Reaction-Path Statistical Mechanics of Enzymatic Kinetics
Hyuntae Lim, YounJoon Jung

TL;DR
This paper develops a reaction-path statistical mechanics framework to analyze single-molecule enzymatic kinetics, revealing phase-separation-like behavior in unbinding events through large deviation theory.
Contribution
It introduces a novel nonequilibrium ensemble based on reaction path entropy to quantify enzyme kinetics without explicit boundary conditions.
Findings
Identifies bimodal unbinding behavior at finite timescales.
Demonstrates phase-separation-like phenomena in enzyme unbinding.
Provides a method to calculate enzymatic reaction timescales without boundary conditions.
Abstract
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…
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