In summary, the evaluation results on CASF-2016, MerckFEP, DUD-E, DEKOIS-v2, and LIT-PCBA underscore the effectiveness of GGAP-CPI-IntEns in handling unseen and imbal- The baseline results are collected from Ref. anced datasets. The integration of bioactivity learning, which mitigates activity cliff-induced discrepancies, combined with a complex structure-free framework, significantly improves the flexibility, efficiency, and accuracy of virtual screening-making our approach a versatile and rapid tool for high-throughput drug discovery applications. f The results for Smina+Vina are collected from Ref, and other results are collected from Ref.