In-silico Profiling of Deleterious Non Synonymous SNPs of Homogentisate 1, 2 Dioxygenase (HGD) Gene for Early Diagnosis of “Alkaptonuria”

Abstract

In-silico characterization and molecular modelling of a single amino acid substitution in HGD (Homogentisate 1,2dioxygenase) gene are mainly caused by the deficiency of enzyme Homogentisate 1,2dioxygenase (HGD). An enzyme HGD involved in the catabolism of amino acids such as tyrosine and phenylalanine. The objective of this study was to analyse non-synonymous SNPs from highly deleterious missense mutations which affect the protein function of HGD gene. Based on 3D structure different computational algorithms were performed to identify deleterious SNPs and assess the influence of mutation by using molecular dynamics simulations and molecular docking. Bioinformatics analysis like SIFT, PolyPhen 2.0, I mutant 3.0, PANTHER, SNPs and GO were performed to predict non deleterious ns-SNPs from missense mutations. Energy minimization was done by using GROMACS followed by RMSD calculations and free-energy values under SWISS-PDB viewer and PyMoL respectively. Later, Trajectory analysis was performed using computational tools like SRIDE, CONSURF, SPPIDER, PSIPRED, FLEXPRED for predicting the probably damaged ns-SNPs. Moreover, molecular docking was performed and identified highly deleterious probably damaging mutation. By operating 10 bioinformatics analysis, we obtained 5 mutations R53W, L61P, G121R, G361R and L430H which have an adverse effect on HGD gene. The results of the ConSurf analysis showed that all of these ns-SNPs are in the highly conserved positions and influence the structure of native proteins. L61P mutation had more effect on protein structure. Later, for future studies these mutations assists to develop an effective drug for the associated disease Alkaptonuria.