目的 利用网络药理学方法、分子对接技术及体外细胞实验研究黄龙合剂基于IL-4/信号转导和转录激活因子6（STAT6）信号通路治疗小儿咳嗽变异性哮喘（CVA）的作用机制。 方法 通过TCMSP、HERB数据库及文献检索获得黄龙合剂组方中药的活性成分及作用靶点，检索GeneCards数据库、OMIM数据库、DrugBank数据库、PharmGKB数据库中CVA相关靶点。对药物-疾病靶点取交集，使用STRING数据库构建交集靶点PPI网络，采用Cytoscape 3.9.1进行网络拓扑分析，筛选核心靶点，并构建“疾病-药物-成分-靶点”网络，筛选核心成分。使用Metascape数据库对交集靶点进行GO功能和KEGG通路富集分析。使用PDB蛋白数据库、PubChem、AutoDock及R语言对核心靶点及核心成分进行分子对接验证。培养大鼠原代气道平滑肌细胞，采用Western blot检测细胞质和细胞核中p-STAT6表达。 结果 得到黄龙合剂治疗CVA的活性成分122个，核心成分包括槲皮素、山柰酚、木犀草素等，核心靶点有JUN、ESR1、TP53、MYC、HIF1α等。GO功能富集分析涉及对外来刺激的反应、对氧气水平的反应、蛋白质磷酸化的正向调控、细胞应激反应的调节等生物过程。KEGG通路富集分析显示，黄龙合剂治疗CVA靶点主要富集于AGE-RAGE信号通路、PI3K-Akt信号通路、TNF信号通路、JAK-STAT信号通路等。分子对接结果显示，核心靶点及药物核心成分有较好的结合活性。细胞实验表明，黄龙合剂可抑制IL-4介导的p-STAT6进入细胞核。 结论 预测了黄龙合剂治疗CVA的有效成分及靶点，其治疗小儿CVA的作用机制可能与抑制IL-4/STAT6信号通路有关。 Objective To study the the mechanism of action of Huanglong Mixture in the treatment of cough variant asthma (CVA) in children based on the IL-4/signal transduction and activator of transcription 6 (STAT6) signaling pathway using network pharmacology methods, molecular docking techniques, and in vitro cell experiments. Methods The components and targets of various TCM components in Huanglong Mixture were searched in TCMSP database, HERB database and literature, and the disease targets of CVA were found in Gene Cards database, OMIM database, DrugBank database and PharmGkb database. The STRING database was used to construct the protein-protein interaction network, and Cytoscape 3.9.1 was used for topology analysis to screen out the core targets. The disease-drug-component-target network was constructed to screen out the core components. The KEGG enrichment analysis and GO enrichment analysis of the intersection targets were performed using Metascape software. PDB protein database, PubChem, Autodock and R language were used for molecular docking verification of core targets and core drug components. Finally, rat primary airway smooth muscle cells were cultured, modeled with interleukin-4 (IL-4), and p-STAT6 expression in the cytoplasm and nucleus was detected by Western blot. Results A total of 122 effective components were obtained, including quercetin, kaempferol, luteolin and so on. The core targets included JUN, ESR1, TP53, MYC, HIF1, etc. GO enrichment analysis involved biological processes such as response to external stimuli, response to oxygen levels, positive regulation of protein phosphorylation, and regulation of cellular stress response. KEGG enrichment analysis showed that the main pathways of Huanglong Mixture in treating CVA included advanced glycation end product-glycation end product receptor (AGE-RAGE) signaling pathway, phosphatidylinositol-3-kinase-protein kinase B (PI3K-Akt) signaling pathway, tumor necrosis factor (TNF) signaling pathway, Janus kinase/signal transduction activation factor (JAK-STAT) signaling pathway. Molecular docking found that the core targets and core drug components had good combination. Cell experiments also confirmed that Huanglong Mixture could inhibit p-STAT6 entering the nucleus. Conclusions The effective components and targets of Huanglong Mixture in the treatment of CVA are successfully predicted. The mechanism of Huanglong Mixture in the treatment of children with CVA may be related to the inhibition of IL-4/STAT6 signaling pathway.
Study on mechanism and Huanglong Mixture in the treatment of children with cough variant asthma and experimental verification based on network pharmacologic analysis
Objective To study the the mechanism of action of Huanglong Mixture in the treatment of cough variant asthma (CVA) in children based on the IL-4/signal transduction and activator of transcription 6 (STAT6) signaling pathway using network pharmacology methods, molecular docking techniques, and in vitro cell experiments. Methods The components and targets of various TCM components in Huanglong Mixture were searched in TCMSP database, HERB database and literature, and the disease targets of CVA were found in Gene Cards database, OMIM database, DrugBank database and PharmGkb database. The STRING database was used to construct the protein-protein interaction network, and Cytoscape 3.9.1 was used for topology analysis to screen out the core targets. The disease-drug-component-target network was constructed to screen out the core components. The KEGG enrichment analysis and GO enrichment analysis of the intersection targets were performed using Metascape software. PDB protein database, PubChem, Autodock and R language were used for molecular docking verification of core targets and core drug components. Finally, rat primary airway smooth muscle cells were cultured, modeled with interleukin-4 (IL-4), and p-STAT6 expression in the cytoplasm and nucleus was detected by Western blot. Results A total of 122 effective components were obtained, including quercetin, kaempferol, luteolin and so on. The core targets included JUN, ESR1, TP53, MYC, HIF1, etc. GO enrichment analysis involved biological processes such as response to external stimuli, response to oxygen levels, positive regulation of protein phosphorylation, and regulation of cellular stress response. KEGG enrichment analysis showed that the main pathways of Huanglong Mixture in treating CVA included advanced glycation end product-glycation end product receptor (AGE-RAGE) signaling pathway, phosphatidylinositol-3-kinase-protein kinase B (PI3K-Akt) signaling pathway, tumor necrosis factor (TNF) signaling pathway, Janus kinase/signal transduction activation factor (JAK-STAT) signaling pathway. Molecular docking found that the core targets and core drug components had good combination. Cell experiments also confirmed that Huanglong Mixture could inhibit p-STAT6 entering the nucleus. Conclusions The effective components and targets of Huanglong Mixture in the treatment of CVA are successfully predicted. The mechanism of Huanglong Mixture in the treatment of children with CVA may be related to the inhibition of IL-4/STAT6 signaling pathway.
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