Linking metabolic activity with drug sensitivity using metabolic influence networks

使用代谢影响网络将代谢活动与药物敏感性联系起来

• 批准号: 10221731
• 负责人: Sriram Chandrasekaran
• 金额: $ 36.64万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10221731
• 关键词: Address; Algorithms; Cell physiology; Cells; Cellular Metabolic Process; Complement; Computer Models; Drug Combinations; Drug Targeting; Environment; Enzyme Inhibitor Drugs; Escherichia coli; Genetic Transcription; Goals; Human Cell Line; Link; Metabolic; Metabolism; Nutrient; Organism; Pharmaceutical Preparations; Pharmacotherapy; Predisposition; Regulation; Research; Signal Transduction; System; Systems Biology; Testing; Yeasts; base; cell type; drug action; drug discovery; drug sensitivity; in vivo; novel strategies; precision medicine; programs; response; tool; uptake

Project Summary The impact of cellular metabolism on drug susceptibility has been observed in a wide range of organisms and cell types. However, how metabolism influences the activity of diverse classes of drugs has not been systematically explored. Linking metabolism and drug sensitivity has been a challenge due to both the impact of metabolism on numerous cellular processes, and the complexity of drug response. To address this, a combination of cutting-edge experimental and computational systems-biology tools will be applied to dissect the mechanisms by which cellular metabolism impacts the activity of drugs. The overall goal of my lab is to develop systems biology algorithms to reconstruct metabolic regulation and harness it for drug discovery. Here we propose to develop a new approach to link metabolism with various cellular process, called the ‘metabolic influence network’. We will use it to predict the impact of metabolic activity of a cell on drugs that inhibit diverse cellular processes. This framework will be applied to E. coli, yeast and human cell lines, allowing us to uncover conserved principles linking metabolism with potency of drugs that target cellular processes such as replication, transcription or signaling. This approach will be tested experimentally by altering cellular metabolic state and drug sensitivity with nutrient screens, enzyme inhibitors and drug combinations. Our systems approach will allow us to quantify the myriad effects of cell metabolism on drug action, including uptake, collateral interactions, and efflux. Ultimately, this research program can help precision medicine efforts by matching therapy based on cellular metabolic activity and the in vivo metabolic environment.

项目总结