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首页> 外文期刊>PLoS Computational Biology >A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism
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A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism

机译:从小分子代谢的角度看药物空间的映射

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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.
机译:小分子药物靶向人类和病原体中的许多核心代谢酶,通常模仿内源性配体。这种作用可能具有治疗或毒性作用,但通常是出乎意料的。需要对药物与新陈代谢之间的交叉点进行大规模映射,以更好地指导药物发现。为了绘制药物与新陈代谢之间的交点,我们使用基于配体的集合特征对药物和代谢物的相关靶标和酶进行了分组,以建立其在化学空间中的相似程度。结果揭示了已被探索用于代谢目标的化学空间,发现成功药物的地方以及仍然存在的新领域。为了帮助其他研究人员进行药物发现,我们创建了一个在线互动地图资源,将药物与新陈代谢联系起来。这些图谱预测了“效应空间”,其中包含人类246种MDDR药物类别中每种可能的目标酶。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中的每一种提供了特定于物种的交互式药物代谢图。药物与代谢物之间的化学相似性联系可预测潜在的毒性,建议新陈代谢的途径并揭示药物的多药理学。代谢图可以交互导航有关潜在代谢药物靶标和目前可用于起诉这些靶标的药物化学的大量生物学数据。因此,这项工作为小分子代谢中基于药物的配体作用预测提供了一种大规模方法。

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