1
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Toopradab B, Xie W, Duan L, Hengphasatporn K, Harada R, Sinsulpsiri S, Shigeta Y, Shi L, Maitarad P, Rungrotmongkol T. Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors. Bioorg Med Chem Lett 2024; 110:129852. [PMID: 38925524 DOI: 10.1016/j.bmcl.2024.129852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 05/17/2024] [Accepted: 06/19/2024] [Indexed: 06/28/2024]
Abstract
The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (Mpro). The ligand-binding pathway sampling method based on parallel cascade selection molecular dynamics (LB-PaCS-MD) simulations was employed to elucidate plausible paths and conformations of ebselen, a synthetic organoselenium drug, within the Mpro catalytic site. Ebselen effectively engaged the active site, adopting proximity to H41 and interacting through the benzoisoselenazole ring in a π-π T-shaped arrangement, with an additional π-sulfur interaction with C145. In addition, the ligand-based drug design using the QSAR with GFA-MLR, RF, and ANN models were employed for biological activity prediction. The QSAR-ANN model showed robust statistical performance, with an r2training exceeding 0.98 and an RMSEtest of 0.21, indicating its suitability for predicting biological activities. Integration the ANN model with the LB-PaCS-MD insights enabled the rational design of novel compounds anchored in the ebselen core structure, identifying promising candidates with favorable predicted IC50 values. The designed compounds exhibited suitable drug-like characteristics and adopted an active conformation similar to ebselen, inhibiting Mpro function. These findings represent a synergistic approach merging ligand and structure-based drug design; with the potential to guide experimental synthesis and enzyme assay testing.
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Affiliation(s)
- Borwornlak Toopradab
- Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok 10330, Thailand; Center of Excellence in Biocatalyst and Sustainable Biotechnology, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Wanting Xie
- Research Center of Nano Science and Technology, Department of Chemistry, College of Science, Shanghai University, Shanghai, 200444 PR China
| | - Lian Duan
- Center for Computational Sciences (CCS), University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan; Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Ibaraki 305-8571, Japan
| | - Kowit Hengphasatporn
- Center for Computational Sciences (CCS), University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Ryuhei Harada
- Center for Computational Sciences (CCS), University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Silpsiri Sinsulpsiri
- Center of Excellence in Biocatalyst and Sustainable Biotechnology, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Yasuteru Shigeta
- Center for Computational Sciences (CCS), University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Liyi Shi
- Research Center of Nano Science and Technology, Department of Chemistry, College of Science, Shanghai University, Shanghai, 200444 PR China; Emerging Industries Institute Shanghai University, Jiaxing, Zhejiang 314006, PR China
| | - Phornphimon Maitarad
- Research Center of Nano Science and Technology, Department of Chemistry, College of Science, Shanghai University, Shanghai, 200444 PR China.
| | - Thanyada Rungrotmongkol
- Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok 10330, Thailand; Center of Excellence in Biocatalyst and Sustainable Biotechnology, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
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2
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Harada R, Morita R, Shigeta Y. Free-Energy Profiles for Membrane Permeation of Compounds Calculated Using Rare-Event Sampling Methods. J Chem Inf Model 2023; 63:259-269. [PMID: 36574612 DOI: 10.1021/acs.jcim.2c01097] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The free-energy profile of a compound is an essential measurement in evaluating the membrane permeation process by means of theoretical methods. Computationally, molecular dynamics (MD) simulation allows the free-energy profile calculation. However, MD simulations frequently fail to sample membrane permeation because they are rare events induced in longer timescales than the accessible timescale of MD, leading to an insufficient conformational search to calculate an incorrect free-energy profile. To achieve a sufficient conformational search, several enhanced sampling methods have been developed and elucidated the membrane permeation process. In addition to these enhanced sampling methods, we proposed a simple yet powerful free-energy calculation of a compound for the membrane permeation process based on originally rare-event sampling methods developed by us. Our methods have a weak dependency on external biases and their optimizations to promote the membrane permeation process. Based on distributed computing, our methods only require the selection of initial structures and their conformational resampling, whereas the enhanced sampling methods may be required to adjust external biases. Furthermore, our methods efficiently search membrane permeation processes with simple scripts without modifying any MD program. As demonstrations, we calculated the free-energy profiles of seven linear compounds for their membrane permeation based on a hybrid conformational search using two rare-event sampling methods, that is, (1) parallel cascade selection MD (PaCS-MD) and (2) outlier flooding method (OFLOOD), combined with a Markov state model (MSM) construction. In the first step, PaCS-MD generated initial membrane permeation paths of a compound. In the second step, OFLOOD expanded the unsearched conformational area around the initial paths, allowing for a broad conformational search. Finally, the trajectories were employed to construct reliable MSMs, enabling correct free-energy profile calculations. Furthermore, we estimated the membrane permeability coefficients of all compounds by constructing the reliable MSMs for their membrane permeation. In conclusion, the calculated coefficients were qualitatively correlated with the experimental measurements (correlation coefficient (R2) = 0.8689), indicating that the hybrid conformational search successfully calculated the free-energy profiles and membrane permeability coefficients of the seven compounds.
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Affiliation(s)
- Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki305-8577, Japan
| | - Rikuri Morita
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki305-8577, Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki305-8577, Japan
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3
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Kurisaki I, Suzuki M. Simulation toolkits at the molecular scale for trans-scale thermal signaling. Comput Struct Biotechnol J 2023; 21:2547-2557. [PMID: 37102156 PMCID: PMC10123322 DOI: 10.1016/j.csbj.2023.03.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 03/22/2023] [Accepted: 03/23/2023] [Indexed: 04/28/2023] Open
Abstract
Thermogenesis is a physiological activity of releasing heat that originates from intracellular biochemical reactions. Recent experimental studies discovered that externally applied heat changes intracellular signaling locally, resulting in global changes in cell morphology and signaling. Therefore, we hypothesize an inevitable contribution of thermogenesis in modulating biological system functions throughout the spatial scales from molecules to individual organisms. One key issue examining the hypothesis, namely, the "trans-scale thermal signaling," resides at the molecular scale on the amount of heat released via individual reactions and by which mechanism the heat is employed for cellular function operations. This review introduces atomistic simulation tool kits for studying the mechanisms of thermal signaling processes at the molecular scale that even state-of-the-art experimental methodologies of today are hardly accessible. We consider biological processes and biomolecules as potential heat sources in cells, such as ATP/GTP hydrolysis and multiple biopolymer complex formation and disassembly. Microscopic heat release could be related to mesoscopic processes via thermal conductivity and thermal conductance. Additionally, theoretical simulations to estimate these thermal properties in biological membranes and proteins are introduced. Finally, we envisage the future direction of this research field.
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Affiliation(s)
- Ikuo Kurisaki
- Waseda Research Institute for Science and Engineering, Waseda University, Bldg. No.55, S Tower, 4th Floor, 3–4-1 Okubo Shinjuku-ku, Tokyo 169–8555, Japan
- Corresponding authors.
| | - Madoka Suzuki
- Institute for Protein Research, Osaka University, 3–2 Yamadaoka, Suita, Osaka 565–0871, Japan
- Corresponding authors.
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4
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Aida H, Shigeta Y, Harada R. Ligand Binding Path Sampling Based on Parallel Cascade Selection Molecular Dynamics: LB-PaCS-MD. MATERIALS 2022; 15:ma15041490. [PMID: 35208030 PMCID: PMC8878848 DOI: 10.3390/ma15041490] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/08/2022] [Accepted: 02/10/2022] [Indexed: 01/09/2023]
Abstract
Parallel cascade selection molecular dynamics (PaCS-MD) is a rare-event sampling method that generates transition pathways between a reactant and product. To sample the transition pathways, PaCS-MD repeats short-time MD simulations from important configurations as conformational resampling cycles. In this study, PaCS-MD was extended to sample ligand binding pathways toward a target protein, which is referred to as LB-PaCS-MD. In a ligand-concentrated environment, where multiple ligand copies are randomly arranged around the target protein, LB-PaCS-MD allows for the frequent sampling of ligand binding pathways. To select the important configurations, we specified the center of mass (COM) distance between each ligand and the relevant binding site of the target protein, where snapshots generated by the short-time MD simulations were ranked by their COM distance values. From each cycle, snapshots with smaller COM distance values were selected as the important configurations to be resampled using the short-time MD simulations. By repeating conformational resampling cycles, the COM distance values gradually decreased and converged to constants, meaning that a set of ligand binding pathways toward the target protein was sampled by LB-PaCS-MD. To demonstrate relative efficiency, LB-PaCS-MD was applied to several proteins, and their ligand binding pathways were sampled more frequently than conventional MD simulations.
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Affiliation(s)
- Hayato Aida
- Graduate School of Science and Technology, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8577, Japan;
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8577, Japan;
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8577, Japan;
- Correspondence:
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5
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Yasuda T, Morita R, Shigeta Y, Harada R. Independent Nontargeted Parallel Cascade Selection Molecular Dynamics (Ino-PaCS-MD) to Enhance the Conformational Sampling of Proteins. J Chem Theory Comput 2021; 17:5933-5943. [PMID: 34410106 DOI: 10.1021/acs.jctc.1c00558] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Biological functions are related to long-time protein dynamics (rare events) that are induced over microseconds. Such protein dynamics can be investigated using molecular dynamics (MD) simulations. However, the detection of rare events remains challenging using conventional MD (cMD) since the accessible timescales of cMD are shorter than those of the biological functions. Recently, the parallel cascade selection MD (PaCS-MD) has been proposed to detect such rare events, wherein transition paths are generated between a given reactant and product. As an extension, the nontargeted PaCS-MD (nt-PaCS-MD) has been proposed to predict the transition paths without requiring reference to any product. Thus, as a further extension, we herein propose independent nt-PaCS-MD, namely, Ino-PaCS-MD, wherein multiple walkers are launched from a set of different starting configurations. Each walker repeats a cycle of restarting short-time MD simulations from configurations with high potentials for making transitions to neighboring metastable states. To further enhance the sampling ability, Ino-PaCS-MD temporarily stops the conformational search and periodically resets the starting configurations so that they are uniformly distributed in a conformational subspace, thereby preventing a given protein from being trapped in one of the metastable states. As a demonstration, Ino-PaCS-MD successfully detects rare events of a maltose-binding protein as open-close transitions with a nanosecond-order simulation time, although a microsecond-order cMD simulation failed to detect these rare events, showing the high sampling efficiency of Ino-PaCS-MD.
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Affiliation(s)
- Takunori Yasuda
- College of Biological Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-0821, Japan
| | - Rikuri Morita
- 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
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
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6
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Wu Y, Qian R, Yang Y, Sheng Y, Li W, Wang W. Activation Pathways and Free Energy Landscapes of the SARS-CoV-2 Spike Protein. ACS OMEGA 2021; 6:23432-23441. [PMID: 34514271 PMCID: PMC8424691 DOI: 10.1021/acsomega.1c03384] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 08/24/2021] [Indexed: 05/09/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses a spike protein (S-protein) to recognize the receptor protein ACE2 of human cells and initiate infection, during which the conformational transition of the S-protein from inactive (down) state to active (up) state is one of the key molecular events determining the infectivity but the underlying mechanism remains poorly understood. In this work, we investigated the activation pathways and free energy landscape of the S-protein of SARS-CoV-2 and compared with those of the closely related counterpart SARS-CoV using molecular dynamics simulations. Our results revealed a large difference between the activation pathways of the two S-proteins. The transition from inactive to an active state for the S-protein of SARS-CoV-2 is more cooperative, involving simultaneous disruptions of several key interfacial hydrogen bonds, and the transition encounters a much higher free energy barrier. In addition, the conformational equilibrium of the SARS-CoV-2 S-protein is more biased to the inactive state compared to that of the SARS-CoV S-protein, suggesting the transient feature of the active state before binding to the receptor protein of the host cell. The key interactions contributing to the difference of the activation pathways and free energy landscapes were discussed. The results provide insights into the molecular mechanism involved in the initial stage of the SARS-CoV-2 infection.
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Affiliation(s)
- Yichao Wu
- Department of Physics, National
Laboratory of Solid State Microstructure, Nanjing University, Nanjing 210093, China
| | - Ruixin Qian
- Department of Physics, National
Laboratory of Solid State Microstructure, Nanjing University, Nanjing 210093, China
| | - Yan Yang
- Department of Physics, National
Laboratory of Solid State Microstructure, Nanjing University, Nanjing 210093, China
| | - Yuebiao Sheng
- Department of Physics, National
Laboratory of Solid State Microstructure, Nanjing University, Nanjing 210093, China
| | - Wenfei Li
- Department of Physics, National
Laboratory of Solid State Microstructure, Nanjing University, Nanjing 210093, China
| | - Wei Wang
- Department of Physics, National
Laboratory of Solid State Microstructure, Nanjing University, Nanjing 210093, China
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7
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Molani Gol R, Kheirouri S. The Effects of Quercetin on the Apoptosis of Human Breast Cancer Cell Lines MCF-7 and MDA-MB-231: A Systematic Review. Nutr Cancer 2021; 74:405-422. [PMID: 33682528 DOI: 10.1080/01635581.2021.1897631] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
This systematic review was performed with a focus on the effects of quercetin (QT) on the human breast cancer cell lines MCF-7 and MDA-MB-231. PubMed, Scopus, Science Direct, and Google Scholar databases were searched up to May 2020 using relevant keywords. All articles written in English evaluating the effects of QT on the human breast cancer cell lines MCF-7 and/or MDA-MB-231 were eligible for the review. Totally, 31 articles were included in this review. Out of them, 23 studies investigated the effects of QT on MCF-7 cells and indicated that QT induces apoptosis in the cells. Of 15 studies that examined the effects of QT on MDA-MB-231 cells, 14 reports showed successful apoptosis. It is concluded that QT might be beneficial in the eliminating of breast cancer cells. However, further clinical trials are warranted to further verify these outcomes.
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Affiliation(s)
- Roghayeh Molani Gol
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.,Department of Nutrition, Faculty of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Sorayya Kheirouri
- Department of Nutrition, Faculty of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
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8
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Morita R, Shigeta Y, Harada R. Rearrangements of Water Molecules in Parallel Cascade Selection Molecular Dynamics Enhance Structural Explorations of Proteins. BULLETIN OF THE CHEMICAL SOCIETY OF JAPAN 2021. [DOI: 10.1246/bcsj.20200174] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Rikuri Morita
- 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
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
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9
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Yasuda T, Shigeta Y, Harada R. The Folding of Trp-cage is Regulated by Stochastic Flip of the Side Chain of Tryptophan. CHEM LETT 2021. [DOI: 10.1246/cl.200699] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Takunori Yasuda
- College of Biological Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0821, Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0821, Japan
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0821, Japan
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10
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Harada R, Yamaguchi K, Shigeta Y. Enhanced Conformational Sampling Method Based on Anomaly Detection Parallel Cascade Selection Molecular Dynamics: ad-PaCS-MD. J Chem Theory Comput 2020; 16:6716-6725. [PMID: 32926622 DOI: 10.1021/acs.jctc.0c00697] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
In the present study, we propose a rare-event sampling method called anomaly detection parallel cascade selection molecular dynamics (ad-PaCS-MD). The original PaCS-MD was designed to generate conformational transition pathways from a given reactant to a product when the latter is known a priori. As an extension of the original method, ad-PaCS-MD has been designed to efficiently search transition pathways from a given reactant without referring to a given product. In ad-PaCS-MD, rarely occurring but essential states (configurations) of proteins for the transitions are identified based on the degrees of an anomaly. In more detail, ad-PaCS-MD adopts an algorithm called an anomaly detection generative adversarial network (anoGAN) as a measure for detecting rarely occurring states to be resampled. Here, the essential configurations with higher degrees of the anomaly are selected with anoGAN and intensively resampled by restarting short-time MD simulations from the selected configurations. By repeating the detections and resampling of configurations with the higher degrees of the anomaly, ad-PaCS-MD automatically and efficiently promotes the rare events and gives a wide range of the free energy landscape by combining with the Markov state model construction. As demonstrations, open-closed transitions of two globular proteins (T4 lysozyme and maltose-binding protein) were promoted with ad-PaCS-MD by referring only to the given starting configurations. In each demonstration, ad-PaCS-MD promoted the large-amplitude open-closed transitions with nanosecond-order simulation times. In conclusion, our demonstrations showed a higher conformational sampling efficiency for ad-PaCS-MD than conventional MD (CMD) because CMD required computational costs of more than microsecond-order simulation times to promote the rare events.
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Affiliation(s)
- Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Kota Yamaguchi
- 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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11
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Aida H, Shigeta Y, Harada R. Regenerations of Initial Velocities in Parallel Cascade Selection Molecular Dynamics (PaCS-MD) Enhance the Conformational Transitions of Proteins. CHEM LETT 2020. [DOI: 10.1246/cl.200196] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Hayato Aida
- Master's Program in Biology , University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0821, Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0821, Japan
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0821, Japan
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12
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Yasuda T, Shigeta Y, Harada R. The Dynamics of S-adenosyl-methionine and S-adenosyl-homocysteine in Mouse Dnmt1 is Driven by Their Structural Flexibilities. CHEM LETT 2020. [DOI: 10.1246/cl.200223] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Takunori Yasuda
- College of Biological Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0821, Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0821, Japan
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0821, Japan
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13
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Ono J, Nakai H. Weighted histogram analysis method for multiple short-time metadynamics simulations. Chem Phys Lett 2020. [DOI: 10.1016/j.cplett.2020.137384] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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14
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Liang X, Li L, Tang J, Komiyama M, Ariga K. Dynamism of Supramolecular DNA/RNA Nanoarchitectonics: From Interlocked Structures to Molecular Machines. BULLETIN OF THE CHEMICAL SOCIETY OF JAPAN 2020. [DOI: 10.1246/bcsj.20200012] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Xingguo Liang
- College of Food Science and Engineering, Ocean University of China, Qingdao 266003, P. R. China
- Laboratory for Marine Drugs and Bioproducts of Qingdao National Laboratory for Marine Science and Technology, Qingdao 266235, P. R. China
| | - Lin Li
- College of Food Science and Engineering, Ocean University of China, Qingdao 266003, P. R. China
| | - Jiaxuan Tang
- College of Food Science and Engineering, Ocean University of China, Qingdao 266003, P. R. China
| | - Makoto Komiyama
- College of Food Science and Engineering, Ocean University of China, Qingdao 266003, P. R. China
| | - Katsuhiko Ariga
- WPI-MANA, National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- Department of Advanced Materials Science, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
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15
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Harada R, Sladek V, Shigeta Y. Nontargeted Parallel Cascade Selection Molecular Dynamics Based on a Nonredundant Selection Rule for Initial Structures Enhances Conformational Sampling of Proteins. J Chem Inf Model 2019; 59:5198-5206. [PMID: 31697897 DOI: 10.1021/acs.jcim.9b00753] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Nontargeted parallel cascade selection molecular dynamics (nt-PaCS-MD) is a method for enhanced conformational sampling of proteins. To search a broad conformational subspace, nt-PaCS-MD repeats cycles of conformational resampling from relevant initial structures. Generally, the conformational sampling efficiency of nt-PaCS-MD depends on a selection rule for the initial structures. In the original nt-PaCS-MD, the initial structures were selected by referring to structural distributions of protein configurations generated by conformational resampling (multiple short-time MD simulations). However, their structural redundancy among the initial structures was neglected for the cycles of conformational resampling, indicating that similar protein configurations might be frequently specified and resampled in every cycle in the original nt-PaCS-MD. To reduce the possibility of resampling from redundant initial structures, we propose an alternative selection rule that accounts for structural similarity among the initial structures. Specifically, a pairwise root-mean-square deviation (RMSD) is defined for all of the initial structures selected for all of the past cycles. Then a set of protein configurations with a larger pairwise RMSD is sequentially specified and resampled in the next cycle, which is regarded to as a history-dependent selection of initial structures by considering a profile of the past specified initial structures. The present scheme, termed extended nt-PaCS-MD, prevents us from resampling a set of redundant protein configurations. To check the conformational sampling efficiency of the extended nt-PaCS-MD, we used a middle-sized protein, T4 lysozyme, in explicit water. Through the assessment, this extended nt-PaCS-MD identified the open-closed transitions of T4 lysozyme more efficiently than the original nt-PaCS-MD.
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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) , 1-7-1 Otemachi , 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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16
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Harada R, Shigeta Y. Selection Rules for Outliers in Outlier Flooding Method Regulate Its Conformational Sampling Efficiency. J Chem Inf Model 2019; 59:3919-3926. [PMID: 31424213 DOI: 10.1021/acs.jcim.9b00546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The outlier flooding method (OFLOOD) has been proposed as an enhanced conformational sampling method of proteins. In OFLOOD, rarely occurring states of proteins are detected as sparse conformational distributions (outliers) with a clustering algorithm. The detected outliers are intensively resampled with short-time molecular dynamics (MD) simulations. As a set of cycles, OFLOOD repeats selections of outliers and their conformational resampling. Herein, as an essential issue to be tackled to perform OFLOOD efficiently, a selection rule for outliers should be carefully specified. Generally, many outliers are detected from distributions on conformational subspaces with the clustering. Judging from its computational costs, it is unreasonable to select all the detected outliers upon the conformational resampling. Therefore, it is important to consider which outliers should be selected from the sparse distributions when restarting their short-time MD simulations with limited computational costs. In this sense, we investigated the conformational sampling efficiency of OFLOOD by changing the selection rules for outliers. To address the conformational sampling efficiency of OFLOOD depending on its selection rules, outliers to be resampled were selected by focusing their probability occurrences (populations of outliers). As a comparison, a random selection rule for outliers was also considered. Through the present assessment, the random selection of outliers showed the most efficient conformational sampling efficiency compared to the other OFLOOD trials using the biased selection rules, indicating that a variety of outliers should be selected and resampled during the OFLOOD cycles. In conclusion, the random outlier selection rule is the best strategy to perform OFLOOD efficiently.
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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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Maji S, Shrestha LK, Ariga K. Nanoarchitectonics for Nanocarbon Assembly and Composite. J Inorg Organomet Polym Mater 2019. [DOI: 10.1007/s10904-019-01294-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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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, SLADEK V, SHIGETA Y. Developments of Rare Event Sampling Methods for Proteins. JOURNAL OF COMPUTER CHEMISTRY-JAPAN 2019. [DOI: 10.2477/jccj.2019-0036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Ryuhei HARADA
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8577 Japan
| | - Vladimir SLADEK
- 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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