1
|
Saldaño TE, Freixas VM, Tosatto SCE, Parisi G, Fernandez-Alberti S. Exploring Conformational Space with Thermal Fluctuations Obtained by Normal-Mode Analysis. J Chem Inf Model 2020; 60:3068-3080. [PMID: 32216314 DOI: 10.1021/acs.jcim.9b01136] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Proteins in their native states can be represented as ensembles of conformers in dynamical equilibrium. Thermal fluctuations are responsible for transitions between these conformers. Normal-modes analysis (NMA) using elastic network models (ENMs) provides an efficient procedure to explore global dynamics of proteins commonly associated with conformational transitions. In the present work, we present an iterative approach to explore protein conformational spaces by introducing structural distortions according to their equilibrium dynamics at room temperature. The approach can be used either to perform unbiased explorations of conformational space or to explore guided pathways connecting two different conformations, e.g., apo and holo forms. In order to test its performance, four proteins with different magnitudes of structural distortions upon ligand binding have been tested. In all cases, the conformational selection model has been confirmed and the conformational space between apo and holo forms has been encompassed. Different strategies have been tested that impact on the efficiency either to achieve a desired conformational change or to achieve a balanced exploration of the protein conformational multiplicity.
Collapse
Affiliation(s)
- Tadeo E Saldaño
- Universidad Nacional de Quilmes/CONICET, Roque Saenz Peña 352, B1876BXD Bernal, Argentina
| | - Victor M Freixas
- Universidad Nacional de Quilmes/CONICET, Roque Saenz Peña 352, B1876BXD Bernal, Argentina
| | - Silvio C E Tosatto
- Department of Biomedical Sciences, University of Padova, Viale G. Colombo 3, 5131 Padova, Italy
| | - Gustavo Parisi
- Universidad Nacional de Quilmes/CONICET, Roque Saenz Peña 352, B1876BXD Bernal, Argentina
| | | |
Collapse
|
2
|
Coarse-grained dynamics of supramolecules: Conformational changes in outer shells of Dengue viruses. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2018; 143:20-37. [PMID: 30273615 DOI: 10.1016/j.pbiomolbio.2018.09.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 09/22/2018] [Accepted: 09/24/2018] [Indexed: 01/12/2023]
Abstract
While structural data on viruses are more and more common, information on their dynamics is much harder to obtain as those viruses form very large molecular complexes. In this paper, we propose a new method for computing the coarse-grained normal modes of such supra-molecules, NormalGo. A new formalism is developed to represent the Hessian of a quadratic potential using tensor products. This formalism is applied to the Tirion elastic potential, as well as to a Gō like potential. When combined with a fast method for computing a select set of eigenpairs of the Hessian, this new formalism enables the computation of thousands of normal modes of a full viral shell with more than one hundred thousand atoms in less than 2 h on a standard desktop computer. We then compare the two coarse-grained potentials. We show that, despite significant differences in their formulations, the Tirion and the Gō like potentials capture very similar dynamics characteristics of the molecule under study. However, we find that the Gō like potential should be preferred as it leads to less local deformations in the structure of the molecule during normal mode dynamics. Finally, we use NormalGo to characterize the structural transitions that occur when FAB fragments bind to the icosahedral outer shell of serotype 3 of the Dengue virus. We have identified residues at the surface of the outer shell that are important for the transition between the FAB-free and FAB-bound conformations, and therefore potentially useful for the design of antibodies to Dengue viruses.
Collapse
|
3
|
Chen YL, Habeck M. Data-driven coarse graining of large biomolecular structures. PLoS One 2017; 12:e0183057. [PMID: 28817608 PMCID: PMC5560709 DOI: 10.1371/journal.pone.0183057] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2017] [Accepted: 07/29/2017] [Indexed: 11/18/2022] Open
Abstract
Advances in experimental and computational techniques allow us to study the structure and dynamics of large biomolecular assemblies at increasingly higher resolution. However, with increasing structural detail it can be challenging to unravel the mechanism underlying the function of molecular machines. One reason is that atomistic simulations become computationally prohibitive. Moreover it is difficult to rationalize the functional mechanism of systems composed of tens of thousands to millions of atoms by following each atom’s movements. Coarse graining (CG) allows us to understand biological structures from a hierarchical perspective and to gradually zoom into the adequate level of structural detail. This article introduces a Bayesian approach for coarse graining biomolecular structures. We develop a probabilistic model that aims to represent the shape of an experimental structure as a cloud of bead particles. The particles interact via a pairwise potential whose parameters are estimated along with the bead positions and the CG mapping between atoms and beads. Our model can also be applied to density maps obtained by cryo-electron microscopy. We illustrate our approach on various test systems.
Collapse
Affiliation(s)
- Yi-Ling Chen
- Statistical Inverse Problems in Biophysics, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany
- Department of NMR based Structural Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany
| | - Michael Habeck
- Statistical Inverse Problems in Biophysics, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany
- Felix Bernstein Institute for Mathematical Statistics in the Biosciences, Georg August University Göttingen, Goldschmidtstrasse 7, 37077 Göttingen, Germany
- * E-mail:
| |
Collapse
|
4
|
Koehl P, Poitevin F, Navaza R, Delarue M. The Renormalization Group and Its Applications to Generating Coarse-Grained Models of Large Biological Molecular Systems. J Chem Theory Comput 2017; 13:1424-1438. [PMID: 28170254 DOI: 10.1021/acs.jctc.6b01136] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Understanding the dynamics of biomolecules is the key to understanding their biological activities. Computational methods ranging from all-atom molecular dynamics simulations to coarse-grained normal-mode analyses based on simplified elastic networks provide a general framework to studying these dynamics. Despite recent successes in studying very large systems with up to a 100,000,000 atoms, those methods are currently limited to studying small- to medium-sized molecular systems due to computational limitations. One solution to circumvent these limitations is to reduce the size of the system under study. In this paper, we argue that coarse-graining, the standard approach to such size reduction, must define a hierarchy of models of decreasing sizes that are consistent with each other, i.e., that each model contains the information of the dynamics of its predecessor. We propose a new method, Decimate, for generating such a hierarchy within the context of elastic networks for normal-mode analysis. This method is based on the concept of the renormalization group developed in statistical physics. We highlight the details of its implementation, with a special focus on its scalability to large systems of up to millions of atoms. We illustrate its application on two large systems, the capsid of a virus and the ribosome translation complex. We show that highly decimated representations of those systems, containing down to 1% of their original number of atoms, still capture qualitatively and quantitatively their dynamics. Decimate is available as an OpenSource resource.
Collapse
Affiliation(s)
- Patrice Koehl
- Department of Computer Sciences and Genome Center, University of California, Davis , Davis, California 95616, United States
| | - Frédéric Poitevin
- Department of Structural Biology, Stanford University , Stanford, California 94305, United States.,Stanford PULSE Institute, SLAC National Accelerator Laboratory, Standford University , Menlo Park, California 94025, United States
| | - Rafael Navaza
- Platform of Crystallogenesis and Crystallography, CiTech, Institut Pasteur , 75015 Paris, France
| | - Marc Delarue
- Unité de Dynamique Structurale des Macromolécules, UMR 3528 du CNRS, Institut Pasteur , 75015 Paris, France
| |
Collapse
|
5
|
Hsieh YC, Poitevin F, Delarue M, Koehl P. Comparative Normal Mode Analysis of the Dynamics of DENV and ZIKV Capsids. Front Mol Biosci 2016; 3:85. [PMID: 28083537 PMCID: PMC5187361 DOI: 10.3389/fmolb.2016.00085] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 12/12/2016] [Indexed: 11/13/2022] Open
Abstract
Key steps in the life cycle of a virus, such as the fusion event as the virus infects a host cell and its maturation process, relate to an intricate interplay between the structure and the dynamics of its constituent proteins, especially those that define its capsid, much akin to an envelope that protects its genomic material. We present a comprehensive, comparative analysis of such interplay for the capsids of two viruses from the flaviviridae family, Dengue (DENV) and Zika (ZIKV). We use for that purpose our own software suite, DD-NMA, which is based on normal mode analysis. We describe the elements of DD-NMA that are relevant to the analysis of large systems, such as virus capsids. In particular, we introduce our implementation of simplified elastic networks and justify their parametrization. Using DD-NMA, we illustrate the importance of packing interactions within the virus capsids on the dynamics of the E proteins of DENV and ZIKV. We identify differences between the computed atomic fluctuations of the E proteins in DENV and ZIKV and relate those differences to changes observed in their high resolution structures. We conclude with a discussion on additional analyses that are needed to fully characterize the dynamics of the two viruses.
Collapse
Affiliation(s)
- Yin-Chen Hsieh
- Department of Computer Science and Genome Center, University of California, Davis Davis, CA, USA
| | - Frédéric Poitevin
- Department of Structural Biology, Stanford UniversityStanford, CA, USA; SLAC National Accelerator Laboratory, Stanford PULSE InstituteMenlo Park, CA, USA
| | - Marc Delarue
- Unit of Structural Dynamics of Macromolecules, UMR 3528 du Centre National de la Recherche Scientifique, Institut Pasteur Paris, France
| | - Patrice Koehl
- Department of Computer Science and Genome Center, University of California, Davis Davis, CA, USA
| |
Collapse
|
6
|
Kurkcuoglu Z, Bahar I, Doruker P. ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution. J Chem Theory Comput 2016; 12:4549-62. [PMID: 27494296 DOI: 10.1021/acs.jctc.6b00319] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events.
Collapse
Affiliation(s)
- Zeynep Kurkcuoglu
- Department of Chemical Engineering and Polymer Research Center, Bogazici University , Bebek 34342, Istanbul, Turkey
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh , Pittsburgh, Pennsylvania 15213, United States
| | - Pemra Doruker
- Department of Chemical Engineering and Polymer Research Center, Bogazici University , Bebek 34342, Istanbul, Turkey
| |
Collapse
|