Studies on the relationship between single nucleotide polymorphisms and protein interactions

This thesis presents an analysis of the relationship between single nucleotide polymorphism (SNPs) and protein–protein interactions. The aim of the thesis is to investigate the distribution of non-synonymous single nucleotide polymorphism (nsSNPs) in terms of their locations in the protein core, at the protein–protein interface sites and on the other areas on the protein surface. The analysis used experimentally verified human protein–protein interactions and nsSNPs from the UniProt humsavar database. A further investigation was performed on a larger SNP dataset from the 1000 Genomes Project (1KGP). Both investigations identified a significant preference for disease-causing SNPs to occur at the protein interface compared to other areas on the protein surface. The three-dimensional structures of protein–protein interfaces were examined in order to propose stereo-chemical explanations for the disease-causing effect of nsSNPs in the humsavar dataset. In addition, three methodologies (i.e., usage of SNP server, structural analysis and usage of GMAF) that could help identify pathogenic variants were presented. Structural analysis was also performed on non-diseasecausing SNPs in order to investigate their possible effects on protein–protein interactions. The result showed that some of the previously classified non-diseasecausing SNPs could potentially be disease-causing SNPs. The myVARIANT program was developed. The program obtains SNPs from 1KGP, maps them to structures, evaluates their distribution on structures and performs a structural analysis. In conclusion, the thesis demonstrates the important role that protein–protein interactions play in disease pathogenesis.Open Acces