A mapping of drug space from the viewpoint of small molecule metabolism.
A mapping of drug space from the viewpoint of small molecule metabolism.
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从小分子代谢的角度对药物空间的映射。
DOI：
10.1371/journal.pcbi.1000474
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发表时间：
2009-08
影响因子：
4.3
通讯作者：
Babbitt PC
中科院分区：
文献类型：
--
作者：
Adams JC;Keiser MJ;Basuino L;Chambers HF;Lee DS;Wiest OG;Babbitt PC
小分子药物靶向人体和病原体中的许多核心代谢酶，通常模拟内源性配体。其作用可能是治疗性的或毒性的，但通常是意想不到的。需要对药物和代谢之间的交叉点进行大规模绘图，以更好地指导药物发现。为了绘制药物和代谢之间的交叉点，我们使用基于配体的集合签名将药物和代谢物按其相关靶标和酶进行分组，以量化其在化学空间中的相似程度。这些结果揭示了已经探索的代谢靶点的化学空间，成功的药物已经被发现，以及还有什么新的领域。为了帮助其他研究人员进行药物发现工作，我们创建了一个将药物与代谢联系起来的交互式地图在线资源。这些图谱预测了人体内246种MDDR药物类别中每一种的“效应空间”，包括可能的靶酶。该在线资源还提供了BioCyc数据库中385种模式生物和病原体的物种特异性交互式药物代谢图。药物和代谢物之间的化学相似性联系预测潜在的毒性，建议代谢途径，并揭示药物的多药理学。代谢图谱能够交互导航关于潜在代谢药物靶点的大量生物学数据和目前可用于起诉这些靶点的药物化学。因此，这项工作提供了一个大规模的方法，以配体为基础的预测药物作用的小分子代谢。所有的人类、植物和动物都使用酶来代谢食物以获得能量，建立和维持身体，并排除毒素。用于清除感染或治疗癌症的药物通常针对细菌或癌细胞中的酶，但这些药物也会干扰人体酶的正常功能。最近的研究已经将药物映射到人类和其他生物体中的酶和许多其他靶点，但尚未关注代谢。在这项研究中，我们提出了一种新的方法来预测什么酶药物可能会影响的基础上的化学相似性类药物和酶使用的天然化学物质。我们已经将该方法应用于246种已知药物类别和385种生物体（包括65种美国国立卫生研究院优先病原体）的集合，以创建代谢中潜在药物作用的地图。我们还展示了预测的连接如何用于寻找杀死病原体的新方法，并避免无意中干扰人类酶。
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. All humans, plants, and animals use enzymes to metabolize food for energy, build and maintain the body, and get rid of toxins. Drugs used to clear infections or cure cancer often target enzymes in bacteria or cancer cells, but the drugs can interfere with the proper function of human enzymes as well. Recent studies have mapped drugs to enzymes and many other targets in humans and other organisms, but have not focused on metabolism. In this study, we present a new method to predict what enzymes drugs might affect based on the chemical similarity between classes of drugs and the natural chemicals used by enzymes. We have applied the method to 246 known drug classes and a collection of 385 organisms (including 65 National Institutes of Health Priority Pathogens) to create maps of potential drug action in metabolism. We also show how the predicted connections can be used to find new ways to kill pathogens and to avoid unintentionally interfering with human enzymes.
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7.3
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Jain, Ajay N.
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Karp, Peter D.