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arXiv 1506.06259physics.comp-phphysics.bio-phphysics.chem-phphysics.data-anq-bio.BM
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基于分子动力学模拟的动力学距离和动力学图

Kinetic distance and kinetic maps from molecular dynamics simulation

Frank Noe, Cecilia Clementi

摘要:

从分子动力学(MD)模拟中表征大分子动力学需要一个可以区分缓慢互变状态的距离度量。在这里,我们建立在扩散映射理论,并定义一个动力学距离的不可约马尔可夫过程,量化如何缓慢分子构象相互转换。给定近似MD马尔可夫算子的特征值和特征向量(反应坐标)的模型,可以计算动力学距离。在这里,我们采用时滞独立成分分析(TICA)。可以缩放TICA分量以提供其中欧几里得距离对应于动力学距离的动力学图。因此,在降维方法中应该保留多少TICA维度的问题变得过时,并且在动力学模型构建中需要指定少一个参数。我们证明了使用TICA和马尔可夫状态模型(MSM)分析的说明性模型,在牛胰蛋白酶抑制剂和蛋白质抑制剂协会在胰蛋白酶和苯甲脒的蛋白质构象动力学的方法。

英文摘要:

Characterizing macromolecular kinetics from molecular dynamics (MD) simulations requires a distance metric that can distinguish slowly-interconverting states. Here we build upon diffusion map theory and define a kinetic distance for irreducible Markov processes that quantifies how slowly molecular conformations interconvert. The kinetic distance can be computed given a model that approximates the eigenvalues and eigenvectors (reaction coordinates) of the MD Markov operator. Here we employ the time-lagged independent component analysis (TICA). The TICA components can be scaled to provide a kinetic map in which the Euclidean distance corresponds to the kinetic distance. As a result, the question of how many TICA dimensions should be kept in a dimensionality reduction approach becomes obsolete, and one parameter less needs to be specified in the kinetic model construction. We demonstrate the approach using TICA and Markov state model (MSM) analyses for illustrative models, protein conformation dynamics in bovine pancreatic trypsin inhibitor and protein-inhibitor association in trypsin and benzamidine.

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