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PaCS-Toolkit:用于并行级联选择分子动力学 (PaCS-MD) 模拟和后续分析的优化软件实用程序。

PaCS-Toolkit: Optimized Software Utilities for Parallel Cascade Selection Molecular Dynamics (PaCS-MD) Simulations and Subsequent Analyses.

机构信息

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.

出版信息

J Phys Chem B. 2024 Apr 18;128(15):3631-3642. doi: 10.1021/acs.jpcb.4c01271. Epub 2024 Apr 5.

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 A receptor.

摘要

并行级联选择分子动力学 (PaCS-MD) 是一种增强构象采样方法,作为“在平行世界中重复时间飞跃”进行,包括在并行环境中进行多个分子动力学 (MD) 模拟的循环,以及选择下一个循环的 MD 的初始结构。我们开发了 PaCS-Toolkit,这是一种优化的软件实用程序,它允许使用不同的 MD 软件和轨迹分析工具来促进 PaCS-MD 模拟的执行,并分析获得的轨迹,包括为随后构建马尔可夫状态模型做准备。PaCS-Toolkit 是用 Python 编写的,与各种计算环境兼容,并允许通过编辑配置文件和指定要使用的 MD 软件和分析工具来轻松定制。我们介绍了 PaCS-Toolkit 的软件设计,并演示了 PaCS-MD 变体的应用:针对肽折叠的原始靶向 PaCS-MD;针对蛋白质结构域运动的均方根偏差 PaCS-MD;以及针对配体从腺苷 A 受体解离的解离 PaCS-MD。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd07/11033871/cc50a59804c8/jp4c01271_0001.jpg

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