OBJECTIVE Combining network pharmacology methods and experimental verification to explore the target and potential mechanism of Huanglong Antitussive Granule in treating asthma.
METHODS With the help of TCMSP, TCMID, Swiss Target Prediction and other databases, the chemical components and targets of Huanglong Antitussive Granule are searched. Through GeneCards, OMIM, Disgenet, Drugbank database to screen out the disease targets of asthma. Use Cytoscape software to construct a network diagram of "drug-component-target-disease" and the interaction relationship between potential targets, and predict the mechanism of action through enrichment analysis. Mice model of asthma was constructed, and the results of network pharmacology enrichment analysis were verified by pathological staining, Elisa detection, q-PCR and Western Blot.
RESULTS A total of 175 active ingredients, 1 026 drug targets, 900 disease targets for asthma and 153 common drug-disease targets were obtained in Huanglong Antitussive Granule. A total of 1 967 entries were obtained by GO enrichment analysis, and KEGG pathway enrichment screened out a total of 84 signaling pathways including TNF signaling pathways. Animal experiments show that Huanglong Antitussive Granule can effectively improve airway inflammation in asthmatic mice, and inhibit the MAPK and NF-κB signaling pathways by affecting the TNF signaling pathway.
CONCLUSION This study initially revealed the mechanism of action of Huanglong Antitussive Granule in treating asthma, providing a reference for clinical medication and follow-up research.
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