2009
DOI: 10.1038/nature08506
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Predicting new molecular targets for known drugs

Abstract: 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, i… Show more

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Cited by 1,521 publications
(1,302 citation statements)
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References 49 publications
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“…Consistent with these studies are observations that 5-HT 2A receptor knockout mice do not exhibit head-twitch response to psychedelics (see also Figure 1). 27,28, 47 The dose-dependent blockage of the effects of psilocybin in humans by the 5-HT 2A receptor antagonist ketanserin further supports the relevance of these findings. 5 It should also be noted that activation of 5-HT 2C receptors attenuates the head-twitch behavior induced by psychedelics.…”
Section: ■ Modeling Psychosis In Animalsmentioning
confidence: 73%
“…Consistent with these studies are observations that 5-HT 2A receptor knockout mice do not exhibit head-twitch response to psychedelics (see also Figure 1). 27,28, 47 The dose-dependent blockage of the effects of psilocybin in humans by the 5-HT 2A receptor antagonist ketanserin further supports the relevance of these findings. 5 It should also be noted that activation of 5-HT 2C receptors attenuates the head-twitch behavior induced by psychedelics.…”
Section: ■ Modeling Psychosis In Animalsmentioning
confidence: 73%
“…QSAR analyses have been developed to predict hepatotoxicity [62]. Similarly, FDA-approved drugs have been searched to identify previously unknown drug target interactions that were confirmed by in vivo testing [63]. These in silico analyses may help identify key chemical ligands associated with SJS.…”
Section: Results: Disproportionate Molecular Targets Identified By Damentioning
confidence: 99%
“…For example, from the data viewpoint, Dudley et al [148] suggested classification into drug-based and disease-based methods. The first group of methods uses some notion of similarity between drugs (e.g., chemical similarity [149], similarity between gene expressions induced by drug actions [74], or drug-side effect similarity [150]) to group drugs and infer a novel drug candidate for repurposing from the group that can perform the same action as other drugs in the group. The second group of methods uses similarities between diseases (e.g., phenotype similarity [151], or similarity between disease symptoms [152]) to group diseases and to infer a novel drug for repurposing by expanding known associations between the drug and some members of the group to the rest of the group.…”
Section: Computational Methods For Drug Repurposing and Personalised mentioning
confidence: 99%