Potential diagnostic markers and therapeutic targets for major depressive disorder based on bioinformatics analysis and molecular docking studies

Major depressive disorder (MDD) is a neuropsychiatric disorder with a high risk of suicide. This study aimed to examine the key genes, microRNAs and TFs associated with MDD. Next generation sequencing (NGS) dataset (GSE275676) was downloaded from the Gene expression omnibus (GEO) database. The DEGs were screened using DESeq2 in R bioconductor tool. We next performed gene ontology (GO) analysis and REACTOME pathway enrichment analysis using the g:Profiler. Moreover, Cytoscape with IMex interactome was utilized to visualize protein-protein interaction (PPI) network and modules of these DEGs. Subsequently, miRNA-hub gene regulatory network, TF-hub gene regulatory network and drug-hub gene interaction network were built by Cytoscape to predict the underlying microRNAs (miRNAs), transcription factors (TFs) and small drug molecules associated with hub genes. Top hub genes in the PPI network were validated by receiver operating characteristic (ROC) curve analysis. Finally, conducted molecular docking with hub genes and corresponding active molecules. We screened 958 DEGs, containing 479 up regulated genes and 479 down regulated genes. GO and REACTOME pathway enrichment analyses revealed that DEGs are mainly enriched in cell communication, synapse, enzyme binding, response to stimulus, cell periphery, signaling receptor binding, neuronal system and immune system. YWHAG, ONECUT1, CALM2, ARRB1, PIK3R1, CDK2, VCAM1, HLA-B, VIM and ERBB2 are the top hub genes in PPI network and modules. The predicted miRNA-hub gene regulatory network identified miRNAs targeting hub genes, and predicted TF-hub gene regulatory network identified TFs. Four drug molecules were predicted including Lumateperone, Thiopental, Golimumab and Chitotriose for treatment of MDD. Molecular docking analysis revealed that isocryptomerin, kushecarpin C, irisflorentin and treptoside were the main active compounds with good binding activities to the hub genes. In conclusion, the findings of this investigation might lead to novel insights on MDD diagnosis, aetiology, and treatment options. In the future, it might be possible to develop particular diagnostics and therapies for MDD by identifying hub genes and studying over and under expressed proteins as therapeutic targets.