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Ikizawa S, Hori T, Wijaya TN, Kono H, Bai Z, Kimizono T, Lu W, Tran DP, Kitao A. PaCS-Toolkit: Optimized Software Utilities for Parallel Cascade Selection Molecular Dynamics (PaCS-MD) Simulations and Subsequent Analyses. J Phys Chem B 2024; 128:3631-3642. [PMID: 38578072 PMCID: PMC11033871 DOI: 10.1021/acs.jpcb.4c01271] [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: 02/27/2024] [Revised: 03/26/2024] [Accepted: 03/26/2024] [Indexed: 04/06/2024]
Abstract
Parallel cascade selection molecular dynamics (PaCS-MD) is an enhanced conformational sampling method conducted as a "repetition of time leaps in parallel worlds", comprising cycles of multiple molecular dynamics (MD) simulations performed in parallel and selection of the initial structures of MDs for the next cycle. We developed PaCS-Toolkit, an optimized software utility enabling the use of different MD software and trajectory analysis tools to facilitate the execution of the PaCS-MD simulation and analyze the obtained trajectories, including the preparation for the subsequent construction of the Markov state model. PaCS-Toolkit is coded with Python, is compatible with various computing environments, and allows for easy customization by editing the configuration file and specifying the MD software and analysis tools to be used. We present the software design of PaCS-Toolkit and demonstrate applications of PaCS-MD variations: original targeted PaCS-MD to peptide folding; rmsdPaCS-MD to protein domain motion; and dissociation PaCS-MD to ligand dissociation from adenosine A2A receptor.
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Affiliation(s)
- Shinji Ikizawa
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Tatsuki Hori
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Tegar Nurwahyu Wijaya
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
- Department
of Chemistry, Universitas Pertamina, Jl. Teuku Nyak Arief, Simprug, Jakarta 12220, Indonesia
| | - Hiroshi Kono
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Zhen Bai
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Tatsuhiro Kimizono
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Wenbo Lu
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Duy Phuoc Tran
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Akio Kitao
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
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Takaba K, Tran DP, Kitao A. Edge expansion parallel cascade selection molecular dynamics simulation for investigating large-amplitude collective motions of proteins. J Chem Phys 2021; 152:225101. [PMID: 32534517 DOI: 10.1063/5.0004654] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
We propose edge expansion parallel cascade selection molecular dynamics (eePaCS-MD) as an efficient adaptive conformational sampling method to investigate the large-amplitude motions of proteins without prior knowledge of the conformational transitions. In this method, multiple independent MD simulations are iteratively conducted from initial structures randomly selected from the vertices of a multi-dimensional principal component subspace. This subspace is defined by an ensemble of protein conformations sampled during previous cycles of eePaCS-MD. The edges and vertices of the conformational subspace are determined by solving the "convex hull problem." The sampling efficiency of eePaCS-MD is achieved by intensively repeating MD simulations from the vertex structures, which increases the probability of rare event occurrence to explore new large-amplitude collective motions. The conformational sampling efficiency of eePaCS-MD was assessed by investigating the open-close transitions of glutamine binding protein, maltose/maltodextrin binding protein, and adenylate kinase and comparing the results to those obtained using related methods. In all cases, the open-close transitions were simulated in ∼10 ns of simulation time or less, offering 1-3 orders of magnitude shorter simulation time compared to conventional MD. Furthermore, we show that the combination of eePaCS-MD and accelerated MD can further enhance conformational sampling efficiency, which reduced the total computational cost of observing the open-close transitions by at most 36%.
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Affiliation(s)
- Kenichiro Takaba
- Pharmaceutical Research Center, Laboratory for Medicinal Chemistry, Asahi Kasei Pharma Corporation, 632-1 Mifuku, Izunokuni, Shizuoka 410-2321, Japan
| | - Duy Phuoc Tran
- School of Life Science and Technology, Tokyo Institute of Technology, M6-13, 2-12-1 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Akio Kitao
- School of Life Science and Technology, Tokyo Institute of Technology, M6-13, 2-12-1 Ookayama, Meguro, Tokyo 152-8550, Japan
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Zhang J, Gong H. Frontier Expansion Sampling: A Method to Accelerate Conformational Search by Identifying Novel Seed Structures for Restart. J Chem Theory Comput 2020; 16:4813-4821. [PMID: 32585102 DOI: 10.1021/acs.jctc.0c00064] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Traditional molecular dynamics (MD) simulations have difficulties in tracking the slow molecular motions, at least partially due to the waste of sampling in already sampled regions. Here, we proposed a new enhanced sampling method, frontier expansion sampling (FEXS), to improve the sampling efficiency of molecular simulations by iteratively selecting seed structures diversely distributed at the "frontier" of an already sampled region to initiate new simulations. Different from other enhanced sampling methods, FEXS identifies the "frontier" seeds by integrating the Gaussian mixture model and the convex hull algorithm, which effectively improves the structural variation among the selected seeds and thus the descendant simulations. Validation in three protein systems, including the folding of chignolin, open-to-closed transition of maltodextrin binding protein, and internal conformational change of bovine pancreatic trypsin inhibitor, confirmed the effectiveness of this novel method in enhancing the sampling of conventional MD simulations to observe the large-scale protein conformational changes. When compared with other enhanced sampling methods like the structural dissimilarity sampling (SDS), FEXS reached at least the same level of sampling efficiency but was capable of providing complementary information in the three tested protein systems.
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Affiliation(s)
- Juanrong Zhang
- MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China.,Beijing Advanced Innovation Center for Structural Biology, Tsinghua University, Beijing 100084, China
| | - Haipeng Gong
- MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China.,Beijing Advanced Innovation Center for Structural Biology, Tsinghua University, Beijing 100084, China
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Harada R, Sladek V, Shigeta Y. Nontargeted Parallel Cascade Selection Molecular Dynamics Using Time-Localized Prediction of Conformational Transitions in Protein Dynamics. J Chem Theory Comput 2019; 15:5144-5153. [DOI: 10.1021/acs.jctc.9b00489] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Vladimir Sladek
- Institute of Chemistry - Centre for Glycomics, Dubravska cesta 9, 84538 Bratislava, Slovakia
- Agency for Medical Research and Development (AMED), Chiyoda-ku, Tokyo 100-0004, Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
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Harada R, Yoshino R, Nishizawa H, Shigeta Y. Temperature–pressure shuffling outlier flooding method enhances the conformational sampling of proteins. J Comput Chem 2019; 40:1530-1537. [DOI: 10.1002/jcc.25806] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 02/07/2019] [Accepted: 02/09/2019] [Indexed: 12/14/2022]
Affiliation(s)
- Ryuhei Harada
- Center for Computational SciencesUniversity of Tsukuba 1‐1‐1 Tennodai, Tsukuba, Ibaraki 305‐8577 Japan
| | - Ryunosuke Yoshino
- Transborder Medical Research CenterUniversity of Tsukuba 1‐1‐1 Tenodai Tsukuba, Ibaraki 305‐8577 Japan
| | - Hiroaki Nishizawa
- Center for Computational SciencesUniversity of Tsukuba 1‐1‐1 Tennodai, Tsukuba, Ibaraki 305‐8577 Japan
| | - Yasuteru Shigeta
- Center for Computational SciencesUniversity of Tsukuba 1‐1‐1 Tennodai, Tsukuba, Ibaraki 305‐8577 Japan
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Harada R, Shigeta Y. Parallel Cascade Selection Molecular Dynamics Simulations for Transition Pathway Sampling of Biomolecules. ADVANCES IN QUANTUM CHEMISTRY 2019. [DOI: 10.1016/bs.aiq.2018.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Harada R. Simple, yet Efficient Conformational Sampling Methods for Reproducing/Predicting Biologically Rare Events of Proteins. BULLETIN OF THE CHEMICAL SOCIETY OF JAPAN 2018. [DOI: 10.1246/bcsj.20180170] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8571, Japan
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Harada R, Mashiko T, Tachikawa M, Hiraoka S, Shigeta Y. Programed dynamical ordering in self-organization processes of a nanocube: a molecular dynamics study. Phys Chem Chem Phys 2018; 20:9115-9122. [DOI: 10.1039/c8cp00284c] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Self-organization processes of a gear-shaped amphiphile molecule (1) to form a hexameric structure (nanocube,16) were inferred from sequential dissociation processes by using molecular dynamics (MD) simulations.
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Affiliation(s)
- Ryuhei Harada
- Center for Computational Sciences
- University of Tsukuba
- Ibaraki 305-8577
- Japan
| | - Takako Mashiko
- Quantum Chemistry Division
- Graduate School of NanobioScience
- Yokohama City University
- Yokoyama City
- Japan
| | - Masanori Tachikawa
- Quantum Chemistry Division
- Graduate School of NanobioScience
- Yokohama City University
- Yokoyama City
- Japan
| | - Shuichi Hiraoka
- Department of Basic Science
- Graduate School of Arts and Sciences
- The University of Tokyo
- Tokyo 153-8902
- Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences
- University of Tsukuba
- Ibaraki 305-8577
- Japan
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Harada R, Shigeta Y. Self-Avoiding Conformational Sampling Based on Histories of Past Conformational Searches. J Chem Inf Model 2017; 57:3070-3078. [PMID: 29111731 DOI: 10.1021/acs.jcim.7b00573] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Self-avoiding conformational sampling (SACS) is proposed as an enhanced conformational sampling method for proteins. In SACS, the following conformational resampling is repeated for a given protein: (1) identification of newly visited states in a subspace and (2) conformational resampling by restarting short-time molecular dynamics (MD) simulations from the newly visited states. To identify the newly visited states, a set of history-dependent histograms projected onto the subspace is used. One is constructed from the trajectories sampled at the current (ith) cycle, and the other is constructed from all of the trajectories accumulated up through the previous ((i - 1)th) cycle. By reference to the history-dependent histograms, the newly visited states appearing at the current (ith) cycle are defined as a difference set between them. By repeating the cycle of conformational resampling, SACS prevents the system from revisiting states that have already been visited for previous cycles, promoting structural transitions via resampling from the newly visited states. To verify the conformational sampling efficiency of SACS, the present method was applied to reveal underlying mechanisms of biologically important domain motions of maltodextrin binding protein in explicit water and successfully reproduced the open-closed transition with a reasonable (nanosecond-order) computational cost.
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Affiliation(s)
- Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba , 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba , 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
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