论文标题
酶动力学的反应路径统计力学
Reaction-Path Statistical Mechanics of Enzymatic Kinetics
论文作者
论文摘要
我们基于大偏差的原理来介绍一个反应路径统计力学形式主义,以量化Michaelis-Menten机制下的单分子酶反应过程的动力学,这体现了生活系统中不平衡的过程。我们的理论方法始于相等的先验概率的原理,并定义了反应路径熵,以构建新的非平衡集合作为可能的化学反应路径的集合。结果,我们使用统计力学的形式主义评估了各种基于路径的分区功能和自由能。它们使我们能够计算给定酶促反应的时间尺度,即使在没有平衡集合所需的明确边界条件的情况下。我们还考虑了固定观察时间的闭合条件下的大偏差理论,以量化酶 - 基底解开速率。结果表明,在有限的时间范围内解开事件中的相位分离样,双峰行为的存在,并且随着其速率函数在长时间的限制中收敛到单相时,行为消失。
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.