Predicting new molecular targets for known drugs

摘要

Although drugs are intended to be selective, at least some bind to several physiological targets, explaining side effects and efficacy. Because many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here we compared 3,665 US Food and Drug Administration (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 β_1 receptor by the transporter inhibitor Prozac, the inhibition of the 5-hydroxytryptamine (5-HT) transporter by the ion channel drug Vadilex, and antagonism of the histamine H_4 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, the drug N,N-dimethyltryptamine (DMT) on serotonergic receptors, was confirmed in a knockout mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs.%大多数药物都是旨在对某一个蛋白目标具有选rn择性，但它们通常也会与几个其他目标结合。rn一些“脱靶”事件会诱导产生具有不同严重程rn度的副作用，尽管这类事件中有些还可能是一rn种药物发挥药效所必需的。本期Nature报告了rn识别已知药物潜在“脱靶”效应的一个新策rn略。研究人员对3，665种经FDA批准用于研究rn工作的药物的结构进行了计算筛选，筛选所针rn对的是数百种蛋白目标，它们是按与其结合的rn配体定义的。根据这些药物与各组配体之间在rn化学上的相似性，研究人员预测出数以千计的rn“脱靶”关联，其中有些在药理化验分析中得rn到证实。这种方法也许可帮助预测和解释已知rn药物及候选药物的副作用，并且还有可能因此rn而发现以前已被批准用于人体的药物的新的临rn床应用。