ABSTRACT
Aim To anticipate the mechanism of zuka- mu granules (ZKMG) in the treatment of bronchial asthma, and to confirm the projected outcomes through in vivo tests via using network pharmacology and molecular docking technology. Methods The database was examined for ZKMG targets, active substances, and prospective targets for bronchial asthma. The protein protein interaction network diagram (PPI) and the medication component target network were created using ZKMG and the intersection targets of bronchial asthma. The Kyoto Encyclopedia of Genes and Genomics (KEGG) and gene ontology (GO) were used for enrichment analysis, and network pharmacology findings were used for molecular docking, ovalbumin (OVA) intraperitoneal injection was used to create a bronchial asthma model, and in vivo tests were used to confirm how ZKMG affected bronchial asthma. Results There were 176 key targets for ZKMG's treatment of bronchial asthma, most of which involved biological processes like signal transduction, negative regulation of apoptotic processes, and angiogenesis. ZKMG contained 194 potentially active components, including quercetin, kaempferol, luteolin, and other important components. Via signaling pathways such TNF, vascular endothelial growth factor A (VEGFA), cancer pathway, and MAPK, they had therapeutic effects on bronchial asthma. Conclusion Key components had strong binding activity with appropriate targets, according to molecular docking data. In vivo tests showed that ZKMG could reduce p-p38, p-ERKl/2, and p-I
ABSTRACT
Objective: To explore the material basis and anti-inflammatory mechanisms of Zukamu granules (ZKMG)based on the headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GCMS) technique and network pharmacology analyses. Methods: HS-SPME-GC-MS technique was used to extract and identify the volatile components of ZKMG. Then combined with the non-volatile components obtained by literature retrieval, we constructed the main chemical composition table. The bioactive components were screened based on the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), and their targets were predicted by the Swiss Target Prediction database. Thereafter, the anti-inflammatory-related targets were screened based on the Thera- peutic Targets Datebase and DrugBank with”Anti-inflammatory”as keyword. Then, the STRING database to analyze protein-protein interaction(PPI)and the software of Cytoscape 3.6.1 was used to construct the component-target-antiinflammatory target network. Finally, enrichment of function and signaling pathways of the target genes was conducted by Gene Ontology(GO)database and the Database for Annotation, Visualization and Integrated Discovery(DAVID). Re- sults: Thirty bioactive components including thymol, kaempferol and quercetin in ZKMG were screened out. Ninety-seven targets were predicted and AKR1B1, ALOX15, ALOX5, CYP1A2, EGFR, CHRM1, NOS3, PLA2G1B, PTGS2, BCHE were key anti-inflammatory targets. Sixty-eight pathways related to anti-inflammation were obtained by KEGG enrichment analysis, mainly including arachidonic acid metabolism, MAPK signaling pathway, inflammatory mediator regulation of TRP channels, IL-17 signaling pathway and NF-κB signaling pathway. Conclusion: This study focuses on the chemical constituents of ZKMG and network pharmacology to predict the material basis and pharmacological mecha- nism of their anti-inflammatory effect, which lays a good foundation for the verification of the later biological experiments and provides certain reference basis for the research on the anti-inflammation mechanism of other compound preparations.