Abstract
Conventional drug discovery routes take decades to identify critical gene signatures involved in a disease. Though in silico platforms and software have simplified the process by reducing the time and energy needed to arrive at significant molecular targets for disease conditions, they are not accessible to everyone. Here, we propose a systematic strategic protocol to identify critical players in the disease pathogenesis using the vast amount of molecular omics data available on various public domains, setting diabetic cardiomyopathy as the case study. We use databases like KEGG, DisGeNET, HMDD, and literature to curate the key genes and miRNAs associated with the disease. We analysed 395 genes and 20 miRNAs for our analysis. Critical pathways like the insulin resistance pathway, the AGE-RAGE pathway, and the PI3K-AKT-mTOR pathway were enriched in our analysis through the Metascape platform. A protein-protein interaction network was generated using the STRING database. The export of this network to the Cytoscape platform helped to identify the clusters, node interactions, and hub genes. Our approach finally identified hsa-miR-302a-3p as the critical miRNA that regulates the highest-ranked hub gene, AKT1. This systematic methodology lays a solid foundation for the identification of critical therapeutic targets for any disease condition, thereby increasing the success rate for further stages of development.