We utilize two distinct methodologies to evaluate the performance of DockM8. The first metric, DockM8-max, involves assessing each target individually by exploring all potential combinations of consensus algorithms, scoring functions, and pose selection strategies to identify and report the best-performing combination for each specific target. Conversely, the DockM8-best metric considers the same range of combinations but focuses on the one that delivers the highest average performance across the entire dataset of targets. Thus, Figure : Evaluation of EF at 1% of DockM8 compared to 21 published protocols on the DEKOIS dataset. Methods are sorted by their median value. Whiskers denote the 10 th and 90 th percentiles. Methods containing the @ symbol refer to either the provenance of the data (@IGN and @Karmadock) or the source of the docking poses, which were used for scoring (@GlideSP).