Identification and Multidimensional Evaluation of Quality Markers in Yupingfeng via UPLC-Q-Orbitrap-MS, Network Pharmacology, UPLC-UV Fingerprint, and UPLC-QQQ-MS

IF 1.7 4区医学 Q4 BIOCHEMICAL RESEARCH METHODS

Biomedical Chromatography Pub Date : 2026-04-02 DOI:10.1002/bmc.70435

Shu Li, Xiaoyu Jin, Huasheng Hu, Xiaodan Wang, Hui Chen, Jian Jin, Ao Xu

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引用次数: 0

Abstract

Yupingfeng (YPF), a classical traditional Chinese medicine (TCM) formula, is widely used to tonify qi and strengthen the exterior. However, research on the quality control of YPF remains limited. A single indicator is insufficient to comprehensively reflect the quality attributes of this complex TCM system. This study aims to investigate the potential quality markers (Q-markers) of YPF with multidimensional analysis. First, 28 specific components of YPF were preliminarily identified by UPLC-Q-Orbitrap-MS/MS based on ingredient specificity. Next, the targets of specific ingredients were predicted using SwissTargetPrediction and analyzed with protein–protein interaction network analysis to obtain 71 core targets. The effectiveness was prioritized through systematic ranking based on network pharmacological analysis. Then, common components shared by YPF powder, YPF preparations, and rat serum were characterized using UPLC-QQQ-MS and UPLC-UV. Finally, 10 compounds, including prim-O-glucosylcimifugin, calycosin-7-O-glucopyranoside, cimifugin, 5-O-methylvisammioside, ononin, sec-O-glucosylhamaudol, calycosin, astragaloside A, formononetin, and atractylenolide II, were identified as the Q-markers of YPF, and a rapid UPLC-QQQ-MS method was developed for their simultaneous determination. Overall, the multidimensional analysis based on the “five principles” was first applied to identify the Q-markers of YPF, thereby providing guidance for the quality control of YPF and its preparations.

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UPLC-Q-Orbitrap-MS、网络药理学、UPLC-UV指纹图谱和UPLC-QQQ-MS对玉屏风药材质量标记物的鉴定及多维评价

玉屏风（YPF）是一种经典的中药配方，被广泛用于补气和强化外表。然而，关于YPF质量控制的研究仍然有限。单一指标不足以全面反映这一复杂中医体系的质量属性。本研究旨在利用多维度分析方法，探索青稞的潜在品质标记（q -marker）。首先，基于成分特异性，采用UPLC-Q-Orbitrap-MS/MS对28种YPF特异性成分进行初步鉴定。接下来，利用SwissTargetPrediction预测特定成分的靶点，并利用蛋白-蛋白相互作用网络分析得到71个核心靶点。基于网络药理学分析，通过系统排序对疗效进行排序。然后采用UPLC-QQQ-MS和UPLC-UV对YPF散、YPF制剂和大鼠血清共有成分进行表征。最终鉴定出10个化合物为YPF的q标记物，分别为prim- o - glucocimifugin、毛蕊花素-7- o -glucopyranoside、毛蕊花素、5-O-methylvisammioside、ononin、seco - o - glucosylhamaudool、毛蕊花素、黄芪甲苷A、刺芒柄花素、白术烯内酯II。总体而言，首先运用基于“五原则”的多维度分析方法，鉴定了青霉霉的q标记，为青霉霉及其制剂的质量控制提供了指导。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Biomedical Chromatography 生物-分析化学

CiteScore

3.60

自引率

5.60%

发文量

268

审稿时长

2.3 months

期刊介绍： Biomedical Chromatography is devoted to the publication of original papers on the applications of chromatography and allied techniques in the biological and medical sciences. Research papers and review articles cover the methods and techniques relevant to the separation, identification and determination of substances in biochemistry, biotechnology, molecular biology, cell biology, clinical chemistry, pharmacology and related disciplines. These include the analysis of body fluids, cells and tissues, purification of biologically important compounds, pharmaco-kinetics and sequencing methods using HPLC, GC, HPLC-MS, TLC, paper chromatography, affinity chromatography, gel filtration, electrophoresis and related techniques.