Literature DB >> 23883057

Parallel Cascade Selection Molecular Dynamics (PaCS-MD) to generate conformational transition pathway.

Ryuhei Harada1, Akio Kitao.   

Abstract

Parallel Cascade Selection Molecular Dynamics (PaCS-MD) is proposed as a molecular simulation method to generate conformational transition pathway under the condition that a set of "reactant" and "product" structures is known a priori. In PaCS-MD, the cycle of short multiple independent molecular dynamics simulations and selection of the structures close to the product structure for the next cycle are repeated until the simulated structures move sufficiently close to the product. Folding of 10-residue mini-protein chignolin from the extended to native structures and open-close conformational transition of T4 lysozyme were investigated by PaCS-MD. In both cases, tens of cycles of 100-ps MD were sufficient to reach the product structures, indicating the efficient generation of conformational transition pathway in PaCS-MD with a series of conventional MD without additional external biases. Using the snapshots along the pathway as the initial coordinates, free energy landscapes were calculated by the combination with multiple independent umbrella samplings to statistically elucidate the conformational transition pathways.

Mesh:

Substances:

Year:  2013        PMID: 23883057     DOI: 10.1063/1.4813023

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  14 in total

1.  Traversing the folding pathway of proteins using temperature-aided cascade molecular dynamics with conformation-dependent charges.

Authors:  Vinod Jani; Uddhavesh Sonavane; Rajendra Joshi
Journal:  Eur Biophys J       Date:  2016-02-13       Impact factor: 1.733

2.  Recent Force Field Strategies for Intrinsically Disordered Proteins.

Authors:  Junxi Mu; Hao Liu; Jian Zhang; Ray Luo; Hai-Feng Chen
Journal:  J Chem Inf Model       Date:  2021-02-16       Impact factor: 4.956

3.  Inositol Hexakisphosphate (IP6) Accelerates Immature HIV-1 Gag Protein Assembly toward Kinetically Trapped Morphologies.

Authors:  Alexander J Pak; Manish Gupta; Mark Yeager; Gregory A Voth
Journal:  J Am Chem Soc       Date:  2022-06-06       Impact factor: 16.383

Review 4.  Understanding ligand-receptor non-covalent binding kinetics using molecular modeling.

Authors:  Zhiye Tang; Christopher C Roberts; Chia-En A Chang
Journal:  Front Biosci (Landmark Ed)       Date:  2017-01-01

5.  Theoretical analyses on a flipping mechanism of UV-induced DNA damage.

Authors:  Ryuma Sato; Ryuhei Harada; Yasuteru Shigeta
Journal:  Biophys Physicobiol       Date:  2016-12-13

6.  Exploring Configuration Space and Path Space of Biomolecules Using Enhanced Sampling Techniques-Searching for Mechanism and Kinetics of Biomolecular Functions.

Authors:  Hiroshi Fujisaki; Kei Moritsugu; Yasuhiro Matsunaga
Journal:  Int J Mol Sci       Date:  2018-10-15       Impact factor: 5.923

7.  Integrating an Enhanced Sampling Method and Small-Angle X-Ray Scattering to Study Intrinsically Disordered Proteins.

Authors:  Chengtao Ding; Sheng Wang; Zhiyong Zhang
Journal:  Front Mol Biosci       Date:  2021-04-15

8.  Reduced efficacy of a Src kinase inhibitor in crowded protein solution.

Authors:  Kento Kasahara; Suyong Re; Grzegorz Nawrocki; Hiraku Oshima; Chiemi Mishima-Tsumagari; Yukako Miyata-Yabuki; Mutsuko Kukimoto-Niino; Isseki Yu; Mikako Shirouzu; Michael Feig; Yuji Sugita
Journal:  Nat Commun       Date:  2021-07-02       Impact factor: 14.919

9.  Unraveling low-resolution structural data of large biomolecules by constructing atomic models with experiment-targeted parallel cascade selection simulations.

Authors:  Junhui Peng; Zhiyong Zhang
Journal:  Sci Rep       Date:  2016-07-05       Impact factor: 4.379

10.  Enhancing Biomolecular Sampling with Reinforcement Learning: A Tree Search Molecular Dynamics Simulation Method.

Authors:  Kento Shin; Duy Phuoc Tran; Kazuhiro Takemura; Akio Kitao; Kei Terayama; Koji Tsuda
Journal:  ACS Omega       Date:  2019-08-19
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.