Abstract: Objective: To investigate the potential targets and molecular mechanisms of paeoniflorin in treating depression using network pharmacology. Methods: Targets of paeoniflorin were predicted via the Swiss Target Prediction database. Depression-related targets were obtained from the GeneCards database, and an intersection of "drug-disease" targets was constructed. A protein-protein interaction (PPI) network was built using the STRING platform, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses (P < 0.05) via DAVID. Results: Twenty-four paeoniflorin targets and 5,443 depression-related targets were identified, yielding 15 intersection targets. The PPI network contained 11 nodes and 18 edges, with core targets including FGF2, HSP90AA1, and others. GO enrichment analysis revealed: biological processes (BP) involving wound healing, cell chemotaxis, and regulation of body fluid levels; cellular components (CC) enriched in cytoplasmic vesicle lumen and platelet alpha granule; molecular functions (MF) associated with heparin binding and glycosaminoglycan binding. KEGG pathway analysis highlighted significant enrichment in PI3K-Akt signaling pathway, Rap1 signaling pathway, and Ras signaling pathway. Conclusion: Paeoniflorin exerts antidepressant effects through multitargets and multipathways, providing a theoretical basis for its therapeutic application in depression.
Abstract: Objective: To investigate the potential targets and molecular mechanisms of paeoniflorin in treating depression using network pharmacology. Methods: Targets of paeoniflorin were predicted via the Swiss Target Prediction database. Depression-related targets were obtained from the GeneCards database, and an intersection of "drug-disease" targets was ...Show More
