Posted by: shrikantmantri | November 2, 2009

Nature Paper: Predicting new molecular targets for known drugs

Nature advance online publication 1 November 2009 | doi:10.1038/nature08506; Received 7 April 2009; Accepted 14 September 2009; Published online 1 November 2009

Predicting new molecular targets for known drugs

Michael J. Keiser1,2,8, Vincent Setola3,8, John J. Irwin1, Christian Laggner1, Atheir I. Abbas4, Sandra J. Hufeisen5, Niels H. Jensen5, Michael B. Kuijer3, Roberto C. Matos3, Thuy B. Tran3, Ryan Whaley3, Richard A. Glennon6, Jérôme Hert1, Kelan L. H. Thomas1,7, Douglas D. Edwards1, Brian K. Shoichet1 & Bryan L. Roth3,5

  1. Department of Pharmaceutical Chemistry,
  2. Graduate Group in Bioinformatics, University of California San Francisco, 1700 4th Street, San Francisco, California 94143-2550, USA
  3. NIMH Psychoactive Drug Screening Program, Department of Pharmacology,
  4. Department of Biochemistry, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106, USA
  5. Department of Pharmacology and Division of Medicinal Chemistry and Natural Products, The University of North Carolina Chapel Hill School of Medicine, Chapel Hill, North Carolina 27759, USA
  6. Department of Medicinal Chemistry, School of Pharmacy, Medical College of Virginia Campus, Virginia Commonwealth University, 410 North 12th Street, PO Box 980540, Richmond, Virginia 23298-0540, USA
  7. University of Michigan Health System, 1500 East Medical Center Drive, Ann Arbor, Michigan 48109, USA
  8. These authors contributed equally to this work.

Correspondence to: Brian K. Shoichet1Bryan L. Roth3,5 Correspondence and requests for materials should be addressed to B.K.S. (Email: or B.L.R. (Email:


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 beta1 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.


Posted via email from Sharing significant bytes —(Shrikant Mantri)


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