Integrating Network Pharmacology and Transcriptomic Strategies to Explore the Pharmacological Mechanism of Paeoniflorin Exerts Antidepressant Effects

Abstract

Background:: Paeoniflorin has been proven to have neuroprotective and antidepressant effects in several studies. However, there is currently no comprehensive elaboration of its antidepressant effects through network pharmacology combined with transcriptomics analysis. The purpose of this study is to explore the potential mechanisms by which paeoniflorin exerts its antidepressant effects using network pharmacology and transcriptomics sequencing approaches. Methods:: We utilized metascape to enrich the intersecting targets for paeoniflorin and depression for enrichment analyses. Additionally, we employed Cytoscape software to construct target pathway networks. For the screening of differentially expressed genes (DEGs) altered by paeoniflorin, we sequenced mRNA from the hippocampal tissue of CUMS model mice using the BMKCloud platform. We further enriched their biological functions and signaling pathways by using the Omishare database. The study utilized a combination of network pharmacology and transcriptomics analysis to evaluate the interactions between paeoniflorin and key targets. The results were then verified through a molecular docking process and a subsequent Western blot experiment. Results:: According to a comprehensive analysis, paeoniflorin has 19 key targets that are closely related to its therapeutic effect. Molecular docking revealed that paeoniflorin has a high affinity for HIF-1α, VEGFA, and other targets. Furthermore, protein expression and immunofluorescence staining analysis showed that paeoniflorin significantly increased the expression level of HIF-1α and VEGFA in the hippocampus of depression model mice. Conclusion:: These findings suggest that paeoniflorin may have therapeutic potential in depression through the activation of the HIF-1α-VEGFA pathway.