High risk genetic variants of human insulin receptor substrate 1(IRS1) infer structural instability and functional interference.
Arittra BhattacharjeeS M Al Muied PrantoIshtiaque AhammadZeshan Mahmud ChowdhuryFarha Matin JulianaKeshob Chandra DasChaman Ara KeyaMd SalimullahPublished in: Journal of biomolecular structure & dynamics (2023)
Insulin receptor substrate 1(IRS1) is a signaling adapter protein encoded by the IRS1 gene. This protein delivers signals from insulin and insulin-like growth factor-1(IGF-1) receptors to the phosphatidylinositol 3-kinases (P13K)/protein kinase B (Akt) and Extracellular signal-regulated kinases (Erk) - Mitogen-activated protein (MAP) kinase pathways, which regulate particular cellular processes. Mutations in this gene have been linked to type 2 diabetes mellitus, a heightened risk of insulin resistance, and an increased likelihood of developing a number of different malignancies. The structure and function of IRS1 could be severely compromised as a result of single nucleotide polymorphism (SNP) type genetic variants. In this study, we focused on identification of the most harmful non-synonymous SNPs (nsSNPs) of the IRS1 gene as well as prediction of their structural and functional consequences. Six different algorithms made the initial prediction that 59 of the 1142 IRS1 nsSNPs would have a negative impact on the protein structure. In-depth evaluations detected 26 nsSNPs located inside the functional domains of IRS1. Following that, 16 nsSNPs were identified as more harmful based on conservation profile, hydrophobic interaction, surface accessibility, homology modelling, and inter-atomic interactions. Following an in-depth analysis of protein stability, M249T (rs373826433), I223T (rs1939785175) and V204G (rs1574667052) were identified as three most deleterious SNPs and were subjected to molecular dynamics simulation for further insights. These findings will help us understand the implications for disease susceptibility, cancer progression, and the efficacy of therapeutic development against IRS1 gene mutants.Communicated by Ramaswamy H. Sarma.
Keyphrases
- genome wide
- type diabetes
- protein kinase
- binding protein
- glycemic control
- molecular dynamics simulations
- insulin resistance
- copy number
- amino acid
- protein protein
- cell proliferation
- signaling pathway
- machine learning
- dna methylation
- endothelial cells
- genome wide identification
- small molecule
- gene expression
- transcription factor
- skeletal muscle
- cardiovascular disease
- adipose tissue
- tyrosine kinase
- ionic liquid
- genome wide analysis
- polycystic ovary syndrome
- molecular docking
- induced pluripotent stem cells
- lymph node metastasis