@article{c7f900c07f9a11df928f000ea68e967b,
title = "Drug target identification using side-effect similarity",
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.",
author = "Monica Campillos and Michael Kuhn and Anne-Claude Gavin and Jensen, {Lars Juhl} and Peer Bork",
note = "Keywords: Adverse Drug Reaction Reporting Systems; Algorithms; Chemistry, Pharmaceutical; Databases, Factual; Drug Evaluation, Preclinical; Drug Labeling; Drug Therapy; Humans; Pharmaceutical Preparations; Probability; Proteins",
year = "2008",
doi = "10.1126/science.1158140",
language = "English",
volume = "321",
pages = "263--6",
journal = "Science",
issn = "0036-8075",
publisher = "American Association for the Advancement of Science",
number = "5886",
}