Fig. 7From: Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for bindingThe average rank assigned to all ligand atoms attaining a score above a specified threshold on the PDBBind test set. Each line corresponds to the performance obtained by an RF_PLEC_4 model trained on a different training set. The model trained on the unbiased ZINC dataset outperforms the models trained on the real-world DUD-E and LIT-PCBA datasets, illustrating that ligand-specific biases hamper the ability of virtual screening models to identify the most important functional groupsBack to article page