The invention discloses a
lead compound virtual screening method and device. The method includes the steps of generation of molecular fingerprints of lead compounds on
drug targets and bioactivity prediction of interaction between the lead compounds and the
drug targets. The generation of the molecular fingerprints includes a
molecular fingerprint part based on a module unit,
a weighting molecularfingerprint part and a bioactivity part. During the bioactivity prediction, ligand molecular fingerprints and bioactivity values are utilized to serve as input of a
random forest regression model, and a prediction model is constructed. Additionally, the device includes a universal tool for
virtual screening on the basis of ligands, a prediction tool for the bioactivity generated when the lead compounds take effects on the
drug targets, and a generation tool of the molecular fingerprints of the lead compounds on the drug targets. At present, molecular fingerprints which are excellent in performance and are used for the bioactivity prediction are often greater in length, and however, by adopting a designed
deep learning algorithm, molecular fingerprints which are excellent in performance and smaller in length can be generated so that the best bioactivity prediction model of
drug target ligands can be obtained.