Protein–Ligand-Based Pharmacophores: Generation and Utility Assessment in Computational Ligand Profiling

Ligand profiling is an emerging computational method for predicting the most likely targets of a bioactive compound and therefore anticipating adverse reactions, side effects and drug repurposing. A few encouraging successes have already been reported using ligand 2-D similarity searches and protein–ligand docking. The current study describes the use of receptor–ligand-derived pharmacophore searches as a tool to link ligands to putative targets. A database of 68,056 pharmacophores was first derived from 8,166 high-resolution protein–ligand complexes. In order to limit the number of queries, a maximum of 10 pharmacophores was generated for each complex according to their predicted selectivity. Pharmacophore search was compared to ligand-centric (2-D and 3-D similarity searches) and docking methods in profiling a set of 157 diverse ligands against a panel of 2,556 unique targets of known X-ray structure. As expected, ligand-based methods outperformed, in most of the cases, structure-based approaches in rank...