LIT-PCBA is a chemical dataset designed to eliminate hidden chemical biases. Derived from bioassays, it mimics experimental screening decks, spans diverse protein targets, and has been validated across multiple screening methods, making it suitable for both structure-and ligand-based virtual screening experiments . In order to test the VS power of DBX2 in realistic scenarios, we focused on three LIT-PCBA targets that were not present in our training set: FEN1, GBA, and MTORC1. The numbers of active and inactive compounds for each LIT-PCBA protein target at the beginning of the retrospective VS experiment and after the first round of Vina docking (with the top 20,000 molecules brought forward) are reported in Table .