Wassermann, Anne, Lounkine, Eugen, Whitebread, Steven, Chen, Shanni, Hughes, Kevin, Guo, Hongqiu, Kutlina, Elena, Fekete, Alexander, Urban, Laszlo, Klumpp, Martin and Glick, Meir (2014) A Screening Pattern Recognition Method Finds New and Divergent Targets for Drugs and Natural Products. ACS Chemical Biology, 9 (7). pp. 1622-1631. ISSN 1554-89291554-8937

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 little overlap among the targets predicted; the drugs were strongly biased towards membrane receptors and the NPs towards 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 interactions 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.

Item Type:	Article
Keywords:	small molecule target prediction, biological descriptor, mechanism-of-action
Date Deposited:	13 Oct 2015 13:13
Last Modified:	04 Jul 2016 23:45
URI:	https://oak.novartis.com/id/eprint/21170