title: Investigation of the therapeutic effectiveness of active components in Sini decoction by a comprehensive GC/LC-MS based metabolomics and network pharmacology approaches.
abstract: As a classical formula, Sini decoction (SND) has been fully proved to be clinically effective in treating doxorubicin (DOX)-induced cardiomyopathy. Current chemomics and pharmacology proved that the total alkaloids (TA), total gingerols (TG), total flavones and total saponins (TFS) are the major active ingredients of Aconitum carmichaelii, Zingiber officinale and Glycyrrhiza uralensis in SND respectively. Our animal experiments in this study demonstrated that the above active ingredients (TAGFS) were more effective than formulas formed by any one or two of the three individual components and nearly the same as SND. However, very little is known about the action mechanisms of TAGFS. Thus, this study aimed to use for the first time the combination of GC/LC-MS based metabolomics and network pharmacology for solving this problem. By metabolomics, it was found that TAGFS worked by regulating six primary pathways. Then, network pharmacology was applied to search for specific targets. 17 potential cardiovascular related targets were found through molecular docking, 11 of which were identified by references, which demonstrated the therapeutic effectiveness of TAGFS using network pharmacology. Among these targets, four targets, including phosphoinositide 3-kinase gamma, insulin receptor, ornithine aminotransferase and glucokinase, were involved in the TAGFS regulated pathways. Moreover, phosphoinositide 3-kinase gamma, insulin receptor and glucokinase were proved to be targets of active components in SND. In addition, our data indicated TA as the principal ingredient in the SND formula, whereas TG and TFS served as adjuvant ingredients. We therefore suggest that dissecting the mode of action of clinically effective formulae with the combination use of metabolomics and network pharmacology may be a good strategy.
authors.affiliation: School of Pharmacy, Second Military Medical University, 325 Guohe Road, Shanghai, 200433, China. yfchai@smmu.edu.cn zzyzyfzhu@163.com.
authors.forename: Si
authors.initials: S
authors.lastname: Chen
authors.forename: Si
authors.initials: S
authors.lastname: Wu
authors.forename: Wuhong
authors.initials: W
authors.lastname: Li
authors.forename: Xiaofei
authors.initials: X
authors.lastname: Chen
authors.forename: Xin
authors.initials: X
authors.lastname: Dong
authors.forename: Guangguo
authors.initials: G
authors.lastname: Tan
authors.forename: Hai
authors.initials: H
authors.lastname: Zhang
authors.forename: Zhanying
authors.initials: Z
authors.lastname: Hong
authors.forename: Zhenyu
authors.initials: Z
authors.lastname: Zhu
authors.forename: Yifeng
authors.initials: Y
authors.lastname: Chai
mesh_terms: D031841:Aconitum / Q000737:chemistry; D000818:Animals; D015415:Biomarkers / Q000097:blood; D009202:Cardiomyopathies / Q000139:chemically induced / Q000188:drug therapy / Q000378:metabolism; D002851:Chromatography, High Pressure Liquid; D004195:Disease Models, Animal; D004317:Doxorubicin / Q000009:adverse effects; D004365:Drugs, Chinese Herbal / Q000494:pharmacology*; D008401:Gas Chromatography-Mass Spectrometry; D020939:Zingiber officinale / Q000737:chemistry; D029882:Glycyrrhiza uralensis / Q000737:chemistry; D053858:Metabolic Networks and Pathways / Q000187:drug effects*; D055432:Metabolomics; D051379:Mice; D062105:Molecular Docking Simulation; D015999:Multivariate Analysis; D019869:Phosphatidylinositol 3-Kinases / Q000378:metabolism; D010936:Plant Extracts / Q000494:pharmacology; D011487:Protein Conformation
chemical_list: D015415:Biomarkers; D004365:Drugs, Chinese Herbal; D010936:Plant Extracts; C478756:sini tang; D004317:Doxorubicin; D019869:Phosphatidylinositol 3-Kinases