化学成分结合网络药理学和质量标记分析用于清肝达肾颗粒的质量评价。

IF 1.8 4区 化学 Q3 CHEMISTRY, ANALYTICAL Analytical Sciences Pub Date : 2024-07-24 DOI:10.1007/s44211-024-00592-w
Huanbo Cheng, Ying Liu, Mengling Xu, Ruixue Shi, Lifei Hu, Yuanming Ba, Guangzhong Wang
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引用次数: 0

摘要

清瘟解毒颗粒(QFDYGs)由多种中药组成,具有多成分、多靶点、整体调控的特点,是治疗2019年冠状病毒病(COVID-19)的有效中药方剂。进一步研究QFDYG的化学成分和药理作用,对质量评价具有重要意义。然而,由于 QFDYGs 成分复杂,目前尚无可靠、简单的分析方法用于质量评价。本研究首先对 QFDYGs 在 LPS 诱导的新西兰兔模型中的解热活性进行了评估,以验证其疗效。结果证明,QFDYGs 可用于解热,有助于预防或控制流感和肺炎的流行。随后,利用 UHPLC-ESI-QTOF-MS/MS 结合网络药理学、质量标记和指纹图谱分析,确定了质量控制条件。通过 UHPLC-ESI-QTOF-MS/MS 对化学成分进行分析,确定了其中的 79 种成分,如山豆根碱、芒果苷、芍药苷等。然后,基于 45 种候选成分(CCs),结合流感和肺炎疾病,采用网络药理学策略筛选出潜在的活性成分。根据药物-CCs-基因-疾病(D-CCs-G-D)网络,筛选出黄芩苷、黄檀香醇、黄芩苷、芍药苷、柴胡皂苷 A、甘草酸和橙皮甙作为质量标志物。通过优化提取方法、色谱条件和方法验证,建立了 7 种质量标志物的含量测定方法。最后,利用这 7 个质量标记结合指纹图谱和主成分分析法(PCA)对 15 个批次的 QFDYGs 进行了质量评价。分析结果表明,黄芩苷、芍药苷、甘草酸和橙皮苷是含量高且稳定的质量标记。15 个批次的 QFDYGs 具有整体一致性和单个成分差异的特点。我们的质量评价研究将为 QFDYGs 的进一步开发和研究提供参考。
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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Chemical composition combined with network pharmacology and quality markers analysis for the quality evaluation of Qing-fei-da-yuan granules

Qing-fei-da-yuan granules (QFDYGs) had been proved to be an effective TCM prescription for treating coronavirus disease 2019 (COVID-19), which are composed of a variety of TCMs, and characterized by multiple components, multiple targets and overall regulation. It is meaningful to further study the chemical composition and pharmacology of QFDYGs for quality evaluation. However, due to the complexity of the components of QFDYGs, there are no reliable and simple analytical methods for current quality evaluation. In this work, antipyretic activity assessment of QFDYGs in the LPS-induced New Zealand rabbit model was carried out to verify the efficacy firstly. It was proved that QFDYGs can be used to relieve fever to help preventing or controlling the prevalence of influenza and pneumonia. Subsequently, UHPLC–ESI-QTOF-MS/MS combined with network pharmacology, quality markers and fingerprint analysis were used to establish the quality control condition. The chemical compositions were analyzed by UHPLC–ESI-QTOF-MS/MS, and 79 of them were identified, such as arecoline, mangiferin, paeoniflorin, etc. Then, the network pharmacology strategy based on 45 candidate components (CCs) in conjunction with influenza and pneumonia diseases was employed to screen the potential active ingredients. According to the drug-CCs-genes-diseases (D-CCs-G-D) networks, baicalein, honokiol, baicalin, paeoniflorin, saikosaponin A, glycyrrhizic acid and hesperidin were selected as quality markers. And a method for content determination of the 7 quality markers was established by optimizing extraction methods, chromatographic conditions and methodological verification. Finally, the quality of 15 batches of QFDYGs was evaluated by using the 7 quality markers combined with fingerprints and principal component analysis (PCA). The analyzed results showed that baicalin, paeoniflorin, glycyrrhizic acid and hesperidin were the high content and stable quality markers. QFDYGs were characterized by overall consistency and individual ingredient differences among the 15 batches. Our quality evaluation study will provide reference for the further development and research of QFDYGs.

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来源期刊
Analytical Sciences
Analytical Sciences 化学-分析化学
CiteScore
2.90
自引率
18.80%
发文量
232
审稿时长
1 months
期刊介绍: Analytical Sciences is an international journal published monthly by The Japan Society for Analytical Chemistry. The journal publishes papers on all aspects of the theory and practice of analytical sciences, including fundamental and applied, inorganic and organic, wet chemical and instrumental methods. This publication is supported in part by the Grant-in-Aid for Publication of Scientific Research Result of the Japanese Ministry of Education, Culture, Sports, Science and Technology.
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