The VS experiment was conducted on three target proteins from the LIT-PCBA database that were not present in the training set: Flap structure-specific endonuclease 1 (FEN1, PDB id: 5FV7) , Glucocerebrosidase (GBA, PDB id: 2XWE) , and Mammalian Target of Rapamycin Complex 1 (MTORC1, PDB id: 5GPG) . As a first step, Vina was used to screen active-inactive sets from LIT-PCBA against each corresponding structure. The top 20,000 compounds based on the Vina ranking were then docked also with AutoDock. 80 binding poses (60 from AutoDock and 20 from Vina) were generated for each ligand-protein complex (Figure ). Rescoring was performed with AutoDock, Vina, DOCK, and Gnina (Gnina rescoring was done by selecting the best pose by CNNScore, then considering its CNNAffinity) . VS performance was evaluated by calculating logarithmic area under the curve (logAUC) , enrichment factors (EF) and Boltzmann-Enhanced Discrimination of ROC (BEDROC) with adjust parameter (α) values of 20 and 80.5 using the CROC Python package , , .