In silico Evaluation of Non-Synonymous SNPs in IRS-1 gene associated with type II diabetes mellitus. Singh Apoorva1, Singh Siddhant1, Anbarasu Anand2,* 1Student, VIT University, Vellore, 632014, Tamil Nadu 2Professor, Department-SBST. Vellore, 632014, Tamil Nadu *Corresponding Author E-mail: dramadan@scs-net.org, mandil@scs-net.org
Online published on 21 August, 2018. Abstract Insulin and insulin-like growth factor (IGF-1) carry out their diverse range of actions via Insulin receptor substrate (IRS) protein. Type 2 diabetes mellitus typically arises when internal insulin-secretory reserves in humans fail to counter-balance for peripheral insulin resistance. Studies have proven that mutations in IRS1 gene are accountable for diabetes mellitus 2. Online databases are available which stores all the mutations occurring in IRS1 gene. With the help of computational methods we can predict which non-synonymous single nucleotide polymorphism (nsSNP) is deleterious and disease causing based on protein function and stability using POLYPHEN-2, PROVEAN, I-MUTANT 2.0, SNP and GO, PHD-SNP and MUTPRED. By comparing the results we can tell which SNP has the highest probability of causing a dysfunction in IRS-1 protein and culminating into Diabetes mellitus type 2. Top Keywords Insulin signaling pathway, IRS gene, Type 2 Diabetes Mellitus, non-synonymous SNPs, SNP analysis, modeling. Top |