Abstract:

Objective To explore the antidepressant mechanism of the main active ingredients of Hypericum perforatum L. through network pharmacology data mining and experimental validation. Methods The main active ingredients of Hypericum perforatum L. were retrieved from the literature and the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. Network pharmacology analysis， GO enrichment analysis， and KEGG pathway enrichment analysis were carried out using the GeneCards， STRING， and DAVID databases. The active ingredient–target network of Hypericum perforatum was constructed with Cytoscape 3.8.2 software. Nodes with a degree value of at least 10 and betweenness centrality of at least 0.01 were selected for topological analysis. Meanwhile， cellular and animal experiments were conducted to validate the results. Microglial cells （BV-2） were divided into four groups： Control， lipopolysaccharide （LPS）， hypericin （HY）， and calcineurin inhibitor （CNIS）. Immunofluorescence was employed to detect the positive expression of ionized calcium-binding adapter molecule 1 （IBA-1）， and Western blot was utilized to determine the expression levels of related proteins. Additionally， C57BL/6J mice were randomly assigned to three groups： Control， depression （DP）， and HY groups （n = 15 per group）. Behavioral tests， such as the light-dark box （LDB）， open field test （OFT）， and tail suspension test （TST）， were used to assess the ameliorative effect of hypericin on chronic unpredictable mild stress （CUMS）-induced depression-like behaviors. Western blot was also used to measure the expression levels of the inflammatory factor tumor necrosis factor-α （TNF-α） and proteins related to the calcium signaling pathway. Results Eight active ingredients were screened from Hypericum perforatum， and 80 potential depression-related targets were predicted. Through visualization analysis of the active ingredients and intersecting genes， it was found that HY plays a major role in the antidepressant effect. The “ingredient?pathway?target” network analysis indicated that the calcium signaling pathway was a key pathway. Cell experiments demonstrated that， in comparison with the Control group， the LPS group showed a significant increase in IBA-1 expression （P < 0.05） and a significant increase in the protein expression of pro-inflammatory cytokines and the CaM-CN-NFAT calcium signaling pathway （P < 0.05）. In contrast， compared with the LPS group， the HY group presented a significant decrease in IBA-1 expression （P < 0.05） and a significant decrease in the protein expression of TNF-α and the CaM-CN-NFAT calcium signaling pathway （P < 0.05）. Animal experiments revealed that， when compared with the Control group， the DP group had a significant shortening of the central zone time in the OFT （P < 0.05）， a significant reduction in the number of transitions in the LDB （P < 0.05）， a significant prolongation of immobility time in the TST （P < 0.05）， and a significant increase in the protein expression of TNF-α and calcium signaling pathway proteins （P < 0.05）. All these changes were reversed in the HY group. Conclusion This study has preliminarily revealed the mechanism of antidepressant active ingredients from Hypericum perforatum L. via network pharmacology analysis combined with in vivo and in vitro validation， thus providing a theoretical basis for further pharmacological research.

Key words: network pharmacology, hypericum perforatum, hypericin, depression, pharmacological mechanism