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Predicting new molecular targets for known drugs

Whereas drugs are intended to be selective, at least some bind to several physiologic targets, explaining both side effects and efficacy. As many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here, we compared 3,665 FDA-approved and investigatio...

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Autores principales: Keiser, Michael J., Setola, Vincent, Irwin, John J., Laggner, Christian, Abbas, Atheir, Hufeisen, Sandra J., Jensen, Niels H., Kuijer, Michael B., Matos, Roberto C., Tran, Thuy B., Whaley, Ryan, Glennon, Richard A., Hert, Jérôme, Thomas, Kelan L.H., Edwards, Douglas D., Shoichet, Brian K., Roth, Bryan L.
Formato: Texto
Lenguaje:English
Publicado: 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2784146/
https://www.ncbi.nlm.nih.gov/pubmed/19881490
http://dx.doi.org/10.1038/nature08506
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author Keiser, Michael J.
Setola, Vincent
Irwin, John J.
Laggner, Christian
Abbas, Atheir
Hufeisen, Sandra J.
Jensen, Niels H.
Kuijer, Michael B.
Matos, Roberto C.
Tran, Thuy B.
Whaley, Ryan
Glennon, Richard A.
Hert, Jérôme
Thomas, Kelan L.H.
Edwards, Douglas D.
Shoichet, Brian K.
Roth, Bryan L.
author_facet Keiser, Michael J.
Setola, Vincent
Irwin, John J.
Laggner, Christian
Abbas, Atheir
Hufeisen, Sandra J.
Jensen, Niels H.
Kuijer, Michael B.
Matos, Roberto C.
Tran, Thuy B.
Whaley, Ryan
Glennon, Richard A.
Hert, Jérôme
Thomas, Kelan L.H.
Edwards, Douglas D.
Shoichet, Brian K.
Roth, Bryan L.
author_sort Keiser, Michael J.
collection PubMed
description Whereas drugs are intended to be selective, at least some bind to several physiologic targets, explaining both side effects and efficacy. As many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here, we compared 3,665 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 β(1) receptor by the transporter inhibitor Prozac, the inhibition of the 5-HT transporter by the ion channel drug Vadilex, and antagonism of the histamine H(4) 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 such, the drug DMT on serotonergic receptors, was confirmed in a knock-out mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs.
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spelling pubmed-27841462010-05-12 Predicting new molecular targets for known drugs Keiser, Michael J. Setola, Vincent Irwin, John J. Laggner, Christian Abbas, Atheir Hufeisen, Sandra J. Jensen, Niels H. Kuijer, Michael B. Matos, Roberto C. Tran, Thuy B. Whaley, Ryan Glennon, Richard A. Hert, Jérôme Thomas, Kelan L.H. Edwards, Douglas D. Shoichet, Brian K. Roth, Bryan L. Nature Article Whereas drugs are intended to be selective, at least some bind to several physiologic targets, explaining both side effects and efficacy. As many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here, we compared 3,665 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 β(1) receptor by the transporter inhibitor Prozac, the inhibition of the 5-HT transporter by the ion channel drug Vadilex, and antagonism of the histamine H(4) 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 such, the drug DMT on serotonergic receptors, was confirmed in a knock-out mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs. 2009-11-01 2009-11-12 /pmc/articles/PMC2784146/ /pubmed/19881490 http://dx.doi.org/10.1038/nature08506 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Keiser, Michael J.
Setola, Vincent
Irwin, John J.
Laggner, Christian
Abbas, Atheir
Hufeisen, Sandra J.
Jensen, Niels H.
Kuijer, Michael B.
Matos, Roberto C.
Tran, Thuy B.
Whaley, Ryan
Glennon, Richard A.
Hert, Jérôme
Thomas, Kelan L.H.
Edwards, Douglas D.
Shoichet, Brian K.
Roth, Bryan L.
Predicting new molecular targets for known drugs
title Predicting new molecular targets for known drugs
title_full Predicting new molecular targets for known drugs
title_fullStr Predicting new molecular targets for known drugs
title_full_unstemmed Predicting new molecular targets for known drugs
title_short Predicting new molecular targets for known drugs
title_sort predicting new molecular targets for known drugs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2784146/
https://www.ncbi.nlm.nih.gov/pubmed/19881490
http://dx.doi.org/10.1038/nature08506
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