Using ROC-AUC to measure VS success across the 43 DUDE-Z targets, DiffDock-L and Vina showed comparable performance when combined with the same scoring function (Figure ). More specifically, when combined with the Vina scoring function, pose sampling with DiffDock-L and Vina yielded AUC averages of 0.76 and 0.75, respectively. When combined with Gnina as the scoring function, the pose sampling methods fared better, achieving averaged AUC values of 0.82 and 0.84, respectively. These results indicate that the two pose sampling methods perform similarly while the choice of the scoring function is more relevant to VS success. VS performance varied across the 43 DUDE-Z targets for all four VS setups, with no VS setup consistently outperforming the others (Figures and and Table ). Considering BEDROC scores ≥ 0.5 as indicative of good VS performance, the combination of Vina+Gnina achieved good screening results for the highest number of targets (12 targets out of 43), followed by DiffDock-L+Gnina (9 targets), DiffDock-L+Vina (5 targets), and Vina+Vina (0 targets). Similarly, among the top-1% ranks, the largest portion of active scaffolds was recovered by Vina+Gnina (19.32%), followed by DiffDock-L+Gnina (17.54%), DiffDock-L+Vina (11.17%), and Vina+Vina (3.89%). Weaker correlations were observed between the AUC values obtained with the same pose sampling method in combination with the two scoring functions (Figure ). Specifically, using Vina as the pose sampling method, the AUC values obtained by the two scoring functions had a Pearson correlation coefficient of 0.64. Using DiffDock-L poses, the correlation coefficient between the AUC values was 0.65. These results indicate the major impact of the scoring functions on VS performance. Whereas the ROC-AUC is a good measure of the overall discriminative power of a VS approach, BEDROC and EF1% focus on quantifying early enrichment, i.e., the method's capacity to place active compounds early in the hit list (e.g., among the top-1% of ranks). Similar to ROC-AUC, DiffDock-L and Vina sampling exhibited comparable performance when paired with the Gnina scoring function, yielding average BEDROC scores of 0.33 and 0.36, and EF1% values of 16.22 and 17.88, respectively. However, when using the Vina scoring function, DiffDock-L demonstrated superior performance relative to Vina sampling, achieving a BEDROC score of 0.22 compared to 0.10 and an EF1% of 10.92 compared to 3.89. Strong correlations were observed for BEDROC and EF1% between the two pose sampling methods but only when used in combination with the Gnina scoring function (BEDROC r = 0.88, 𝘱-value < 10 -4 ; EF1% r = 0.86, 𝘱-value < 10 -4 ). Combined with the Vina scoring function, the correlation between the VS results obtained with the two pose sampling methods was much weaker (BEDROC r = 0.30, 𝘱-value = 0.05; EF1% r = 0.06, 𝘱-value = 0.71).