Molecular dynamics (MD) simulations can mechanistically explain receptor function. However, the enormous data sets that they may imply can be a hurdle. Plante and colleagues (Molecules, 2019) recently described a machine learning approach to the analysis of MD simulations. The approach successfully classified ligands and identified functional receptor motifs and thus it seems promising for mechanism-based drug discovery.