title: A screening pattern recognition method finds new and divergent targets for drugs and natural products.
abstract: Computational target prediction methods using chemical descriptors have been applied exhaustively in drug discovery to elucidate the mechanisms-of-action (MOAs) of small molecules. To predict truly novel and unexpected small molecule-target interactions, compounds must be compared by means other than their chemical structure alone. Here we investigated predictions made by a method, HTS fingerprints (HTSFPs), that matches patterns of activities in experimental screens. Over 1,400 drugs and 1,300 natural products (NPs) were screened in more than 200 diverse assays, creating encodable activity patterns. The comparison of these activity patterns to an MOA-annotated reference panel led to the prediction of 5,281 and 2,798 previously unknown targets for the NP and drug sets, respectively. Intriguingly, there was limited overlap among the targets predicted; the drugs were more biased toward membrane receptors and the NPs toward soluble enzymes, consistent with the idea that they represent unexplored pharmacologies. Importantly, HTSFPs inferred targets that were beyond the prediction capabilities of standard chemical descriptors, especially for NPs but also for the more explored drug set. Of 65 drug-target predictions that we tested in vitro, 48 (73.8%) were confirmed with AC50 values ranging from 38 nM to 29 μM. Among these interactions was the inhibition of cyclooxygenases 1 and 2 by the HIV protease inhibitor Tipranavir. These newly discovered targets that are phylogenetically and phylochemically distant to the primary target provide an explanation for spontaneous bleeding events observed for patients treated with this drug, a physiological effect that was previously difficult to reconcile with the drug's known MOA.
authors.affiliation: Novartis Institutes for Biomedical Research Inc. , 250 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
authors.forename: Anne Mai
authors.initials: AM
authors.lastname: Wassermann
authors.forename: Eugen
authors.initials: E
authors.lastname: Lounkine
authors.forename: Laszlo
authors.initials: L
authors.lastname: Urban
authors.forename: Steven
authors.initials: S
authors.lastname: Whitebread
authors.forename: Shanni
authors.initials: S
authors.lastname: Chen
authors.forename: Kevin
authors.initials: K
authors.lastname: Hughes
authors.forename: Hongqiu
authors.initials: H
authors.lastname: Guo
authors.forename: Elena
authors.initials: E
authors.lastname: Kutlina
authors.forename: Alexander
authors.initials: A
authors.lastname: Fekete
authors.forename: Martin
authors.initials: M
authors.lastname: Klumpp
authors.forename: Meir
authors.initials: M
authors.lastname: Glick
mesh_terms: D001688:Biological Products / Q000737:chemistry* / Q000494:pharmacology*; D062313:Databases, Pharmaceutical; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D008958:Models, Molecular; D058990:Molecular Targeted Therapy; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D010600:Pharmacology; D054852:Small Molecule Libraries / Q000737:chemistry* / Q000494:pharmacology*
chemical_list: D001688:Biological Products; D004364:Pharmaceutical Preparations; D054852:Small Molecule Libraries