药品
计算生物学
化学相似性
相似性(几何)
鉴定(生物学)
药物靶点
表型
副作用(计算机科学)
药理学
药物相互作用
结构相似性
化学
生物
计算机科学
生物化学
基因
人工智能
图像(数学)
植物
程序设计语言
作者
Mónica Campillos,Michael Kuhn,Anne‐Claude Gavin,Lars Juhl Jensen,Peer Bork
出处
期刊:Science
[American Association for the Advancement of Science (AAAS)]
日期:2008-07-11
卷期号:321 (5886): 263-266
被引量:1092
标识
DOI:10.1126/science.1158140
摘要
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.
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