Elucidating the Type 2 Diabetes Regulatory Network: Identification of EGFR as a Key Hub and Novel Drug Candidates

IntroductionType 2 diabetes (T2D) is a complex metabolic disorder with incompletely understood molecular mechanisms. This study aimed to elucidate the T2D regulatory network and identify potential drug targets and candidates. MethodsWe performed differential gene expression analysis on multiple T2D datasets, constructed protein-protein interaction networks, and conducted a meta-analysis to identify key hub genes. Functional enrichment analysis was performed on the resulting network. Structure-based virtual screening targeting EGFR, followed by molecular dynamics simulations, was used to identify potential drug candidates. ResultsEGFR emerged as a consistently top-ranked hub gene across studies. The regulatory network comprised hub genes, transcription factors, and miRNAs involved in processes such as apoptosis regulation, cellular response to organic substances, and reactive oxygen species metabolism. Virtual screening identified three compounds with favorable ADMET properties and strong binding affinities to EGFR, outperforming control drugs. These compounds demonstrated stable interactions in molecular dynamics simulations. ConclusionsOur integrative analysis provides new insights into the T2D regulatory network, highlighting EGFR as a potential therapeutic target. The identified drug candidates offer promising avenues for T2D treatment and related disorders involving EGFR signaling, bridging systems biology and drug discovery approaches in metabolic disease research.