Exact Topology of the Dynamic Probability Surface of an Activated Process by Persistent Homology.
Exact Topology of the Dynamic Probability Surface of an Activated Process by Persistent Homology.
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DOI：
10.1021/acs.jpcb.1c00904
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发表时间：
2021-05-13
期刊：
影响因子：
--
通讯作者：
Liang J
中科院分区：
文献类型：
--
作者：
Manuchehrfar F;Li H;Tian W;Ma A;Liang J
为了深入了解活化过程的反应机理，我们引入了一种精确的方法来量化潜在动力学过程的高维概率表面的拓扑结构。代替莫尔斯指标，我们研究了高维位形空间上概率曲面的超水平集序列的同调群。丙氨酸二肽异构化，一个原型的活化过程中，我们确定的概率峰和连接脊的位置，沿着与措施，他们的全球突出。而不是一个鞍点，过渡态系综（TSE）的构象是在最突出的概率峰后的反应物/产品，当适当的反应坐标。基于直觉的模型，即使是那些表现出双阱的模型，也无法捕捉到激活过程的动态。峰值出现、突出和位置可以在子空间投影上被扭曲。虽然主成分分析考虑了构象变化，但它夸大了表面拓扑结构的复杂性，破坏了拓扑特征的动态特性。与此相反，TSE自然出现的反应物/产物盆地以外的最突出的峰，当投影到一个子空间的最小尺寸包含的反应坐标。我们的方法具有通用性，可以应用于研究其他激活过程的高维概率表面的拓扑结构。
To gain insight into reaction mechanism of activated processes, we introduce an exact approach for quantifying the topology of high-dimensional probability surfaces of the underlying dynamic processes. Instead of Morse indexes, we study the homology groups of a sequence of superlevel sets of the probability surface over high-dimensional configuration spaces using persistent homology. For alanine-dipeptide isomerization, a prototype of activated processes, we identify locations of probability peaks and connecting-ridges, along with measures of their global prominence. Instead of a saddle-point, the transition state ensemble (TSE) of conformations are at the most prominent probability peak after reactants/products, when proper reaction coordinates are included. Intuition-based models, even those exhibiting a double-well, fail to capture the dynamics of the activated process. Peak occurrence, prominence, and locations can be distorted upon subspace projection. While principal component analysis account for conformational variance, it inflates the complexity of the surface topology and destroy dynamic properties of the topological features. In contrast, TSE emerges naturally as the most prominent peak beyond the reactant/product basins, when projected to a subspace of minimum dimension containing the reaction coordinates. Our approach is general and can be applied to investigate the topology of high-dimensional probability surfaces of other activated process.
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DOI：
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发表时间：
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影响因子：
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