摘要Uncovering conserved 3D protein-ligand binding patterns on the basis of functional groups(FGs)shared by a variety of small molecules can greatly expand our knowledge of protein-ligand interactions.Despite that conserved binding patterns for a few commonly used FGs have been reported in the literature,large-scale identification and evaluation of FG-based 3D binding motifs are still lacking.Here,we propose a computational method,Automatic FG-based Three-dimensional Motif Extractor(AFTME),for automatic mapping of 3D motifs to different FGs of a specific ligand.Applying our method to 233 naturally-occurring ligands,we define 481 FG-binding motifs that are highly conserved across different ligand-binding pockets.Systematic analysis further reveals four main classes of binding motifs corresponding to distinct sets of FGs.Combinations of FG-binding motifs facilitate the binding of proteins to a wide spectrum of ligands with various binding affinities.Finally,we show that our FG-motif map can be used to nominate FGs that potentially bind to specific drug targets,thus providing useful insights and guidance for rational design of small-molecule drugs.