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Network pharmacology combined with metabolomics to study the mechanism of Shenyan Kangfu Tablets in the treatment of diabetic nephropathy

中医药 代谢组学 药丸 机制(生物学) 医学 糖尿病肾病 药理学 药方 传统医学 糖尿病 药品 计算生物学 生物信息学 系统药理学 生物 内分泌学 替代医学 病理 哲学 认识论
作者
Xiaoli Wang,Qiaoyu He,Qian Chen,Beibei Xue,Jia Wang,Tao Wang,Hong Liu,Xiaopeng Chen
出处
期刊:Journal of Ethnopharmacology [Elsevier]
卷期号:270: 113817-113817 被引量:21
标识
DOI:10.1016/j.jep.2021.113817
摘要

Shenyan Kangfu Tablets (SYKFT) is a traditional prescription evolved from Shenqi Pills. It has been included in the Synopsis of the Golden Chamber for more than 2000 years. SYKFT was listed as a national Chinese medicine protected class by the China Food and Drug Administration. Diabetic nephropathy (DN) is one of the serious microvascular diseases caused by diabetes and is also one of the important factors leading to the death of patients. The pathogenesis of DN is diverse and complex, and there is no particularly effective drug treatment. There is clinical evidence that SYKFT has a good therapeutic effect on DN with no obvious adverse effects, but the mechanism of treatment is not clear. In this study, network pharmacology was combined with metabolomics technology to explore the mechanism of SYKFT in the treatment of DN. First, the research team conducted a qualitative study of the chemical components contained in SYKFT, and carried out network pharmacology to search for potential targets based on the characterized chemical components. Second, we analysed the metabolic profile of db/db mouse urine based on UHPLC-QTOF-MS technology, and biomarkers were identified by multivariate statistical analysis. Then, we performed further pathway enrichment analysis. Finally, the results of metabolomics and network pharmacology were conjointly analysed. Seventy-five chemical components of SYKFT were identified. According to the TCMSP database, the corresponding targets of the qualitatively identified components were searched, and a total of 36 potentially active components and 160 targets related to DN were obtained. A total of 38 biomarkers were found in metabolomics based on UHPLC-QTOF-MS technology. Biosynthesis of unsaturated fatty acids and starch and sucrose metabolism are the most related pathways, the former of which has been rarely reported concerning DN. Finally, the results of the joint analysis show that two targets, hexokinase 2 (HK2) and maltase glucoamylase (MGAM), are the overlapping targets. It means they are not only the related targets of pathways involved in potential biomarkers in metabolomics but also the intersection targets of diseases and drugs identified by network pharmacology. The study reveals that the potential mechanism of SYKFT is most related to insulin resistance (IR) in the treatment of DN. It also proves that network pharmacology combined with metabolomics to find the mechanisms by which herbs treat complex diseases is a feasible tool.
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