Learning protein-ligand unbinding pathways via single-parameter community detection

Understanding the dynamics of biomolecular complexes, e. g. , of protein-ligand (un) binding, requires the understanding of paths such systems take between metastable states. In MD simulation data, paths are usually not observable per se, but need to be inferred from simulation trajectories. Here we present a novel approach to cluster trajectories based on a community detection algorithm that requires the definition of only a single free parameter. Using the streptavidin-biotin complex as benchmark system and the A2a adenosine receptor in complex with the inhibitor ZM241385 as an elaborate application, we demonstrate how such clusters of trajectories correspond to pathways, and how the approach helps in the identification of reaction coordinates for a considered (un) binding process.