An integrated approach to discriminate the quality markers of Traditional Chinese medicine preparation based on multi-dimensional characteristic network: Shenqi Jiangtang Granule as a case

• Published in: Journal of ethnopharmacology Vol. 278; p. 114277
• Main Authors: Zhang, Hui, Chen, Ruoyu, Xu, Cong, Zhang, Guimin, Guan, Yongxia, Feng, Qun, Yao, Jingchun, Yan, Jizhong
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 05.10.2021
• Subjects: Diabetes mellitus; Multi-dimensional characteristic network; Quality markers; Shenqi jiangtang granule; Traditional Chinese medicine; Quality markers; TCMSP; YZDP; Diabetes mellitus; Traditional Chinese medicine; DM; DN; TLC; Multi-dimensional characteristic network; HMs; UF-LC-MS; SJG; Shenqi jiangtang granule; CZP; Q-markers; TCM; UPLC-Q/TOF-MS
• ISSN: 0378-8741; 1872-7573
• DOI: 10.1016/j.jep.2021.114277

Due to the complexity of traditional Chinese medicine (TCM), the current quality evaluation of TCM are difficult to associate with clinical efficacy. Shenqi Jiangtang Granule (SJG), a classical TCM formula, is proven as a therapy for treatment of type II diabetes mellitus (DM) and complications while the substantial basis of the therapeutic effects is not clear. The present study proposed an integrated approach to discriminate the quality markers (Q-markers) based on multi-dimensional characteristic network for quality control of TCM. The multi-dimensional characteristic network was established by “Spider-web” mode, which was comprehensively integrating “compatibility-content-activity- efficiency-stability” of the candidate ingredients. The activity dimension was evaluated by the inhibitory activity of SJG on α-glucosidase and aldose reductase. The efficacy dimension was assessed through the association between the compounds and the target pathway of diabetic nephropathy (DN) based on integrated pharmacology platform. Each dimension for the feature network was quantified by multivariate statistical analysis, and regression area of the candidate compounds was constructed in the network. Finally, the candidate compounds were sorted comprehensively by the regression area. A total of 30 chemical compounds with effective hypoglycemic activity were identified as the potential Q-markers. From the data analysis, three dimensions of activity, efficacy and content performed a greater impact on the regression area of the characteristic network. Among these compounds, ginsenoside Re, ginsenoside Rd, ginsenoside Rg1, calycosin, ginsenoside Rb1, formononetin, astragaloside IV, ginsenoside Rf, ginsenoside Rc, notoginsenoside Fe, schisandrol A, gomisin D were screened out as the candidate Q-markers of SJG. The multi-dimensional characteristic network integrating compatibility, content, activity, efficiency and stability is efficient to discriminate the potential Q-markers of TCM prescription. Our results demonstrated that 12 candidate compounds from Panax Ginseng, Radix Astragali and Schisandrae Chinensis might select as Q-markers for qualitative evaluation of SJG. [Display omitted]