Enhanced Sampling of Protein Conformational Changes via True Reaction Coordinates from Energy Relaxation

TL;DR

This paper introduces a method to compute true reaction coordinates from energy relaxation simulations, significantly accelerating protein conformational change sampling and enabling more natural transition pathways in molecular dynamics.

Contribution

The study presents a novel approach to identify true reaction coordinates from energy relaxation, improving enhanced sampling efficiency for protein conformational changes.

Findings

Accelerated conformational changes by 10^5 to 10^15-fold.

Generated natural transition pathways with unbiased trajectories.

Enabled predictive sampling from a single protein structure.

Abstract

The bottleneck in enhanced sampling lies in finding collective variables (CVs) that can effectively accelerate protein conformational changes. True reaction coordinates (tRCs) that can predict the committor are considered the optimal CVs, but identifying them requires unbiased natural reactive trajectories, which, paradoxically, depend on effective enhanced sampling. Using the generalized work functional method, we found that tRCs control both conformational changes and energy relaxation, enabling us to compute tRCs from energy relaxation simulations. Applying bias to tRCs accelerated conformational changes and ligand dissociation in HIV-1 protease and the PDZ2 domain by 10^5 to 10^15-fold. The resulting trajectories follow natural transition pathways, enabling efficient generation of natural reactive trajectories. In contrast, biased trajectories from empirical CVs often display non-physical features. Furthermore, by computing tRCs from a single protein structure, our method enables predictive sampling of conformational changes. These findings significantly broaden the range of protein functional processes accessible to molecular dynamics simulations.