Efficient Estimation of Transition Rates as Functions of pH

TL;DR

This paper introduces a new method to efficiently estimate pH-dependent transition rates by combining canonical ensemble simulations, reweighting techniques, and discretization of the Fokker-Planck equation, demonstrated on a tripeptide.

Contribution

It presents a novel approach that reduces the need for extensive Grand Canonical Ensemble sampling by leveraging canonical ensemble simulations and advanced analysis methods.

Findings

Successfully estimated transition rates for pH-dependent systems.

Validated approach on the tripeptide Ala-Asp-Ala.

Demonstrated efficiency over traditional sampling methods.

Abstract

Extracting the kinetic properties of a system whose dynamics depend on the pH of the environment with which it exchanges energy and atoms requires sampling the Grand Canonical Ensemble. As an alternative, we present a novel strategy that requires simulating only the most recurrent Canonical Ensembles that compose the Grand Canonical Ensemble. The simulations are used to estimate the Gran Canonical distribution for a specific pH value by reweighting and to construct the transition rate matrix by discretizing the Fokker-Planck equation by Square Root Approximation and robust Perron Cluster Cluster Analysis. As an application, we have studied the tripeptide Ala-Asp-Ala.