Construction of "2R network pharmacology" research method for effective components of traditional Chinese medicine based on "prediction of dominant components-screening of potential targets"

Abstract

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.