The distance matrix thus calculated is clustered using the affinity propagation algorithm from the scikit-learn package. Typically, one cluster emerges as dominant with 10+ members over 30 egress paths. The centroid of the dominant cluster, which we call the main egress path, is then used to drive the unbinding of the ligand in the subsequent iMetaD stage. Here for clarity, we assume that both paths had to be extended to the length of another path in the ensemble, not shown. C) The metric is calculated as pairwise RMSD after optimal alignment on the receptor. Pairwise RMSD is added to the metric only when at least one waypoint in a pair is not solvent-exposed.