OBJECTIVE  To explore the pharmacological mechanism of erucic acid in the treatment of influenza pneumonia by combining transcriptome and network pharmacology.

METHODS  A549 cells were infected with influenza A H1N1 virus strain to construct an influenza infection model. After the model was successfully constructed, Trizol reagent was utilized to extract total cell RNA for transcriptome sequencing, and differential expressed genes for erucic acid treatment of influenza were obtained and trend analysis was performed. Further screening of rescue genes for erucic acid intervention in influenza was performed for GO function and KEGG pathway enrichment analysis. The erucic acid targets were predicted by CTD, PharmMapper, PRED, and STP databases, and the intersection with the rescue genes was taken to obtain the common genes of erucic acid targets and rescue genes(i.e., the core genes for erucic acid intervention in influenza). The core gene protein-protein interaction(PPI) network was constructed on the STRING platform, and the key core genes for erucic acid to prevent and treat influenza were screened by Cytoscape software. Then, molecular docking and molecular dynamics simulation techniques were used to verify the binding activity of key core genes with erucic acid, and gene set enrichment analysis(GSEA) was used to analyze the overall activation level of key core gene-related pathways, and further visualization analysis was performed.

RESULTS  The RNA sequencing data quality was satisfactory, with PCA results validating sample grouping reliability. Compared with the normal group, virus groups exhibited 8431 differentially expressed genes(DEGs), comprising 3447 upregulated and 4984 downregulated genes. Compared with the virus group, the high-dose erucic acid group showed 618 upregulated and 1 246 downregulated DEGs. Differential gene trend analysis identified five statistically significant drug-response modules: 65, 14, 63, 5, and 53. Transcriptome analysis revealed 911 rescue genes following erucic acid intervention. GO enrichment analysis indicated that erucic acid’s anti-influenza mechanism primarily involves inflammatory response suppression and immune function regulation. KEGG pathway enrichment suggested that erucic acid's therapeutic effects operate through cytokine-receptor interaction, TNF signaling, NF-κB signaling, IL-17 signaling, and metabolic pathways. The intersection of rescue genes and erucic acid targets yielded 28 core genes. PPI network construction and median degree filtering identified 8 key genes: PTGS2, TLR4, TRPV1, IDO1, ARG2, PTGER4, NOS2, and FAAH. Molecular docking and molecular dynamics simulation verified favorable binding activity between erucic acid and these key genes. GSEA analysis and visualization of correlations between key genes and regulatory molecules demonstrated pathway activation in the virus group, which was suppressed by erucic acid intervention. This suggested erucic acid exhibits anti-influenza effects through dual mechanisms: inhibiting virus-induced inflammation via the TLR4/MYD88/NF-κB pathway, and modulating cellular metabolism and host immune response through IDO1, ARG2, and NOS2 expression regulation.

CONCLUSION  Erucic acid has strong binding activity to TLR4, PTGS2, IDO1, NF-κB and other molecules, and can inhibit the expression of genes related to NF-κB signaling pathway and metabolic pathway, alleviate influenza virus-mediated inflammatory response and modulate influenza virus-induced metabolic changes.