Relating protein pharmacology by ligand chemistry

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MJ Keiser, keiser@gmail.com1, Bryan L. Roth, bryan_roth@med.unc.edu2, BN Armburster2, P Ernsberger2, John J Irwin, jji@cgl.ucsf.edu1, and Brian K. Shoichet, shoichet@cgl.ucsf.edu1. (1) Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 4th Street, San Francisco, CA 94143, (2) National Institute of Mental Health Psychoactive Drug Screening Program and Department of Pharmacology, University of North Carolina at Chapel Hill, 8032 Burnett-Womack, CB # 7365, Chapel Hill, NC 27599
We present a technique that quantitatively groups and relates proteins based on the chemical similarity of their ligands. Starting with 65,000 ligands annotated into sets for hundreds of drug targets, we computed a similarity score between each set using ligand topology. The significance of the resulting similarity scores, normalized using a statistical model, were expressed as a minimum spanning tree to map the sets together. Although these maps are connected solely by chemical similarity, biologically sensible clusters nevertheless emerged. Links among unexpected targets also emerged, among them that methadone, emetine and loperamide (Imodium) may antagonize muscarinic M3, alpha2 adrenergic and neurokinin NK2 receptors, respectively. These predictions were subsequently confirmed experimentally. Relating receptors by ligand chemistry organizes biology to reveal unexpected relationships that may be assayed using the ligands themselves. It has not escaped our notice that this approach may be useful for drug repurposing.