Using grid search we observed a maximum increase of 31.6 percentage points for the target KITH, and using beam search we observed a maximum increase of 44.2 percentage points, also for the target KITH. DockOpt creates a comprehensive report for each target, which can be accessed at dudez2022.docking.org. In this paper, we illustrate the features of these reports using actual results for two DUDE-Z targets as examples, HIV-1 protease (HIVPR) and coagulation factor VIIa (FA7) (Figure ). Each report includes a linear-log ROC plot of the enrichment of the positive class over the negative class. (Figure ). This plot captures the performance of a docking model in a single visualization, with the area under the curve (AUC) serving as a quantitative measure of model quality. Next, the report includes additional plots that provide insight into the respective contributions of the terms of the scoring function of the docking program, thereby revealing potential biases that may influence the evaluation of docking models (e.g., imbalanced representations of properties in the dataset, such as charge). The split violin charts (Figure ) show the scores of the binary classes grouped by net molecular charge.