Identification of anti-inflammatory mechanism of action and molecular targets of Hypericum perforatum in the treatment of major depression based on bioinformatics methods and machine learning

Abstract

Abstract Background Major depressive disorder (MDD) is one of the most common psychiatric disorders worldwide. The diagnosis and treatment of MDD is a major clinical issue. Hypericum perforatum (HP) is a traditional herb that has been shown to have antidepressant effects, but its mechanism is unclear. This study combined bioinformatics approach and molecular docking prediction to identify the mechanism of action and molecular targets of HP for the treatment of MDD from the perspective of signaling pathways and immune inflammation. Methods We performed differential analysis and weighted gene co-expression network analysis (WGCNA) with the GSE98793 depression expression dataset to intersect the identified DEGs and significant module genes to obtain intersection genes. Three databases, CTD, DisGeNET and GeneCards, were used to retrieve MDD-related gene intersections to obtain MDD predicted targets. The validated targets were retrieved from the TCMSP database. The enriched pathways were analyzed separately to obtain KEGGa, KEGGb and KEGGc. 13 key pathways were obtained by combining them. The PPI network was constructed by extracting the intersection of genes and HP validated targets on all key pathways. Five key therapeutic targets (AKT1, MAPK1, MYC, EGF, HSP90AA1) were obtained using MCODE and machine learning (LASSO, SVM-REF). Clinical diagnostic assessments (Nomogram, ROC, Correlation, Intergroup expression), gene set enrichment analysis (GSEA) were performed for the 5 key targets. In addition, immuno-infiltration analysis was performed on the MDD dataset to explore the regulatory mechanisms of the 5 key targets. Finally, molecular docking prediction was performed for the targets of HP active ingredients on MDD. Results Differential expression analysis and WGCNA module analysis yielded 933 potential targets for MDD. Three disease databases were intersected to 982 MDD predicted targets. The TCMSP retrieved 275 valid targets for HP. Separate enrichment analysis intersected to 13 key pathways. Five key targets (AKT1, MAPK1, MYC, EGF, HSP90AA1) were finally screened based on all enriched genes and HP valid targets. Combined with the signaling pathway and immune infiltration analysis, the effect of peripheral immunity on MDD and the important role of neutrophils in immune inflammation were investigated. Finally, the binding of HP active ingredients (quercetin, kaempferol and luteolin) and all 5 key targets was predicted based on molecular docking. Conclusions The active constituents (quercetin, kaempferol and luteolin) of Hypericum perforatum may act on MDD and its inflammatory symptoms through key targets (AKT1, MAPK1, MYC, EGF, HSP90AA1) and pathways such as neutrophil extracellular trap formation.