成分分析

基于UPLC-LTQ Orbitrap MS和网络药理学的参麦颗粒质量标志物研究*

  • 刘亚茹 ,
  • 雷蓉 ,
  • 曹春琪 ,
  • 刘永利
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  • 1.河北医科大学, 石家庄050017;
    2.河北省药品医疗器械检验研究院 河北省中药质量评价与标准研究重点实验室, 石家庄 050227
第一作者 Tel:15630152393;E-mail:1981284811@qq.com
**雷 蓉 Tel:(0311)85212007;E-mail:honaaa@126.com;刘永利 Tel:(0311)69086006;E-mail:liuyongli2008@126.com

收稿日期: 2023-11-27

  网络出版日期: 2025-01-07

基金资助

*中国药品监管科学行动计划第二批重点项目─中药有效性安全性评价及全过程质量控制研究项目(NMPAJGKX-2023-024)

Study on quality markers of Shenmai granules based on UPLC-LTQ Orbitrap MS and network pharmacology*

  • LIU Ya-ru ,
  • LEI Rong ,
  • CAO Chun-qi ,
  • LIU Yong-li
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  • 1. Hebei Medical University, Shijiazhuang 050017, China;
    2. Hebei Key Laboratory of Traditional Chinese Medicine Quality Evaluation and Standard Research, Hebei Institute for Drug and Medical Device Control, Shijiazhuang 050227, China

Received date: 2023-11-27

  Online published: 2025-01-07

摘要

目的: 采用超高效液相色谱-离子阱静电场轨道阱质谱(UPLC-LTQ Orbitrap MS)技术和网络药理学对参麦颗粒的质量标志物(Q-Marker)进行预测分析。方法: 采用Shimadzu Shim-pack gist C18 (100 mm×2.1 mm,2 μm)色谱柱,以乙腈-0.1%甲酸水为流动相,进行梯度洗脱,正、负离子模式扫描,利用TCMSP、Swiss Target Prediction、GeneCards等数据库进行靶点预测,构建“成分-靶点”网络图,探讨参麦颗粒的Q-Marker。结果: 共鉴定出71个成分,筛选得到活性成分14个,将其作为Q-Marker候选成分进行网络药理学分析,结果表明人参皂苷Rf、人参皂苷Rg3、人参皂苷F2、甲基麦冬黄烷酮A、麦冬皂苷C、麦冬皂苷D、甲基麦冬黄酮A、麦冬黄烷酮C、甲基麦冬黄酮B、甜菜碱、蒲公英萜酮、美迪紫檀素、山药素Ⅰ可能通过作用于PI3K-Akt通路,调控蛋白磷酸化反应来调节和控制蛋白质的活力和功能,从而达到养阴生津的功效。结论: 本研究阐明了参麦颗粒的化学成分,结合网络药理学探究参麦颗粒发挥养阴生津功效的作用机制并预测参麦颗粒的Q-Marker,为参麦颗粒的药效物质基础及质量标准的完善奠定基础。

本文引用格式

刘亚茹 , 雷蓉 , 曹春琪 , 刘永利 . 基于UPLC-LTQ Orbitrap MS和网络药理学的参麦颗粒质量标志物研究*[J]. 药物分析杂志, 2024 , 44(10) : 1685 -1698 . DOI: 10.16155/j.0254-1793.2023-0759

Abstract

Objective: To predict the quality marker (Q-Marker) of Shenmai granules by ultra-performance liquid chromatography-ion trap/electrostatic field Orbitrap mass spectrometry (UPLC-LTQ Orbitrap MS) and network pharmacology. Methods: The chromatography was performed on a Shimadzu Shim-pack gist C18 column (100 mm×2.1 mm, 2 μm) with acetonitrile-0.1% formic acid water as the mobile phase with gradient elution and the mass spectrometry was scanned in positive and negative ion modes. Databases such as TCMSP, Swiss Target Prediction and GeneCards were used to predict the core targets and construct the “composition-traget” network diagram to explore the Q-Marker of Shenmai granules. Results: A total of 71 compounds were identified, and 14 active components were screened as Q-Marker candidates for network pharmacological analysis. The results of network pharmacology indicated that ginsenoside Rf, ginsenoside Rg3, ginsenoside F2, methylophiopogonanone A, ophiopogonin C, ophiopogonin D, methylophiopogonone A, ophiopogonanone C, methylophiopogonone B, betaine, taraxerone, medicarpin and batatasin I might regulate and control protein activity and function by acting on the PI3K-Akt pathway, regulating protein phosphorylation reactions, thereby achieving the effect of Yangyin Shengjin production. Conclusion: This study elucidates the chemical composition of Shenmai granules, explores the mechanism of Shenmai granules in Yangyin Shengjin and predicts the Q-Marker through network pharmacology, laying the foundation for the improvement of the pharmacological substance foundation and quality standards of Shenmai granules.

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