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Krieger JM, Doljanin F, Bogetti AT, Zhang F, Manivarma T, Bahar I, Mikulska-Ruminska K. WatFinder: a ProDy tool for protein-water interactions. Bioinformatics 2024; 40:btae516. [PMID: 39152994 PMCID: PMC11349191 DOI: 10.1093/bioinformatics/btae516] [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: 06/14/2024] [Revised: 08/08/2024] [Accepted: 08/15/2024] [Indexed: 08/19/2024] Open
Abstract
SUMMARY We introduce WatFinder, a tool designed to identify and visualize protein-water interactions (water bridges, water-mediated associations, or water channels, fluxes, and clusters) relevant to protein stability, dynamics, and function. WatFinder is integrated into ProDy, a Python API broadly used for structure-based prediction of protein dynamics. WatFinder provides a suite of functions for generating raw data as well as outputs from statistical analyses. The ProDy framework facilitates comprehensive automation and efficient analysis of the ensembles of structures resolved for a given protein or the time-evolved conformations from simulations in explicit water, as illustrated in five case studies presented in the Supplementary Material. AVAILABILITY AND IMPLEMENTATION ProDy is open-source and freely available under MIT License from https://github.com/ProDy/ProDy.
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Affiliation(s)
- James M Krieger
- Biocomputing Unit, Department of Macromolecular Structure, National Center for Biotechnology (CNB-CSIC), Calle Darwin 3, Campus UAM Cantoblanco, 28049, Madrid, Spain
| | - Frane Doljanin
- Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University in Torun, 87100, Torun, Poland
- Department of Physics, Faculty of Science, University of Split, 21000, Split, Croatia
| | - Anthony T Bogetti
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, United States
| | - Feng Zhang
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, United States
| | - Thiliban Manivarma
- Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University in Torun, 87100, Torun, Poland
| | - Ivet Bahar
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, United States
- Department of Biochemistry and Cell Biology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, United States
| | - Karolina Mikulska-Ruminska
- Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University in Torun, 87100, Torun, Poland
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2
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Banerjee A, Zhang S, Bahar I. Genome structural dynamics: insights from Gaussian network analysis of Hi-C data. Brief Funct Genomics 2024:elae014. [PMID: 38654598 DOI: 10.1093/bfgp/elae014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 03/11/2024] [Accepted: 04/02/2024] [Indexed: 04/26/2024] Open
Abstract
Characterization of the spatiotemporal properties of the chromatin is essential to gaining insights into the physical bases of gene co-expression, transcriptional regulation and epigenetic modifications. The Gaussian network model (GNM) has proven in recent work to serve as a useful tool for modeling chromatin structural dynamics, using as input high-throughput chromosome conformation capture data. We focus here on the exploration of the collective dynamics of chromosomal structures at hierarchical levels of resolution, from single gene loci to topologically associating domains or entire chromosomes. The GNM permits us to identify long-range interactions between gene loci, shedding light on the role of cross-correlations between distal regions of the chromosomes in regulating gene expression. Notably, GNM analysis performed across diverse cell lines highlights the conservation of the global/cooperative movements of the chromatin across different types of cells. Variations driven by localized couplings between genomic loci, on the other hand, underlie cell differentiation, underscoring the significance of the four-dimensional properties of the genome in defining cellular identity. Finally, we demonstrate the close relation between the cell type-dependent mobility profiles of gene loci and their gene expression patterns, providing a clear demonstration of the role of chromosomal 4D features in defining cell-specific differential expression of genes.
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Affiliation(s)
- Anupam Banerjee
- Laufer Center for Physical & Quantitative Biology, Stony Brook University, NY 11794, USA
| | - She Zhang
- OpenEye, Cadence Molecular Sciences, Santa Fe, NM 87508, USA
| | - Ivet Bahar
- Laufer Center for Physical & Quantitative Biology, Stony Brook University, NY 11794, USA
- Department of Biochemistry and Cell Biology, Renaissance School of Medicine, Stony Brook University, NY 11794, USA
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3
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Kumar S, Dubey R, Mishra R, Gupta S, Dwivedi VD, Ray S, Jha NK, Verma D, Tsai LW, Dubey NK. Repurposing of SARS-CoV-2 compounds against Marburg Virus using MD simulation, mm/GBSA, PCA analysis, and free energy landscape. J Biomol Struct Dyn 2024:1-20. [PMID: 38450706 DOI: 10.1080/07391102.2024.2323701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 01/22/2024] [Indexed: 03/08/2024]
Abstract
The significant mortality rate associated with Marburg virus infection made it the greatest hazard among infectious diseases. Drug repurposing using in silico methods has been crucial in identifying potential compounds that could prevent viral replication by targeting the virus's primary proteins. This study aimed at repurposing the drugs of SARS-CoV-2 for identifying potential candidates against the matrix protein VP40 of the Marburg virus. Virtual screening was performed where the control compound, Nilotinib, showed a binding score of -9.99 kcal/mol. Based on binding scores, hit compounds 9549298, 11960895, 44545852, 51039094, and 89670174 were selected that had a lower binding score than the control. Subsequent molecular dynamics (MD) simulation revealed that compound 9549298 consistently formed a hydrogen bond with the residue Gln290. This was observed both in molecular docking and MD simulation poses, indicating a strong and significant interaction with the protein. 11960895 had the most stable and consistent RMSD pattern exhibited in 100 ns simulation, while 9549298 had the most identical RMSD plot compared to the control molecule. MM/PBSA analysis showed that the binding free energy (ΔG) of 9549298 and 11960895 was lower than the control, with -30.84 and -38.86 kcal/mol, respectively. It was observed by the PCA (principal component analysis) and FEL (free energy landscape) analysis that compounds 9549298 and 11960895 had lesser conformational variation. Overall, this study proposed 9549298 and 11960895 as potential binders of VP40 MARV that can cause its inhibition, however it inherently lacks experimental validation. Furthermore, the study proposes in-vitro experiments as the next step to validate these computational findings, offering a practical approach to further explore these compounds' potential as antiviral agents.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Sanjay Kumar
- Biological and Bio-computational Lab, Department of Life Science, School of Basic Science and Research, Sharda University, Greater Noida, UP, India
| | - Rajni Dubey
- Division of Cardiology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei City, Taiwan
| | - Richa Mishra
- Department of Computer Engineering, Parul University, Vadodara, Gujarat, India
| | - Saurabh Gupta
- Department of Biotechnology, GLA University, Mathura, Uttar Pradesh, India
| | - Vivek Dhar Dwivedi
- Center for Global Health Research, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India
- Bioinformatics Research Division, Greater Noida, UP, India
| | - Subhasree Ray
- Department of Life Science, School of Basic Science and Research, Sharda University, Greater Noida, India
| | - Niraj Kumar Jha
- School of Bioengineering & Biosciences, Lovely Professional University, Phagwara, India
- Centre of Research Impact and Outreach, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
| | - Devvret Verma
- Department of Biotechnology, Graphic Era (Deemed to Be University), Dehradun, Uttarakhand, India
| | - Lung-Wen Tsai
- Department of Medicine Research, Taipei Medical University Hospital, Taipei, Taiwan
- Department of Information Technology Office, Taipei Medical University Hospital, Taipei, Taiwan
- Graduate Institute of Data Science, College of Management, Taipei Medical University, Taipei, Taiwan
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4
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Ventura C, Banerjee A, Zacharopoulou M, Itzhaki LS, Bahar I. Tandem-repeat proteins conformational mechanics are optimized to facilitate functional interactions and complexations. Curr Opin Struct Biol 2024; 84:102744. [PMID: 38134536 DOI: 10.1016/j.sbi.2023.102744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 10/30/2023] [Accepted: 11/24/2023] [Indexed: 12/24/2023]
Abstract
The architectures of tandem-repeat proteins are distinct from those of globular proteins. Individual modules, each comprising small structural motifs of 20-40 residues, are arrayed in a quasi one-dimensional fashion to form striking, elongated, horseshoe-like, and superhelical architectures, stabilized solely by short-range interaction. The spring-like shapes of repeat arrays point to elastic modes of action, and these proteins function as adapter molecules or 'hubs,' propagating signals within multi-subunit assemblies in diverse biological contexts. This flexibility is apparent in the dramatic variability observed in the structures of tandem-repeat proteins in different complexes. Here, using computational analysis, we demonstrate the striking ability of just one or a few global motions to recapitulate these structures. These findings show how the mechanics of repeat arrays are robustly enabled by their unique architecture. Thus, the repeating architecture has been optimized by evolution to favor functional modes of motions. The global motions enabling functional transitions can be fully visualized at http://bahargroup.org/tr_web.
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Affiliation(s)
- Carlos Ventura
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, 11794, USA; Department of Chemistry, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Anupam Banerjee
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Maria Zacharopoulou
- Department of Pharmacology, University of Cambridge, Cambridge, CB2 1PD, UK. https://twitter.com/maria_zach_
| | - Laura S Itzhaki
- Department of Pharmacology, University of Cambridge, Cambridge, CB2 1PD, UK.
| | - Ivet Bahar
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, 11794, USA; Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, NY, 11794, USA.
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Krieger JM, Sorzano COS, Carazo JM. Scipion-EM-ProDy: A Graphical Interface for the ProDy Python Package within the Scipion Workflow Engine Enabling Integration of Databases, Simulations and Cryo-Electron Microscopy Image Processing. Int J Mol Sci 2023; 24:14245. [PMID: 37762547 PMCID: PMC10532346 DOI: 10.3390/ijms241814245] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/10/2023] [Accepted: 09/15/2023] [Indexed: 09/29/2023] Open
Abstract
Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common theme has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows, together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.
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Affiliation(s)
- James M. Krieger
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Campus Universidad Autónoma de Madrid, Darwin 3, Cantoblanco, 28049 Madrid, Spain
| | | | - Jose Maria Carazo
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Campus Universidad Autónoma de Madrid, Darwin 3, Cantoblanco, 28049 Madrid, Spain
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6
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Konkankit CC, Rackovsky S. Global Survey of Protein Dynamic Properties. J Phys Chem B 2023. [PMID: 37368985 DOI: 10.1021/acs.jpcb.3c02609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
Using tools developed to study the dynamic bioinformatics of proteins, we are able to study the dynamic characteristics of very large numbers of protein sequences simultaneously. We study herein the distribution of protein sequences in a space determined by sequence mobility. It is shown that there are statistically significant differences in mobility distribution between folded sequences of different structural classes and between those and sequences of intrinsically disordered proteins. It is also shown that the several regions of mobility space differ significantly with respect to structural makeup. Helical proteins are shown to have distinctive dynamic characteristics at both extremes of the mobility spectrum.
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Affiliation(s)
- Chilaluck C Konkankit
- Department of Chemistry and Chemical Biology, Baker Laboratory, Cornell University, Ithaca, New York 14853, United States
| | - S Rackovsky
- Department of Biochemistry and Biophysics, University of Rochester School of Medicine and Dentistry, Rochester, New York 14642, United States
- Department of Chemistry and Chemical Biology, Baker Laboratory, Cornell University, Ithaca, New York 14853, United States
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7
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Liu X, Zhang H, Zhou Z, Prabhakaran P, Vongsangnak W, Hu G, Xiao F. Functional insight into Cordyceps militaris sugar transporters by structure modeling, network analysis and allosteric regulation. Phys Chem Chem Phys 2023; 25:14311-14323. [PMID: 37183444 DOI: 10.1039/d2cp05611a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Insights into the structures, functions and dynamics of Cordyceps militaris (C. militaris) sugar transporters are necessary for understanding their versatile metabolic capability for fungal growth. The sequence-function relationship study of 85 C. militaris sugar transporters showed that there is a gap between phylogenetic-based subfamily classification and their functions. Beyond protein sequences, structural modeling and principal component analysis of the structural ensemble revealed the different folds of the Car and Org subfamilies. Performing channel detection and network analysis found that the Alp and Hex subfamilies can be specifically distinguished from others by the betweenness of channel residues. Signature dynamics analysis further suggested that the Hex subfamily demonstrates different dynamics, with high flexibility at the H1 region in TM11. Furthermore, the H1 region as an allosteric site was examined by network parameter calculations that guided allosteric pathways between this region and the channel cavity. Together with gene expression data of C. militaris, e.g., Hex06741 in the Hex subfamily, it was promisingly expressed when sugar utilization was altered. This work demonstrates an in silico framework for investigating C. militaris sugar transporters as an example case study of the allosteric activity of the Hex subfamily and can facilitate sugar transporter engineering design that can further optimize the preferable sugar utilization and fermentation process of C. militaris.
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Affiliation(s)
- Xin Liu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou 215123, China.
- Institute of Blood and Marrow Transplantation, Medical College of Soochow University, Jiangsu Institute of Hematology, The first Affiliated Hospital of Soochow University, Collaborative Innovation Center of Hematology, National Clinical Research Center for Hematologic Diseases, Soochow University, Suzhou 215123, China
| | - Hanyang Zhang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou 215123, China.
| | - Ziyun Zhou
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou 215123, China.
- Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Soochow University, Suzhou, 215123, China
| | - Pranesha Prabhakaran
- Interdisciplinary Graduate Program in Bioscience, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand
- Omics Center for Agriculture, Bioresources, Food, and Health, Kasetsart University (OmiKU), Bangkok 10900, Thailand
| | - Wanwipa Vongsangnak
- Omics Center for Agriculture, Bioresources, Food, and Health, Kasetsart University (OmiKU), Bangkok 10900, Thailand
- Department of Zoology, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou 215123, China.
- Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Soochow University, Suzhou, 215123, China
| | - Fei Xiao
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou 215123, China.
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8
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Banerjee A, Bahar I. Structural Dynamics Predominantly Determine the Adaptability of Proteins to Amino Acid Deletions. Int J Mol Sci 2023; 24:8450. [PMID: 37176156 PMCID: PMC10179678 DOI: 10.3390/ijms24098450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 05/01/2023] [Accepted: 05/06/2023] [Indexed: 05/15/2023] Open
Abstract
The insertion or deletion (indel) of amino acids has a variety of effects on protein function, ranging from disease-forming changes to gaining new functions. Despite their importance, indels have not been systematically characterized towards protein engineering or modification goals. In the present work, we focus on deletions composed of multiple contiguous amino acids (mAA-dels) and their effects on the protein (mutant) folding ability. Our analysis reveals that the mutant retains the native fold when the mAA-del obeys well-defined structural dynamics properties: localization in intrinsically flexible regions, showing low resistance to mechanical stress, and separation from allosteric signaling paths. Motivated by the possibility of distinguishing the features that underlie the adaptability of proteins to mAA-dels, and by the rapid evaluation of these features using elastic network models, we developed a positive-unlabeled learning-based classifier that can be adopted for protein design purposes. Trained on a consolidated set of features, including those reflecting the intrinsic dynamics of the regions where the mAA-dels occur, the new classifier yields a high recall of 84.3% for identifying mAA-dels that are stably tolerated by the protein. The comparative examination of the relative contribution of different features to the prediction reveals the dominant role of structural dynamics in enabling the adaptation of the mutant to mAA-del without disrupting the native fold.
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Affiliation(s)
- Anupam Banerjee
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Ivet Bahar
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
- Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, NY 11794, USA
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9
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Modi T, Campitelli P, Heyden M, Ozkan SB. Correlated Evolution of Low-Frequency Vibrations and Function in Enzymes. J Phys Chem B 2023; 127:616-622. [PMID: 36633931 DOI: 10.1021/acs.jpcb.2c05983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Previous studies of the flexibility of ancestral proteins suggest that proteins evolve their function by altering their native state ensemble. Here, we propose a more direct method to analyze such changes during protein evolution by comparing thermally activated vibrations at frequencies below 6 THz, which report on the dynamics of collective protein modes. We analyzed the backbone vibrational density of states of ancestral and extant β-lactamases and thioredoxins and observed marked changes in the vibrational spectrum in response to evolution. Coupled with previously observed changes in protein flexibility, the observed shifts of vibrational mode densities suggest that protein dynamics and dynamical allostery are critical factors for the evolution of enzymes with specialized catalytic and biophysical properties.
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Affiliation(s)
- Tushar Modi
- Department of Physics, Arizona State University, Tempe, Arizona85287, United States
| | - Paul Campitelli
- Department of Physics, Arizona State University, Tempe, Arizona85287, United States
| | - Matthias Heyden
- School of Molecular Sciences, Arizona State University, Tempe, Arizona85287, United States
| | - S Banu Ozkan
- Department of Physics, Arizona State University, Tempe, Arizona85287, United States
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10
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Wingert B, Doruker P, Bahar I. Activation and Speciation Mechanisms in Class A GPCRs. J Mol Biol 2022; 434:167690. [PMID: 35728652 PMCID: PMC10129049 DOI: 10.1016/j.jmb.2022.167690] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 06/10/2022] [Accepted: 06/13/2022] [Indexed: 01/03/2023]
Abstract
Accurate development of allosteric modulators of GPCRs require a thorough assessment of their sequence, structure, and dynamics, toward gaining insights into their mechanisms of actions shared by family members, as well as dynamic features that distinguish subfamilies. Building on recent progress in the characterization of the signature dynamics of proteins, we analyzed here a dataset of 160 Class A GPCRs to determine their sequence similarities, structural landscape, and dynamic features across different species (human, bovine, mouse, squid, and rat), different activation states (active/inactive), and different subfamilies. The two dominant directions of variability across experimentally resolved structures, identified by principal component analysis of the dataset, shed light to cooperative mechanisms of activation, subfamily differentiation, and speciation of Class A GPCRs. The analysis reveals the functional significance of the conformational flexibilities of specific structural elements, including: the dominant role of the intracellular loop 3 (ICL3) together with the cytoplasmic ends of the adjoining helices TM5 and TM6 in enabling allosteric activation; the role of particular structural motifs at the extracellular loop 2 (ECL2) connecting TM4 and TM5 in binding ligands specific to different subfamilies; or even the differentiation of the N-terminal conformation across different species. Detailed analyses of the modes of motions accessible to the members of the dataset and their variations across members demonstrate how the active and inactive states of GPCRs obey distinct conformational dynamics. The collective fluctuations of the GPCRs are robustly defined in the active state, while the inactive conformers exhibit broad variance among members.
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Affiliation(s)
- Bentley Wingert
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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In Search of a Dynamical Vocabulary: A Pipeline to Construct a Basis of Shared Traits in Large-Scale Motions of Proteins. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12147157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The paradigmatic sequence–structure–dynamics–function relation in proteins is currently well established in the scientific community; in particular, a large effort has been made to probe the first connection, indeed providing convincing evidence of its strength and rationalizing it in a quantitative and general framework. In contrast, however, the role of dynamics as a link between structure and function has eluded a similarly clear-cut verification and description. In this work, we propose a pipeline aimed at building a basis for the quantitative characterization of the large-scale dynamics of a set of proteins, starting from the sole knowledge of their native structures. The method hinges on a dynamics-based clusterization, which allows a straightforward comparison with structural and functional protein classifications. The resulting basis set, obtained through the application to a group of related proteins, is shown to reproduce the salient large-scale dynamical features of the dataset. Most interestingly, the basis set is shown to encode the fluctuation patterns of homologous proteins not belonging to the initial dataset, thus highlighting the general applicability of the pipeline used to build it.
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12
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Krieger JM, Sorzano COS, Carazo JM, Bahar I. Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0. Acta Crystallogr D Struct Biol 2022; 78:399-409. [PMID: 35362464 PMCID: PMC8972803 DOI: 10.1107/s2059798322001966] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 02/18/2022] [Indexed: 11/24/2022] Open
Abstract
Cryo-electron microscopy (cryoEM) has become a well established technique with the potential to produce structures of large and dynamic supramolecular complexes that are not amenable to traditional approaches for studying structure and dynamics. The size and low resolution of such molecular systems often make structural modelling and molecular dynamics simulations challenging and computationally expensive. This, together with the growing wealth of structural data arising from cryoEM and other structural biology methods, has driven a trend in the computational biophysics community towards the development of new pipelines for analysing global dynamics using coarse-grained models and methods. At the centre of this trend has been a return to elastic network models, normal mode analysis (NMA) and ensemble analyses such as principal component analysis, and the growth of hybrid simulation methodologies that make use of them. Here, this field is reviewed with a focus on ProDy, the Python application programming interface for protein dynamics, which has been developed over the last decade. Two key developments in this area are highlighted: (i) ensemble NMA towards extracting and comparing the signature dynamics of homologous structures, aided by the recent SignDy pipeline, and (ii) pseudoatom fitting for more efficient global dynamics analyses of large and low-resolution supramolecular assemblies from cryoEM, revisited in the CryoDy pipeline. It is believed that such a renewal and extension of old models and methods in new pipelines will be critical for driving the field forward into the next cryoEM revolution.
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Affiliation(s)
- James Michael Krieger
- Biocomputing Unit, Centro Nacional de Biotecnología (CSIC), Calle Darwin 3, 28049 Madrid, Spain
| | - Carlos Oscar S. Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnología (CSIC), Calle Darwin 3, 28049 Madrid, Spain
| | - Jose Maria Carazo
- Biocomputing Unit, Centro Nacional de Biotecnología (CSIC), Calle Darwin 3, 28049 Madrid, Spain
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213, USA
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13
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A Comparative Evaluation of the Structural and Dynamic Properties of Insect Odorant Binding Proteins. Biomolecules 2022; 12:biom12020282. [PMID: 35204784 PMCID: PMC8961588 DOI: 10.3390/biom12020282] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 01/23/2022] [Accepted: 01/24/2022] [Indexed: 02/01/2023] Open
Abstract
Insects devote a major part of their metabolic resources to the production of odorant binding proteins (OBPs). Although initially, these proteins were implicated in the solubilisation, binding and transport of semiochemicals to olfactory receptors, it is now recognised that they may play diverse, as yet uncharacterised, roles in insect physiology. The structures of these OBPs, the majority of which are known as “classical” OBPs, have shed some light on their potential functional roles. However, the dynamic properties of these proteins have received little attention despite their functional importance. Structural dynamics are encoded in the native protein fold and enable the adaptation of proteins to substrate binding. This paper provides a comparative review of the structural and dynamic properties of OBPs, making use of sequence/structure analysis, statistical and theoretical physics-based methods. It provides a new layer of information and additional methodological tools useful in unravelling the relationship between structure, dynamics and function of insect OBPs. The dynamic properties of OBPs, studied by means of elastic network models, reflect the similarities/dissimilarities observed in their respective structures and provides insights regarding protein motions that may have important implications for ligand recognition and binding. Furthermore, it was shown that the OBPs studied in this paper share conserved structural ‘core’ that may be of evolutionary and functional importance.
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14
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Kaynak BT, Krieger JM, Dudas B, Dahmani ZL, Costa MGS, Balog E, Scott AL, Doruker P, Perahia D, Bahar I. Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods. Front Mol Biosci 2022; 9:832847. [PMID: 35187088 PMCID: PMC8855042 DOI: 10.3389/fmolb.2022.832847] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 01/12/2022] [Indexed: 12/17/2022] Open
Abstract
Recent years have seen several hybrid simulation methods for exploring the conformational space of proteins and their complexes or assemblies. These methods often combine fast analytical approaches with computationally expensive full atomic molecular dynamics (MD) simulations with the goal of rapidly sampling large and cooperative conformational changes at full atomic resolution. We present here a systematic comparison of the utility and limits of four such hybrid methods that have been introduced in recent years: MD with excited normal modes (MDeNM), collective modes-driven MD (CoMD), and elastic network model (ENM)-based generation, clustering, and relaxation of conformations (ClustENM) as well as its updated version integrated with MD simulations (ClustENMD). We analyzed the predicted conformational spaces using each of these four hybrid methods, applied to four well-studied proteins, triosephosphate isomerase (TIM), 3-phosphoglycerate kinase (PGK), HIV-1 protease (PR) and HIV-1 reverse transcriptase (RT), which provide extensive ensembles of experimental structures for benchmarking and comparing the methods. We show that a rigorous multi-faceted comparison and multiple metrics are necessary to properly assess the differences between conformational ensembles and provide an optimal protocol for achieving good agreement with experimental data. While all four hybrid methods perform well in general, being especially useful as computationally efficient methods that retain atomic resolution, the systematic analysis of the same systems by these four hybrid methods highlights the strengths and limitations of the methods and provides guidance for parameters and protocols to be adopted in future studies.
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Affiliation(s)
- Burak T. Kaynak
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - James M. Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Balint Dudas
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Laboratoire de Biologie et Pharmacologie Appliquée, Ecole Normale Supérieure Paris-Saclay, Gif-sur-Yvette, France
- Department of Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary
| | - Zakaria L. Dahmani
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mauricio G. S. Costa
- Programa de Computação Científica, Vice-Presiden̂cia de Educação, Informação e Comunicação, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Erika Balog
- Department of Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary
| | - Ana Ligia Scott
- Laboratory of Bioinformatics and Computational Biology, Center of Mathematics, Computation and Cognition, Federal University of ABC-UFABC, Santo André, Brazil
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Ivet Bahar, ; David Perahia, ; Pemra Doruker,
| | - David Perahia
- Laboratoire de Biologie et Pharmacologie Appliquée, Ecole Normale Supérieure Paris-Saclay, Gif-sur-Yvette, France
- *Correspondence: Ivet Bahar, ; David Perahia, ; Pemra Doruker,
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Ivet Bahar, ; David Perahia, ; Pemra Doruker,
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15
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Xie J, Wang S, Xu Y, Deng M, Lai L. Uncovering the Dominant Motion Modes of Allosteric Regulation Improves Allosteric Site Prediction. J Chem Inf Model 2021; 62:187-195. [PMID: 34964625 DOI: 10.1021/acs.jcim.1c01267] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Allostery is an important mechanism that biological systems use to regulate function at a distant site. Allosteric drugs have attracted much attention in recent years due to their high specificity and the possibility of overcoming existing drug-resistant mutations. However, the discovery of allosteric drugs remains challenging as allosteric regulation mechanisms are not clearly understood and allosteric sites cannot be accurately predicted. In this study, we analyzed the dominant modes that determine motion correlations between allosteric and orthosteric sites using the Gaussian network model and found that motion correlations between allosteric and orthosteric sites are dominated by either fast or slow vibrational modes. This dependence of modes results from the relative locations of the two sites and local secondary structures. Based on these analyses, we developed CorrSite2.0 to predict allosteric sites by taking the maximum of the Z-scores calculated from using either slow or fast modes. The prediction accuracy of CorrSite2.0 outperformed other commonly used allosteric site prediction methods with prediction accuracy over 90.0%. Our study uncovers the relationship of protein structure, dynamics, and allosteric regulation and demonstrates that using the dominant motion modes greatly improves allosteric site prediction accuracy. CorrSite2.0 has been integrated into the CavityPlus web server, which can be accessed at http://www.pkumdl.cn/cavityplus. CorrSite2.0 provides a powerful and user-friendly tool for allosteric drug and protein design.
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Affiliation(s)
- Juan Xie
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Shiwei Wang
- PTN Graduate Program, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Youjun Xu
- BNLMS, Peking-Tsinghua Center for Life Sciences at the College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Minghua Deng
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.,School of Mathematical Sciences, Peking University, Beijing 100871, China.,Center for Statistical Science, Peking University, Beijing 100871, China
| | - Luhua Lai
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.,BNLMS, Peking-Tsinghua Center for Life Sciences at the College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
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16
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Structural dynamics in the evolution of a bilobed protein scaffold. Proc Natl Acad Sci U S A 2021; 118:2026165118. [PMID: 34845009 PMCID: PMC8694067 DOI: 10.1073/pnas.2026165118] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/20/2021] [Indexed: 11/18/2022] Open
Abstract
Proteins conduct numerous complex biological functions by use of tailored structural dynamics. The molecular details of how these emerged from ancestral peptides remains mysterious. How does nature utilize the same repertoire of folds to diversify function? To shed light on this, we analyzed bilobed proteins with a common structural core, which is spread throughout the tree of life and is involved in diverse biological functions such as transcription, enzymatic catalysis, membrane transport, and signaling. We show here that the structural dynamics of the structural core differentiate predominantly via terminal additions during a long-period evolution. This diversifies substrate specificity and, ultimately, biological function. Novel biophysical tools allow the structural dynamics of proteins and the regulation of such dynamics by binding partners to be explored in unprecedented detail. Although this has provided critical insights into protein function, the means by which structural dynamics direct protein evolution remain poorly understood. Here, we investigated how proteins with a bilobed structure, composed of two related domains from the periplasmic-binding protein–like II domain family, have undergone divergent evolution, leading to adaptation of their structural dynamics. We performed a structural analysis on ∼600 bilobed proteins with a common primordial structural core, which we complemented with biophysical studies to explore the structural dynamics of selected examples by single-molecule Förster resonance energy transfer and Hydrogen–Deuterium exchange mass spectrometry. We show that evolutionary modifications of the structural core, largely at its termini, enable distinct structural dynamics, allowing the diversification of these proteins into transcription factors, enzymes, and extracytoplasmic transport-related proteins. Structural embellishments of the core created interdomain interactions that stabilized structural states, reshaping the active site geometry, and ultimately altered substrate specificity. Our findings reveal an as-yet-unrecognized mechanism for the emergence of functional promiscuity during long periods of evolution and are applicable to a large number of domain architectures.
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17
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Evolution of dynamical networks enhances catalysis in a designer enzyme. Nat Chem 2021; 13:1017-1022. [PMID: 34413499 DOI: 10.1038/s41557-021-00763-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 06/30/2021] [Indexed: 02/08/2023]
Abstract
Activation heat capacity is emerging as a crucial factor in enzyme thermoadaptation, as shown by the non-Arrhenius behaviour of many natural enzymes. However, its physical origin and relationship to the evolution of catalytic activity remain uncertain. Here we show that directed evolution of a computationally designed Kemp eliminase reshapes protein dynamics, which gives rise to an activation heat capacity absent in the original design. These changes buttress transition-state stabilization. Extensive molecular dynamics simulations show that evolution results in the closure of solvent-exposed loops and a better packing of the active site. Remarkably, this gives rise to a correlated dynamical network that involves the transition state and large parts of the protein. This network tightens the transition-state ensemble, which induces a negative activation heat capacity and non-linearity in the activity-temperature dependence. Our results have implications for understanding enzyme evolution and suggest that selectively targeting the conformational dynamics of the transition-state ensemble by design and evolution will expedite the creation of novel enzymes.
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18
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Smit JH, Krishnamurthy S, Srinivasu BY, Parakra R, Karamanou S, Economou A. Probing Universal Protein Dynamics Using Hydrogen-Deuterium Exchange Mass Spectrometry-Derived Residue-Level Gibbs Free Energy. Anal Chem 2021; 93:12840-12847. [PMID: 34523340 DOI: 10.1021/acs.analchem.1c02155] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is a powerful technique to monitor protein intrinsic dynamics. The technique provides high-resolution information on how protein intrinsic dynamics are altered in response to biological signals, such as ligand binding, oligomerization, or allosteric networks. However, identification, interpretation, and visualization of such events from HDX-MS data sets is challenging as these data sets consist of many individual data points collected across peptides, time points, and experimental conditions. Here, we present PyHDX, an open-source Python package and webserver, that allows the user to batch extract the universal quantity Gibbs free energy at residue levels over multiple protein conditions and homologues. The output is directly visualized on a linear map or 3D structures or is exported as .csv files or PyMOL scripts.
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Affiliation(s)
- Jochem H Smit
- Department of Microbiology, Immunology and Transplantation, Rega Institute of Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, 3000 Leuven, Belgium
| | - Srinath Krishnamurthy
- Department of Microbiology, Immunology and Transplantation, Rega Institute of Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, 3000 Leuven, Belgium
| | - Bindu Y Srinivasu
- Department of Microbiology, Immunology and Transplantation, Rega Institute of Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, 3000 Leuven, Belgium
| | - Rinky Parakra
- Department of Microbiology, Immunology and Transplantation, Rega Institute of Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, 3000 Leuven, Belgium
| | - Spyridoula Karamanou
- Department of Microbiology, Immunology and Transplantation, Rega Institute of Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, 3000 Leuven, Belgium
| | - Anastassios Economou
- Department of Microbiology, Immunology and Transplantation, Rega Institute of Medical Research, Laboratory of Molecular Bacteriology, KU Leuven, 3000 Leuven, Belgium
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19
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Tang QY, Kaneko K. Dynamics-Evolution Correspondence in Protein Structures. PHYSICAL REVIEW LETTERS 2021; 127:098103. [PMID: 34506164 DOI: 10.1103/physrevlett.127.098103] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 07/28/2021] [Indexed: 06/13/2023]
Abstract
The genotype-phenotype mapping of proteins is a fundamental question in structural biology. In this Letter, with the analysis of a large dataset of proteins from hundreds of protein families, we quantitatively demonstrate the correlations between the noise-induced protein dynamics and mutation-induced variations of native structures, indicating the dynamics-evolution correspondence of proteins. Based on the investigations of the linear responses of native proteins, the origin of such a correspondence is elucidated. It is essential that the noise- and mutation-induced deformations of the proteins are restricted on a common low-dimensional subspace, as confirmed from the data. These results suggest an evolutionary mechanism of the proteins gaining both dynamical flexibility and evolutionary structural variability.
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Affiliation(s)
- Qian-Yuan Tang
- Center for Complex Systems Biology, Universal Biology Institute, University of Tokyo, Komaba 3-8-1, Meguro-ku, Tokyo 153-8902, Japan
- Lab for Neural Computation and Adaptation, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Kunihiko Kaneko
- Center for Complex Systems Biology, Universal Biology Institute, University of Tokyo, Komaba 3-8-1, Meguro-ku, Tokyo 153-8902, Japan
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20
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Rauer C, Sen N, Waman VP, Abbasian M, Orengo CA. Computational approaches to predict protein functional families and functional sites. Curr Opin Struct Biol 2021; 70:108-122. [PMID: 34225010 DOI: 10.1016/j.sbi.2021.05.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 05/13/2021] [Accepted: 05/25/2021] [Indexed: 01/06/2023]
Abstract
Understanding the mechanisms of protein function is indispensable for many biological applications, such as protein engineering and drug design. However, experimental annotations are sparse, and therefore, theoretical strategies are needed to fill the gap. Here, we present the latest developments in building functional subclassifications of protein superfamilies and using evolutionary conservation to detect functional determinants, for example, catalytic-, binding- and specificity-determining residues important for delineating the functional families. We also briefly review other features exploited for functional site detection and new machine learning strategies for combining multiple features.
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Affiliation(s)
- Clemens Rauer
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Neeladri Sen
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Vaishali P Waman
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Mahnaz Abbasian
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Christine A Orengo
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
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21
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Gating and modulation of a hetero-octameric AMPA glutamate receptor. Nature 2021; 594:454-458. [PMID: 34079129 PMCID: PMC7611729 DOI: 10.1038/s41586-021-03613-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 05/05/2021] [Indexed: 02/06/2023]
Abstract
AMPA receptors (AMPARs) mediate the majority of excitatory transmission in the brain and enable the synaptic plasticity that underlies learning1. A diverse array of AMPAR signalling complexes are established by receptor auxiliary subunits, which associate with the AMPAR in various combinations to modulate trafficking, gating and synaptic strength2. However, their mechanisms of action are poorly understood. Here we determine cryo-electron microscopy structures of the heteromeric GluA1-GluA2 receptor assembled with both TARP-γ8 and CNIH2, the predominant AMPAR complex in the forebrain, in both resting and active states. Two TARP-γ8 and two CNIH2 subunits insert at distinct sites beneath the ligand-binding domains of the receptor, with site-specific lipids shaping each interaction and affecting the gating regulation of the AMPARs. Activation of the receptor leads to asymmetry between GluA1 and GluA2 along the ion conduction path and an outward expansion of the channel triggers counter-rotations of both auxiliary subunit pairs, promoting the active-state conformation. In addition, both TARP-γ8 and CNIH2 pivot towards the pore exit upon activation, extending their reach for cytoplasmic receptor elements. CNIH2 achieves this through its uniquely extended M2 helix, which has transformed this endoplasmic reticulum-export factor into a powerful AMPAR modulator that is capable of providing hippocampal pyramidal neurons with their integrative synaptic properties.
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22
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Echave J. Fast computational mutation-response scanning of proteins. PeerJ 2021; 9:e11330. [PMID: 33976988 PMCID: PMC8067912 DOI: 10.7717/peerj.11330] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 03/31/2021] [Indexed: 12/21/2022] Open
Abstract
Studying the effect of perturbations on protein structure is a basic approach in protein research. Important problems, such as predicting pathological mutations and understanding patterns of structural evolution, have been addressed by computational simulations that model mutations using forces and predict the resulting deformations. In single mutation-response scanning simulations, a sensitivity matrix is obtained by averaging deformations over point mutations. In double mutation-response scanning simulations, a compensation matrix is obtained by minimizing deformations over pairs of mutations. These very useful simulation-based methods may be too slow to deal with large proteins, protein complexes, or large protein databases. To address this issue, I derived analytical closed formulas to calculate the sensitivity and compensation matrices directly, without simulations. Here, I present these derivations and show that the resulting analytical methods are much faster than their simulation counterparts.
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Affiliation(s)
- Julian Echave
- Instituto de Ciencias Físicas, Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, San Martín, Buenos Aires, Argentina
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23
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Zhang S, Krieger JM, Zhang Y, Kaya C, Kaynak B, Mikulska-Ruminska K, Doruker P, Li H, Bahar I. ProDy 2.0: Increased Scale and Scope after 10 Years of Protein Dynamics Modelling with Python. Bioinformatics 2021; 37:3657-3659. [PMID: 33822884 PMCID: PMC8545336 DOI: 10.1093/bioinformatics/btab187] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 03/16/2021] [Indexed: 12/31/2022] Open
Abstract
Summary ProDy, an integrated application programming interface developed for modelling and analysing protein dynamics, has significantly evolved in recent years in response to the growing data and needs of the computational biology community. We present major developments that led to ProDy 2.0: (i) improved interfacing with databases and parsing new file formats, (ii) SignDy for signature dynamics of protein families, (iii) CryoDy for collective dynamics of supramolecular systems using cryo-EM density maps and (iv) essential site scanning analysis for identifying sites essential to modulating global dynamics. Availability and implementation ProDy is open-source and freely available under MIT License from https://github.com/prody/ProDy. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- She Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - James M Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yan Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Cihan Kaya
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Burak Kaynak
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Karolina Mikulska-Ruminska
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Hongchun Li
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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24
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Zhang Y, Krieger J, Mikulska-Ruminska K, Kaynak B, Sorzano COS, Carazo JM, Xing J, Bahar I. State-dependent sequential allostery exhibited by chaperonin TRiC/CCT revealed by network analysis of Cryo-EM maps. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2021; 160:104-120. [PMID: 32866476 PMCID: PMC7914283 DOI: 10.1016/j.pbiomolbio.2020.08.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 06/25/2020] [Accepted: 08/16/2020] [Indexed: 12/17/2022]
Abstract
The eukaryotic chaperonin TRiC/CCT plays a major role in assisting the folding of many proteins through an ATP-driven allosteric cycle. Recent structures elucidated by cryo-electron microscopy provide a broad view of the conformations visited at various stages of the chaperonin cycle, including a sequential activation of its subunits in response to nucleotide binding. But we lack a thorough mechanistic understanding of the structure-based dynamics and communication properties that underlie the TRiC/CCT machinery. In this study, we present a computational methodology based on elastic network models adapted to cryo-EM density maps to gain a deeper understanding of the structure-encoded allosteric dynamics of this hexadecameric machine. We have analysed several structures of the chaperonin resolved in different states toward mapping its conformational landscape. Our study indicates that the overall architecture intrinsically favours cooperative movements that comply with the structural variabilities observed in experiments. Furthermore, the individual subunits CCT1-CCT8 exhibit state-dependent sequential events at different states of the allosteric cycle. For example, in the ATP-bound state, subunits CCT5 and CCT4 selectively initiate the lid closure motions favoured by the overall architecture; whereas in the apo form of the heteromer, the subunit CCT7 exhibits the highest predisposition to structural change. The changes then propagate through parallel fluxes of allosteric signals to neighbours on both rings. The predicted state-dependent mechanisms of sequential activation provide new insights into TRiC/CCT intra- and inter-ring signal transduction events.
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Affiliation(s)
- Yan Zhang
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - James Krieger
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Karolina Mikulska-Ruminska
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Burak Kaynak
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | | | - José-María Carazo
- Centro Nacional de Biotecnología (CSIC), Darwin, 3, 28049, Madrid, Spain
| | - Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA.
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25
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Gong W, Liu Y, Zhao Y, Wang S, Han Z, Li C. Equally Weighted Multiscale Elastic Network Model and Its Comparison with Traditional and Parameter-Free Models. J Chem Inf Model 2021; 61:921-937. [PMID: 33496590 DOI: 10.1021/acs.jcim.0c01178] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Dynamical properties of proteins play an essential role in their function exertion. The elastic network model (ENM) is an effective and efficient tool in characterizing the intrinsic dynamical properties encoded in biomacromolecule structures. The Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. Here, we introduce an equally weighted multiscale ENM (equally weighted mENM) based on the original mENM (denoted as mENM), in which fitting weights of Kirchhoff/Hessian matrixes in mENM are removed since they neglect the details of pairwise interactions. Then, we perform its comparison with the mENM, traditional ENM, and parameter-free ENM (pfENM) in reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM performs best, while the equally weighted mENM performs also well, better than the traditional ENM and pfENM models. As to the dynamical cross-correlation map calculation, mENM performs worst, while the results produced from the equally weighted mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Furthermore, encouragingly, the equally weighted mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while the mANM fails in all the cases. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.
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Affiliation(s)
- Weikang Gong
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China.,Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing 100124, China
| | - Yang Liu
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China.,Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing 100124, China
| | - Yanpeng Zhao
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China.,Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing 100124, China
| | - Shihao Wang
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China.,Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing 100124, China
| | - Zhongjie Han
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China.,Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing 100124, China
| | - Chunhua Li
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China.,Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing 100124, China
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26
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Ponzoni L, Peñaherrera DA, Oltvai ZN, Bahar I. Rhapsody: predicting the pathogenicity of human missense variants. Bioinformatics 2020; 36:3084-3092. [PMID: 32101277 PMCID: PMC7214033 DOI: 10.1093/bioinformatics/btaa127] [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: 08/06/2019] [Revised: 12/27/2019] [Accepted: 02/21/2020] [Indexed: 12/22/2022] Open
Abstract
MOTIVATION The biological effects of human missense variants have been studied experimentally for decades but predicting their effects in clinical molecular diagnostics remains challenging. Available computational tools are usually based on the analysis of sequence conservation and structural properties of the mutant protein. We recently introduced a new machine learning method that demonstrated for the first time the significance of protein dynamics in determining the pathogenicity of missense variants. RESULTS Here, we present a new interface (Rhapsody) that enables fully automated assessment of pathogenicity, incorporating both sequence coevolution data and structure- and dynamics-based features. Benchmarked against a dataset of about 20 000 annotated variants, the methodology is shown to outperform well-established and/or advanced prediction tools. We illustrate the utility of Rhapsody by in silico saturation mutagenesis studies of human H-Ras, phosphatase and tensin homolog and thiopurine S-methyltransferase. AVAILABILITY AND IMPLEMENTATION The new tool is available both as an online webserver at http://rhapsody.csb.pitt.edu and as an open-source Python package (GitHub repository: https://github.com/prody/rhapsody; PyPI package installation: pip install prody-rhapsody). Links to additional resources, tutorials and package documentation are provided in the 'Python package' section of the website. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Luca Ponzoni
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Daniel A Peñaherrera
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Zoltán N Oltvai
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.,Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA.,Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
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27
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Wingert B, Krieger J, Li H, Bahar I. Adaptability and specificity: how do proteins balance opposing needs to achieve function? Curr Opin Struct Biol 2020; 67:25-32. [PMID: 33053463 DOI: 10.1016/j.sbi.2020.08.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 08/30/2020] [Accepted: 08/30/2020] [Indexed: 12/14/2022]
Abstract
Many proteins select from a small repertoire of 3-dimensional folds retained over evolutional timescales and recruited for different functions, with changes in local structure and sequence to enable specificity. Recent studies have revealed the evolutionary constraints on protein dynamics to achieve function. The significance of protein dynamics in simultaneously satisfying conformational flexibility/malleability and stability/precision requirements becomes clear upon dissecting the spectrum of equilibrium motions accessible to fold families. Accessibility to highly conserved global modes of motions shared by family members, to low-to-intermediate-frequency modes that distinguish subfamilies and confer specificity, and to conserved high-frequency modes ensuring chemical precision and core stability underlies functional specialization while exploiting highly versatile folds. These design principles are illustrated for the family of PDZ domains.
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Affiliation(s)
- Bentley Wingert
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213 USA
| | - James Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213 USA
| | - Hongchun Li
- Research Center for Computer-Aided Drug Discovery at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213 USA.
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28
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Krieger JM, Doruker P, Scott AL, Perahia D, Bahar I. Towards gaining sight of multiscale events: utilizing network models and normal modes in hybrid methods. Curr Opin Struct Biol 2020; 64:34-41. [PMID: 32622329 DOI: 10.1016/j.sbi.2020.05.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 05/13/2020] [Accepted: 05/20/2020] [Indexed: 11/28/2022]
Abstract
With the explosion of normal mode analyses (NMAs) based on elastic network models (ENMs) in the last decade, and the proven precision of MD simulations for visualizing interactions at atomic scale, many hybrid methods have been proposed in recent years. These aim at exploiting the best of both worlds: the atomic precision of MD that often fall short of exploring time and length scales of biological interest, and the capability of ENM-NMA to predict the cooperative and often functional rearrangements of large structures and assemblies, albeit at low resolution. We present an overview of recent progress in the field with examples of successful applications highlighting the utility of such hybrid methods and pointing to emerging future directions guided by advances in experimental characterization of biomolecular systems structure and dynamics.
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Affiliation(s)
- James M Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Ana Ligia Scott
- Laboratory of Bioinformatics and Computational Biology, Federal University of ABC, Santo André, SP, Brazil
| | - David Perahia
- Laboratoire de Biologie et de Pharmacologie Appliquée, Ecole Normale Superieure Paris-Saclay, UMR 8113, CNRS, 4 Avenue des Sciences, 91190 Gif-sur-Yvette, France
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA.
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29
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Bhat AS, Dustin Schaeffer R, Kinch L, Medvedev KE, Grishin NV. Recent advances suggest increased influence of selective pressure in allostery. Curr Opin Struct Biol 2020; 62:183-188. [PMID: 32302874 DOI: 10.1016/j.sbi.2020.02.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 02/21/2020] [Accepted: 02/25/2020] [Indexed: 12/19/2022]
Abstract
Allosteric regulation of protein functions is ubiquitous in organismal biology, but the principles governing its evolution are not well understood. Here we discuss recent studies supporting the large-scale existence of latent allostery in ancestor proteins of superfamilies. As suggested, the evolution of allostery could be driven by the need for specificity in paralogs of slow evolving protein complexes with conserved active sites. The same slow evolution is displayed by purifying selection exhibited in allosteric proteins with somatic mutations involved in cancer, where disease-associated mutations are enriched in both orthosteric and allosteric sites. Consequently, disease-associated variants can be used to identify druggable allosteric sites that are specific for paralogs in protein superfamilies with otherwise similar functions.
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Affiliation(s)
- Archana S Bhat
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States
| | - Richard Dustin Schaeffer
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States
| | - Lisa Kinch
- Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States
| | - Kirill E Medvedev
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States
| | - Nick V Grishin
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States; Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States.
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30
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Zhang S, Chen F, Bahar I. Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation. Nucleic Acids Res 2020; 48:1131-1145. [PMID: 31828312 PMCID: PMC7026660 DOI: 10.1093/nar/gkz1102] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2019] [Revised: 11/01/2019] [Accepted: 11/22/2019] [Indexed: 12/19/2022] Open
Abstract
Advances in chromosome conformation capture techniques as well as computational characterization of genomic loci structural dynamics open new opportunities for exploring the mechanistic aspects of genome-scale differences across different cell types. We examined here the dynamic basis of variabilities between different cell types by investigating their chromatin mobility profiles inferred from Hi-C data using an elastic network model representation of the chromatin. Our comparative analysis of sixteen cell lines reveals close similarities between chromosomal dynamics across different cell lines on a global scale, but notable cell-specific variations emerge in the detailed spatial mobilities of genomic loci. Closer examination reveals that the differences in spatial dynamics mainly originate from the difference in the frequencies of their intrinsically accessible modes of motion. Thus, even though the chromosomes of different types of cells have access to similar modes of collective movements, not all modes are deployed by all cells, such that the effective mobilities and cross-correlations of genomic loci are cell-type-specific. Comparison with RNA-seq expression data reveals a strong overlap between highly expressed genes and those distinguished by high mobilities in the present study, in support of the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation.
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Affiliation(s)
- She Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Fangyuan Chen
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.,School of Medicine, Tsinghua University, Beijing 100084, China
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
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31
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Abboud A, Bédoucha P, Byška J, Arnesen T, Reuter N. Dynamics-function relationship in the catalytic domains of N-terminal acetyltransferases. Comput Struct Biotechnol J 2020; 18:532-547. [PMID: 32206212 PMCID: PMC7078549 DOI: 10.1016/j.csbj.2020.02.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 02/14/2020] [Accepted: 02/25/2020] [Indexed: 12/15/2022] Open
Abstract
N-terminal acetyltransferases (NATs) belong to the superfamily of acetyltransferases. They are enzymes catalysing the transfer of an acetyl group from acetyl coenzyme A to the N-terminus of polypeptide chains. N-terminal acetylation is one of the most common protein modifications. To date, not much is known on the molecular basis for the exclusive substrate specificity of NATs. All NATs share a common fold called GNAT. A characteristic of NATs is the β6β7 hairpin loop covering the active site and forming with the α1α2 loop a narrow tunnel surrounding the catalytic site in which cofactor and polypeptide meet and exchange an acetyl group. We investigated the dynamics-function relationships of all available structures of NATs covering the three domains of Life. Using an elastic network model and normal mode analysis, we found a common dynamics pattern conserved through the GNAT fold; a rigid V-shaped groove formed by the β4 and β5 strands and splitting the fold in two dynamical subdomains. Loops α1α2, β3β4 and β6β7 all show clear displacements in the low frequency normal modes. We characterized the mobility of the loops and show that even limited conformational changes of the loops along the low-frequency modes are able to significantly change the size and shape of the ligand binding sites. Based on the fact that these movements are present in most low-frequency modes, and common to all NATs, we suggest that the α1α2 and β6β7 loops may regulate ligand uptake and the release of the acetylated polypeptide.
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Affiliation(s)
- Angèle Abboud
- Department of Informatics, University of Bergen, Bergen, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Pierre Bédoucha
- Department of Informatics, University of Bergen, Bergen, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Jan Byška
- Department of Informatics, University of Bergen, Bergen, Norway
- Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Thomas Arnesen
- Department of Biological Sciences, University of Bergen, Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
- Department of Surgery, Haukeland University Hospital, Bergen, Norway
| | - Nathalie Reuter
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
- Department of Chemistry, University of Bergen, Bergen, Norway
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32
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Campitelli P, Modi T, Kumar S, Ozkan SB. The Role of Conformational Dynamics and Allostery in Modulating Protein Evolution. Annu Rev Biophys 2020; 49:267-288. [PMID: 32075411 DOI: 10.1146/annurev-biophys-052118-115517] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Advances in sequencing techniques and statistical methods have made it possible not only to predict sequences of ancestral proteins but also to identify thousands of mutations in the human exome, some of which are disease associated. These developments have motivated numerous theories and raised many questions regarding the fundamental principles behind protein evolution, which have been traditionally investigated horizontally using the tip of the phylogenetic tree through comparative studies of extant proteins within a family. In this article, we review a vertical comparison of the modern and resurrected ancestral proteins. We focus mainly on the dynamical properties responsible for a protein's ability to adapt new functions in response to environmental changes. Using the Dynamic Flexibility Index and the Dynamic Coupling Index to quantify the relative flexibility and dynamic coupling at a site-specific, single-amino-acid level, we provide evidence that the migration of hinges, which are often functionally critical rigid sites, is a mechanism through which proteins can rapidly evolve. Additionally, we show that disease-associated mutations in proteins often result in flexibility changes even at positions distal from mutational sites, particularly in the modulation of active site dynamics.
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Affiliation(s)
- Paul Campitelli
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, Arizona 85281, USA; , ,
| | - Tushar Modi
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, Arizona 85281, USA; , ,
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, Pennsylvania 19122, USA; .,Department of Biology, Temple University, Philadelphia, Pennsylvania 19122, USA.,Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - S Banu Ozkan
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, Arizona 85281, USA; , ,
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33
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Li H, Doruker P, Hu G, Bahar I. Modulation of Toroidal Proteins Dynamics in Favor of Functional Mechanisms upon Ligand Binding. Biophys J 2020; 118:1782-1794. [PMID: 32130874 DOI: 10.1016/j.bpj.2020.01.046] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 01/05/2020] [Accepted: 01/27/2020] [Indexed: 12/16/2022] Open
Abstract
Toroidal proteins serve as molecular machines and play crucial roles in biological processes such as DNA replication and RNA transcription. Despite progress in the structural characterization of several toroidal proteins, we still lack a mechanistic understanding of the significance of their architecture, oligomerization states, and intermolecular interactions in defining their biological function. In this work, we analyze the collective dynamics of toroidal proteins with different oligomerization states, namely, dimeric and trimeric DNA sliding clamps, nucleocapsid proteins (4-, 5-, and 6-mers) and Trp RNA-binding attenuation proteins (11- and 12-mers). We observe common global modes, among which cooperative rolling stands out as a mechanism enabling DNA processivity, and clamshell motions as those underlying the opening/closure of the sliding clamps. Alterations in global dynamics due to complexation with DNA or the clamp loader are shown to assist in enhancing motions to enable robust function. The analysis provides new insights into the differentiation and enhancement of functional motions upon intersubunit and intermolecular interactions.
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Affiliation(s)
- Hongchun Li
- Center for Systems Biology, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China; Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania; Research Center for Computer-Aided Drug Discovery, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Guang Hu
- Center for Systems Biology, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China.
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
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34
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Domain-mediated interactions for protein subfamily identification. Sci Rep 2020; 10:264. [PMID: 31937869 PMCID: PMC6959277 DOI: 10.1038/s41598-019-57187-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 12/23/2019] [Indexed: 11/24/2022] Open
Abstract
Within a protein family, proteins with the same domain often exhibit different cellular functions, despite the shared evolutionary history and molecular function of the domain. We hypothesized that domain-mediated interactions (DMIs) may categorize a protein family into subfamilies because the diversified functions of a single domain often depend on interacting partners of domains. Here we systematically identified DMI subfamilies, in which proteins share domains with DMI partners, as well as with various functional and physical interaction networks in individual species. In humans, DMI subfamily members are associated with similar diseases, including cancers, and are frequently co-associated with the same diseases. DMI information relates to the functional and evolutionary subdivisions of human kinases. In yeast, DMI subfamilies contain proteins with similar phenotypic outcomes from specific chemical treatments. Therefore, the systematic investigation here provides insights into the diverse functions of subfamilies derived from a protein family with a link-centric approach and suggests a useful resource for annotating the functions and phenotypic outcomes of proteins.
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35
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Zhang Y, Doruker P, Kaynak B, Zhang S, Krieger J, Li H, Bahar I. Intrinsic dynamics is evolutionarily optimized to enable allosteric behavior. Curr Opin Struct Biol 2019; 62:14-21. [PMID: 31785465 DOI: 10.1016/j.sbi.2019.11.002] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 10/31/2019] [Accepted: 11/04/2019] [Indexed: 12/13/2022]
Abstract
Allosteric behavior is central to the function of many proteins, enabling molecular machinery, metabolism, signaling and regulation. Recent years have shown that the intrinsic dynamics of allosteric proteins defined by their 3-dimensional architecture or by the topology of inter-residue contacts favors cooperative motions that bear close similarity to structural changes they undergo during their allosteric actions. These conformational motions are usually driven by energetically favorable or soft modes at the low frequency end of the mode spectrum, and they are evolutionarily conserved among orthologs. These observations brought into light evolutionary adaptation mechanisms that help maintain, optimize or regulate allosteric behavior as the evolution from bacterial to higher organisms introduces sequential heterogeneities and structural complexities.
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Affiliation(s)
- Yan Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Burak Kaynak
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - She Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - James Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Hongchun Li
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA; Research Center for Computer-Aided Drug Discovery, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA.
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36
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Cheng MH, Ponzoni L, Sorkina T, Lee JY, Zhang S, Sorkin A, Bahar I. Trimerization of dopamine transporter triggered by AIM-100 binding: Molecular mechanism and effect of mutations. Neuropharmacology 2019; 161:107676. [PMID: 31228486 DOI: 10.1016/j.neuropharm.2019.107676] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Revised: 06/17/2019] [Accepted: 06/18/2019] [Indexed: 10/26/2022]
Abstract
Recent work demonstrated the propensity of dopamine transporters (DATs) to form trimers or higher oligomers, enhanced upon binding a furopyrimidine, AIM-100. AIM-100 binding promotes DAT endocytosis and thereby moderates dopaminergic transmission. Despite the neurobiological significance of these events, the molecular mechanisms that underlie the stabilization of DAT trimer and the key interactions that modulate the trimerization of DAT, and not serotonin transporter SERT, remain unclear. In the present study, we determined three structural models, termed trimer-W238, -C306 and -Y303, for possible trimerization of DATs . To this aim, we used structural data resolved for DAT and its structural homologs that share the LeuT fold, advanced computational modeling and simulations, site-directed mutagenesis experiments and live-cell imaging assays. The models are in accord with the versatility of LeuT fold to stabilize dimeric or higher order constructs. Selected residues show a high propensity to occupy interfacial regions. Among them, D231-W238 in the extracellular loop EL2, including the intersubunit salt-bridge forming pair D231/D232-R237 (not present in SERT) (in trimer-W238), the loop EL3 (trimers-C306 and -Y303), and W497 on the intracellularly exposed IL5 loop (trimer-C306) and its spatial neighbors (e.g. K525) near the C-terminus are computationally predicted and experimentally confirmed to play important roles in enabling the correct folding and/or oligomerization of DATs in the presence of AIM-100. The study suggests the possibility of controlling the effective transport of dopamine by altering the oligomerization state of DAT upon small molecule binding, as a possible intervention strategy to modulate dopaminergic signaling. This article is part of the issue entitled 'Special Issue on Neurotransmitter Transporters'.
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Affiliation(s)
- Mary Hongying Cheng
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Luca Ponzoni
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tatiana Sorkina
- Department of Cell Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ji Young Lee
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - She Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alexander Sorkin
- Department of Cell Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
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