1
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Dahmani Z, Scott AL, Vénien-Bryan C, Perahia D, Costa MG. MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search. J Chem Inf Model 2024; 64:5151-5160. [PMID: 38907694 PMCID: PMC11234365 DOI: 10.1021/acs.jcim.3c02007] [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: 01/03/2024] [Revised: 06/17/2024] [Accepted: 06/17/2024] [Indexed: 06/24/2024]
Abstract
Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.
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Affiliation(s)
- Zakaria
L. Dahmani
- School
of Medicine, Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch I Bldg, 3420 Forbes Avenue, Pittsburgh, Pennsylvania 15260, United States
- UMR
7590, CNRS, Museum National d’Histoire Naturelle, Institut
de Minéralogie, Physique des Matériaux et Cosmochimie,
IMPMC, Sorbonne Université, 4 place Jussieu, Paris 75005, France
| | - Ana Ligia Scott
- CMCC,
Computational Biophysics and Biology, Universidade Federal do ABC, Avenida dos Estados 5001, São Paulo, Santo André 09210-580, Brazil
- Université
de Strasbourg—IGBMC—Departament de Biologie structurale
integrative, 1 rue Laurent
Fries BP, Illkirch 10142
67404, CEDEX, France
| | - Catherine Vénien-Bryan
- UMR
7590, CNRS, Museum National d’Histoire Naturelle, Institut
de Minéralogie, Physique des Matériaux et Cosmochimie,
IMPMC, Sorbonne Université, 4 place Jussieu, Paris 75005, France
| | - David Perahia
- Laboratoire
de Biologie et Pharmacologie Appliquée, UMR 8113, École
Normale Supérieure Paris-Saclay, Gif-sur-Yvette 91190, France
| | - Mauricio G.S Costa
- UMR
7590, CNRS, Museum National d’Histoire Naturelle, Institut
de Minéralogie, Physique des Matériaux et Cosmochimie,
IMPMC, Sorbonne Université, 4 place Jussieu, Paris 75005, France
- Laboratoire
de Biologie et Pharmacologie Appliquée, UMR 8113, École
Normale Supérieure Paris-Saclay, Gif-sur-Yvette 91190, France
- Programa de Computação Científica,
Vice-Presidência de Educação, Informação
e Comunicação, Fundação Oswaldo Cruz, Av.Brasil 4365, Residência
Oficial, Manguinhos, Rio de Janeiro 21040-900, Brazil
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2
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Bock LV, Igaev M, Grubmüller H. Single-particle Cryo-EM and molecular dynamics simulations: A perfect match. Curr Opin Struct Biol 2024; 86:102825. [PMID: 38723560 DOI: 10.1016/j.sbi.2024.102825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 04/08/2024] [Accepted: 04/09/2024] [Indexed: 05/19/2024]
Abstract
Knowledge of the structure and dynamics of biomolecules is key to understanding the mechanisms underlying their biological functions. Single-particle cryo-electron microscopy (cryo-EM) is a powerful structural biology technique to characterize complex biomolecular systems. Here, we review recent advances of how Molecular Dynamics (MD) simulations are being used to increase and enhance the information extracted from cryo-EM experiments. We will particularly focus on the physics underlying these experiments, how MD facilitates structure refinement, in particular for heterogeneous and non-isotropic resolution, and how thermodynamic and kinetic information can be extracted from cryo-EM data.
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Affiliation(s)
- Lars V Bock
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Am Fassberg 11, Göttingen, 37077, Germany. https://twitter.com/Pogoscience
| | - Maxim Igaev
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Am Fassberg 11, Göttingen, 37077, Germany. https://twitter.com/maxotubule
| | - Helmut Grubmüller
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Am Fassberg 11, Göttingen, 37077, Germany.
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3
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Vuillemot R, Harastani M, Hamitouche I, Jonic S. MDSPACE and MDTOMO Software for Extracting Continuous Conformational Landscapes from Datasets of Single Particle Images and Subtomograms Based on Molecular Dynamics Simulations: Latest Developments in ContinuousFlex Software Package. Int J Mol Sci 2023; 25:20. [PMID: 38203192 PMCID: PMC10779004 DOI: 10.3390/ijms25010020] [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: 11/06/2023] [Revised: 12/16/2023] [Accepted: 12/17/2023] [Indexed: 01/12/2024] Open
Abstract
Cryo electron microscopy (cryo-EM) instrumentation allows obtaining 3D reconstruction of the structure of biomolecular complexes in vitro (purified complexes studied by single particle analysis) and in situ (complexes studied in cells by cryo electron tomography). Standard cryo-EM approaches allow high-resolution reconstruction of only a few conformational states of a molecular complex, as they rely on data classification into a given number of classes to increase the resolution of the reconstruction from the most populated classes while discarding all other classes. Such discrete classification approaches result in a partial picture of the full conformational variability of the complex, due to continuous conformational transitions with many, uncountable intermediate states. In this article, we present the software with a user-friendly graphical interface for running two recently introduced methods, namely, MDSPACE and MDTOMO, to obtain continuous conformational landscapes of biomolecules by analyzing in vitro and in situ cryo-EM data (single particle images and subtomograms) based on molecular dynamics simulations of an available atomic model of one of the conformations. The MDSPACE and MDTOMO software is part of the open-source ContinuousFlex software package (starting from version 3.4.2 of ContinuousFlex), which can be run as a plugin of the Scipion software package (version 3.1 and later), broadly used in the cryo-EM field.
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Affiliation(s)
| | | | | | - Slavica Jonic
- IMPMC-UMR 7590 CNRS, Sorbonne Université, MNHN, 75005 Paris, France
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4
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Miyashita O, Tama F. Advancing cryo-electron microscopy data analysis through accelerated simulation-based flexible fitting approaches. Curr Opin Struct Biol 2023; 82:102653. [PMID: 37451233 DOI: 10.1016/j.sbi.2023.102653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 05/30/2023] [Accepted: 06/19/2023] [Indexed: 07/18/2023]
Abstract
Flexible fitting based on molecular dynamics simulation is a technique for structure modeling from cryo-EM data. It has been utilized for nearly two decades, and while cryo-EM resolution has improved significantly, it remains a powerful approach that can provide structural and dynamical insights that are not directly accessible from experimental data alone. Molecular dynamics simulations provide a means to extract atomistic details of conformational changes that are encoded in cryo-EM data and can also assist in improving the quality of structural models. Additionally, molecular dynamics simulations enable the characterization of conformational heterogeneity in cryo-EM data. We will summarize the advancements made in these techniques and highlight recent developments in this field.
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Affiliation(s)
- Osamu Miyashita
- RIKEN Center for Computational Science, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
| | - Florence Tama
- RIKEN Center for Computational Science, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; Department of Physics, Graduate School of Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan; Institute of Transformative Bio-Molecules, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan.
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5
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Yvonnesdotter L, Rovšnik U, Blau C, Lycksell M, Howard RJ, Lindahl E. Automated simulation-based membrane protein refinement into cryo-EM data. Biophys J 2023; 122:2773-2781. [PMID: 37277992 PMCID: PMC10397807 DOI: 10.1016/j.bpj.2023.05.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 04/02/2023] [Accepted: 05/31/2023] [Indexed: 06/07/2023] Open
Abstract
The resolution revolution has increasingly enabled single-particle cryogenic electron microscopy (cryo-EM) reconstructions of previously inaccessible systems, including membrane proteins-a category that constitutes a disproportionate share of drug targets. We present a protocol for using density-guided molecular dynamics simulations to automatically refine atomistic models into membrane protein cryo-EM maps. Using adaptive force density-guided simulations as implemented in the GROMACS molecular dynamics package, we show how automated model refinement of a membrane protein is achieved without the need to manually tune the fitting force ad hoc. We also present selection criteria to choose the best-fit model that balances stereochemistry and goodness of fit. The proposed protocol was used to refine models into a new cryo-EM density of the membrane protein maltoporin, either in a lipid bilayer or detergent micelle, and we found that results do not substantially differ from fitting in solution. Fitted structures satisfied classical model-quality metrics and improved the quality and the model-to-map correlation of the x-ray starting structure. Additionally, the density-guided fitting in combination with generalized orientation-dependent all-atom potential was used to correct the pixel-size estimation of the experimental cryo-EM density map. This work demonstrates the applicability of a straightforward automated approach to fitting membrane protein cryo-EM densities. Such computational approaches promise to facilitate rapid refinement of proteins under different conditions or with various ligands present, including targets in the highly relevant superfamily of membrane proteins.
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Affiliation(s)
- Linnea Yvonnesdotter
- Science for Life Laboratory & Swedish e-Science Research Center, Department of Applied Physics, KTH Royal Institute of Technology, Solna, Sweden
| | - Urška Rovšnik
- Science for Life Laboratory & Swedish e-Science Research Center, Department of Applied Physics, KTH Royal Institute of Technology, Solna, Sweden
| | - Christian Blau
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden
| | - Marie Lycksell
- Science for Life Laboratory & Swedish e-Science Research Center, Department of Applied Physics, KTH Royal Institute of Technology, Solna, Sweden
| | - Rebecca Joy Howard
- Science for Life Laboratory & Swedish e-Science Research Center, Department of Applied Physics, KTH Royal Institute of Technology, Solna, Sweden
| | - Erik Lindahl
- Science for Life Laboratory & Swedish e-Science Research Center, Department of Applied Physics, KTH Royal Institute of Technology, Solna, Sweden; Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden.
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6
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Vuillemot R, Rouiller I, Jonić S. MDTOMO method for continuous conformational variability analysis in cryo electron subtomograms based on molecular dynamics simulations. Sci Rep 2023; 13:10596. [PMID: 37391578 PMCID: PMC10313669 DOI: 10.1038/s41598-023-37037-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 06/14/2023] [Indexed: 07/02/2023] Open
Abstract
Cryo electron tomography (cryo-ET) allows observing macromolecular complexes in their native environment. The common routine of subtomogram averaging (STA) allows obtaining the three-dimensional (3D) structure of abundant macromolecular complexes, and can be coupled with discrete classification to reveal conformational heterogeneity of the sample. However, the number of complexes extracted from cryo-ET data is usually small, which restricts the discrete-classification results to a small number of enough populated states and, thus, results in a largely incomplete conformational landscape. Alternative approaches are currently being investigated to explore the continuity of the conformational landscapes that in situ cryo-ET studies could provide. In this article, we present MDTOMO, a method for analyzing continuous conformational variability in cryo-ET subtomograms based on Molecular Dynamics (MD) simulations. MDTOMO allows obtaining an atomic-scale model of conformational variability and the corresponding free-energy landscape, from a given set of cryo-ET subtomograms. The article presents the performance of MDTOMO on a synthetic ABC exporter dataset and an in situ SARS-CoV-2 spike dataset. MDTOMO allows analyzing dynamic properties of molecular complexes to understand their biological functions, which could also be useful for structure-based drug discovery.
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Affiliation(s)
- Rémi Vuillemot
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, CC 115, 4 Place Jussieu, 75005, Paris, France
- Department of Biochemistry and Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Isabelle Rouiller
- Department of Biochemistry and Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, VIC, 3010, Australia
- Australian Research Council Centre for Cryo-Electron Microscopy of Membrane Proteins, Parkville, VIC, 3052, Australia
| | - Slavica Jonić
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, CC 115, 4 Place Jussieu, 75005, Paris, France.
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7
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Flechsig H, Ando T. Protein dynamics by the combination of high-speed AFM and computational modeling. Curr Opin Struct Biol 2023; 80:102591. [PMID: 37075535 DOI: 10.1016/j.sbi.2023.102591] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 03/06/2023] [Accepted: 03/08/2023] [Indexed: 04/21/2023]
Abstract
High-speed atomic force microscopy (HS-AFM) allows direct observation of biological molecules in dynamic action. However, HS-AFM has no atomic resolution. This article reviews recent progress of computational methods to infer high-resolution information, including the construction of 3D atomistic structures, from experimentally acquired resolution-limited HS-AFM images.
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Affiliation(s)
- Holger Flechsig
- Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa, 920-1192, Japan
| | - Toshio Ando
- Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa, 920-1192, Japan.
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8
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Vuillemot R, Mirzaei A, Harastani M, Hamitouche I, Fréchin L, Klaholz BP, Miyashita O, Tama F, Rouiller I, Jonic S. MDSPACE: Extracting Continuous Conformational Landscapes from Cryo-EM Single Particle Datasets Using 3D-to-2D Flexible Fitting based on Molecular Dynamics Simulation. J Mol Biol 2023; 435:167951. [PMID: 36638910 DOI: 10.1016/j.jmb.2023.167951] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 12/08/2022] [Accepted: 01/03/2023] [Indexed: 01/12/2023]
Abstract
This article presents an original approach for extracting atomic-resolution landscapes of continuous conformational variability of biomolecular complexes from cryo electron microscopy (cryo-EM) single particle images. This approach is based on a new 3D-to-2D flexible fitting method, which uses molecular dynamics (MD) simulation and is embedded in an iterative conformational-landscape refinement scheme. This new approach is referred to as MDSPACE, which stands for Molecular Dynamics simulation for Single Particle Analysis of Continuous Conformational hEterogeneity. The article describes the MDSPACE approach and shows its performance using synthetic and experimental datasets.
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Affiliation(s)
- Rémi Vuillemot
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France; Department of Biochemistry & Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Victoria, Australia
| | - Alex Mirzaei
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Mohamad Harastani
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Ilyes Hamitouche
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Léo Fréchin
- Centre for Integrative Biology, Department of Integrated Structural Biology, IGBMC-UMR 7104 CNRS, U964 Inserm, Université de Strasbourg, Strasbourg, France
| | - Bruno P Klaholz
- Centre for Integrative Biology, Department of Integrated Structural Biology, IGBMC-UMR 7104 CNRS, U964 Inserm, Université de Strasbourg, Strasbourg, France
| | | | - Florence Tama
- RIKEN Center for Computational Science, Kobe, Japan; Institute of Transformative Biomolecules, Graduate School of Science, Nagoya University, Nagoya, Japan; Department of Physics, Graduate School of Science, Nagoya University, Nagoya, Japan
| | - Isabelle Rouiller
- Department of Biochemistry & Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Victoria, Australia
| | - Slavica Jonic
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France.
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9
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Harastani M, Vuillemot R, Hamitouche I, Moghadam NB, Jonic S. ContinuousFlex: Software package for analyzing continuous conformational variability of macromolecules in cryo electron microscopy and tomography data. J Struct Biol 2022; 214:107906. [PMID: 36244611 DOI: 10.1016/j.jsb.2022.107906] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 09/02/2022] [Accepted: 10/07/2022] [Indexed: 11/06/2022]
Abstract
ContinuousFlex is a user-friendly open-source software package for analyzing continuous conformational variability of macromolecules in cryo electron microscopy (cryo-EM) and cryo electron tomography (cryo-ET) data. In 2019, ContinuousFlex became available as a plugin for Scipion, an image processing software package extensively used in the cryo-EM field. Currently, ContinuousFlex contains software for running (1) recently published methods HEMNMA-3D, TomoFlow, and NMMD; (2) earlier published methods HEMNMA and StructMap; and (3) methods for simulating cryo-EM and cryo-ET data with conformational variability and methods for data preprocessing. It also includes external software for molecular dynamics simulation (GENESIS) and normal mode analysis (ElNemo), used in some of the mentioned methods. The HEMNMA software has been presented in the past, but not the software of other methods. Besides, ContinuousFlex currently also offers a deep learning extension of HEMNMA, named DeepHEMNMA. In this article, we review these methods in the context of the ContinuousFlex package, developed to facilitate their use by the community.
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Affiliation(s)
- Mohamad Harastani
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Rémi Vuillemot
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Ilyes Hamitouche
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Nima Barati Moghadam
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Slavica Jonic
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France.
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10
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The ribosome stabilizes partially folded intermediates of a nascent multi-domain protein. Nat Chem 2022; 14:1165-1173. [PMID: 35927328 PMCID: PMC7613651 DOI: 10.1038/s41557-022-01004-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 06/20/2022] [Indexed: 12/13/2022]
Abstract
Co-translational folding is crucial to ensure the production of biologically active proteins. The ribosome can alter the folding pathways of nascent polypeptide chains, yet a structural understanding remains largely inaccessible experimentally. We have developed site-specific labelling of nascent chains to detect and measure, using 19F nuclear magnetic resonance (NMR) spectroscopy, multiple states accessed by an immunoglobulin-like domain within a tandem repeat protein during biosynthesis. By examining ribosomes arrested at different stages during translation of this common structural motif, we observe highly broadened NMR resonances attributable to two previously unidentified intermediates, which are stably populated across a wide folding transition. Using molecular dynamics simulations and corroborated by cryo-electron microscopy, we obtain models of these partially folded states, enabling experimental verification of a ribosome-binding site that contributes to their high stabilities. We thus demonstrate a mechanism by which the ribosome could thermodynamically regulate folding and other co-translational processes. ![]()
Most proteins must fold co-translationally on the ribosome to adopt biologically active conformations, yet structural, mechanistic descriptions are lacking. Using 19F NMR spectroscopy to study a nascent multi-domain protein has now enabled the identification of two co-translational folding intermediates that are significantly more stable than intermediates formed off the ribosome, suggesting that the ribosome may thermodynamically regulate folding.
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11
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DeVore K, Chiu PL. Probing Structural Perturbation of Biomolecules by Extracting Cryo-EM Data Heterogeneity. Biomolecules 2022; 12:628. [PMID: 35625556 PMCID: PMC9138638 DOI: 10.3390/biom12050628] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/15/2022] [Accepted: 04/18/2022] [Indexed: 02/04/2023] Open
Abstract
Single-particle cryogenic electron microscopy (cryo-EM) has become an indispensable tool to probe high-resolution structural detail of biomolecules. It enables direct visualization of the biomolecules and opens a possibility for averaging molecular images to reconstruct a three-dimensional Coulomb potential density map. Newly developed algorithms for data analysis allow for the extraction of structural heterogeneity from a massive and low signal-to-noise-ratio (SNR) cryo-EM dataset, expanding our understanding of multiple conformational states, or further implications in dynamics, of the target biomolecule. This review provides an overview that briefly describes the workflow of single-particle cryo-EM, including imaging and data processing, and new methods developed for analyzing the data heterogeneity to understand the structural variability of biomolecules.
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Affiliation(s)
| | - Po-Lin Chiu
- School of Molecular Sciences, Biodesign Center for Applied Structural Discovery, Arizona State University, Tempe, AZ 85287, USA;
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12
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Vuillemot R, Miyashita O, Tama F, Rouiller I, Jonic S. NMMD: Efficient cryo-EM flexible fitting based on simultaneous Normal Mode and Molecular Dynamics atomic displacements. J Mol Biol 2022; 434:167483. [PMID: 35150654 DOI: 10.1016/j.jmb.2022.167483] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 01/18/2022] [Accepted: 01/31/2022] [Indexed: 11/28/2022]
Abstract
Atomic models of cryo electron microscopy (cryo-EM) maps of biomolecular conformations are often obtained by flexible fitting of the maps with available atomic structures of other conformations (e.g., obtained by X-ray crystallography). This article presents a new flexible fitting method, NMMD, which combines normal mode analysis (NMA) and molecular dynamics simulation (MD). Given an atomic structure and a cryo-EM map to fit, NMMD simultaneously estimates global atomic displacements based on NMA and local displacements based on MD. NMMD was implemented by modifying EMfit, a flexible fitting method using MD only, in GENESIS 1.4. As EMfit, NMMD can be run with replica exchange umbrella sampling procedure. The new method was tested using a variety of EM maps (synthetic and experimental, with different noise levels and resolutions). The results of the tests show that adding normal modes to MD-based fitting makes the fitting faster (40% in average) and, in the majority of cases, more accurate.
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Affiliation(s)
- Rémi Vuillemot
- IMPMC - UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France; Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Victoria, Australia
| | | | - Florence Tama
- Institute of Transformative Biomolecules and Department of Physics, Graduate School of Science, Nagoya University, Japan
| | - Isabelle Rouiller
- Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Victoria, Australia
| | - Slavica Jonic
- IMPMC - UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France.
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13
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Niina T, Matsunaga Y, Takada S. Rigid-body fitting to atomic force microscopy images for inferring probe shape and biomolecular structure. PLoS Comput Biol 2021; 17:e1009215. [PMID: 34283829 PMCID: PMC8323932 DOI: 10.1371/journal.pcbi.1009215] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 07/30/2021] [Accepted: 06/26/2021] [Indexed: 12/01/2022] Open
Abstract
Atomic force microscopy (AFM) can visualize functional biomolecules near the physiological condition, but the observed data are limited to the surface height of specimens. Since the AFM images highly depend on the probe tip shape, for successful inference of molecular structures from the measurement, the knowledge of the probe shape is required, but is often missing. Here, we developed a method of the rigid-body fitting to AFM images, which simultaneously finds the shape of the probe tip and the placement of the molecular structure via an exhaustive search. First, we examined four similarity scores via twin-experiments for four test proteins, finding that the cosine similarity score generally worked best, whereas the pixel-RMSD and the correlation coefficient were also useful. We then applied the method to two experimental high-speed-AFM images inferring the probe shape and the molecular placement. The results suggest that the appropriate similarity score can differ between target systems. For an actin filament image, the cosine similarity apparently worked best. For an image of the flagellar protein FlhAC, we found the correlation coefficient gave better results. This difference may partly be attributed to the flexibility in the target molecule, ignored in the rigid-body fitting. The inferred tip shape and placement results can be further refined by other methods, such as the flexible fitting molecular dynamics simulations. The developed software is publicly available. Observation of functional dynamics of individual biomolecules is important to understand molecular mechanisms of cellular phenomena. High-speed (HS) atomic force microscopy (AFM) is a powerful tool that enables us to visualize the real-time dynamics of working biomolecules under near-physiological conditions. However, the information available by the AFM images is limited to the two-dimensional surface shape detected via the force to the probe. While the surface information is affected by the shape of the probe tip, the probe shape itself cannot be directly measured before each AFM measurement. To overcome this problem, we have developed a computational method to simultaneously infer the probe tip shape and the molecular placement from an AFM image. We show that our method successfully estimates the effective AFM tip shape and visualizes a structure with a more accurate placement. The estimation of a molecular placement with the correct probe tip shape enables us to obtain more insights into functional dynamics of the molecule from HS-AFM images.
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Affiliation(s)
- Toru Niina
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | - Yasuhiro Matsunaga
- Graduate School of Science and Engineering, Saitama University, Saitama, Japan
| | - Shoji Takada
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
- * E-mail:
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14
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Mori T, Terashi G, Matsuoka D, Kihara D, Sugita Y. Efficient Flexible Fitting Refinement with Automatic Error Fixing for De Novo Structure Modeling from Cryo-EM Density Maps. J Chem Inf Model 2021; 61:3516-3528. [PMID: 34142833 PMCID: PMC9282639 DOI: 10.1021/acs.jcim.1c00230] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Structural modeling of proteins from cryo-electron microscopy (cryo-EM) density maps is one of the challenging issues in structural biology. De novo modeling combined with flexible fitting refinement (FFR) has been widely used to build a structure of new proteins. In de novo prediction, artificial conformations containing local structural errors such as chirality errors, cis peptide bonds, and ring penetrations are frequently generated and cannot be easily removed in the subsequent FFR. Moreover, refinement can be significantly suppressed due to the low mobility of atoms inside the protein. To overcome these problems, we propose an efficient scheme for FFR, in which the local structural errors are fixed first, followed by FFR using an iterative simulated annealing (SA) molecular dynamics protocol with the united atom (UA) model in an implicit solvent model; we call this scheme "SAUA-FFR". The best model is selected from multiple flexible fitting runs with various biasing force constants to reduce overfitting. We apply our scheme to the decoys obtained from MAINMAST and demonstrate an improvement of the best model of eight selected proteins in terms of the root-mean-square deviation, MolProbity score, and RWplus score compared to the original scheme of MAINMAST. Fixing the local structural errors can enhance the formation of secondary structures, and the UA model enables progressive refinement compared to the all-atom model owing to its high mobility in the implicit solvent. The SAUA-FFR scheme realizes efficient and accurate protein structure modeling from medium-resolution maps with less overfitting.
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Affiliation(s)
- Takaharu Mori
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
| | - Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana 47907, United States
| | - Daisuke Matsuoka
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
| | - Daisuke Kihara
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana 47907, United States.,Department of Computer Science, Purdue University, West Lafayette, Indiana 47907, United States
| | - Yuji Sugita
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan.,RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,RIKEN Center for Biosystems Dynamics Research, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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15
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Kulik M, Mori T, Sugita Y. Multi-Scale Flexible Fitting of Proteins to Cryo-EM Density Maps at Medium Resolution. Front Mol Biosci 2021; 8:631854. [PMID: 33842541 PMCID: PMC8025875 DOI: 10.3389/fmolb.2021.631854] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Accepted: 01/26/2021] [Indexed: 11/13/2022] Open
Abstract
Structure determination using cryo-electron microscopy (cryo-EM) medium-resolution density maps is often facilitated by flexible fitting. Avoiding overfitting, adjusting force constants driving the structure to the density map, and emulating complex conformational transitions are major concerns in the fitting. To address them, we develop a new method based on a three-step multi-scale protocol. First, flexible fitting molecular dynamics (MD) simulations with coarse-grained structure-based force field and replica-exchange scheme between different force constants replicas are performed. Second, fitted Cα atom positions guide the all-atom structure in targeted MD. Finally, the all-atom flexible fitting refinement in implicit solvent adjusts the positions of the side chains in the density map. Final models obtained via the multi-scale protocol are significantly better resolved and more reliable in comparison with long all-atom flexible fitting simulations. The protocol is useful for multi-domain systems with intricate structural transitions as it preserves the secondary structure of single domains.
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Affiliation(s)
- Marta Kulik
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako-shi, Japan
| | - Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako-shi, Japan
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako-shi, Japan.,RIKEN Center for Computational Science, Kobe, Japan.,RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
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16
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Fuchigami S, Niina T, Takada S. Case Report: Bayesian Statistical Inference of Experimental Parameters via Biomolecular Simulations: Atomic Force Microscopy. Front Mol Biosci 2021; 8:636940. [PMID: 33778008 PMCID: PMC7987833 DOI: 10.3389/fmolb.2021.636940] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 01/25/2021] [Indexed: 11/13/2022] Open
Abstract
The atomic force microscopy (AFM) is a powerful tool for imaging structures of molecules bound on surfaces. To gain high-resolution structural information, one often superimposes structure models on the measured images. Motivated by high flexibility of biomolecules, we previously developed a flexible-fitting molecular dynamics (MD) method that allows protein structural changes upon superimposing. Since the AFM image largely depends on the AFM probe tip geometry, the fitting process requires accurate estimation of the parameters related to the tip geometry. Here, we performed a Bayesian statistical inference to estimate a tip radius of the AFM probe from a given AFM image via flexible-fitting molecular dynamics (MD) simulations. We first sampled conformations of the nucleosome that fit well the reference AFM image by the flexible-fitting with various tip radii. We then estimated an optimal tip parameter by maximizing the conditional probability density of the AFM image produced from the fitted structure.
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Affiliation(s)
- Sotaro Fuchigami
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | | | - Shoji Takada
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
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17
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Seffernick JT, Lindert S. Hybrid methods for combined experimental and computational determination of protein structure. J Chem Phys 2020; 153:240901. [PMID: 33380110 PMCID: PMC7773420 DOI: 10.1063/5.0026025] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/10/2020] [Indexed: 02/04/2023] Open
Abstract
Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein-protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions.
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Affiliation(s)
- Justin T. Seffernick
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
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18
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Resolving the data asynchronicity in high-speed atomic force microscopy measurement via the Kalman Smoother. Sci Rep 2020; 10:18393. [PMID: 33110182 PMCID: PMC7592071 DOI: 10.1038/s41598-020-75463-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 10/14/2020] [Indexed: 11/09/2022] Open
Abstract
High-speed atomic force microscopy (HS-AFM) is a scanning probe microscopy that can capture structural dynamics of biomolecules in real time at single molecule level near physiological condition. Albeit much improvement, while scanning one frame of HS-AFM movies, biomolecules often change their conformations largely. Thus, the obtained frame images can be hampered by the time-difference, the asynchronicity, in the data acquisition. Here, to resolve this data asynchronicity in the HS-AFM movie, we developed Kalman filter and smoother methods, some of the sequential Bayesian filtering approaches. The Kalman filter/smoother methods use alternative steps of a short time-propagation by a linear dynamical system and a correction by the likelihood of AFM data acquired pixel by pixel. We first tested the method using a toy model of a diffusing cone, showing that the Kalman smoother method outperforms to reproduce the ground-truth movie. We then applied the Kalman smoother to a synthetic movie for conformational change dynamics of a motor protein, i.e., dynein, confirming the superiority of the Kalman smoother. Finally, we applied the Kalman smoother to two real HS-AFM movies, FlhAC and centralspindlin, reducing distortion and noise in the AFM movies. The method is general and can be applied to any HS-AFM movies.
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19
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Koukos P, Bonvin A. Integrative Modelling of Biomolecular Complexes. J Mol Biol 2020; 432:2861-2881. [DOI: 10.1016/j.jmb.2019.11.009] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Revised: 11/12/2019] [Accepted: 11/13/2019] [Indexed: 12/31/2022]
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20
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Dodd T, Yan C, Ivanov I. Simulation-Based Methods for Model Building and Refinement in Cryoelectron Microscopy. J Chem Inf Model 2020; 60:2470-2483. [PMID: 32202798 DOI: 10.1021/acs.jcim.0c00087] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Advances in cryoelectron microscopy (cryo-EM) have revolutionized the structural investigation of large macromolecular assemblies. In this review, we first provide a broad overview of modeling methods used for flexible fitting of molecular models into cryo-EM density maps. We give special attention to approaches rooted in molecular simulations-atomistic molecular dynamics and Monte Carlo. Concise descriptions of the methods are given along with discussion of their advantages, limitations, and most popular alternatives. We also describe recent extensions of the widely used molecular dynamics flexible fitting (MDFF) method and discuss how different model-building techniques could be incorporated into new hybrid modeling schemes and simulation workflows. Finally, we provide two illustrative examples of model-building and refinement strategies employing MDFF, cascade MDFF, and RosettaCM. These examples come from recent cryo-EM studies that elucidated transcription preinitiation complexes and shed light on the functional roles of these assemblies in gene expression and gene regulation.
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Affiliation(s)
- Thomas Dodd
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302, United States.,Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30302, United States
| | - Chunli Yan
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302, United States.,Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30302, United States
| | - Ivaylo Ivanov
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302, United States.,Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30302, United States
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21
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Niina T, Fuchigami S, Takada S. Flexible Fitting of Biomolecular Structures to Atomic Force Microscopy Images via Biased Molecular Simulations. J Chem Theory Comput 2020; 16:1349-1358. [PMID: 31909999 DOI: 10.1021/acs.jctc.9b00991] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
High-speed (HS) atomic force microscopy (AFM) is a prominent imaging technology that observes large-scale structural dynamics of biomolecules near the physiological condition, but the AFM data are limited to the surface shape of specimens. Rigid-body fitting methods were developed to obtain molecular structures that fit to an AFM image, without accounting for conformational changes. Here, we developed a method to fit flexibly a three-dimensional (3D) biomolecular structure into an AFM image. First, we describe a method to produce a pseudo-AFM image from a given 3D structure in a differentiable form. Then, using a correlation function between the experimental AFM image and the computational pseudo-AFM image, we developed a flexible fitting molecular dynamics (MD) simulation method by which we obtain protein structures that well fit to the given AFM image. We first test it with a twin experiment; using an AFM image produced from a protein structure different from its native conformation as a reference, we performed the flexible fitting MD simulations to sample conformations that fit well the reference AFM image, and the method was confirmed to work well. Then, parameter dependence in the protocol was discussed. Finally, we applied the method to a real experimental HS-AFM image for a flagellar protein FlhA, demonstrating its applicability. We also test the rigid-body fitting of a molecular structure to an AFM image. Our method will be a general tool for dynamic structure modeling based on HS-AFM images and is publicly available through the CafeMol software.
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Affiliation(s)
- Toru Niina
- Department of Biophysics, Graduate School of Science , Kyoto University , Kyoto 606-8502 , Japan
| | - Sotaro Fuchigami
- Department of Biophysics, Graduate School of Science , Kyoto University , Kyoto 606-8502 , Japan
| | - Shoji Takada
- Department of Biophysics, Graduate School of Science , Kyoto University , Kyoto 606-8502 , Japan
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22
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Costa MGS, Fagnen C, Vénien-Bryan C, Perahia D. A New Strategy for Atomic Flexible Fitting in Cryo-EM Maps by Molecular Dynamics with Excited Normal Modes (MDeNM-EMfit). J Chem Inf Model 2020; 60:2419-2423. [DOI: 10.1021/acs.jcim.9b01148] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Mauricio G. S. Costa
- Fundacao Oswaldo Cruz, Programa de Computação Científica, Vice-Presidência de Educação, Informação e Comunicação, Av. Brasil 4365, Residência Oficial, Manguinhos, 21040-900 Rio de Janeiro, Brazil
- Sorbonne Université, UMR 7590, CNRS, Museum National d’Histoire Naturelle, Institut de Minéralogie, Physique des Matériaux et Cosmochimie, IMPMC, 4 place Jussieu, 75005 Paris, France
- École Normale Supérieure Paris-Saclay, UMR 8113, CNRS, Laboratoire de Biologie et de Pharmacologie Appliquée 61 Av du Président Wilson, 94235 Cachan, France
| | - Charline Fagnen
- Sorbonne Université, UMR 7590, CNRS, Museum National d’Histoire Naturelle, Institut de Minéralogie, Physique des Matériaux et Cosmochimie, IMPMC, 4 place Jussieu, 75005 Paris, France
- École Normale Supérieure Paris-Saclay, UMR 8113, CNRS, Laboratoire de Biologie et de Pharmacologie Appliquée 61 Av du Président Wilson, 94235 Cachan, France
| | - Catherine Vénien-Bryan
- Sorbonne Université, UMR 7590, CNRS, Museum National d’Histoire Naturelle, Institut de Minéralogie, Physique des Matériaux et Cosmochimie, IMPMC, 4 place Jussieu, 75005 Paris, France
| | - David Perahia
- École Normale Supérieure Paris-Saclay, UMR 8113, CNRS, Laboratoire de Biologie et de Pharmacologie Appliquée 61 Av du Président Wilson, 94235 Cachan, France
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23
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Alnabati E, Kihara D. Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps. Molecules 2019; 25:molecules25010082. [PMID: 31878333 PMCID: PMC6982917 DOI: 10.3390/molecules25010082] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 12/20/2019] [Accepted: 12/20/2019] [Indexed: 01/16/2023] Open
Abstract
Cryo-electron microscopy (cryo-EM) has now become a widely used technique for structure determination of macromolecular complexes. For modeling molecular structures from density maps of different resolutions, many algorithms have been developed. These algorithms can be categorized into rigid fitting, flexible fitting, and de novo modeling methods. It is also observed that machine learning (ML) techniques have been increasingly applied following the rapid progress of the ML field. Here, we review these different categories of macromolecule structure modeling methods and discuss their advances over time.
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Affiliation(s)
- Eman Alnabati
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
- Correspondence:
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24
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Kim DN, Moriarty NW, Kirmizialtin S, Afonine PV, Poon B, Sobolev OV, Adams PD, Sanbonmatsu K. Cryo_fit: Democratization of flexible fitting for cryo-EM. J Struct Biol 2019; 208:1-6. [PMID: 31279069 PMCID: PMC7112765 DOI: 10.1016/j.jsb.2019.05.012] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 05/31/2019] [Indexed: 12/18/2022]
Abstract
Cryo-electron microscopy (cryo-EM) is becoming a method of choice for describing native conformations of biomolecular complexes at high resolution. The rapid growth of cryo-EM in recent years has created a high demand for automated solutions, both in hardware and software. Flexible fitting of atomic models to three-dimensional (3D) cryo-EM reconstructions by molecular dynamics (MD) simulation is a popular technique but often requires technical expertise in computer simulation. This work introduces cryo_fit, a package for the automatic flexible fitting of atomic models in cryo-EM maps using MD simulation. The package is integrated with the Phenix software suite. The module was designed to automate the multiple steps of MD simulation in a reproducible manner, as well as facilitate refinement and validation through Phenix. Through the use of cryo_fit, scientists with little experience in MD simulation can produce high quality atomic models automatically and better exploit the potential of cryo-EM.
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Affiliation(s)
- Doo Nam Kim
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Nigel W Moriarty
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA
| | - Serdal Kirmizialtin
- Chemistry Program, Science Division, New York University, Abu Dhabi, United Arab Emirates
| | - Pavel V Afonine
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA
| | - Billy Poon
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA
| | - Oleg V Sobolev
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA
| | - Paul D Adams
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA; Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA
| | - Karissa Sanbonmatsu
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM, USA; New Mexico Consortium, Los Alamos, NM, USA.
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25
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Lei D, Liu J, Liu H, Cleveland TE, Marino JP, Lei M, Ren G. Single-Molecule 3D Images of "Hole-Hole" IgG1 Homodimers by Individual-Particle Electron Tomography. Sci Rep 2019; 9:8864. [PMID: 31221961 PMCID: PMC6586654 DOI: 10.1038/s41598-019-44978-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Accepted: 05/30/2019] [Indexed: 12/20/2022] Open
Abstract
The engineering of immunoglobulin-G molecules (IgGs) is of wide interest for improving therapeutics, for example by modulating the activity or multiplexing the specificity of IgGs to recognize more than one antigen. Optimization of engineered IgG requires knowledge of three-dimensional (3D) structure of synthetic IgG. However, due to flexible nature of the molecules, their structural characterization is challenging. Here, we use our reported individual-particle electron tomography (IPET) method with optimized negative-staining (OpNS) for direct 3D reconstruction of individual IgG hole-hole homodimer molecules. The hole-hole homodimer is an undesired variant generated during the production of a bispecific antibody using the knob-into-hole heterodimer technology. A total of 64 IPET 3D density maps at ~15 Å resolutions were reconstructed from 64 individual molecules, revealing 64 unique conformations. In addition to the known Y-shaped conformation, we also observed an unusual X-shaped conformation. The 3D structure of the X-shaped conformation contributes to our understanding of the structural details of the interaction between two heavy chains in the Fc domain. The IPET approach, as an orthogonal technique to characterize the 3D structure of therapeutic antibodies, provides insight into the 3D structural variety and dynamics of heterogeneous IgG molecules.
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Affiliation(s)
- Dongsheng Lei
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Jianfang Liu
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Hongbin Liu
- Protein Analytical Chemistry, Genentech Inc., South San Francisco, CA, 94080, USA
| | - Thomas E Cleveland
- Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, MD, 20850, USA
| | - John P Marino
- Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, MD, 20850, USA
| | - Ming Lei
- Protein Analytical Chemistry, Genentech Inc., South San Francisco, CA, 94080, USA.
| | - Gang Ren
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
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26
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Peng J, Yuan C, Ma R, Zhang Z. Backmapping from Multiresolution Coarse-Grained Models to Atomic Structures of Large Biomolecules by Restrained Molecular Dynamics Simulations Using Bayesian Inference. J Chem Theory Comput 2019; 15:3344-3353. [PMID: 30908042 DOI: 10.1021/acs.jctc.9b00062] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Coarse-grained (CG) simulations have allowed access to larger length scales and longer time scales in the study of the dynamic processes of large biomolecules than all-atom (AA) molecular dynamics (MD) simulations. Backmapping from CG models to AA structures has long been studied because it enables us to gain detailed structure insights from CG simulations. Many methods first construct an AA structure from the CG model by fragments, random placement, or geometrical rules and subsequently optimize the solution via energy minimization, simulated annealing or position-restrained simulations. However, such methods may only work well on residue-level CG models and cannot consider the deviations of CG models. In this work, we describe, to the best of our knowledge, a new backmapping method based on Bayesian inference and restrained MD simulations. Restraints with log harmonic energy terms are defined according to the target CG model using the Bayesian inference in which the CG deviations can be estimated. From an initial AA structure obtained from either high-resolution experiments or homology modeling, a MD simulation with the aforementioned restraints is performed to obtain a final AA structure that is a backmapping of the target CG model. The method was validated using multiresolution CG models of the soluble extracellular region of the human epidermal growth factor receptor and was further applied to construct AA structures from CG simulations of the nucleosome core particle. The results demonstrate that our method can generate accurate AA structures of different types of biomolecules from multiple CG models with either residue-level resolution or much lower resolution than one-site-per-residue.
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Affiliation(s)
- Junhui Peng
- Hefei National Laboratory for Physical Science at Microscale and School of Life Sciences , University of Science and Technology of China , Hefei , Anhui 230026 , People's Republic of China
| | - Chuang Yuan
- Hefei National Laboratory for Physical Science at Microscale and School of Life Sciences , University of Science and Technology of China , Hefei , Anhui 230026 , People's Republic of China
| | - Rongsheng Ma
- Hefei National Laboratory for Physical Science at Microscale and School of Life Sciences , University of Science and Technology of China , Hefei , Anhui 230026 , People's Republic of China
| | - Zhiyong Zhang
- Hefei National Laboratory for Physical Science at Microscale and School of Life Sciences , University of Science and Technology of China , Hefei , Anhui 230026 , People's Republic of China
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27
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Harada R, Shigeta Y. How low-resolution structural data predict the conformational changes of a protein: a study on data-driven molecular dynamics simulations. Phys Chem Chem Phys 2019; 20:17790-17798. [PMID: 29922770 DOI: 10.1039/c8cp02246a] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Parallel cascade selection molecular dynamics (PaCS-MD) is a conformational sampling method for generating transition pathways between a given reactant and a product. PaCS-MD repeats the following two steps: (1) selections of initial structures relevant to transitions and (2) their conformational resampling. When selecting the initial structures, several measures are utilized to identify their potential to undergo transitions. In the present study, low-resolution structural data obtained from small angle scattering (SAXS) and cryo-electron microscopy (EM) are adopted as the measures in PaCS-MD to promote the conformational transitions of proteins, which is defined as SAXS-/EM-driven targeted PaCS-MD. By selecting the essential structures that have high correlations with the low-resolution structural data, the SAXS-/EM-driven targeted PaCS-MD identifies a set of transition pathways between the reactant and the product. As a demonstration, the present method successfully predicted the open-closed transition pathway of the lysine-, arginine-, ornithine-binding protein with a ns-order simulation time, indicating that the data-driven PaCS-MD simulation might work to promote the conformational transitions of proteins efficiently.
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Affiliation(s)
- Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Ibaraki 305-8577, Japan.
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28
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Igaev M, Kutzner C, Bock LV, Vaiana AC, Grubmüller H. Automated cryo-EM structure refinement using correlation-driven molecular dynamics. eLife 2019; 8:e43542. [PMID: 30829573 PMCID: PMC6424565 DOI: 10.7554/elife.43542] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 03/03/2019] [Indexed: 12/22/2022] Open
Abstract
We present a correlation-driven molecular dynamics (CDMD) method for automated refinement of atomistic models into cryo-electron microscopy (cryo-EM) maps at resolutions ranging from near-atomic to subnanometer. It utilizes a chemically accurate force field and thermodynamic sampling to improve the real-space correlation between the modeled structure and the cryo-EM map. Our framework employs a gradual increase in resolution and map-model agreement as well as simulated annealing, and allows fully automated refinement without manual intervention or any additional rotamer- and backbone-specific restraints. Using multiple challenging systems covering a wide range of map resolutions, system sizes, starting model geometries and distances from the target state, we assess the quality of generated models in terms of both model accuracy and potential of overfitting. To provide an objective comparison, we apply several well-established methods across all examples and demonstrate that CDMD performs best in most cases.
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Affiliation(s)
- Maxim Igaev
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
| | - Carsten Kutzner
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
| | - Lars V Bock
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
| | - Andrea C Vaiana
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
| | - Helmut Grubmüller
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
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SAXS-guided Enhanced Unbiased Sampling for Structure Determination of Proteins and Complexes. Sci Rep 2018; 8:17748. [PMID: 30531946 PMCID: PMC6288155 DOI: 10.1038/s41598-018-36090-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 11/12/2018] [Indexed: 02/08/2023] Open
Abstract
Molecular simulations can be utilized to predict protein structure ensembles and dynamics, though sufficient sampling of molecular ensembles and identification of key biologically relevant conformations remains challenging. Low-resolution experimental techniques provide valuable structural information on biomolecule at near-native conditions, which are often combined with molecular simulations to determine and refine protein structural ensembles. In this study, we demonstrate how small angle x-ray scattering (SAXS) information can be incorporated in Markov state model-based adaptive sampling strategy to enhance time efficiency of unbiased MD simulations and identify functionally relevant conformations of proteins and complexes. Our results show that using SAXS data combined with additional information, such as thermodynamics and distance restraints, we are able to distinguish otherwise degenerate structures due to the inherent ambiguity of SAXS pattern. We further demonstrate that adaptive sampling guided by SAXS and hybrid information can significantly reduce the computation time required to discover target structures. Overall, our findings demonstrate the potential of this hybrid approach in predicting near-native structures of proteins and complexes. Other low-resolution experimental information can be incorporated in a similar manner to collectively enhance unbiased sampling and improve the accuracy of structure prediction from simulation.
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Mori T, Kulik M, Miyashita O, Jung J, Tama F, Sugita Y. Acceleration of cryo-EM Flexible Fitting for Large Biomolecular Systems by Efficient Space Partitioning. Structure 2018; 27:161-174.e3. [PMID: 30344106 DOI: 10.1016/j.str.2018.09.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 06/22/2018] [Accepted: 09/18/2018] [Indexed: 01/21/2023]
Abstract
Flexible fitting is a powerful technique to build the 3D structures of biomolecules from cryoelectron microscopy (cryo-EM) density maps. One popular method is a cross-correlation coefficient-based approach, where the molecular dynamics (MD) simulation is carried out with the biasing potential that includes the cross-correlation coefficient between the experimental and simulated density maps. Here, we propose efficient parallelization schemes for the calculation of the cross-correlation coefficient to accelerate flexible fitting. Our schemes are tested for small, medium, and large biomolecules using CPU and hybrid CPU + GPU architectures. The scheme for the atomic decomposition MD is suitable for small proteins such as Ca2+-ATPase with the all-atom Go model, while that for the domain decomposition MD is better for larger systems such as ribosome with the all-atom Go or the all-atom explicit solvent models. Our methods allow flexible fitting for various biomolecules with reasonable computational cost. This approach also connects high-resolution structure refinements with investigation of protein structure-function relationship.
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Affiliation(s)
- Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
| | - Marta Kulik
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
| | - Osamu Miyashita
- RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Jaewoon Jung
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan; RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Florence Tama
- RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; Department of Physics, Graduate School of Science, and Institute of Transformative Bio-Molecules, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan; RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; RIKEN Center for Biosystems Dynamics Research, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
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31
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Kovacs JA, Galkin VE, Wriggers W. Accurate flexible refinement of atomic models against medium-resolution cryo-EM maps using damped dynamics. BMC STRUCTURAL BIOLOGY 2018; 18:12. [PMID: 30219048 PMCID: PMC6139150 DOI: 10.1186/s12900-018-0089-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 08/02/2018] [Indexed: 12/30/2022]
Abstract
BACKGROUND Dramatic progress has recently been made in cryo-electron microscopy technologies, which now make possible the reconstruction of a growing number of biomolecular structures to near-atomic resolution. However, the need persists for fitting and refinement approaches that address those cases that require modeling assistance. METHODS In this paper, we describe algorithms to optimize the performance of such medium-resolution refinement methods. These algorithms aim to automatically optimize the parameters that define the density shape of the flexibly fitted model, as well as the time-dependent damper cutoff distance. Atomic distance constraints can be prescribed for cases where extra containment of parts of the structure is helpful, such as in regions where the density map is poorly defined. Also, we propose a simple stopping criterion that estimates the probable onset of overfitting during the simulation. RESULTS The new set of algorithms produce more accurate fitting and refinement results, and yield a faster rate of convergence of the trajectory toward the fitted conformation. The latter is also more reliable due to the overfitting warning provided to the user. CONCLUSIONS The algorithms described here were implemented in the new Damped-Dynamics Flexible Fitting simulation tool "DDforge" in the Situs package.
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Affiliation(s)
- Julio A Kovacs
- Department of Mechanical and Aerospace Engineering, Old Dominion University, Norfolk, VA, USA
| | - Vitold E Galkin
- Department of Physiological Sciences, Eastern Virginia Medical School, Norfolk, VA, USA
| | - Willy Wriggers
- Department of Mechanical and Aerospace Engineering, Old Dominion University, Norfolk, VA, USA.
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32
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Tiwari SP, Tama F, Miyashita O. Searching for 3D structural models from a library of biological shapes using a few 2D experimental images. BMC Bioinformatics 2018; 19:320. [PMID: 30208849 PMCID: PMC6134691 DOI: 10.1186/s12859-018-2358-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Accepted: 09/03/2018] [Indexed: 01/08/2023] Open
Abstract
Background Advancements in biophysical experimental techniques have pushed the limits in terms of the types of phenomena that can be characterized, the amount of data that can be produced and the resolution at which we can visualize them. Single particle techniques such as Electron Microscopy (EM) and X-ray free electron laser (XFEL) scattering require a large number of 2D images collected to resolve three-dimensional (3D) structures. In this study, we propose a quick strategy to retrieve potential 3D shapes, as low-resolution models, from a few 2D experimental images by searching a library of 2D projection images generated from existing 3D structures. Results We developed the protocol to assemble a non-redundant set of 3D shapes for generating the 2D image library, and to retrieve potential match 3D shapes for query images, using EM data as a test. In our strategy, we disregard differences in volume size, giving previously unknown structures and conformations a greater number of 3D biological shapes as possible matches. We tested the strategy using images from three EM models as query images for searches against a library of 22750 2D projection images generated from 250 random EM models. We found that our ability to identify 3D shapes that match the query images depends on how complex the outline of the 2D shapes are and whether they are represented in the search image library. Conclusions Through our computational method, we are able to quickly retrieve a 3D shape from a few 2D projection images. Our approach has the potential for exploring other types of 2D single particle structural data such as from XFEL scattering experiments, for providing a tool to interpret low-resolution data that may be insufficient for 3D reconstruction, and for estimating the mixing of states or conformations that could exist in such experimental data. Electronic supplementary material The online version of this article (10.1186/s12859-018-2358-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sandhya P Tiwari
- Computational Structural Biology Unit, RIKEN Center for Computational Science, Kobe, Japan
| | - Florence Tama
- Computational Structural Biology Unit, RIKEN Center for Computational Science, Kobe, Japan. .,Graduate School of Science, Department of Physics & Institute of Transformative Bio-Molecules (WPI-ITbM), Nagoya University, Nagoya, Japan.
| | - Osamu Miyashita
- Computational Structural Biology Unit, RIKEN Center for Computational Science, Kobe, Japan
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33
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Cassidy CK, Himes BA, Luthey-Schulten Z, Zhang P. CryoEM-based hybrid modeling approaches for structure determination. Curr Opin Microbiol 2018; 43:14-23. [PMID: 29107896 PMCID: PMC5934336 DOI: 10.1016/j.mib.2017.10.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Revised: 10/04/2017] [Accepted: 10/09/2017] [Indexed: 12/21/2022]
Abstract
Recent advances in cryo-electron microscopy (cryoEM) have dramatically improved the resolutions at which vitrified biological specimens can be studied, revealing new structural and mechanistic insights over a broad range of spatial scales. Bolstered by these advances, much effort has been directed toward the development of hybrid modeling methodologies for the construction and refinement of high-fidelity atomistic models from cryoEM data. In this brief review, we will survey the key elements of cryoEM-based hybrid modeling, providing an overview of available computational tools and strategies as well as several recent applications.
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Affiliation(s)
- C Keith Cassidy
- Department of Physics, Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Benjamin A Himes
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Zaida Luthey-Schulten
- Department of Chemistry, Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Peijun Zhang
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; Electron Bio-Imaging Centre, Diamond Light Sources, Harwell Science and Innovation Campus, Didcot OX11 0DE, UK.
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34
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Abstract
Biological macromolecules often undergo large conformational rearrangements during a functional cycle. To simulate these structural transitions with full atomic detail typically demands extensive computational resources. Moreover, it is unclear how to incorporate, in a principled way, additional experimental information that could guide the structural transition. This article develops a probabilistic model for conformational transitions in biomolecules. The model can be viewed as a network of anharmonic springs that break, if the experimental data support the rupture of bonds. Hamiltonian Monte Carlo in internal coordinates is used to infer structural transitions from experimental data, thereby sampling large conformational transitions without distorting the structure. The model is benchmarked on a large set of conformational transitions. Moreover, we demonstrate the use of the probabilistic network model for integrative modeling of macromolecular complexes based on data from crosslinking followed by mass spectrometry.
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Affiliation(s)
- 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
| | - Thach Nguyen
- Felix Bernstein Institute for Mathematical Statistics in the Biosciences, Georg August University Göttingen, Goldschmidtstrasse 7, 37077, Göttingen, Germany
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35
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Tekpinar M. Flexible fitting to cryo-electron microscopy maps with coarse-grained elastic network models. MOLECULAR SIMULATION 2018. [DOI: 10.1080/08927022.2018.1431835] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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36
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Abstract
Over the past several years, single-particle cryo-electron microscopy (cryo-EM) has emerged as a leading method for elucidating macromolecular structures at near-atomic resolution, rivaling even the established technique of X-ray crystallography. Cryo-EM is now able to probe proteins as small as hemoglobin (64 kDa) while avoiding the crystallization bottleneck entirely. The remarkable success of cryo-EM has called into question the continuing relevance of X-ray methods, particularly crystallography. To say that the future of structural biology is either cryo-EM or crystallography, however, would be misguided. Crystallography remains better suited to yield precise atomic coordinates of macromolecules under a few hundred kilodaltons in size, while the ability to probe larger, potentially more disordered assemblies is a distinct advantage of cryo-EM. Likewise, crystallography is better equipped to provide high-resolution dynamic information as a function of time, temperature, pressure, and other perturbations, whereas cryo-EM offers increasing insight into conformational and energy landscapes, particularly as algorithms to deconvolute conformational heterogeneity become more advanced. Ultimately, the future of both techniques depends on how their individual strengths are utilized to tackle questions at the frontiers of structural biology. Structure determination is just one piece of a much larger puzzle: a central challenge of modern structural biology is to relate structural information to biological function. In this perspective, we share insight from several leaders in the field and examine the unique and complementary ways in which X-ray methods and cryo-EM can shape the future of structural biology.
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Affiliation(s)
- Susannah C. Shoemaker
- Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA
| | - Nozomi Ando
- Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA
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37
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Mehaffey MR, Cammarata MB, Brodbelt JS. Tracking the Catalytic Cycle of Adenylate Kinase by Ultraviolet Photodissociation Mass Spectrometry. Anal Chem 2018; 90:839-846. [PMID: 29188992 PMCID: PMC5750083 DOI: 10.1021/acs.analchem.7b03591] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The complex interplay of dynamic protein plasticity and specific side-chain interactions with substrate molecules that allows enzymes to catalyze reactions has yet to be fully unraveled. Top-down ultraviolet photodissociation (UVPD) mass spectrometry is used to track snapshots of conformational fluctuations in the phosphotransferase adenylate kinase (AK) throughout its active reaction cycle by characterization of complexes containing AK and each of four different adenosine phosphate ligands. Variations in efficiencies of UVPD backbone cleavages were consistently observed for three α-helices and the adenosine binding regions for AK complexes representing different steps of the catalytic cycle, implying that these stretches of the protein sample various structural microstates as the enzyme undergoes global open-to-closed transitions. Focusing on the conformational impact of recruiting or releasing the Mg2+ cofactor highlights two loop regions for which fragmentation increases upon UVPD, signaling an increase in loop flexibility as the metal cation disrupts the loop interactions with the substrate ligands. Additionally, the observation of holo ions and variations in UVPD backbone cleavage efficiency at R138 implicate this conserved active site residue in stabilizing the donor phosphoryl group during catalysis. This study showcases the utility of UVPD-MS to provide insight into conformational fluctuations of single residues for active enzymes.
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Affiliation(s)
- M. Rachel Mehaffey
- Department of Chemistry, University of Texas at Austin, Austin, TX 78712
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38
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Miyashita O, Tama F. Hybrid Methods for Macromolecular Modeling by Molecular Mechanics Simulations with Experimental Data. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1105:199-217. [PMID: 30617831 DOI: 10.1007/978-981-13-2200-6_13] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Hybrid approaches for the modeling of macromolecular complexes that combine computational molecular mechanics simulations with experimental data are discussed. Experimental data for biological molecular structures are often low-resolution, and thus, do not contain enough information to determine the atomic positions of molecules. This is especially true when the dynamics of large macromolecules are the focus of the study. However, computational modeling can complement missing information. Significant increase in computational power, as well as the development of new modeling algorithms allow us to model structures of biological macromolecules reliably, using experimental data as references. We review the basics of molecular mechanics approaches, such as atomic model force field, and coarse-grained models, molecular dynamics simulation and normal mode analysis and describe how they could be used for flexible fitting hybrid modeling with experimental data, especially from cryo-EM and SAXS.
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Affiliation(s)
| | - Florence Tama
- RIKEN R-CCS, Kobe, Hyōgo, Japan. .,Department of Physics and ITbM, Nagoya University, Nagoya, Japan.
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39
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Dou H, Burrows DW, Baker ML, Ju T. Flexible Fitting of Atomic Models into Cryo-EM Density Maps Guided by Helix Correspondences. Biophys J 2017. [PMID: 28636906 DOI: 10.1016/j.bpj.2017.04.054] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Although electron cryo-microscopy (cryo-EM) has recently achieved resolutions of better than 3 Å, at which point molecular modeling can be done directly from the density map, analysis and annotation of a cryo-EM density map still primarily rely on fitting atomic or homology models to the density map. In this article, we present, to our knowledge, a new method for flexible fitting of known or modeled protein structures into cryo-EM density maps. Unlike existing methods that are guided by local density gradients, our method is guided by correspondences between the α-helices in the density map and model, and does not require an initial rigid-body fitting step. Compared with current methods on both simulated and experimental density maps, our method not only achieves greater accuracy for proteins with large deformations but also runs as fast or faster than many of the other flexible fitting routines.
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Affiliation(s)
- Hang Dou
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri.
| | - Derek W Burrows
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri
| | - Matthew L Baker
- Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas
| | - Tao Ju
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri
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40
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Abstract
RosettaES, an algorithm that uses a fragment-based sampling strategy, improves macromolecular structure modeling from cryo-EM data at 3–5-Å resolution. Accurate atomic modeling of macromolecular structures into cryo-electron microscopy (cryo-EM) maps is a major challenge, as the moderate resolution makes accurate placement of atoms difficult. We present Rosetta enumerative sampling (RosettaES), an automated tool that uses a fragment-based sampling strategy for de novo model completion of macromolecular structures from cryo-EM density maps at 3–5-Å resolution. On a benchmark set of nine proteins, RosettaES was able to identify near-native conformations in 85% of segments. RosettaES was also used to determine models for three challenging macromolecular structures.
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41
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Miyashita O, Kobayashi C, Mori T, Sugita Y, Tama F. Flexible fitting to cryo-EM density map using ensemble molecular dynamics simulations. J Comput Chem 2017; 38:1447-1461. [PMID: 28370077 DOI: 10.1002/jcc.24785] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Revised: 01/26/2017] [Accepted: 02/22/2017] [Indexed: 12/25/2022]
Abstract
Flexible fitting is a computational algorithm to derive a new conformational model that conforms to low-resolution experimental data by transforming a known structure. A common application is against data from cryo-electron microscopy to obtain conformational models in new functional states. The conventional flexible fitting algorithms cannot derive correct structures in some cases due to the complexity of conformational transitions. In this study, we show the importance of conformational ensemble in the refinement process by performing multiple fittings trials using a variety of different force constants. Application to simulated maps of Ca2+ ATPase and diphtheria toxin as well as experimental data of release factor 2 revealed that for these systems, multiple conformations with similar agreement with the density map exist and a large number of fitting trials are necessary to generate good models. Clustering analysis can be an effective approach to avoid over-fitting models. In addition, we show that an automatic adjustment of the biasing force constants during the fitting process, implemented as replica-exchange scheme, can improve the success rate. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Osamu Miyashita
- Advanced Institute for Computational Science, RIKEN, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan
| | - Chigusa Kobayashi
- Advanced Institute for Computational Science, RIKEN, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan
| | - Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan.,iTHES, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan
| | - Yuji Sugita
- Advanced Institute for Computational Science, RIKEN, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan.,Theoretical Molecular Science Laboratory, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan.,iTHES, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan.,Quantitative Biology Center, RIKEN, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan
| | - Florence Tama
- Advanced Institute for Computational Science, RIKEN, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan.,Department of Physics and ITbM, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi, 464-8602, Japan
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42
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Habeck M. Bayesian Modeling of Biomolecular Assemblies with Cryo-EM Maps. Front Mol Biosci 2017; 4:15. [PMID: 28382301 PMCID: PMC5360716 DOI: 10.3389/fmolb.2017.00015] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 03/07/2017] [Indexed: 01/09/2023] Open
Abstract
A growing array of experimental techniques allows us to characterize the three-dimensional structure of large biological assemblies at increasingly higher resolution. In addition to X-ray crystallography and nuclear magnetic resonance in solution, new structure determination methods such cryo-electron microscopy (cryo-EM), crosslinking/mass spectrometry and solid-state NMR have emerged. Often it is not sufficient to use a single experimental method, but complementary data need to be collected by using multiple techniques. The integration of all datasets can only be achieved by computational means. This article describes Inferential structure determination, a Bayesian approach to integrative modeling of biomolecular complexes with hybrid structural data. I will introduce probabilistic models for cryo-EM maps and outline Markov chain Monte Carlo algorithms for sampling model structures from the posterior distribution. I will focus on rigid and flexible modeling with cryo-EM data and discuss some of the computational challenges of Bayesian inference in the context of biomolecular modeling.
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Affiliation(s)
- Michael Habeck
- Statistical Inverse Problems in Biophysics, Max Planck Institute for Biophysical ChemistryGöttingen, Germany; Felix Bernstein Institute for Mathematical Statistics in the Biosciences, University of GöttingenGöttingen, Germany
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43
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Qi Y, Lee J, Singharoy A, McGreevy R, Schulten K, Im W. CHARMM-GUI MDFF/xMDFF Utilizer for Molecular Dynamics Flexible Fitting Simulations in Various Environments. J Phys Chem B 2016; 121:3718-3723. [PMID: 27936734 DOI: 10.1021/acs.jpcb.6b10568] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
X-ray crystallography and cryo-electron microscopy are two popular methods for the structure determination of biological molecules. Atomic structures are derived through the fitting and refinement of an initial model into electron density maps constructed by both experiments. Two computational approaches, MDFF and xMDFF, have been developed to facilitate this process by integrating the experimental data with molecular dynamics simulation. However, the setup of an MDFF/xMDFF simulation requires knowledge of both experimental and computational methods, which is not straightforward for nonexpert users. In addition, sometimes it is desirable to include realistic environments, such as explicit solvent and lipid bilayers during the simulation, which poses another challenge even for expert users. To alleviate these difficulties, we have developed MDFF/xMDFF Utilizer in CHARMM-GUI that helps users to set up an MDFF/xMDFF simulation. The capability of MDFF/xMDFF Utilizer is greatly enhanced by integration with other CHARMM-GUI modules, including protein structure manipulation, a diverse set of lipid types, and all-atom CHARMM and coarse-grained PACE force fields. With this integration, various simulation environments are available for MDFF Utilizer (vacuum, implicit/explicit solvent, and bilayers) and xMDFF Utilizer (vacuum and solution). In this work, three examples are shown to demonstrate the usage of MDFF/xMDFF Utilizer.
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Affiliation(s)
- Yifei Qi
- Department of Biological Sciences and Bioengineering Program, Lehigh University , 111 Research Drive, Bethlehem, Pennsylvania 18015, United States
| | - Jumin Lee
- Department of Biological Sciences and Bioengineering Program, Lehigh University , 111 Research Drive, Bethlehem, Pennsylvania 18015, United States
| | - Abhishek Singharoy
- Beckman Institute and Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States
| | - Ryan McGreevy
- Beckman Institute and Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States
| | - Klaus Schulten
- Beckman Institute and Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States
| | - Wonpil Im
- Department of Biological Sciences and Bioengineering Program, Lehigh University , 111 Research Drive, Bethlehem, Pennsylvania 18015, United States
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44
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Singharoy A, Teo I, McGreevy R, Stone JE, Zhao J, Schulten K. Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps. eLife 2016; 5. [PMID: 27383269 PMCID: PMC4990421 DOI: 10.7554/elife.16105] [Citation(s) in RCA: 115] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 07/06/2016] [Indexed: 12/12/2022] Open
Abstract
Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services. DOI:http://dx.doi.org/10.7554/eLife.16105.001 To understand the roles that proteins and other large molecules play inside cells, it is important to determine their structures. One of the techniques that researchers can use to do this is called cryo-electron microscopy (cryo-EM), which rapidly freezes molecules to fix them in position before imaging them in fine detail. The cryo-EM images are like maps that show the approximate position of atoms. These images must then be processed in order to build a three-dimensional model of the protein that shows how its atoms are arranged relative to each other. One computational approach called Molecular Dynamics Flexible Fitting (MDFF) works by flexibly fitting possible atomic structures into cryo-EM maps. Although this approach works well with relatively undetailed (or ‘low resolution’) cryo-EM images, it struggles to handle the high-resolution cryo-EM maps now being generated. Singharoy, Teo, McGreevy et al. have now developed two MDFF methods – called cascade MDFF and resolution exchange MDFF – that help to resolve atomic models of biological molecules from cryo-EM images. Each method can refine poorly guessed models into ones that are consistent with the high-resolution experimental images. The refinement is achieved by interpreting a range of images that starts with a ‘fuzzy’ image. The contrast of the image is then progressively improved until an image is produced that has a resolution that is good enough to almost distinguish individual atoms. The method works because each cryo-EM image shows not just one, but a collection of atomic structures that the molecule can take on, with the fuzzier parts of the image representing the more flexible parts of the molecule. By taking into account this flexibility, the large-scale features of the protein structure can be determined first from the fuzzier images, and increasing the contrast of the images allows smaller-scale refinements to be made to the structure. The MDFF tools have been designed to be easy to use and are available to researchers at low cost through cloud computing platforms. They can now be used to unravel the structure of many different proteins and protein complexes including those involved in photosynthesis, respiration and protein synthesis. DOI:http://dx.doi.org/10.7554/eLife.16105.002
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Affiliation(s)
- Abhishek Singharoy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Ivan Teo
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Ryan McGreevy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - John E Stone
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Jianhua Zhao
- Department of Biochemistry and Biophysics, University of California San Francisco School of Medicine, San Francisco, United States
| | - Klaus Schulten
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States
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45
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Peng J, Zhang Z. Unraveling low-resolution structural data of large biomolecules by constructing atomic models with experiment-targeted parallel cascade selection simulations. Sci Rep 2016; 6:29360. [PMID: 27377017 PMCID: PMC4932515 DOI: 10.1038/srep29360] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 06/17/2016] [Indexed: 11/09/2022] Open
Abstract
Various low-resolution experimental techniques have gained more and more popularity in obtaining structural information of large biomolecules. In order to interpret the low-resolution structural data properly, one may need to construct an atomic model of the biomolecule by fitting the data using computer simulations. Here we develop, to our knowledge, a new computational tool for such integrative modeling by taking the advantage of an efficient sampling technique called parallel cascade selection (PaCS) simulation. For given low-resolution structural data, this PaCS-Fit method converts it into a scoring function. After an initial simulation starting from a known structure of the biomolecule, the scoring function is used to pick conformations for next cycle of multiple independent simulations. By this iterative screening-after-sampling strategy, the biomolecule may be driven towards a conformation that fits well with the low-resolution data. Our method has been validated using three proteins with small-angle X-ray scattering data and two proteins with electron microscopy data. In all benchmark tests, high-quality atomic models, with generally 1-3 Å from the target structures, are obtained. Since our tool does not need to add any biasing potential in the simulations to deform the structure, any type of low-resolution data can be implemented conveniently.
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Affiliation(s)
- Junhui Peng
- Hefei National Laboratory for Physical Science at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026, People’s Republic of China
| | - Zhiyong Zhang
- Hefei National Laboratory for Physical Science at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026, People’s Republic of China
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Yang K, Różycki B, Cui F, Shi C, Chen W, Li Y. Sampling Enrichment toward Target Structures Using Hybrid Molecular Dynamics-Monte Carlo Simulations. PLoS One 2016; 11:e0156043. [PMID: 27227775 PMCID: PMC4881967 DOI: 10.1371/journal.pone.0156043] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Accepted: 05/09/2016] [Indexed: 01/08/2023] Open
Abstract
Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE), is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD)-Monte Carlo (MC) approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS) intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD) from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation.
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Affiliation(s)
- Kecheng Yang
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bartosz Różycki
- Institute of Physics, Polish Academy of Sciences, Aleja Lotników 32/46, 02–668, Warsaw, Poland
| | - Fengchao Cui
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
- * E-mail: (FC); (YL)
| | - Ce Shi
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
| | - Wenduo Chen
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
| | - Yunqi Li
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
- * E-mail: (FC); (YL)
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Goh BC, Hadden JA, Bernardi RC, Singharoy A, McGreevy R, Rudack T, Cassidy CK, Schulten K. Computational Methodologies for Real-Space Structural Refinement of Large Macromolecular Complexes. Annu Rev Biophys 2016; 45:253-78. [PMID: 27145875 DOI: 10.1146/annurev-biophys-062215-011113] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed.
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Affiliation(s)
- Boon Chong Goh
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Jodi A Hadden
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Rafael C Bernardi
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Abhishek Singharoy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Ryan McGreevy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Till Rudack
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - C Keith Cassidy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Klaus Schulten
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801;
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McGreevy R, Teo I, Singharoy A, Schulten K. Advances in the molecular dynamics flexible fitting method for cryo-EM modeling. Methods 2016; 100:50-60. [PMID: 26804562 PMCID: PMC4848153 DOI: 10.1016/j.ymeth.2016.01.009] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Revised: 01/16/2016] [Accepted: 01/20/2016] [Indexed: 02/02/2023] Open
Abstract
Molecular Dynamics Flexible Fitting (MDFF) is an established technique for fitting all-atom structures of molecules into corresponding cryo-electron microscopy (cryo-EM) densities. The practical application of MDFF is simple but requires a user to be aware of and take measures against a variety of possible challenges presented by each individual case. Some of these challenges arise from the complexity of a molecular structure or the limited quality of available structural models and densities to be interpreted, while others stem from the intricacies of MDFF itself. The current article serves as an overview of the strategies that have been developed since MDFF's inception to overcome common challenges and successfully perform MDFF simulations.
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Affiliation(s)
- Ryan McGreevy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA
| | - Ivan Teo
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Abhishek Singharoy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA
| | - Klaus Schulten
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA; Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
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Xu X, Yan C, Wohlhueter R, Ivanov I. Integrative Modeling of Macromolecular Assemblies from Low to Near-Atomic Resolution. Comput Struct Biotechnol J 2015; 13:492-503. [PMID: 26557958 PMCID: PMC4588362 DOI: 10.1016/j.csbj.2015.08.005] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Revised: 08/09/2015] [Accepted: 08/13/2015] [Indexed: 02/02/2023] Open
Abstract
While conventional high-resolution techniques in structural biology are challenged by the size and flexibility of many biological assemblies, recent advances in low-resolution techniques such as cryo-electron microscopy (cryo-EM) and small angle X-ray scattering (SAXS) have opened up new avenues to define the structures of such assemblies. By systematically combining various sources of structural, biochemical and biophysical information, integrative modeling approaches aim to provide a unified structural description of such assemblies, starting from high-resolution structures of the individual components and integrating all available information from low-resolution experimental methods. In this review, we describe integrative modeling approaches, which use complementary data from either cryo-EM or SAXS. Specifically, we focus on the popular molecular dynamics flexible fitting (MDFF) method, which has been widely used for flexible fitting into cryo-EM maps. Second, we describe hybrid molecular dynamics, Rosetta Monte-Carlo and minimum ensemble search (MES) methods that can be used to incorporate SAXS into pseudoatomic structural models. We present concise descriptions of the two methods and their most popular alternatives, along with select illustrative applications to protein/nucleic acid assemblies involved in DNA replication and repair.
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Affiliation(s)
- Xiaojun Xu
- Department of Chemistry, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA 30302, USA
| | - Chunli Yan
- Department of Chemistry, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA 30302, USA
| | - Robert Wohlhueter
- Department of Chemistry, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA 30302, USA
| | - Ivaylo Ivanov
- Department of Chemistry, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA 30302, USA
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50
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Whitford PC. The ribosome's energy landscape: Recent insights from computation. Biophys Rev 2015; 7:301-310. [PMID: 28510226 PMCID: PMC5418421 DOI: 10.1007/s12551-014-0155-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2014] [Accepted: 11/25/2014] [Indexed: 01/25/2023] Open
Abstract
The ever-increasing capacity of computing resources has extended ribosome calculations from the study of small-scale fluctuations to large-scale barrier-crossing processes. As the field of computational/theoretical biophysics shifts focus to large-scale conformational transitions, there is a growing need for a systematic framework to interpret and analyze ribosome dynamics. To this end, energy landscape principles, largely developed for the study of biomolecular folding, have proven to be invaluable. These tools not only provide a foundation for describing simulations but can be used to reconcile experimental results, as well. In this review, I will discuss recent efforts to employ computational methods to reveal the characteristics of the ribosome's landscape and how these studies can help guide a new generation of experiments that more closely probe the underlying energetics. As a result of these investigations, general principles about ribosome function are beginning to emerge, including that: (1) small-scale fluctuations are the result of structure, rather than detailed energetics, (2) molecular flexibility leads to entropically favored rearrangements, and (3) tRNA dynamics may be accurately described as diffusive movement across an energy landscape.
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Affiliation(s)
- Paul Charles Whitford
- Department of Physics, Northeastern University Dana Research Center 123, 360 Huntington Ave, Boston, MA, 02115, USA.
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