文献类型：期刊文献

中文题名：基于网络药理学及指纹图谱的黄芪质量标志物预测

英文题名：Prediction of Q-markers of Astragali Radix based on network pharmacology and fingerprint

作者：张淑娟[1,2];张育贵[1,2];李东辉[1,2];吴红伟[1,2];牛江涛[1,2];司昕蕾[1,2];李越峰[1,2]

第一作者：张淑娟

机构：[1]甘肃中医药大学,甘肃兰州730000;[2]甘肃省中药质量与标准研究重点实验室,甘肃兰州730000

第一机构：甘肃中医药大学

年份：2021

卷号：46

期号：11

起止页码：2691

中文期刊名：中国中药杂志

外文期刊名：China Journal of Chinese Materia Medica

收录：CSTPCD;;Scopus;北大核心:【北大核心2020】；CSCD:【CSCD2021_2022】；PubMed;

基金：国家自然科学基金项目(81960713);自然科学基金创新基地和人才计划项目(18JR3RA197);甘肃省中药质量与标准研究重点实验室开放基金项目(ZYZL18-008)。

语种：中文

中文关键词：黄芪;质量标志物;网络药理学;指纹图谱;黄芪甲苷;毛蕊异黄酮葡萄糖苷;芒柄花苷

外文关键词：Astragali Radix;quality marker(Q-marker);network pharmacology;fingerprint;astragalosideⅣ;calycosin-7-O-β-D-glucoside;ononin

摘要：黄芪为常用的大宗药材之一,其用药历史悠久,临床应用广泛。近年来,黄芪栽培变异品种及多种掺杂混淆品充斥市场,导致黄芪质量良莠不齐,故其质量控制方法一直是黄芪药材研究的热点,因此找出黄芪药材的质量标志物,对全面评价黄芪质量具有重要意义。该研究通过高效液相色谱法建立15批黄芪药材的指纹图谱,采用化学模式识别方法偏最小二乘法判别分析(PLS-DA)筛选出造成组间差异的主要标志性成分,结合文献研究及网络药理学分析,利用SwissTargetPrediction和PubChem Compound等数据库分析有效成分的对应靶点和通路并在Cytoscape 3.7.1软件中绘制出"成分-靶点-通路"图,预测出潜在的质量标志物。结果表明,建立的指纹图谱中成功指认出28个共有峰,筛选出3种差异成分可作为潜在质量标志物,依次为黄芪甲苷、毛蕊异黄酮葡萄糖苷和芒柄花苷。该研究建立的HPLC指纹图谱方法简便可行,筛选出3种可作为黄芪潜在质量标志物的化学成分,有助于黄芪药材质量评价方法的提升,为黄芪质量的全面控制提供参考,同时也为黄芪药效关联物质基础的研究及作用机制的探索奠定基础。
Astragali Radix is one of the most commonly used medicinal materials. In recent years, its cultivated varieties and a variety of adulterants have flooded the market, which makes its quality uneven, and the development of quality control methods has become a research hotspot. Therefore, figuring out the quality markers of Astragali Radix is of great significance for its comprehensive evaluation. In this study, the fingerprints of 15 batches of Astragali Radix were established by HPLC, and the main components causing intergroup differences were screened out by PLS-DA. On the basis of literature review and network pharmacology analysis, the targets and pathways of active ingredients were obtained from SwissTargetPrediction, PubChem Compound and other databases, and then the "component-target-pathway" network was constructed with Cytoscape 3.7.1 for the prediction of potential quality markers. Twenty-eight common peaks were identified in the established fingerprint, and three differential components were selected as potential quality markers for Astragali Radix, which were astragaloside Ⅳ, calycosin-7-O-β-D-glucoside and ononin. The proposed method based on HPLC fingerprint of Astragali Radix is convenient and feasible, facilitating the improvement in its quality control.