Department of Chemistry and Biochemistry, University of Arizona, 1306 East University Blvd., Tucson, Arizona 85721, United States.
J Chem Theory Comput. 2022 Jun 14;18(6):3997-4004. doi: 10.1021/acs.jctc.2c00186. Epub 2022 May 10.
Simulation methods like transition path sampling (TPS) generate an abundance of information buried in the collection of reactive trajectories that they generate. However, only limited use has been made of this information, mainly for the identification of the reaction coordinate. The standard TPS tools have been designed for monitoring the progress of the system from reactants to products. However, the reaction coordinate does not contain all the information regarding the mechanism. In our earlier work, we have used TPS on enzymatic systems and have identified important motions in the reactant well that prepares the system for the reaction. Since these events take place in the reactant well, they are beyond the reach of standard TPS postprocessing methods. We present a simple scheme for identifying the common trends in enzymatic trajectories. This scheme was designed for a specific class of enzymatic reactions: it can be used for identifying motions that guide the system to reaction-ready conformations. We have applied it to two enzymatic systems that we have studied in the past, formate dehydrogenase and purine nucleoside phosphorylase, and we were able to identify interactions, far from the transition state, that are important for preparing the system for the reaction but that had been overlooked in earlier work.
模拟方法，如过渡态抽样（TPS），会生成大量隐藏在它们所生成的反应轨迹集合中的信息。然而，这些信息的利用非常有限，主要用于识别反应坐标。标准的 TPS 工具被设计用于监测系统从反应物到产物的进展。然而，反应坐标并不包含关于机制的所有信息。在我们之前的工作中，我们已经在酶系统上使用了 TPS，并在反应物中识别出了为反应做准备的重要运动。由于这些事件发生在反应物中，它们超出了标准 TPS 后处理方法的范围。我们提出了一种识别酶轨迹共同趋势的简单方案。该方案是为特定类别的酶反应设计的：它可用于识别引导系统达到反应准备状态的运动。我们已经将其应用于过去研究过的两种酶系统，甲酸脱氢酶和嘌呤核苷磷酸化酶，并能够识别出远离过渡态的相互作用，这些相互作用对于为反应准备系统非常重要，但在早期工作中被忽视了。
