Free energy, rates, and mechanism of transmembrane dimerization in lipid bilayers from dynamically unbiased molecular dynamics simulations

TL;DR

This paper presents a novel method using short, unbiased molecular dynamics trajectories to accurately determine free energy, rates, and mechanisms of transmembrane protein dimerization in lipid bilayers, avoiding complex biasing schemes.

Contribution

The authors introduce a new approach that merges short unbiased simulations to study membrane protein assembly, bypassing the need for collective variables or biasing forces.

Findings

Successfully sampled spontaneous protein dimerization in lipid bilayers.

Obtained converged free energy profiles and kinetic rates.

Demonstrated effectiveness with coarse-grained Martini force field.

Abstract

The assembly of proteins in membranes plays a key role in many crucial cellular pathways. Despite their importance, characterizing transmembrane assembly remains challenging for experiments and simulations. Equilibrium molecular dynamics simulations do not cover the time scales required to sample the typical transmembrane assembly. Hence, most studies rely on enhanced sampling schemes that steer the dynamics of transmembrane proteins along a collective variable that should encode all slow degrees of freedom. However, given the complexity of the condensed-phase lipid environment, this is far from trivial, with the consequence that free energy profiles of dimerization can be poorly converged. Here, we introduce an alternative approach, which relies only on simulating short, dynamically unbiased trajectory segments, avoiding using collective variables or biasing forces. By merging all trajectories, we obtain free energy profiles, rates, and mechanisms of transmembrane dimerization with the same set of simulations. We showcase our algorithm by sampling the spontaneous association and dissociation of a transmembrane protein in a lipid bilayer, the popular coarse-grained Martini force field. Our algorithm represents a promising way to investigate assembly processes in biologically relevant membranes, overcoming some of the challenges of conventional methods.