The virtual functional profile of non-synonymous single nucleotide polymorphisms of the TGFβ1 gene

It is evident that mechanisms within the TGF-β signalling pathway can assume pivotal functions in a multitude of pathological conditions. These factors have been demonstrated to be associated with a multitude of pathological conditions, including, but not limited to, infectious diseases, inflammatory diseases, fibrotic diseases, abnormal wound healing, developmental disorders, and tumours. The objective of this thesis study is to examine the effects of pathogenic nsSNPs on the TGFβ1 gene. To this end, the aim is to identify them using in silico tools and to perform structural and functional analyses using computational approaches. This will allow investigation of their impact on protein structure, function, and disease association. In this thesis study, nsSNPs of the TGFβ1 gene were obtained from the ClinVar database and analysed using in silico tools (SIFT, PROVEAN, PolyPhen-2, Fathmm-xf, SNP&GO). The variants with the highest pathogenicity were determined to be V339D, P363R, C387G, H312Y, L298P, R50C, M382T, L260P, Y328C, I49S, and C387S. These 11 variants were analysed using ConSurf to examine their conservation scores on the protein. The variants I49S, R50C, L298P, H312Y, Y328C, P363R, M382T, C387G, and C387S were identified as being located in the most conserved region. ERIS protein stability analyses revealed that the C387G, C387S, I49S, V339D, L260P, L298P, M382T, and R50C variants disrupt protein stability. The application of the HOPE (Hierarchical Organization of Protein Expression) analysis revealed alterations in the size, current, and hydrophobicity of the 11 variants. In the MutPred-2 analysis, all 11 variants exhibited biochemical losses and gains. In the I-TASSER results, the variant with the highest C-score for each nsSNP variant, L260P (-0.31), was selected.