半夏陈皮治疗小儿痰邪积肺证咳嗽变异性哮喘的网络药理学研究

Bin Xin , Tianyi Liu , Yue Wu , Qingyang Hu , Xue Dong , Huanhuan Wang , Zhong Li
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摘要

目的以网络药理学和分子对接技术为基础,探讨半夏陈皮治疗咳嗽变异性哮喘痰邪积肺综合征的分子机制。方法采用TCMSP数据库对板夏陈皮的有效成分及作用靶点进行筛选。使用GeneCards、OMIM和PharmGKB数据库获得咳嗽变异性哮喘的靶点。利用Cytoscape 3.9.1软件构建“对联药物活性成分靶标”网络,根据度值筛选关键成分。蛋白质-蛋白质相互作用数据来自STRING数据库,核心靶标通过Cytoscape插件cytoNCA进行筛选。核心靶标在David数据库中进行GO和KEGG途径富集分析。分子对接技术用于验证关键成分与核心靶标之间的结合能。结果板夏陈皮中有16个有效成分和118个潜在靶点,2429个咳嗽变异性哮喘靶点,72个交叉靶点。板夏陈皮治疗咳嗽变异性哮喘的主要成分为:诺比林、黄芩苷、柚皮素、豆甾醇、β-谷甾醇和针叶树素。板夏陈皮治疗CVA的核心靶点是FOS、MMP9、AKT1、CASP3、TP53、JUN和VEGFA。分子对接结果表明,板夏陈皮治疗CVA的关键成分和核心靶点具有良好的结合亲和力。结论活性成分可能与MMP9、AKT1、VEGFR和FOS作用,减少嗜酸性粒细胞和中性粒细胞的积聚,化痰,减轻气道炎症,降低气道阻力和高反应性,用于治疗CVA。本研究为临床用药及后续研究提供了参考。
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Network pharmacological study of Banxia-Chenpi in the treatment of cough variant asthma in children with phlegm evil accumulation lung syndrome

Objective

To explore the molecular mechanism of Banxia -Chenpi in the treatment of cough variant asthma with phlegm evil accumulation lung syndrome based on network pharmacology and molecular docking technology.

Methods

TCMSP database was used to screen the active ingredients and targets of Banxia-Chenpi. GeneCards, OMIM and PharmGKB databases were used to obtain the targets of cough variant asthma. Cytoscape 3.9.1 software was used to construct the “couplet medicines-active ingredients-targets” network and screen key ingredients according to the degree value. The protein–protein interaction data were obtained from the STRING database and core targets were screened by Cytoscape plugin cytoNCA. The core targets conduct GO and KEGG pathway enrichment analyses in the David database. Molecular docking technology was used to verify the binding energy between key ingredients and core targets.

Results

There were 16 active ingredients and potential 118 targets in Banxia-Chenpi,2429 cough variant asthma targets, and 72 intersection targets. The key ingredients of the Banxia-Chenpi in treating cough variant asthma were nobiletin, baicalein, naringenin, stigmasterol, beta-sitosterol and coniferin. The core targets of the Banxia-Chenpi for CVA treatment were FOS, MMP9, AKT1, CASP3, TP53, JUN and VEGFA. The molecular docking results indicated key ingredients and core targets of the Banxia-Chenpi in CVA treatment had a good binding affinity.

Conclusion

Active ingredients maybe act on MMP9, AKT1, VEGFR and FOS to reduce eosinophils and neutrophils accumulation, dissolve phlegm, alleviate airway inflammation, and reduce airway resistance and hyperresponsiveness for treating CVA. This study provides a reference for clinical medication and subsequent research.

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