Muroi Makoto, Osada Hiroyuki
Chemical Biology Research Group, RIKEN CSRS, Wako, Saitama, Japan.
J Antibiot (Tokyo). 2021 Oct;74(10):639-650. doi: 10.1038/s41429-021-00437-y. Epub 2021 Jul 20.
The Warburg effect, a widely known characteristic of cancer cells, refers to the utilization of glycolysis under aerobic conditions for extended periods of time. Recent studies have revealed that cancer cells are capable of reprogramming their metabolic pathways to meet vigorous metabolic demands. New anticancer drugs that target the complicated metabolic systems of cancer cells are being developed. Identifying the potential targets of novel compounds that affect cancer metabolism may enable the discovery of new therapeutic targets for cancer treatment, and hasten the development of anticancer drugs. Historically, various drug screening techniques such as the analysis of a compound's antiproliferative effect on cancer cells and proteomic methods, that enable target identification have been used to obtain many useful drugs from natural products. Here, we review proteomics-based target identification methods applicable to natural products that affect cancer metabolism.
瓦伯格效应是癌细胞广为人知的一个特征,指的是在有氧条件下长时间利用糖酵解。最近的研究表明,癌细胞能够重新编程其代谢途径以满足旺盛的代谢需求。针对癌细胞复杂代谢系统的新型抗癌药物正在研发中。识别影响癌症代谢的新型化合物的潜在靶点,可能有助于发现癌症治疗的新靶点,并加速抗癌药物的研发。从历史上看,各种药物筛选技术,如分析化合物对癌细胞的抗增殖作用以及能实现靶点识别的蛋白质组学方法,已被用于从天然产物中获取许多有用的药物。在此,我们综述适用于影响癌症代谢的天然产物的基于蛋白质组学的靶点识别方法。