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从小分子代谢角度对药物空间的映射。

A mapping of drug space from the viewpoint of small molecule metabolism.

作者信息

Adams James Corey, Keiser Michael J, Basuino Li, Chambers Henry F, Lee Deok-Sun, Wiest Olaf G, Babbitt Patricia C

机构信息

Graduate Program in Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, California, USA.

出版信息

PLoS Comput Biol. 2009 Aug;5(8):e1000474. doi: 10.1371/journal.pcbi.1000474. Epub 2009 Aug 21.

Abstract

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the "effect space" comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism.

摘要

小分子药物作用于人类和病原体中的许多核心代谢酶,常常模拟内源性配体。其效果可能具有治疗作用或毒性作用,但往往出乎意料。需要对药物与代谢之间的交叉点进行大规模映射,以更好地指导药物研发。为了映射药物与代谢之间的交叉点,我们利用基于配体的集合特征,根据相关靶点和酶对药物和代谢物进行了分组,这些特征用于量化它们在化学空间中的相似程度。结果揭示了针对代谢靶点所探索的化学空间、已发现成功药物的区域以及仍有待探索的新领域。为了帮助其他研究人员开展药物研发工作,我们创建了将药物与代谢相联系的交互式地图在线资源。这些地图预测了人类246种MDDR药物类别中每种药物可能的靶点酶所构成的“效应空间”。该在线资源还为BioCyc数据库集合中的385种模式生物和病原体提供了物种特异性的交互式药物代谢地图。药物与代谢物之间的化学相似性联系预测潜在毒性、提示代谢途径并揭示药物多药理学特性。这些代谢地图能够对关于潜在代谢药物靶点的海量生物学数据以及目前可用于作用这些靶点的药物化学进行交互式导航。因此,这项工作提供了一种基于配体预测小分子代谢中药物作用的大规模方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c1e/2727484/81e89c462689/pcbi.1000474.g001.jpg

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