Drug Target Identification Using Side-Effect Similarity

by: Monica Campillos, Michael Kuhn, Anne-Claude Gavin, Lars J Jensen, Peer Bork

Science, Vol. 321, No. 5886. (11 July 2008), pp. 263-266.

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Abstract

Targets for drugs have so far been predicted on the basis of molecular or cellular features, for example, by exploiting similarity in chemical structure or in activity across cell lines. We used phenotypic side-effect similarities to infer whether two drugs share a target. Applied to 746 marketed drugs, a network of 1018 side effect-driven drug-drug relations became apparent, 261 of which are formed by chemically dissimilar drugs from different therapeutic indications. We experimentally tested 20 of these unexpected drug-drug relations and validated 13 implied drug-target relations by in vitro binding assays, of which 11 reveal inhibition constants equal to less than 10 micromolar. Nine of these were tested and confirmed in cell assays, documenting the feasibility of using phenotypic information to infer molecular interactions and hinting at new uses of marketed drugs. 10.1126/science.1158140

@article{citeulike:2986542, abstract = {Targets for drugs have so far been predicted on the basis of molecular or cellular features, for example, by exploiting similarity in chemical structure or in activity across cell lines. We used phenotypic side-effect similarities to infer whether two drugs share a target. Applied to 746 marketed drugs, a network of 1018 side effect-driven drug-drug relations became apparent, 261 of which are formed by chemically dissimilar drugs from different therapeutic indications. We experimentally tested 20 of these unexpected drug-drug relations and validated 13 implied drug-target relations by in vitro binding assays, of which 11 reveal inhibition constants equal to less than 10 micromolar. Nine of these were tested and confirmed in cell assays, documenting the feasibility of using phenotypic information to infer molecular interactions and hinting at new uses of marketed drugs. 10.1126/science.1158140}, author = {Campillos, Monica and Kuhn, Michael and Gavin, Anne-Claude and Jensen, Lars J. and Bork, Peer }, citeulike-article-id = {2986542}, doi = {10.1126/science.1158140}, journal = {Science}, keywords = {drug, emot, target}, month = {July}, number = {5886}, pages = {263--266}, posted-at = {2008-07-18 22:52:11}, priority = {2}, title = {Drug Target Identification Using Side-Effect Similarity}, url = {http://dx.doi.org/10.1126/science.1158140}, volume = {321}, year = {2008} }

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TY - JOUR ID - citeulike:2986542 L3 - citeulike-article-id:2986542 TI - Drug Target Identification Using Side-Effect Similarity JF - Science VL - 321 IS - 5886 SP - 263 EP - 266 N2 - Targets for drugs have so far been predicted on the basis of molecular or cellular features, for example, by exploiting similarity in chemical structure or in activity across cell lines. We used phenotypic side-effect similarities to infer whether two drugs share a target. Applied to 746 marketed drugs, a network of 1018 side effect-driven drug-drug relations became apparent, 261 of which are formed by chemically dissimilar drugs from different therapeutic indications. We experimentally tested 20 of these unexpected drug-drug relations and validated 13 implied drug-target relations by in vitro binding assays, of which 11 reveal inhibition constants equal to less than 10 micromolar. Nine of these were tested and confirmed in cell assays, documenting the feasibility of using phenotypic information to infer molecular interactions and hinting at new uses of marketed drugs. 10.1126/science.1158140 KW - drug KW - emot KW - target AU - Campillos, Monica AU - Kuhn, Michael AU - Gavin, Anne-Claude AU - Jensen, Lars AU - Bork, Peer PY - 2008/07/11/ UR - http://dx.doi.org/10.1126/science.1158140 ER -

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