标题： 酶动力学的反应路径统计力学 显示英文标题

标题： Reaction-Path Statistical Mechanics of Enzymatic Kinetics

摘要： 我们引入了一种基于大偏差原理的反应路径统计力学形式，以量化单分子酶促反应过程在米氏机制下的动力学，这体现了生命系统中的非平衡过程。 我们的理论方法从等先验概率原理出发，并定义反应路径熵来构建一个新的非平衡系综，作为可能化学反应路径的集合。 结果是我们使用统计力学的形式评估了各种基于路径的配分函数和自由能。 它们使我们能够计算给定酶促反应的时间尺度，即使在没有用于平衡系综的显式边界条件的情况下。 我们还考虑了在固定观测时间的闭合边界条件下大偏差理论，以量化酶-底物解离速率。 结果表明，在有限时间尺度下，解离事件存在类似相分离的双峰行为，且随着其率函数在长时间极限下收敛到单一相，该行为消失。 显示英文摘要

摘要： We introduce a reaction-path statistical mechanics formalism based on the principle of large deviations to quantify the kinetics of single-molecule enzymatic reaction processes under the Michaelis-Menten mechanism, which exemplifies an out-of-equilibrium process in the living system. Our theoretical approach begins with the principle of equal a priori probabilities and defines the reaction path entropy to construct a new nonequilibrium ensemble as a collection of possible chemical reaction paths. As a result, we evaluate a variety of path-based partition functions and free energies using the formalism of statistical mechanics. They allow us to calculate the timescales of a given enzymatic reaction, even in the absence of an explicit boundary condition that is necessary for the equilibrium ensemble. We also consider the large deviation theory under a closed-boundary condition of the fixed observation time to quantify the enzyme-substrate unbinding rates. The result demonstrates the presence of a phase-separation-like, bimodal behavior in unbinding events at a finite timescale, and the behavior vanishes as its rate function converges to a single phase in the long-time limit.