Network Pharmacology‐Based Approach for Investigating the Role of Xanthii Fructus in Treatment of Allergic Rhinitis

Abstract

Xanthii Fructus (XF) has been used for treatment of allergic rhinitis (AR), but its pharmacological mechanism of action remains unclear. We aimed to explore the potential mechanism of XF in treatment of AR by using a network pharmacology approach combined with in vivo verification experiments in this study. We identified 945 AR-related pathogenic genes, 11 active components in XF and 178 targets of those active components by corresponding databases. Finally, 54 targets of active components from XF in treatment of AR were identified by the Protein-protein interaction (PPI) network, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, among which Tumor Necrosis Factor (TNF), Mitogen-activated Protein Kinase 3 (MAPK3), Prostaglandin G/H Synthase 2 (PTGS2), Epidermal Growth Factor Receptor (EGFR) showed strongest interactions. The molecular docking analysis showed that moupinamide could bind to EGFR at LEU704 and LEU703, and PTGS2 at TRP387; 24-Ethylcholest-4-en-3-one was identified to bind to MAPK3 at THR347. The validation of quantitative real-time reverse transcription PCR (RT-PCR) showed that XF decreased the levels of MAPK3, PTGS2, and EGFR expression in the nasal mucosa from AR mice gavaged with an XF water decoction. Meanwhile, the levels of interleukin (IL)-4, IL-5 and IL-13were also decreased after the treatment of XF by Enzyme-linked immunosorbent assay (ELISA). Our results provide the pharmacological mechanism and possible intervention targets of XF in treatment of AR.

Network pharmacology analysis of Huangqi reveals quercetin as a therapeutic for allergic rhinitis via the RELA-regulated IFNG/IRF1 axis response

“…However, further investigation is required to fully understand the therapeutic potential of Huangqi as a natural and safe alternative for treating AR. In recent years, network pharmacology and molecular docking have emerged as powerful computational methods that aid drug discovery and accelerate the identi cation and development of new disease treatments (Liang et al, 2019, Cheng et al, 2022, Cong et al, 2023, Liu et al, 2023. By integrating multiple data sources, these methodologies provide a more comprehensive understanding of the potential therapeutic targets and active compounds of natural products ( Our research employed network pharmacology to identify potential therapeutic targets and active compounds of Huangqi for treating AR.…”