manyumwa C, Khairallah A, Agajanian S, Oluyemi O, Verkhivker GM, Tastan Bishop Ö. Integrated Computational Approaches and Tools forAllosteric Drug Discovery. Int J Mol Sci 2020; 21:E847. [PMID: 32013012 PMCID: PMC7036869 DOI: 10.3390/ijms21030847] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Revised: 01/20/2020] [Accepted: 01/21/2020] [Indexed: 12/16/2022] Open
Abstract
Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.
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Affiliation(s)
- Olivier Sheik Amamuddy
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Wayde Veldman
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Colleen Manyumwa
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Afrah Khairallah
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Steve Agajanian
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA; (S.A.); (O.O.)
| | - Odeyemi Oluyemi
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA; (S.A.); (O.O.)
| | - Gennady M. Verkhivker
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA; (S.A.); (O.O.)
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
| | - Özlem Tastan Bishop
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
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26
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Leveraging protein dynamics to identify cancer mutational hotspots using 3D structures. Proc Natl Acad Sci U S A 2019; 116:18962-18970. [PMID: 31462496 PMCID: PMC6754584 DOI: 10.1073/pnas.1901156116] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Large-scale exome sequencing of tumors has enabled the identification of cancer drivers using recurrence-based approaches. Some of these methods also employ 3D protein structures to identify mutational hotspots in cancer-associated genes. In determining such mutational clusters in structures, existing approaches overlook protein dynamics, despite its essential role in protein function. We present a framework to identify cancer driver genes using a dynamics-based search of mutational hotspot communities. Mutations are mapped to protein structures, which are partitioned into distinct residue communities. These communities are identified in a framework where residue-residue contact edges are weighted by correlated motions (as inferred by dynamics-based models). We then search for signals of positive selection among these residue communities to identify putative driver genes, while applying our method to the TCGA (The Cancer Genome Atlas) PanCancer Atlas missense mutation catalog. Overall, we predict 1 or more mutational hotspots within the resolved structures of proteins encoded by 434 genes. These genes were enriched among biological processes associated with tumor progression. Additionally, a comparison between our approach and existing cancer hotspot detection methods using structural data suggests that including protein dynamics significantly increases the sensitivity of driver detection.
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27
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Astl L, Verkhivker GM. Data-driven computational analysis of allosteric proteins by exploring protein dynamics, residue coevolution and residue interaction networks. Biochim Biophys Acta Gen Subj 2019:S0304-4165(19)30179-5. [PMID: 31330173 DOI: 10.1016/j.bbagen.2019.07.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2019] [Revised: 07/15/2019] [Accepted: 07/17/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND Computational studies of allosteric interactions have witnessed a recent renaissance fueled by the growing interest in modeling of the complex molecular assemblies and biological networks. Allosteric interactions in protein structures allow for molecular communication in signal transduction networks. METHODS In this work, we performed a large scale comprehensive and multi-faceted analysis of >300 diverse allosteric proteins and complexes with allosteric modulators. By modeling and exploring coarse-grained dynamics, residue coevolution, and residue interaction networks for allosteric proteins, we have determined unifying molecular signatures shared by allosteric systems. RESULTS The results of this study have suggested that allosteric inhibitors and allosteric activators may differentially affect global dynamics and network organization of protein systems, leading to diverse allosteric mechanisms. By using structural and functional data on protein kinases, we present a detailed case study that that included atomic-level analysis of coevolutionary networks in kinases bound with allosteric inhibitors and activators. CONCLUSIONS We have found that coevolutionary networks can form direct communication pathways connecting functional regions and can recapitulate key regulatory sites and interactions responsible for allosteric signaling in the studied protein systems. The results of this computational investigation are compared with the experimental studies and reveal molecular signatures of known regulatory hotspots in protein kinases. GENERAL SIGNIFICANCE This study has shown that allosteric inhibitors and allosteric activators can have a different effect on residue interaction networks and can exploit distinct regulatory mechanisms, which could open up opportunities for probing allostery and new drug combinations with broad range of activities.
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Affiliation(s)
- Lindy Astl
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, United States of America
| | - Gennady M Verkhivker
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, United States of America; Department of Pharmacology, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States of America.
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28
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On the perturbation nature of allostery: sites, mutations, and signal modulation. Curr Opin Struct Biol 2019; 56:18-27. [DOI: 10.1016/j.sbi.2018.10.008] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 10/27/2018] [Accepted: 10/30/2018] [Indexed: 10/27/2022]
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29
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Guarnera E, Berezovsky IN. Toward Comprehensive Allosteric Control over Protein Activity. Structure 2019; 27:866-878.e1. [PMID: 30827842 DOI: 10.1016/j.str.2019.01.014] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 11/23/2018] [Accepted: 01/25/2019] [Indexed: 01/14/2023]
Abstract
Universality of allosteric signaling in proteins, molecular machines, and receptors complemented by the great advantages of prospected allosteric drugs in the highly specific, non-competitive, and modulatory nature of their actions calls for deeper theoretical understanding of allosteric communication. We present a computational model that makes it possible to tackle the problem of modulating the energetics of protein allosteric communication. In the context of the energy landscape paradigm, allosteric signaling is always a result of perturbations, such as ligand binding, mutations, and intermolecular interactions. The calculation of local partition functions in the protein harmonic model with perturbations allows us to evaluate the energetics of allosteric communication at the single-residue level. In this framework, Allosteric Signaling Maps are proposed as a tool to exhaustively describe allosteric communication in the protein, to tune already existing signaling, and to design new elements of regulation for taking the protein activity under allosteric control.
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Affiliation(s)
- Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A(∗)STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A(∗)STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore 117579, Singapore.
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30
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Astl L, Tse A, Verkhivker GM. Interrogating Regulatory Mechanisms in Signaling Proteins by Allosteric Inhibitors and Activators: A Dynamic View Through the Lens of Residue Interaction Networks. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1163:187-223. [DOI: 10.1007/978-981-13-8719-7_9] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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31
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Zhang W, Xie J, Lai L. Correlation Between Allosteric and Orthosteric Sites. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1163:89-105. [PMID: 31707701 DOI: 10.1007/978-981-13-8719-7_5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Correlation between an allosteric site and its orthosteric site refers to the phenomenon that perturbations like ligand binding, mutation, or posttranslational modifications at the allosteric site leverage variation in the orthosteric site. Understanding this kind of correlation not only helps to disclose how information is transmitted in allosteric regulation but also provides clues for allosteric drug discovery. This chapter starts with an overview of correlation studies on allosteric and orthosteric sites and then introduces recent progress in evolutionary and simulation-based dynamic studies. Discussions and perspectives on future directions are also given.
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Affiliation(s)
- Weilin Zhang
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China
- Center for Quantitative Biology, AAIS, Peking University, Beijing, China
| | - Juan Xie
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China
- Center for Quantitative Biology, AAIS, Peking University, Beijing, China
| | - Luhua Lai
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China.
- Center for Quantitative Biology, AAIS, Peking University, Beijing, China.
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32
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Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response. PLoS Comput Biol 2018; 14:e1006228. [PMID: 29912863 PMCID: PMC6023240 DOI: 10.1371/journal.pcbi.1006228] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 06/28/2018] [Accepted: 05/23/2018] [Indexed: 12/27/2022] Open
Abstract
The omnipresence of allosteric regulation together with the fundamental role of structural dynamics in this phenomenon have initiated a great interest to the detection of regulatory exosites and design of corresponding effectors. However, despite a general consensus on the key role of dynamics most of the earlier efforts on the prediction of allosteric sites are heavily crippled by the static nature of the underlying methods, which are either structure-based approaches seeking for deep surface pockets typical for “traditional” orthosteric drugs or sequence-based techniques exploiting the conservation of protein sequences. Because of the critical role of global protein dynamics in allosteric signaling, we investigate the hypothesis of reversibility in allosteric communication, according to which allosteric sites can be detected via the perturbation of the functional sites. The reversibility is tested here using our structure-based perturbation model of allostery, which allows one to analyze the causality and energetics of allosteric communication. We validate the “reverse perturbation” hypothesis and its predictive power on a set of classical allosteric proteins, then, on the independent extended benchmark set. We also show that, in addition to known allosteric sites, the perturbation of the functional sites unravels rather extended protein regions, which can host latent regulatory exosites. These protein parts that are dynamically coupled with functional sites can also be used for inducing and tuning allosteric communication, and an exhaustive exploration of the per-residue contributions to allosteric effects can eventually lead to the optimal modulation of protein activity. The site-effector interactions necessary for a specific mode and level of allosteric communication can be fine-tuned by adjusting the site’s structure to an available effector molecule and by the design or selection of an appropriate ligand. Recent advances in the development of allosteric drugs allow one to fully appreciate the sheer power of allosteric effectors in the avoiding toxicity, receptor desensitization and modulatory rather than on/off mode of action, compared to the traditional orthosteric compounds. The detection of allosteric sites is one of the major challenges in the quest for allosteric drugs. This work proposes a “reverse perturbation” approach for identifying allosteric sites as a result of a perturbation applied to the functional ones. We show that according to the traditional Monod-Changeux-Jacob’s definition of allostery, considering non-overlapping regulatory and functional sites is a critical prerequisite for the successful detection of allosteric sites. Using the reverse perturbation method, it is possible to determine wide protein regions with a potential to induce an allosteric response and to adjust its strength. Further studies on inducing and fine-tuning of allosteric signalling seem to be of a great importance for efficient design of non-orthosteric ligands in the development of novel drugs.
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33
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Greener JG, Sternberg MJE. Structure-based prediction of protein allostery. Curr Opin Struct Biol 2018; 50:1-8. [DOI: 10.1016/j.sbi.2017.10.002] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2017] [Accepted: 10/02/2017] [Indexed: 11/15/2022]
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34
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Song K, Liu X, Huang W, Lu S, Shen Q, Zhang L, Zhang J. Improved Method for the Identification and Validation of Allosteric Sites. J Chem Inf Model 2017; 57:2358-2363. [DOI: 10.1021/acs.jcim.7b00014] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Kun Song
- Department of Pathophysiology, Key Laboratory
of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
| | - Xinyi Liu
- Department of Pathophysiology, Key Laboratory
of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
| | - Wenkang Huang
- Department of Pathophysiology, Key Laboratory
of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
| | - Shaoyong Lu
- Department of Pathophysiology, Key Laboratory
of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
| | - Qiancheng Shen
- Department of Pathophysiology, Key Laboratory
of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
| | - Lu Zhang
- Department of Pathophysiology, Key Laboratory
of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
| | - Jian Zhang
- Department of Pathophysiology, Key Laboratory
of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
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35
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Krimm I. Identifying Protein Allosteric Transitions for Drug Discovery with 1D NMR. ChemMedChem 2017; 12:901-904. [PMID: 28263035 DOI: 10.1002/cmdc.201700064] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 03/06/2017] [Indexed: 01/04/2023]
Abstract
Allosteric drugs present many advantages over orthosteric drugs and are therefore an attractive approach in drug discovery, despite being highly challenging. First, the binding of ligands in protein allosteric pockets do not ensure an allosteric effect, and second, allosteric ligands can possess diverse modes of pharmacology even within a compound family. Herein we report a new method to: 1) detect allosteric communication between protein binding sites, and 2) compare the effect of allosteric ligands on the allosteric transitions of the protein target. The method, illustrated with glycogen phosphorylase, consists of comparing 1D saturation transfer difference (STD) NMR spectra of a molecular spy (here fragments) in the absence and presence of allosteric ligands. The modification of the STD NMR spectrum of the fragment indicates whether the protein dynamics/conformations have been changed in the presence of the allosteric modulator, thereby highlighting allosteric coupling between the binding pocket of the reference compound (in this case the fragment) and the allosteric pocket.
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Affiliation(s)
- Isabelle Krimm
- CNRS, Université Claude Bernard Lyon 1, ENS de Lyon, Institut des Sciences Analytiques, UMR 5280, 5 rue de la Doua, 69100, Villeurbanne, France
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36
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Greener JG, Filippis I, Sternberg MJE. Predicting Protein Dynamics and Allostery Using Multi-Protein Atomic Distance Constraints. Structure 2017; 25:546-558. [PMID: 28190781 PMCID: PMC5343748 DOI: 10.1016/j.str.2017.01.008] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 11/24/2016] [Accepted: 01/19/2017] [Indexed: 11/16/2022]
Abstract
The related concepts of protein dynamics, conformational ensembles and allostery are often difficult to study with molecular dynamics (MD) due to the timescales involved. We present ExProSE (Exploration of Protein Structural Ensembles), a distance geometry-based method that generates an ensemble of protein structures from two input structures. ExProSE provides a unified framework for the exploration of protein structure and dynamics in a fast and accessible way. Using a dataset of apo/holo pairs it is shown that existing coarse-grained methods often cannot span large conformational changes. For T4-lysozyme, ExProSE is able to generate ensembles that are more native-like than tCONCOORD and NMSim, and comparable with targeted MD. By adding additional constraints representing potential modulators, ExProSE can predict allosteric sites. ExProSE ranks an allosteric pocket first or second for 27 out of 58 allosteric proteins, which is similar and complementary to existing methods. The ExProSE source code is freely available.
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Affiliation(s)
- Joe G Greener
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK.
| | - Ioannis Filippis
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
| | - Michael J E Sternberg
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
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37
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Proteome-Scale Investigation of Protein Allosteric Regulation Perturbed by Somatic Mutations in 7,000 Cancer Genomes. Am J Hum Genet 2017; 100:5-20. [PMID: 27939638 DOI: 10.1016/j.ajhg.2016.09.020] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2016] [Accepted: 09/27/2016] [Indexed: 02/05/2023] Open
Abstract
The allosteric regulation triggering the protein's functional activity via conformational changes is an intrinsic function of protein under many physiological and pathological conditions, including cancer. Identification of the biological effects of specific somatic variants on allosteric proteins and the phenotypes that they alter during tumor initiation and progression is a central challenge for cancer genomes in the post-genomic era. Here, we mapped more than 47,000 somatic missense mutations observed in approximately 7,000 tumor-normal matched samples across 33 cancer types into protein allosteric sites to prioritize the mutated allosteric proteins and we tested our prediction in cancer cell lines. We found that the deleterious mutations identified in cancer genomes were more significantly enriched at protein allosteric sites than tolerated mutations, suggesting a critical role for protein allosteric variants in cancer. Next, we developed a statistical approach, namely AlloDriver, and further identified 15 potential mutated allosteric proteins during pan-cancer and individual cancer-type analyses. More importantly, we experimentally confirmed that p.Pro360Ala on PDE10A played a potential oncogenic role in mediating tumorigenesis in non-small cell lung cancer (NSCLC). In summary, these findings shed light on the role of allosteric regulation during tumorigenesis and provide a useful tool for the timely development of targeted cancer therapies.
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38
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Su CTT, Ling WL, Lua WH, Haw YX, Gan SKE. Structural analyses of 2015-updated drug-resistant mutations in HIV-1 protease: an implication of protease inhibitor cross-resistance. BMC Bioinformatics 2016; 17:500. [PMID: 28155724 PMCID: PMC5259968 DOI: 10.1186/s12859-016-1372-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Background Strategies to control HIV for improving the quality of patient lives have been aided by the Highly Active Anti-Retroviral Therapy (HAART), which consists of a cocktail of inhibitors targeting key viral enzymes. Numerous new drugs have been developed over the past few decades but viral resistances to these drugs in the targeted viral enzymes are increasingly reported. Nonetheless the acquired mutations often reduce viral fitness and infectivity. Viral compensatory secondary-line mutations mitigate this loss of fitness, equipping the virus with a broad spectrum of resistance against these drugs. While structural understanding of the viral protease and its drug resistance mutations have been well established, the interconnectivity and development of structural cross-resistance remain unclear. This paper reports the structural analyses of recent clinical mutations on the drug cross-resistance effects from various protease and protease inhibitors (PIs) complexes. Methods Using the 2015 updated clinical HIV protease mutations, we constructed a structure-based correlation network and a minimum-spanning tree (MST) based on the following features: (i) topology of the PI-binding pocket, (ii) allosteric effects of the mutations, and (iii) protease structural stability. Results and conclusion Analyis of the network and the MST of dominant mutations conferring resistance to the seven PIs (Atazanavir-ATV, Darunavir-DRV, Indinavir-IDV, Lopinavir-LPV, Nelfinavir-NFV, Saquinavir-SQV, and Tipranavir-TPV) showed that cross-resistance can develop easily across NFV, SQV, LPV, IDV, and DRV, but not for ATV or TPV. Through estimation of the changes in vibrational entropies caused by each reported mutation, some secondary mutations were found to destabilize protease structure. Our findings provide an insight into the mechanism of PI cross-resistance and may also be useful in guiding the selection of PI in clinical treatment to delay the onset of cross drug resistance. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1372-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Chinh Tran-To Su
- Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore, 138671, Singapore.
| | - Wei-Li Ling
- Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore, 138671, Singapore
| | - Wai-Heng Lua
- Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore, 138671, Singapore
| | - Yu-Xuan Haw
- Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore, 138671, Singapore
| | - Samuel Ken-En Gan
- Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore, 138671, Singapore. .,p53 Laboratory, Agency for Science, Technology, and Research (A*STAR), Singapore, 138648, Singapore.
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39
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Kurochkin IV, Guarnera E, Wong JH, Eisenhaber F, Berezovsky IN. Toward Allosterically Increased Catalytic Activity of Insulin-Degrading Enzyme against Amyloid Peptides. Biochemistry 2016; 56:228-239. [PMID: 27982586 DOI: 10.1021/acs.biochem.6b00783] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The physiological role of insulin-degrading enzyme (IDE) in the intracytosolic clearance of amyloid β (Aβ) and other amyloid-like peptides supports a hypothesis that human IDE hyperactivation could be therapeutically beneficial for the treatment of late-onset Alzheimer's disease (AD). The major challenge standing in the way of this goal is increasing the specific catalytic activity of IDE against the Aβ substrate. There were previous indications that the allosteric mode of IDE activity regulation could potentially provide a highly specific path toward degradation of amyloid-like peptides, while not dramatically affecting activity against other substrates. Recently developed theoretical concepts are used here to explore potential allosteric modulation of the IDE activity as a result of single-residue mutations. Five candidates are selected for experimental follow-up and allosteric free energy calculations: Ser137Ala, Lys396Ala, Asp426Ala, Phe807Ala, and Lys898Ala. Our experiments show that three mutations (Ser137Ala, Phe807Ala, and Lys898Ala) decrease the Km of the Aβ substrate. Mutation Lys898Ala results in increased catalytic activity of IDE; on the other hand, Lys364Ala does not change the activity and Asp426Ala diminishes it. Quantifying effects of mutations in terms of allosteric free energy, we show that favorable mutations lead to stabilization of the catalytic sites and other function-relevant distal sites as well as increased dynamics of the IDE-N and IDE-C halves that allow efficient substrate entrance and cleavage. A possibility for intramolecular upregulation of IDE activity against amyloid peptides via allosteric mutations calls for further investigations in this direction. Ultimately, we are hopeful it will lead to the development of IDE-based drugs for the treatment of the late-onset form of AD characterized by an overall impairment of Aβ clearance.
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Affiliation(s)
- Igor V Kurochkin
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR) , 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR) , 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Jin H Wong
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR) , 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Frank Eisenhaber
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR) , 30 Biopolis Street, #07-01, Matrix, Singapore 138671.,Department of Biological Sciences (DBS), National University of Singapore (NUS) , 8 Medical Drive, Singapore 117579.,School of Computer Engineering (SCE), Nanyang Technological University (NTU) , 50 Nanyang Drive, Singapore 637553
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR) , 30 Biopolis Street, #07-01, Matrix, Singapore 138671.,Department of Biological Sciences (DBS), National University of Singapore (NUS) , 8 Medical Drive, Singapore 117579
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40
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Marques SM, Daniel L, Buryska T, Prokop Z, Brezovsky J, Damborsky J. Enzyme Tunnels and Gates As Relevant Targets in Drug Design. Med Res Rev 2016; 37:1095-1139. [PMID: 27957758 DOI: 10.1002/med.21430] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Revised: 10/11/2016] [Accepted: 11/07/2016] [Indexed: 12/28/2022]
Abstract
Many enzymes contain tunnels and gates that are essential to their function. Gates reversibly switch between open and closed conformations and thereby control the traffic of small molecules-substrates, products, ions, and solvent molecules-into and out of the enzyme's structure via molecular tunnels. Many transient tunnels and gates undoubtedly remain to be identified, and their functional roles and utility as potential drug targets have received comparatively little attention. Here, we describe a set of general concepts relating to the structural properties, function, and classification of these interesting structural features. In addition, we highlight the potential of enzyme tunnels and gates as targets for the binding of small molecules. The different types of binding that are possible and the potential pharmacological benefits of such targeting are discussed. Twelve examples of ligands bound to the tunnels and/or gates of clinically relevant enzymes are used to illustrate the different binding modes and to explain some new strategies for drug design. Such strategies could potentially help to overcome some of the problems facing medicinal chemists and lead to the discovery of more effective drugs.
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Affiliation(s)
- Sergio M Marques
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic
| | - Lukas Daniel
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Tomas Buryska
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Zbynek Prokop
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Jan Brezovsky
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Jiri Damborsky
- Loschmidt Laboratories, Faculty of Science, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, RECETOX, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,International Centre for Clinical Research, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
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41
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Berezovsky IN, Guarnera E, Zheng Z, Eisenhaber B, Eisenhaber F. Protein function machinery: from basic structural units to modulation of activity. Curr Opin Struct Biol 2016; 42:67-74. [PMID: 27865209 DOI: 10.1016/j.sbi.2016.10.021] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Revised: 09/26/2016] [Accepted: 10/31/2016] [Indexed: 11/29/2022]
Abstract
Contemporary protein structure is a result of the trade off between the laws of physics and the evolutionary selection. The polymer nature of proteins played a decisive role in establishing the basic structural and functional units of soluble proteins. We discuss how these elementary building blocks work in the hierarchy of protein domain structure, co-translational folding, as well as in enzymatic activity and molecular interactions. Next, we consider modulators of the protein function, such as intermolecular interactions, disorder-to-order transitions, and allosteric signaling, acting via interference with the protein's structural dynamics. We also discuss the post-translational modifications, which is a complementary intricate mechanism evolved for regulation of protein functions and interactions. In conclusion, we assess an anticipated contribution of discussed topics to the future advancements in the field.
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Affiliation(s)
- Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore 117579, Singapore.
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore
| | - Zejun Zheng
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore
| | - Birgit Eisenhaber
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore
| | - Frank Eisenhaber
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore; School of Computer Engineering (SCE), Nanyang Technological University (NTU), 50 Nanyang Drive, Singapore 637553, Singapore
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42
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Long S, Tian P. Nonlinear backbone torsional pair correlations in proteins. Sci Rep 2016; 6:34481. [PMID: 27708342 PMCID: PMC5052647 DOI: 10.1038/srep34481] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Accepted: 09/14/2016] [Indexed: 12/27/2022] Open
Abstract
Protein allostery requires dynamical structural correlations. Physical origin of which, however, remain elusive despite intensive studies during last two and half decades. Based on analysis of molecular dynamics (MD) simulation trajectories for ten proteins with different sizes and folds, we found that nonlinear backbone torsional pair (BTP) correlations, which are mainly spatially long-ranged and are dominantly executed by loop residues, exist extensively in most analyzed proteins. Examination of torsional motion for correlated BTPs suggested that such nonlinear correlations are mainly associated aharmonic torsional state transitions and in some cases strongly anisotropic local torsional motion of participating torsions, and occur on widely different and relatively longer time scales. In contrast, correlations between backbone torsions in stable α helices and β strands are mainly linear and spatially short-ranged, and are more likely to associate with harmonic local torsional motion. Further analysis revealed that the direct cause of nonlinear contributions are heterogeneous linear correlations. These findings implicate a general search strategy for novel allosteric modulation sites of protein activities.
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Affiliation(s)
- Shiyang Long
- School of Life Sciences, Jilin University, Changchun, 130012 China
| | - Pu Tian
- School of Life Sciences, Jilin University, Changchun, 130012 China.,MOE Key Laboratory of Molecular Enzymology and Engineering, Jilin University, Changchun, 130012 China
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43
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Ma X, Meng H, Lai L. Motions of Allosteric and Orthosteric Ligand-Binding Sites in Proteins are Highly Correlated. J Chem Inf Model 2016; 56:1725-33. [DOI: 10.1021/acs.jcim.6b00039] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Xiaomin Ma
- Center for Quantitative Biology, ‡BNLMS, State Key
Laboratory for Structural
Chemistry of Unstable and Stable Species, College of Chemistry and
Molecular Engineering, and §Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Hu Meng
- Center for Quantitative Biology, ‡BNLMS, State Key
Laboratory for Structural
Chemistry of Unstable and Stable Species, College of Chemistry and
Molecular Engineering, and §Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Luhua Lai
- Center for Quantitative Biology, ‡BNLMS, State Key
Laboratory for Structural
Chemistry of Unstable and Stable Species, College of Chemistry and
Molecular Engineering, and §Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
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44
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Schueler-Furman O, Wodak SJ. Computational approaches to investigating allostery. Curr Opin Struct Biol 2016; 41:159-171. [PMID: 27607077 DOI: 10.1016/j.sbi.2016.06.017] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 06/23/2016] [Indexed: 01/01/2023]
Abstract
Allosteric regulation plays a key role in many biological processes, such as signal transduction, transcriptional regulation, and many more. It is rooted in fundamental thermodynamic and dynamic properties of macromolecular systems that are still poorly understood and are moreover modulated by the cellular context. Here we review the computational approaches used in the investigation of allosteric processes in protein systems. We outline how the models of allostery have evolved from their initial formulation in the sixties to the current views, which more fully account for the roles of the thermodynamic and dynamic properties of the system. We then describe the major classes of computational approaches employed to elucidate the mechanisms of allostery, the insights they have provided, as well as their limitations. We complement this analysis by highlighting the role of computational approaches in promising practical applications, such as the engineering of regulatory modules and identifying allosteric binding sites.
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Affiliation(s)
- Ora Schueler-Furman
- Department of Microbiology and Molecular Genetics, Institute for Medical Research Israel-Canada (IMRIC), Hebrew University, Hadassah Medical School, POB 12272, Jerusalem 91120, Israel
| | - Shoshana J Wodak
- VIB Structural Biology Research Center, VUB, Pleinlaan 2, 1050 Brussels, Belgium.
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45
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Villalobos P, Soto F, Baez M, Babul J. Regulatory network of the allosteric ATP inhibition of E. coli phosphofructokinase-2 studied by hybrid dimers. Biochimie 2016; 128-129:209-16. [PMID: 27591700 DOI: 10.1016/j.biochi.2016.08.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2015] [Accepted: 08/29/2016] [Indexed: 12/26/2022]
Abstract
We have proposed an allosteric ATP inhibition mechanism of Pfk-2 determining the structure of different forms of the enzyme together with a kinetic enzyme analysis. Here we complement the mechanism by using hybrid oligomers of the homodimeric enzyme to get insights about the allosteric communication pathways between the same sites or different ones located in different subunits. Kinetic analysis of the hybrid enzymes indicate that homotropic interactions between allosteric sites for ATP or between substrate sites for fructose-6-P have a minor effect on the enzymatic inhibition induced by ATP. In fact, the sigmoid response for fructose-6-P observed at elevated ATP concentrations can be eliminated even though the enzymatic inhibition is still operative. Nevertheless, leverage coupling analysis supports heterotropic interactions between the allosteric ATP and fructose-6-P binding occurring between and within each subunit.
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Affiliation(s)
- Pablo Villalobos
- Departamento de Biología, Facultad de Ciencias, Universidad de Chile, Santiago, Chile
| | - Francisco Soto
- Departamento de Biología, Facultad de Ciencias, Universidad de Chile, Santiago, Chile
| | - Mauricio Baez
- Departamento de Bioquímica y Biología Molecular, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago, Chile.
| | - Jorge Babul
- Departamento de Biología, Facultad de Ciencias, Universidad de Chile, Santiago, Chile.
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46
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Clarke D, Sethi A, Li S, Kumar S, Chang RWF, Chen J, Gerstein M. Identifying Allosteric Hotspots with Dynamics: Application to Inter- and Intra-species Conservation. Structure 2016; 24:826-837. [PMID: 27066750 PMCID: PMC4883016 DOI: 10.1016/j.str.2016.03.008] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Revised: 01/01/2016] [Accepted: 03/04/2016] [Indexed: 01/17/2023]
Abstract
The rapidly growing volume of data being produced by next-generation sequencing initiatives is enabling more in-depth analyses of conservation than previously possible. Deep sequencing is uncovering disease loci and regions under selective constraint, despite the fact that intuitive biophysical reasons for such constraint are sometimes absent. Allostery may often provide the missing explanatory link. We use models of protein conformational change to identify allosteric residues by finding essential surface pockets and information-flow bottlenecks, and we develop a software tool that enables users to perform this analysis on their own proteins of interest. Though fundamentally 3D-structural in nature, our analysis is computationally fast, thereby allowing us to run it across the PDB and to evaluate general properties of predicted allosteric residues. We find that these tend to be conserved over diverse evolutionary time scales. Finally, we highlight examples of allosteric residues that help explain poorly understood disease-associated variants.
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Affiliation(s)
- Declan Clarke
- Department of Chemistry, Yale University, 225 Prospect Street, New Haven, CT 06520, USA
| | - Anurag Sethi
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Shantao Li
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Computer Science, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Sushant Kumar
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Richard W F Chang
- Yale College, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Jieming Chen
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Integrated Graduate Program in Physical and Engineering Biology, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA; Department of Computer Science, Yale University, 260/266 Whitney Avenue, PO Box 208114, New Haven, CT 06520, USA.
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47
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Wagner JR, Lee CT, Durrant JD, Malmstrom RD, Feher VA, Amaro RE. Emerging Computational Methods for the Rational Discovery of Allosteric Drugs. Chem Rev 2016; 116:6370-90. [PMID: 27074285 PMCID: PMC4901368 DOI: 10.1021/acs.chemrev.5b00631] [Citation(s) in RCA: 148] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
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Allosteric drug development holds
promise for delivering medicines
that are more selective and less toxic than those that target orthosteric
sites. To date, the discovery of allosteric binding sites and lead
compounds has been mostly serendipitous, achieved through high-throughput
screening. Over the past decade, structural data has become more readily
available for larger protein systems and more membrane protein classes
(e.g., GPCRs and ion channels), which are common allosteric drug targets.
In parallel, improved simulation methods now provide better atomistic
understanding of the protein dynamics and cooperative motions that
are critical to allosteric mechanisms. As a result of these advances,
the field of predictive allosteric drug development is now on the
cusp of a new era of rational structure-based computational methods.
Here, we review algorithms that predict allosteric sites based on
sequence data and molecular dynamics simulations, describe tools that
assess the druggability of these pockets, and discuss how Markov state
models and topology analyses provide insight into the relationship
between protein dynamics and allosteric drug binding. In each section,
we first provide an overview of the various method classes before
describing relevant algorithms and software packages.
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Affiliation(s)
- Jeffrey R Wagner
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Christopher T Lee
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Jacob D Durrant
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Robert D Malmstrom
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Victoria A Feher
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Rommie E Amaro
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
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48
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Chattopadhyay A, O’Connor CJ, Zhang F, Galvagnion C, Galloway WRJD, Tan YS, Stokes JE, Rahman T, Verma C, Spring DR, Itzhaki LS. Discovery of a small-molecule binder of the oncoprotein gankyrin that modulates gankyrin activity in the cell. Sci Rep 2016; 6:23732. [PMID: 27046077 PMCID: PMC4820706 DOI: 10.1038/srep23732] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Accepted: 03/04/2016] [Indexed: 01/04/2023] Open
Abstract
Gankyrin is an ankyrin-repeat oncoprotein whose overexpression has been implicated in the development of many cancer types. Elevated gankyrin levels are linked to aberrant cellular events including enhanced degradation of tumour suppressor protein p53, and inhibition of gankyrin activity has therefore been identified as an attractive anticancer strategy. Gankyrin interacts with several partner proteins, and a number of these protein-protein interactions (PPIs) are of relevance to cancer. Thus, molecules that bind the PPI interface of gankyrin and interrupt these interactions are of considerable interest. Herein, we report the discovery of a small molecule termed cjoc42 that is capable of binding to gankyrin. Cell-based experiments demonstrate that cjoc42 can inhibit gankyrin activity in a dose-dependent manner: cjoc42 prevents the decrease in p53 protein levels normally associated with high amounts of gankyrin, and it restores p53-dependent transcription and sensitivity to DNA damage. The results represent the first evidence that gankyrin is a "druggable" target with small molecules.
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Affiliation(s)
| | | | - Fengzhi Zhang
- Department of Chemistry, Lensfield Road, Cambridge CB2 1EW, UK
| | | | | | - Yaw Sing Tan
- Department of Chemistry, Lensfield Road, Cambridge CB2 1EW, UK
- Bioinformatics Institute (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671
| | - Jamie E. Stokes
- Department of Chemistry, Lensfield Road, Cambridge CB2 1EW, UK
| | - Taufiq Rahman
- Department of Pharmacology, Tennis Court Road, Cambridge CB2 1PD, UK
| | - Chandra Verma
- Bioinformatics Institute (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551
- Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543
| | - David R. Spring
- Department of Chemistry, Lensfield Road, Cambridge CB2 1EW, UK
| | - Laura S. Itzhaki
- Department of Pharmacology, Tennis Court Road, Cambridge CB2 1PD, UK
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49
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Guarnera E, Berezovsky IN. Allosteric sites: remote control in regulation of protein activity. Curr Opin Struct Biol 2016; 37:1-8. [DOI: 10.1016/j.sbi.2015.10.004] [Citation(s) in RCA: 88] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Revised: 10/19/2015] [Accepted: 10/22/2015] [Indexed: 01/22/2023]
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50
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Guarnera E, Berezovsky IN. Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication. PLoS Comput Biol 2016; 12:e1004678. [PMID: 26939022 PMCID: PMC4777440 DOI: 10.1371/journal.pcbi.1004678] [Citation(s) in RCA: 89] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 11/25/2015] [Indexed: 11/18/2022] Open
Abstract
Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design. The 50th anniversary of Monod-Changeux-Jacob seminal paper “Allosteric proteins and cellular control systems” became the hallmark of a new wave in the allostery studies and the turning point in our vision of allostery and its implications in protein engineering and drug design. Recent experimental and theoretical works clearly show relevance of allosteric phenomenon to drug design, unraveling advantages of allosteric drugs in comparison to traditional orthosteric compounds. Remarkable simplicity of allosteric effectors and, at the same time, their potentially high specificity is one of the most important traits. The non conserved nature of allosteric ligands is a basis for avoiding drug resistance, and existence of latent regulatory sites make them attractive drug targets. The model presented in this work provides a theoretical framework for the quantification of the causality and energetics of allosteric regulation, which is a prerequisite for design of effector molecules with required characteristics. The synthesis between the thermodynamics of allostery and the intrinsic atomic nature of proteins and their interactions with the allosteric effectors accomplished in this work is a small initial step in the long endeavor towards future allosteric drugs.
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Affiliation(s)
- Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), Singapore
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