A ligand-based approach to mining the chemogenomic space of drugs.

The practical implementation and validation of a ligand-based approach to mining the chemogenomic space of drugs is presented and applied to the in silico target profiling of 767 drugs against 684 targets of therapeutic relevance. The results reveal that drugs targeting aminergic G protein-coupled receptors (GPCRs) show the most promiscuous pharmacological profiles. The detection of cross-pharmacologies between aminergic GPCRs and the opioid, sigma, NMDA, and 5-HT3 receptors aggravate the potential promiscuity of those drugs, predominantly including analgesics, antidepressants, and antipsychotics.