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A Meshless Discretization Method for Markov State Models Applied to Explicit Water Peptide Folding Simulations

机译:马尔可夫状态模型的无网格离散化方法在显式水肽折叠模拟中的应用

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Markov State Models (MSMs) are widely used to represent molecular conformational changes as jump-like transitions between subsets of the confor-mational state space. However, the simulation of peptide folding in explicit water is usually said to be unsuitable for the MSM framework. In this article, we summarize the theoretical background of MSMs and indicate that explicit water simulations do not contradict these principles. The algorithmic framework of a meshless conformational space discretization is applied to an explicit water system and the sampling results are compared to a long-term molecular dynamics trajectory. The meshless discretization approach is based on spectral clustering of stochastic matrices (MSMs) and allows for a parallelization of MD simulations. In our example of Trialanine we were able to compute the same distribution of a long term simulation in less computing time.
机译:马尔可夫状态模型(MSM)被广泛用来表示分子构象变化,即构象状态空间子集之间的跳跃状跃迁。但是,通常认为在显性水中模拟肽折叠不适合MSM框架。在本文中,我们总结了MSM的理论背景,并指出显式水模拟与这些原理并不矛盾。将无网格构象空间离散化的算法框架应用于显式水系统,并将采样结果与长期分子动力学轨迹进行比较。无网格离散化方法基于随机矩阵(MSM)的光谱聚类,并允许MD模拟的并行化。在我们的Trialanine示例中,我们能够以更少的计算时间来计算长期仿真的相同分布。

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