Zhou Meng-Nan, Chen Xiang-Yang, Chen Xiao-He, Su Cong-Ping, Li Lin, Jiang Yan-Yan, Zhang Wei, Guo Shu-Zhen, Liu Bin
School of Chinese Materia Medica, Beijing University of Chinese Medicine Beijing 102488, China.
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine Beijing 100029, China.
Zhongguo Zhong Yao Za Zhi. 2021 May;46(9):2363-2369. doi: 10.19540/j.cnki.cjcmm.20210222.201.
Chinese traditional medicine compound is the main form of Chinese medicine clinical application. The elucidation of the effective components of traditional Chinese medicine is one of the key scientific issues to promote the modernization of traditional Chinese medicine. At present, there are many research ideas on the effective components of traditional Chinese medicine compounds. By analyzing the current status and existing problems of existing research ideas, the author proposes a "double reduction network pharmacology"(2 R network pharmacology) research method based on "prediction of dominant components-potential target selection". Chemical components with good properties were selected by ADMET property prediction technology, and compared with the blood components and target organ components to determine the dominant components with potential therapeutic effect, that is "reducing constituents"; the potential core regulatory pathway of traditional Chinese medicine compound was enriched by RNA-Seq technology combined with network database, and then the target of traditional Chinese medicine compound was mined based on the signal pathway, that is "reducing targets". To improve the efficiency and accuracy of effective component screening, the network relationship of "component target" was established by the related technology of network pharmacology. The purpose of this study is to provide practical research ideas and methods for clarifying the effective components of traditional Chinese medicine, revealing the law of compatibility of traditional Chinese medicine and clarifying the target of drug action.
中药复方是中医临床应用的主要形式。阐明中药有效成分是推动中医药现代化的关键科学问题之一。目前,关于中药复方有效成分的研究思路众多。通过分析现有研究思路的现状及存在问题,作者提出一种基于“优势成分预测-潜在靶点筛选”的“双降网络药理学”(2R网络药理学)研究方法。利用ADMET性质预测技术筛选出性质优良的化学成分,并与血液成分及靶器官成分进行比较,确定具有潜在治疗作用的优势成分,即“降成分”;通过RNA-Seq技术结合网络数据库富集中药复方潜在的核心调控通路,然后基于信号通路挖掘中药复方的靶点,即“降靶点”。利用网络药理学相关技术建立“成分-靶点”网络关系,以提高有效成分筛选的效率和准确性。本研究旨在为阐明中药有效成分、揭示中药配伍规律及明确药物作用靶点提供切实可行的研究思路和方法。