Both, ligands from the validation set and those selected at each iteration, have narrow dynamic ranges of predicted binding free energies (Fig. ). Combined with the remaining model errors this leads to low correlations between the predicted and reference free energies, when evaluated within those ligand sets. Additionally, the predicted free energies of the strongest binders selected at each iteration are often underestimated (Fig. ). Nevertheless, the models are still able to distinguish strongly and weakly binding ligands, reaching near perfect true positive rates for the yet unmeasured ligands in later iterations (Fig. ). Furthermore, every iteration provides further enrichment of high affinity ligands in the training set.