Chemical composition combined with network pharmacology and quality markers analysis for the quality evaluation of Qing-fei-da-yuan granules

• Published in: Analytical sciences 2024-09, Vol.40 (9), p.1593-1609
• Main Authors: Cheng, Huanbo, Liu, Ying, Xu, Mengling, Shi, Ruixue, Hu, Lifei, Ba, Yuanming, Wang, Guangzhong
• Format: Article
• Language: English
• Subjects: Analytical Chemistry; Animals; Antipyretics - analysis; Antipyretics - chemistry; Antipyretics - pharmacology; Biomarkers - analysis; Chemistry; Chemistry and Materials Science; Chromatography, High Pressure Liquid; COVID-19 Drug Treatment; Drugs, Chinese Herbal - analysis; Drugs, Chinese Herbal - chemistry; Drugs, Chinese Herbal - pharmacology; Glucosides - analysis; Glucosides - chemistry; Glucosides - pharmacology; Male; Monoterpenes - analysis; Monoterpenes - chemistry; Monoterpenes - pharmacology; Network Pharmacology; Original Paper; Quality Control; Rabbits; Tandem Mass Spectrometry - methods
• ISSN: 0910-6340; 1348-2246; 1348-2246
• DOI: 10.1007/s44211-024-00592-w

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. Graphical abstract