Predicting new molecular targets for known drugs.
Predicting new molecular targets for known drugs.
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尽管药物是有选择性的，但至少有一些药物能与几个生理靶点结合，从而解释了副作用和疗效。由于存在许多药物-靶标组合，因此通过计算探索可能的相互作用将是有用的。在这里，我们比较了3，665种FDA批准和研究药物与数百种靶点，通过其配体定义每个靶点。药物和配体之间的化学相似性预测了数千种意想不到的关联。对30种药物进行了实验研究，包括转运蛋白抑制剂百忧解（Prozac）对β_1受体的拮抗作用，离子通道药物Vadilex对5-HT转运蛋白的抑制作用，以及酶抑制剂Rescriptor对组胺H_4受体的拮抗作用。总体而言，确认了23种新的药物-靶点关联，其中5种是有效的（< 100 nM）。在基因敲除小鼠中证实了药物DMT对肾上腺素能受体的生理相关性。化学相似性方法是系统的和全面的，并且可能提示许多药物的副作用和新适应症。
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 β1 receptor by the transporter inhibitor Prozac, the inhibition of the 5-HT transporter by the ion channel drug Vadilex, and antagonism of the histamine H4 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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DOI：
10.1126/science.1166127
发表时间：
2009-02-13
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Fontanilla D;Johannessen M;Hajipour AR;Cozzi NV;Jackson MB;Ruoho AE
通讯作者：
Ruoho AE
影响因子：
7.6
作者：
Jensen, Niels H.;Rodriguiz, Ramona M.;Roth, Bryan L.
通讯作者：
Roth, Bryan L.
影响因子：
6.5
作者：
Dijkstra, Dorothea;Stark, Holger;Gutzmer, Ralf
通讯作者：
Gutzmer, Ralf
影响因子：
1.6
作者：
Marona-Lewicka, Danuta;Nichols, David E.
通讯作者：
Nichols, David E.
影响因子：
56.9
作者：
Campillos, Monica;Kuhn, Michael;Bork, Peer
通讯作者：
Bork, Peer