ACS Chem Biol. 2012 Jan 20;7(1):166-71. doi: 10.1021/cb200348m. Epub 2011 Dec 1.
New strategies are needed to circumvent increasing outbreaks of resistant strains of pathogens and to expand the dwindling supply of effective antimicrobials. A common impediment to drug development is the lack of an easy approach to determine the in vivo mechanism of action and efficacy of novel drug leads. Toward this end, we describe an unbiased approach to predict in vivo mechanisms of action from NMR metabolomics data. Mycobacterium smegmatis, a non-pathogenic model organism for Mycobacterium tuberculosis, was treated with 12 known drugs and 3 chemical leads identified from a cell-based assay. NMR analysis of drug-induced changes to the M. smegmatis metabolome resulted in distinct clustering patterns correlating with in vivo drug activity. The clustering of novel chemical leads relative to known drugs provides a mean to identify a protein target or predict in vivo activity.
需要新的策略来规避不断增加的耐药病原体菌株的爆发，并扩大有限的有效抗菌药物供应。药物开发的一个常见障碍是缺乏一种简单的方法来确定新型药物先导物的体内作用机制和疗效。为此，我们描述了一种从 NMR 代谢组学数据预测体内作用机制的无偏方法。耻垢分枝杆菌（Mycobacterium smegmatis）是结核分枝杆菌（Mycobacterium tuberculosis）的非致病性模式生物，用 12 种已知药物和 3 种从基于细胞的测定中鉴定出的化学先导物进行了处理。用 NMR 分析药物诱导的耻垢分枝杆菌代谢组变化，得到与体内药物活性相关的不同聚类模式。与已知药物相比，新型化学先导物的聚类为鉴定蛋白质靶标或预测体内活性提供了一种方法。
