Revealing new therapeutic opportunities in hypertension through network-driven integrative genetic analysis and drug target prediction approach

Epidemiological studies have established that untreated hypertension (HTN) is a major independent risk factor for developing cardiovascular diseases (CVD), stroke, renal failure, and other conditions. Several important studies have been published to prevent and manage HTN; however, antihypertensive agents' optimal choice remains controversial. Therefore, the present study is undertaken to update our knowledge in the primary treatment of HTN, specifically in the setting of other three important diseases. MicroRNAs (miRNAs) are remarkably stable short endogenous conserved non-coding RNAs that bind to the mRNA at its (3′ UTR) to regulate its gene expression by causing translational repression or mRNA degradation. Through their coordinated activities on different pathways and networks, individual miRNAs control normal and pathological cellular processes. Therefore, to identify the critical miRNA-mRNA-TF interactions, we performed systematic bioinformatics analysis. We have also employed the molecular modelling and docking approach to identify the therapeutic target that delivers novel empathies into Food and Drug Administration approved and herbal drug response physiology. Gene Expression Omnibus (GEO) was employed to identify the differentially expressed genes (DEGs) and hub genes- KNG1, HLA-DPB1, CXCL8, IL1B, and BCL2. The HTN associated feed-forward loop (FFL) network included miR-9-5p, KNG1 and AR. We employed high throughput screening to get the best interacting compounds, telmisartan and limonin, that provided a significant docking score (−13.3 and −12.0 kcal/mol) and a potential protective effect that may help to combat the impact of HTN. The present study provides novel insight into HTN etiology through the identification of mRNAs and miRNAs and associated pathways.