Explicit models of motions to understand protein side-chain dynamics

TL;DR

This paper introduces explicit motion models based on molecular dynamics simulations and Fokker-Planck equations to better understand protein side-chain dynamics and improve relaxation data analysis.

Contribution

It presents a novel approach that moves beyond model-free methods by designing mechanistic models of motion for protein side-chains.

Findings

Explicit models better fit relaxation data

Provides mechanistic insights into protein dynamics

Links motion models to configuration entropy

Abstract

Nuclear magnetic relaxation is widely used to probe protein dynamics. For decades, most analyses of relaxation in proteins have relied successfully on the model-free approach, forgoing mechanistic descriptions of motions. Model-free types of correlation functions cannot describe a large carbon-13 relaxation dataset in protein sidechains. Here, we use molecular dynamics simulations to design explicit models of motion and solve Fokker-Planck diffusion equations. These models of motion provide better agreement with relaxation data, mechanistic insight and a direct link to configuration entropy.