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中国精品科技期刊2020
罗慧英,吴步梅,马天玥,等. 基于网络药理学与分子对接探讨兰州软儿梨止咳化痰作用机制[J]. 华体会体育,2023,44(23):11−20. doi: 10.13386/j.issn1002-0306.2023010103.
引用本文: 罗慧英,吴步梅,马天玥,等. 基于网络药理学与分子对接探讨兰州软儿梨止咳化痰作用机制[J]. 华体会体育,2023,44(23):11−20. doi: 10.13386/j.issn1002-0306.2023010103.
LUO Huiying, WU Bumei, MA Tianyue, et al. Based on Network Pharmacology and Molecular Docking to Discuss the Mechanism of Antitussive and Expectorant Action of Ruanerli[J]. Science and Technology of Food Industry, 2023, 44(23): 11−20. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023010103.
Citation: LUO Huiying, WU Bumei, MA Tianyue, et al. Based on Network Pharmacology and Molecular Docking to Discuss the Mechanism of Antitussive and Expectorant Action of Ruanerli[J]. Science and Technology of Food Industry, 2023, 44(23): 11−20. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023010103.

基于网络药理学与分子对接探讨兰州软儿梨止咳化痰作用机制

Based on Network Pharmacology and Molecular Docking to Discuss the Mechanism of Antitussive and Expectorant Action of Ruanerli

  • 摘要: 采用网络药理学方法预测软儿梨止咳化痰作用及其机制,并采用分子对接和动物实验对预测结果予以验证。通过文献调研和TCMSP等数据库筛选得到软儿梨的成分与作用靶点,与GeneCards数据库中“咳嗽(cough)”和“痰(sputum)”相关的两组基因相映射,得到软儿梨止咳化痰作用的靶点基因。通过Metascape平台对靶点基因进行GO和KEGG富集分析;通过STRING数据平台构建靶点基因间PPI网络;利用Cytoscape插件CytoHubba筛选软儿梨止咳化痰作用Top10基因,并通过Metascape数据平台对Top10基因进行KEGG通路富集以预测软儿梨止咳化痰作用可能涉及的信号通路。通过Autodock Vina对预测所得Top10基因蛋白和软儿梨Top3活性成分进行分子对接;最后通过氨水引咳试验和酚红排泄试验对预测所得结果进行验证。经多数据库联合分析,发现软儿梨中已见报道的化学成分有51个,对应作用靶点282个,其中80个与止咳化痰作用有关,根据Degree值筛选出的Top10基因主要富集在与感染和免疫相关通路上。分子对接试验证明Top10基因与PPI网络中排名前3位的化学成分(咖啡酸、芦丁、戊醛)有较强的结合活性。动物实验证明软儿梨可以明显抑制小鼠氨水引发的咳嗽反应,降低血清中IL-6和IL-13水平,增加小鼠气管酚红的排泄量。PCR和WB检测发现,软儿梨可降低炎症相关基因IL6、IL1B、VEGFA、PTGS2、MAPK3的mRNA水平和蛋白表达,软儿梨的止咳化痰作用可能与降低炎性基因表达,减少致炎因子释放有关。

     

    Abstract: The antitussive and expectorant effects of Ruanerli and its mechanism were investigated by methods of network pharmacology. The outcomes predicted were verified by molecular docking and animal experiments. The components and targets of Ruanerli were obtained by literature investigation and TCMSP database screen. Mapping with two groups of genes related to "cough" and "sputum" from GeneCards database, the target genes of antitussive and expectorant effects of Ruanerli were obtained. GO and KEGG enrichment analysis of the target genes was performed by Metascape platform. The PPI network among the target genes was constructed through STRING data platform. Cytoscape plugin CytoHubba was used to screen the Top10 genes related to antitussive and expectorant effects of Ruanerli, and KEGG pathway enrichment was performed on the Top10 genes through Metascape data platform to predict the possible signal pathways involved in antitussive and expectorant effects of Ruanerli. Autodock Vina was used for molecular docking between the predicted Top10 gene proteins and the Top 3 active ingredients of Ruanerli. Finally, the predicted results were verified by ammonia induced cough test and phenol red excretion test. According to the analysis of multiple databases, 51 chemical components and 282 corresponding targets have been reported, eighty of them were related to the antitussive and expectorant effects of Ruanerli. The Top10 genes selected by Degree value were mainly concentrated in infection and immune-related pathways. Molecular docking test showed that the Top10 genes had strong binding activity with the Top3 chemical components (Caffeic acid, Rutin and Valeraldehyde) in PPI network. Animal experiments showed that the cough induced by ammonia was significantly inhibited when treated with Ruanerli in mice. The levels of IL-6 and IL-13 in serum were reduced and the excretion of phenol red in mice trachea was increased. PCR and WB detection showed that the mRNA levels and protein expressions of inflammatory genes IL6, IL1B, VEGFA, PTGS2 and MAPK3 were decreased, suggesting that the antitussive and expectorant effects of Ruanerli might be related to decreasing the expression of inflammatory genes and the release of inflammatory factors.

     

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