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基于网络药理学和指纹图谱对黄芪Q-标志物的预测

[Prediction of Q-markers of Astragali Radix based on network pharmacology and fingerprint].

作者信息

Zhang Shu-Juan, Zhang Yu-Gui, Li Dong-Hui, Wu Hong-Wei, Niu Jiang-Tao, Si Xin-Lei, Li Yue-Feng

机构信息

Gansu University of Chinese Medicine Lanzhou 730000,China Key Laboratory of Standard and Quality Research of Chinese Medicine of Gansu Province Lanzhou 730000,China.

出版信息

Zhongguo Zhong Yao Za Zhi. 2021 Jun;46(11):2691-2698. doi: 10.19540/j.cnki.cjcmm.20200925.201.

Abstract

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.

摘要

黄芪是最常用的药材之一。近年来,其栽培品种和各种掺伪品充斥市场,导致其质量参差不齐,质量控制方法的开发成为研究热点。因此,明确黄芪的质量标志物对其综合评价具有重要意义。本研究采用高效液相色谱法建立了15批黄芪的指纹图谱,并通过偏最小二乘法判别分析筛选出引起组间差异的主要成分。在文献综述和网络药理学分析的基础上,从SwissTargetPrediction、PubChem Compound等数据库中获取活性成分的作用靶点和通路,然后用Cytoscape 3.7.1构建“成分-靶点-通路”网络,预测潜在的质量标志物。在所建立的指纹图谱中鉴定出28个共有峰,选择3个差异成分作为黄芪潜在的质量标志物,分别为黄芪甲苷Ⅳ、毛蕊异黄酮葡萄糖苷和芒柄花苷。所提出的基于黄芪高效液相色谱指纹图谱的方法简便可行,有助于提高其质量控制水平。

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