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基于超高效液相色谱-四极杆飞行时间串联质谱、网络药理学和实验验证的综合植物化学分析,以探索[药物名称]治疗慢性支气管炎的潜在机制 。 (注:原文中“for Chronic Bronchitis”前缺少具体药物名称等关键信息,翻译只能做到此程度)

Integrated Phytochemical Analysis Based on UPLC-Q-TOF-MS/MS, Network Pharmacology, and Experiment Verification to Explore the Potential Mechanism of for Chronic Bronchitis.

作者信息

Deng Yaling, Ren Hongmin, Ye Xianwen, Xia Lanting, Liu Minmin, Liu Ying, Yang Ming, Yang Songhong, Ye Xide, Zhang Jinlian

机构信息

Pharmacy College, Jiangxi University of Traditional Chinese Medicine, Nanchang, China.

Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Traditional Chinese Medicine, Nanchang, China.

出版信息

Front Pharmacol. 2020 Sep 8;11:564131. doi: 10.3389/fphar.2020.564131. eCollection 2020.

DOI:10.3389/fphar.2020.564131
PMID:33013400
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7506058/
Abstract

BACKGROUND AND AIM

(PG) has been widely used for treating chronic bronchitis (CB). However, the material basis and underlying mechanism of action of PG against CB have not yet been elucidated.

METHODS

To analyze the ingredients in PG, ultraperformance liquid chromatography-quadrupole-time-of-flight tandem mass (UPLC-Q-TOF-MS/MS) technology was performed. Subsequently, using data mining and network pharmacology methodology, combined with Discovery Studio 2016 (DS), Cytoscape v3.7.1, and other software, active ingredients, drug-disease targets, and key pathways of PG in the treatment of CB were evaluated. Finally, the reliability of the core targets was evaluated using molecular docking technology and studies.

RESULTS

A total of 36 compounds were identified in PG. According to the basic properties of the compounds, 10 major active ingredients, including platycodin D, were obtained. Based on the data mining approach, the Traditional Chinese Medicine Systems Pharmacology Database, and the Analysis Platform (TCMSP), GeneCards, and other databases were used to obtain targets related to the active ingredients of PG and CB. Network analysis was performed on 144 overlapping gene symbols, and twenty core targets, including interleukin-6 (IL-6) and tumor necrosis factor (TNF), which indicated that the potential signaling pathway that was most relevant to the treatment of CB was the IL-17 signaling pathway.

CONCLUSION

In this study, ingredient analysis, network pharmacology analysis, and experiment verification were combined, and revealed that PG can be used to treat CB by reducing inflammation. Our findings provide novel insight into the mechanism of action of Chinese medicine. Furthermore, our data are of value for the research and development of novel drugs and the application thereof.

摘要

背景与目的

桔梗已被广泛用于治疗慢性支气管炎(CB)。然而,桔梗治疗慢性支气管炎的物质基础及潜在作用机制尚未阐明。

方法

采用超高效液相色谱-四极杆-飞行时间串联质谱(UPLC-Q-TOF-MS/MS)技术分析桔梗中的成分。随后,运用数据挖掘和网络药理学方法,结合Discovery Studio 2016(DS)、Cytoscape v3.7.1等软件,评估桔梗治疗慢性支气管炎的活性成分、药物-疾病靶点及关键通路。最后,采用分子对接技术和研究评估核心靶点的可靠性。

结果

在桔梗中总共鉴定出36种化合物。根据化合物的基本性质,获得了包括桔梗皂苷D在内的10种主要活性成分。基于数据挖掘方法,利用中药系统药理学数据库及分析平台(TCMSP)、GeneCards等数据库获取与桔梗活性成分及慢性支气管炎相关的靶点。对144个重叠基因符号进行网络分析,得到20个核心靶点,包括白细胞介素-6(IL-6)和肿瘤坏死因子(TNF),这表明与慢性支气管炎治疗最相关的潜在信号通路是IL-17信号通路。

结论

本研究将成分分析、网络药理学分析与实验验证相结合,揭示了桔梗可通过减轻炎症来治疗慢性支气管炎。我们的研究结果为中药作用机制提供了新的见解。此外,我们的数据对新药研发及其应用具有参考价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/25251bb6dafd/fphar-11-564131-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/6173a094222d/fphar-11-564131-g005.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/b5a9432db1af/fphar-11-564131-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/25251bb6dafd/fphar-11-564131-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/05b24f62d385/fphar-11-564131-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/f583f6b82304/fphar-11-564131-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/1bde4e80d7fd/fphar-11-564131-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/6173a094222d/fphar-11-564131-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/7ca3bf1c710c/fphar-11-564131-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dcd/7506058/b5a9432db1af/fphar-11-564131-g007.jpg
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