Determination of harmful SNPs in the LCAT gene association with fish eye disease by In Slico methods

Fish eye disease is an extremely rare disease of cholesterol metabolism in which lecithin cholesterolacyl transferase deficiency leads to increased serum free cholesterol levels. Today, SNPs located in coding regions and non-coding regions of DNA have been shown to be associated with many diseases. Among these, missense SNPs are very important as they are responsible for amino acid differences that result in functional diversity of proteins in humans. In this thesis study, an analysis study was carried out using in silico methods. In order to perform in silico analyzes of missense SNPs in the LCAT gene associated with fisheye disease, publicly available databases and online software tools were used. Information about SNPs in the LCAT gene was accessed from the NCBI dnSNP database and 2836 SNPs were detected. Among these SNPs, the missense ones were filtered and 795 detected SNPs were selected for research. Amino acid changes predicted to be deleterious were simultaneously filtered out in each of the SIFT, PolyPhen-2, PROVEAN, SNPs&GO, Mutation Assessor, SNAP2 and PhD-SNP software tools. A total of 7 variants have been found to be harmful in all programs. I-Mutant and MUpro software tools were used to predict the possible effects of 7 variants, which were later found to be deleterious, on protein stabilization. In the study conducted with the I-Mutant 3.0 software tool, it was determined that all 7 variants had a reducing effect on protein stabilization. As a result of the analysis conducted with the MUpro online software tool, it was determined that all of the amino acid changes reduced protein stabilization of 7 SNPs that were determined to be harmful/disease-related among the missense SNPs of the LCAT gene. This study was conducted to guide diagnostic and experimental studies. It is recommended that SNPs predicted to be high risk be evaluated as a priority in experimental and clinical studies related to fish eye disease.