The Oden Institute, University of Texas at Austin, Austin, Texas 78712, United States.
Qingdao Institute for Theoretical and Computational Sciences, Institute of Frontier and Interdisciplinary Science, Shandong University, Qingdao, Shandong 266237, China.
J Chem Theory Comput. 2022 Nov 8;18(11):6952-6965. doi: 10.1021/acs.jctc.2c00708. Epub 2022 Oct 3.
Milestoning is a theory and an algorithm that computes kinetics and thermodynamics at long time scales. It is based on partitioning the (phase) space into cells and running a large number of short trajectories between the boundaries of the cells. The termination points of the trajectories are analyzed with the Milestoning theory to obtain kinetic and thermodynamic information. Managing the tens to hundreds of thousands of Milestoning trajectories is a challenge, which we handle with a python script, ScMiles. Here, we introduce a new version of the python script ScMiles2 to conduct Milestoning simulations. Major enhancements are: (i) post analysis of Milestoning trajectories to obtain the free energy, mean first passage time, the committor function, and exit times; (ii) similar to (i) but the post analysis is for a single long trajectory; (iii) we support the use of the GROMACS software in addition to NAMD; (iv) a restart option; (v) the automated finding, sampling, and launching trajectories from new milestones that are found on the fly; and (vi) support Milestoning calculations with several coarse variables and for complex reaction coordinates. We also evaluate the simulation parameters and suggest new algorithmic features to enhance the rate of convergence of observables. We propose the use of an iteration-averaged kinetic matrix for a rapid approach to asymptotic values. Illustrations are provided for small systems and one large example.
Milestoning 是一种理论和算法,可用于计算长时间尺度的动力学和热力学。它基于将(相)空间划分为单元格,并在单元格边界之间运行大量短轨迹。通过 Milestoning 理论分析轨迹的终止点,以获得动力学和热力学信息。管理数万到数十万条 Milestoning 轨迹是一个挑战,我们使用 Python 脚本 ScMiles 来处理。在这里,我们引入了一个新版本的 Python 脚本 ScMiles2 来进行 Milestoning 模拟。主要增强功能包括:(i) 对 Milestoning 轨迹进行后分析以获得自由能、平均首次通过时间、配分函数和退出时间;(ii) 类似于 (i),但后分析是针对单个长轨迹;(iii) 除了 NAMD 之外,我们还支持使用 GROMACS 软件;(iv) 重启选项;(v) 自动发现、采样和从新发现的里程碑上启动轨迹;(vi) 支持具有多个粗变量和复杂反应坐标的 Milestoning 计算。我们还评估了模拟参数,并提出了新的算法特性,以提高观测值的收敛速度。我们建议使用迭代平均动力学矩阵来快速接近渐近值。提供了小系统和一个大系统的示例。