Considering median EF 1% values, DockM8-max outperforms all state-of-the-art methods with an median EF 1% of 29.6%, while DockM8-best lands at rank 5 (18.05%). The other three top-scoring methods are IGN, RTMScore and GenScore, with median EF 1% s between 19 and 26%. Another promising result is that the DockM8-max combination always results in an EF 1% higher than 10% for any of the targets in the dataset (the lowest being 10.32% for cpy2a6), while all other methods, including DockM8-best, show poor performance for individual targets (down to EF 1% of 0%). These observations are also supported by the AUC-ROC and BEDROC metrics for which DockM8-max achieves median values of 0.813 and 0.633 respectively (see Supporting Information). The generalizability of scoring functions and virtual screening protocols has been a long-standing challenge in computer-aided drug design. From these data, it is clear that DockM8 provides an avenue to partially remediate this problem by providing the user with a large number of possible combinations, allowing the subsequent tailoring of the conditions to the target being studied. The five best (on average according to EF1%) DockM8 methods are shown in Table .