IN SILICO PREDICTION AND FUNCTIONAL ANALYSIS OF NONSYNONYMOUS SNPS OF HUMAN TSHR GENE

Abstract

TSHR (Thyroid-stimulating hormone receptor) is a vital thyrocyte membrane protein in the thyroid gland and a risk factor for TSH abnormalities. Genetic variations in the TSHR are directly involved in the pathogenesis of autoimmune hypothyroidism, Graves’ disease, toxic adenomas, familial and sporadic non-autoimmune hypothyroidism, and forms of resistance to TSH. Identifying deleterious non-synonymous SNPs in the TSHR gene is crucial in understanding how these genetic variations affect its structure and function. In current study, potentially pathogenic nsSNPs were predicted using a combination of functional prediction tools, including SIFT, PROVEAN, PhD-SNP, SNP&GO and PolyPhen2. To further assess the impact of these nsSNPs on protein stability and function, MutPred, I-Mutant, Mupro and ConSurf, were employed. The 3D structure was predicted using TrRosetta, while gene and protein interaction network were explored using GeneMANIA and STRING, respectively. This analysis identified 5 pathogenic nsSNPs, rs142063461 (P68S), rs2075179 (N187K), rs121908871 (C390W), rs121908885 (L467), rs2140111252 (W488R) within the coding region of TSHR gene. The tools predicted decreasing in the protein stability and have higher RMSD values for these nsSNPs and showed deviation in structure from wild type TSHR protein. The prediction of gene-gene interaction showed the interaction of TSHR with other genes and its importance in different pathways, such as cAMP signaling pathway, MAPK, and GPCR pathway. The identified pathogenic nsSNPs of TSHR using computational analysis in this study could be used for large population-based investigations, diagnosis and can help in precision medicine.