Prediction of nonsynonymouse SNPs effects in Esterogene Receptor (ESR) gene on Protein Structure and Performance in Khuzestani Buffaloes

Recent developments in DNA sequencing and computational algorithms have leading to the discovery of higher value SNPs. In this research, several computational algorithms were used to express the effect of ESRα gene SNPs on protein function in buffalo genome. In this study genomic information of 112 Khuzestani buffaloes that revealed by Affymetrix-90K-SNP-Chip were used. We found two SNPs for ESRα gene. The analysis of these SNPs was performed using Sift, Provean servers. Sift by calculating a zero coefficient, predict that SNPs effects were destructive and effective on protein function. Provean algorithm predict a natural effect by calculating a coefficient of -0.08 for Thr15Ala-SNP and a score of -0.13 for Argenin 43 Histedin-SNP. The SNPs were examined using I-mutant for further investigation of SNPs effects on Protein stability. I-mutant algorithm predict the effect of SNP on protein stability by regression and based on the change in free energy (DDG=-0.49). The result suggestedthat Thronin15Alanin-SNP at 25 °C and pH=7 will reduce the protein stability and Argenin 43 Histedin-SNP, because of its score (DDG=-0.53), has same effect on protein stability. ESRα protein modeling was performed by I-taser server. Validation of the models by Ramachandran plot and Pro-SA server, indicating a deviation in the mutant protein compared to the natural model. Molecular docking in both natural and mutant models indicates no direct changes in the amino acids involved in the interaction. However by side effect and indirectly there is a decrease in ligand binding affinity for the receptor in the mutated model compare to the natural model.