1
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Jung J, Yagi K, Tan C, Oshima H, Mori T, Yu I, Matsunaga Y, Kobayashi C, Ito S, Ugarte La Torre D, Sugita Y. GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models. J Phys Chem B 2024. [PMID: 38876465 DOI: 10.1021/acs.jpcb.4c02096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2024]
Abstract
GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.
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Affiliation(s)
- Jaewoon Jung
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Kiyoshi Yagi
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Cheng Tan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Hiraku Oshima
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
- Graduate School of Life Science, University of Hyogo, Harima Science Park City, Hyogo 678-1297, Japan
| | - Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department of Chemistry, Tokyo University of Science, Shinjuku-ku, Tokyo 162-8601, Japan
| | - Isseki Yu
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department of Bioinformatics, Maebashi Institute of Technology, Maebashi, Gunma 371-0816, Japan
| | - Yasuhiro Matsunaga
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan
| | - Chigusa Kobayashi
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Shingo Ito
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Diego Ugarte La Torre
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
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2
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Ishida H, Matsumoto A, Tanaka H, Okuda A, Morishima K, Wade PA, Kurumizaka H, Sugiyama M, Kono H. Structural and Dynamic Changes of Nucleosome upon GATA3 Binding. J Mol Biol 2023; 435:168308. [PMID: 37805066 PMCID: PMC10843466 DOI: 10.1016/j.jmb.2023.168308] [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: 08/03/2023] [Revised: 09/30/2023] [Accepted: 10/03/2023] [Indexed: 10/09/2023]
Abstract
Pioneer factors, which can directly bind to nucleosomes, have been considered to change chromatin conformations. However, the binding impact on the nucleosome is little known. Here, we show how the pioneer factor GATA3 binds to nucleosomal DNA and affects the conformation and dynamics of nucleosomes by using a combination of SAXS, molecular modeling, and molecular dynamics simulations. Our structural models, consistent with the SAXS data, indicate that only one of the two DNA binding domains, N- and C-fingers, of GATA3 binds to an end of the DNA in solution. Our MD simulations further showed that the other unbound end of the DNA increases the fluctuation and enhances the DNA dissociation from the histone core when the N-finger binds to a DNA end, a site near the entry or exit of the nucleosome. However, this was not true for the binding of the C-finger that binds to a location about 15 base pairs distant from the DNA end. In this case, DNA dissociation occurred on the bound end. Taken together, we suggest that the N-finger and C-finger bindings of GATA3 commonly enhance DNA dissociation at one of the two DNA ends (the bound end for the C-finger binding and the unbound end for the N-finger binding), leading to triggering a conformational change in the chromatin.
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Affiliation(s)
- Hisashi Ishida
- Institute for Quantum Life Science, Institutes for Quantum Science and Technology, 4-9-1 Anagawa, Inage-ku, Chiba city, Chiba 263-8555, Japan
| | - Atsushi Matsumoto
- Institute for Quantum Life Science, Institutes for Quantum Science and Technology, 4-9-1 Anagawa, Inage-ku, Chiba city, Chiba 263-8555, Japan
| | - Hiroki Tanaka
- Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan; Present address: Department of Structural Virology, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan
| | - Aya Okuda
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Ken Morishima
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Paul A Wade
- Epigenetics and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC 27709, USA
| | - Hitoshi Kurumizaka
- Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
| | - Masaaki Sugiyama
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Hidetoshi Kono
- Institute for Quantum Life Science, Institutes for Quantum Science and Technology, 4-9-1 Anagawa, Inage-ku, Chiba city, Chiba 263-8555, Japan; Graduate School of Science, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan.
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3
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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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4
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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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5
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Alshammari M, He J. Combining Cryo-EM Density Map and Residue Contact for Protein Secondary Structure Topologies. Molecules 2021; 26:7049. [PMID: 34834140 PMCID: PMC8624718 DOI: 10.3390/molecules26227049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 11/01/2021] [Accepted: 11/15/2021] [Indexed: 11/23/2022] Open
Abstract
Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. A topology of secondary structures defines the mapping between a set of sequence segments and a set of traces of secondary structures in three-dimensional space. In order to enhance accuracy in ranking secondary structure topologies, we explored a method that combines three sources of information: a set of sequence segments in 1D, a set of amino acid contact pairs in 2D, and a set of traces in 3D at the secondary structure level. A test of fourteen cases shows that the accuracy of predicted secondary structures is critical for deriving topologies. The use of significant long-range contact pairs is most effective at enriching the rank of the maximum-match topology for proteins with a large number of secondary structures, if the secondary structure prediction is fairly accurate. It was observed that the enrichment depends on the quality of initial topology candidates in this approach. We provide detailed analysis in various cases to show the potential and challenge when combining three sources of information.
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Affiliation(s)
| | - Jing He
- Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA;
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6
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Yagi K, Re S, Mori T, Sugita Y. Weight average approaches for predicting dynamical properties of biomolecules. Curr Opin Struct Biol 2021; 72:88-94. [PMID: 34592697 DOI: 10.1016/j.sbi.2021.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 08/21/2021] [Accepted: 08/24/2021] [Indexed: 11/16/2022]
Abstract
Recent advances in atomistic molecular dynamics (MD) simulations of biomolecules allow us to explore their conformational spaces widely, observing large-scale conformational fluctuations or transitions between distinct structures. To reproduce or refine experimental data using MD simulations, structure ensembles, which are characterized by multiple structures and their statistical weights on the rugged free-energy landscapes, are often used. Here, we summarize weight average approaches for various experimental measurements. Weight average approaches are now applied to hybrid quantum mechanics/molecular mechanics MD simulations to predict fast vibrational motions in a protein with a high accuracy for better understanding of molecular functions from atomic structures.
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Affiliation(s)
- Kiyoshi Yagi
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Suyong Re
- RIKEN Center for Biosystems Dynamics Research, 1-6-5 Minatojima-Minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health, and Nutrition 7-6-8, Saito-Asagi, Ibaraki, Osaka, 567-0085, Japan
| | - Takaharu Mori
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Yuji Sugita
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan; RIKEN Center for Biosystems Dynamics Research, 1-6-5 Minatojima-Minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
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7
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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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8
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Wang X, Alnabati E, Aderinwale TW, Maddhuri Venkata Subramaniya SR, Terashi G, Kihara D. Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning. Nat Commun 2021; 12:2302. [PMID: 33863902 PMCID: PMC8052361 DOI: 10.1038/s41467-021-22577-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 03/19/2021] [Indexed: 12/21/2022] Open
Abstract
An increasing number of density maps of macromolecular structures, including proteins and DNA/RNA complexes, have been determined by cryo-electron microscopy (cryo-EM). Although lately maps at a near-atomic resolution are routinely reported, there are still substantial fractions of maps determined at intermediate or low resolutions, where extracting structure information is not trivial. Here, we report a new computational method, Emap2sec+, which identifies DNA or RNA as well as the secondary structures of proteins in cryo-EM maps of 5 to 10 Å resolution. Emap2sec+ employs the deep Residual convolutional neural network. Emap2sec+ assigns structural labels with associated probabilities at each voxel in a cryo-EM map, which will help structure modeling in an EM map. Emap2sec+ showed stable and high assignment accuracy for nucleotides in low resolution maps and improved performance for protein secondary structure assignments than its earlier version when tested on simulated and experimental maps.
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Affiliation(s)
- Xiao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Eman Alnabati
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Tunde W Aderinwale
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | | | - Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, IN, USA.
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.
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9
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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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10
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Kim DN, Gront D, Sanbonmatsu KY. Practical Considerations for Atomistic Structure Modeling with Cryo-EM Maps. J Chem Inf Model 2020; 60:2436-2442. [PMID: 32422044 PMCID: PMC7891309 DOI: 10.1021/acs.jcim.0c00090] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
We describe common approaches to atomistic structure modeling with single particle analysis derived cryo-EM maps. Several strategies for atomistic model building and atomistic model fitting methods are discussed, including selection criteria and implementation procedures. In covering basic concepts and caveats, this short perspective aims to help facilitate active discussion between scientists at different levels with diverse backgrounds.
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Affiliation(s)
- Doo Nam Kim
- Computational Biology Team, Biological Science Division, Pacific Northwest National Laboratory, Richland, Washington, 99354, United States
| | - Dominik Gront
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Karissa Y. Sanbonmatsu
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, New Mexico, 87545, United States
- New Mexico Consortium, Los Alamos, New Mexico, 87544, United States
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11
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Mori T, Sekine SI. Overview of the "1SBA: integrative approaches towards understanding of gene expression" session at the 57th BSJ meeting. Biophys Rev 2020; 12:253-254. [PMID: 32056111 DOI: 10.1007/s12551-020-00644-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 02/09/2020] [Indexed: 12/28/2022] Open
Affiliation(s)
- Takaharu Mori
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan.
| | - Shun-Ichi Sekine
- RIKEN Center for Biosystems Dynamics Research, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045, Japan
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12
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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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13
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Mori T, Sugita Y. Implicit Micelle Model for Membrane Proteins Using Superellipsoid Approximation. J Chem Theory Comput 2019; 16:711-724. [DOI: 10.1021/acs.jctc.9b00783] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, 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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14
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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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