ROADMAP FOR DRUG DISCOVERY IN SMALL MOLECULE METABOLISM

小分子代谢药物发现路线图

• 批准号: 8170555
• 负责人: PATRICIA CLEMENT BABBITT
• 金额: $ 1.79万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8170555
• 关键词: Animal Model; Bacteria; Chemicals; Collection; Computer Retrieval of Information on Scientific Projects Database; Databases; Drug Delivery Systems; Enzymes; Funding; Grant; Human; Institution; Ligands; Link; Maps; Metabolic; Metabolism; Methods; Pharmaceutical Preparations; Research; Research Personnel; Resources; Route; Source; Therapeutic; Toxic effect; United States National Institutes of Health; base; drug discovery; drug metabolism; methicillin resistant Staphylococcus aureus; novel; pathogen; small molecule

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Small molecule metabolism is a tempting yet treacherous domain for drug discovery. Numerous drugs target metabolic enzymes in humans and bacteria, often mimicking their substrates, with both therapeutic and toxic effect. To provide a large-scale overview of the intersection between drugs and metabolism, we first group drugs and metabolites by their associated targets and enzymes, then create ligand-based set signatures to quantify their degree of difference in chemical space. This 'roadmap' illustrates what chemical space surrounding metabolism has been explored, where successful drugs have been found, and what novel territory remains. Using links between drug and metabolite sets, we predict the 'effect space' comprising a drug's likely metabolic targets. These links indicate potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. To aid other researchers in their drug discovery efforts, we have created an online resource of species-specific maps linking drugs to metabolism for 385 model organisms and pathogens in the BioCyc database collection. We have applied our method to select and then experimentally confirm novel drug targets in the rising pathogenic threat methicillin-resistant Staphylococcus aureus.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目及 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 中心，不一定是研究者的机构。 小分子代谢对于药物发现来说是一个诱人但危险的领域。许多药物针对人类和细菌中的代谢酶，通常模仿其底物，具有治疗作用和毒性作用。为了提供药物与代谢之间交叉点的大规模概述，我们首先按相关靶点和酶对药物和代谢物进行分组，然后创建基于配体的集合特征来量化它们在化学空间中的差异程度。这个“路线图”说明了围绕新陈代谢的化学空间已经被探索，在哪里发现了成功的药物，以及仍然存在哪些新领域。利用药物和代谢物集之间的联系，我们预测包含药物可能的代谢目标的“效应空间”。这些链接表明潜在的毒性，提示代谢途径，并揭示药物的多药理学。为了帮助其他研究人员进行药物发现工作，我们创建了一个物种特异性图谱在线资源，将药物与 BioCyc 数据库集合中 385 种模式生物和病原体的代谢联系起来。我们应用我们的方法来选择并通过实验确认新的药物靶点，以应对日益增加的致病威胁耐甲氧西林金黄色葡萄球菌。