Predicting new molecular targets for known drugs

MJ Keiser, V Setola, JJ Irwin, C Laggner, AI Abbas… - Nature, 2009 - nature.com
MJ Keiser, V Setola, JJ Irwin, C Laggner, AI Abbas, SJ Hufeisen, NH Jensen, MB Kuijer…
Nature, 2009nature.com
Although drugs are intended to be selective, at least some bind to several physiological
targets, explaining side effects and efficacy. Because many drug–target combinations exist,
it would be useful to explore possible interactions computationally. Here we compared 3,665
US Food and Drug Administration (FDA)-approved and investigational drugs against
hundreds of targets, defining each target by its ligands. Chemical similarities between drugs
and ligand sets predicted thousands of unanticipated associations. Thirty were tested …
Abstract
Although drugs are intended to be selective, at least some bind to several physiological targets, explaining side effects and efficacy. Because many drug–target combinations exist, it would be useful to explore possible interactions computationally. Here we compared 3,665 US Food and Drug Administration (FDA)-approved and investigational drugs against hundreds of targets, defining each target by its ligands. Chemical similarities between drugs and ligand sets predicted thousands of unanticipated associations. Thirty were tested experimentally, including the antagonism of the β1 receptor by the transporter inhibitor Prozac, the inhibition of the 5-hydroxytryptamine (5-HT) transporter by the ion channel drug Vadilex, and antagonism of the histamine H4 receptor by the enzyme inhibitor Rescriptor. Overall, 23 new drug–target associations were confirmed, five of which were potent (<100 nM). The physiological relevance of one, the drug N,N-dimethyltryptamine (DMT) on serotonergic receptors, was confirmed in a knockout mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs.
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