{"title":"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。","authors":"Huanbo Cheng, Ying Liu, Mengling Xu, Ruixue Shi, Lifei Hu, Yuanming Ba, Guangzhong Wang","doi":"10.1007/s44211-024-00592-w","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p><h3>Graphical abstract</h3><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":7802,"journal":{"name":"Analytical Sciences","volume":"40 9","pages":"1593 - 1609"},"PeriodicalIF":1.8000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Chemical composition combined with network pharmacology and quality markers analysis for the quality evaluation of Qing-fei-da-yuan granules\",\"authors\":\"Huanbo Cheng, Ying Liu, Mengling Xu, Ruixue Shi, Lifei Hu, Yuanming Ba, Guangzhong Wang\",\"doi\":\"10.1007/s44211-024-00592-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p><h3>Graphical abstract</h3><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>\",\"PeriodicalId\":7802,\"journal\":{\"name\":\"Analytical Sciences\",\"volume\":\"40 9\",\"pages\":\"1593 - 1609\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical Sciences\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s44211-024-00592-w\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Sciences","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1007/s44211-024-00592-w","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
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.
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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