Deciphering deleterious missense variants in the MC4R gene in the pathogenesis of obesity

The MC4R gene plays a critical role in regulating food intake, making it an important model for studying genetic mutations that impact the protein function. This study aimed to identify the most deleterious functional and structural variants in individuals with obesity by analyzing SNPs from the NCBI dbSNP database and selecting pathogenic variants from ClinVar. Bioinformatics tools were employed to predict deleterious SNPs, and conservation analysis was performed using ConSurf. Stability predictions were made with MUpro, I-Mutant2.0, and iStable. The 3D structure of the MC4R protein was examined using YASARA view. A total of 20 out of 348 missense mutations were associated with obesity. Fifteen of these variants were predicted to be the most deleterious. Eight variants located in conserved regions were found to significantly reduce protein stability and cause structural changes (S58C, E61K, N62S, I69R, D90N, R165Q, P299H, and I316S), indicating their potential as obesity biomarkers and therapeutic targets.