To evaluate the possibility that the increased enrichment observed during optimization with DockOpt could simply be due to the large number of docking models tested, we employ the Bonferroni correction to adjust the p-value threshold for statistical significance (Figure ). The Bonferroni correction is a widely used method to control the family-wise error rate in multiple hypothesis testing, accounting for the increased likelihood of false positives when conducting a larger number of tests. The correction involves dividing the desired p-value by the number of tests performed; for example, a p-value of p = 0.01 (the default in DockOpt) corrected for 1000 tests would become 10 -5 .