Computational analysis of missense variants of human MC4R and childhood obesity

Abstract

Industrialized and developing nations face severe public health problems related to childhood obesity. Previous studies revealed that the melanocortin-4 receptor gene (MC4R) is the most prevalent monogenic cause of severe early obesity. Due to its influence on food intake and energy expenditure via neuronal melanocor-tin-4 receptor pathways, MC4R is recognized as a regulator of energy homeostasis. This study used a variety of computational systems to analyze 273 missense variations of MC4R in silico. Several tools, including PolyPhen, PROVEAN, SIFT, SNAP2, MutPred2, PROVEAN, SNP&GO and Mu-Pro, I-Mutant, PhD-SNP, SAAFEC-SEQ I-Mutant, and ConSurf, were used to make predictions of 13 extremely confident nsSNPs that are harmful and disease-causing (E308k, P299L, D298H, C271F, C271R, P260L, T246N, G243R, C196Y, W174C, Y157S, D126Y, and D90G). The results of our study suggest that these MC4R nsSNPs may disrupt normal protein function, leading to an increased risk of childhood obesity. These results highlight the potential use of these nsSNPs as biomarkers to predict susceptibility to obesity and as targets for personalized interventions.