A Supervised Molecular Dynamics Approach to Unbiased Ligand–Protein Unbinding

The recent paradigm shift toward
the use of the kinetics parameters
in place of thermodynamic constants is leading the computational chemistry
community to develop methods for studying the mechanisms of drug binding
and unbinding. From this standpoint, molecular dynamics (MD) plays
an important role in delivering insight at the molecular scale. However,
a known limitation of MD is that the time scales are usually far from
those involved in ligand–receptor unbinding events. Here, we
show that the algorithm behind supervised MD (SuMD) can simulate the
dissociation mechanism of druglike small molecules while avoiding
the input of any energy bias to facilitate the transition. SuMD was
tested on seven different intermolecular complexes, covering four
G protein-coupled receptors: the A2A and A1 adenosine
receptors, the orexin 2 and the muscarinic 2 receptors, and the soluble
globular enzyme epoxide hydrolase. SuMD well-described the multistep
nature of ligand–receptor dissociation, rationalized previous
experimental data and produced valuable working hypotheses for structure–kinetics
relationships.