Nonsynonymous single nucleotide polymorphisms (nsSNPs) are one of the most common forms of mutations known to disrupt the product of translation thereby altering the protein structure-function relationship. GULP1 (PTB domain-containing engulfment adaptor protein 1) is an evolutionarily conserved adaptor protein that has been associated with glycated hemoglobin (HbA1c) in Genome-Wide Association Studies (GWAS). In order to understand the role of GULP1 in the etiology of diabetes, it is important to study some functional nsSNPs present within the GULP1 protein. We, therefore, used a SNPinformatics approach to retrieve, classify, and determine the stability effect of some nsSNPs. Y27C, G142D, A144T, and Y149C were jointly predicted by the pathogenic-classifying tools to be disease-causing, however, only G142D, A144T, and Y149C had their structural architecture perturbed as predicted by I-MUTANT and MuPro. Interestingly, G142D and Y149C occur at positions 142 and 149 of GULP1 which coincidentally are found within the binding site of GULP1. Protein-Protein interaction analysis also revealed that GULP1 interacted with 10 proteins such as Cell division cycle 5-like protein (CDC5L), ADP-ribosylation factor 6 (ARF6), Arf-GAP with coiled-coil (ACAP1), and Multiple epidermal growth factor-like domains protein 10 (MEGF10), etc. Taken together, rs1357922096, rs1264999716, and rs128246649 could be used as genetic biomarkers for the diagnosis of diabetes. However, being a computational study, these nsSNPs require experimental validation to explore their metabolic involvement in the pathogenesis of diseases.
Keywords: GULP1; MD Simulation; Nonsynonymous single nucleotide; SNPinformatics; polymorphisms (nsSNPs).