Global Journal of Medical Research, F: Diseases, Volume 22 Issue 4

the activity of the enzyme by three molecular mechanisms: decrease of stability of individual protomers, disruption of protomer–protomer interactions or modification of residues in the active site region (Nemethova et al., 2016). The effects of SNPs on HGD protein structure and functions still remains elusive; therefore, in this present study, the deleterious effect of SNPs on HGD gene were analyzedby using various computational databases and bioinformatics tools. Instead of biological experiment confirmation, the study tries to provide a useful method for fast and cost effective screening for pathologic SNPs. II. M aterial and M ethods a) Data retrieval Data was retrieved from the SNP database of the National Center for Biotechnology Information (dbSNP) (http://www.ncbi.nlm.nih.gov/snp) . The NCBI SNP database (https://www.ncbi.nlm.nih.gov/snp ) was used to access the SNPs of the HGD gene (Oct 2021). The primary sequence of the protein (Uniprot accession number: Q93099) encoded by the HGD_HUMAN gene was obtained from the UniProt database (Oct 2021). b) Gene MANIA software Interaction of this gene with other genes was investigated using Gene MANIA (http://genemania.org ). It is a flexible user-friendly website for generating hypotheses about gene function, analyzing gene lists, and prioritizing genes for functional assays. Given a query gene list, Gene MANIA finds functionally similar genes using a wealth of genomics and proteomics data. In this mode, it weights each functional genomic dataset according to its predictive value for the query. (Franz,et al., 2018). c) Functional and structural analysis of the SNPs Only missense SNPs were selected from the NCBI SNPs database as they can modify the sequence of the amino acid encoded by the protein and have the potential to disturb the structural arrangement and function of the proteins. The functional effect of the SNPs on the protein was investigated using SIFT, Provean, Polyphen-2, SNPs& GO, and PHD-SNPs. The stability of the protein as the result of the mutation was studied using I- Mutant and MUPro, and finally the effect of the nsSNPs on the structure was predicted using Project Hope software. i. SIFT (Sorting Intolerant from Tolerant) This software was developed by Kumar et al., 2009. It predicts whether an amino acid substitution a ff ects protein function based on sequence homology and the physical properties of amino acids. SIFT uses sequence homology among related genes and domains across species to predict the impact of all 20 possible amino acids at a given position, allowing users to determine which nsSNPs would be of most interest to study by sorting variants by this prediction score. It gives scores to each amino acid residue ranging from zero to one. The SIFT prediction is given as a tolerance index (TI) score ranging from 0.0 to 1.0, which is the normalized probability that the amino acid change is tolerated. The threshold intolerance score for SNPs is 0.05 or less (Amberger et al., 2009). ii. Provean (Protein Variation Effect Analysis) Is a software tool that predicts whether an amino acid substitution has an impact on the biological function of a protein. Provean is useful for filtering sequence variants to identify nonsynonymous variants that are predicted to be functionally important. The performance of Provean is comparable to popular tools such as SIFT or PolyPhen-2 (Choi et al., 2012). A fast computation approach to obtain pairwise sequence alignment scores enabled the generation of precomputed Provean predictions for 20 single AA substitutions at every amino acid position of all protein sequences in humans and mice (Choi, 2012). iii. Polyphen-2 (Polymorphism Phenotyping v2) It is a multiple sequence alignment server that aligns sequences using structural information. Input for the PolyPhen-2 server is either a protein sequence or accession number together with sequence position with two amino acid variants. (Ramensky et al.,2002).It estimates the position-specific independent count score (PSIC) for every variant and then determines the difference between them, the higher the PSI, the higher the functional impact of the amino acid on the protein function may be. Prediction outcomes could be classified as probably damaging, possibly damaging or benign according to the score ranging from (0–1) (Adzhubei et al., 2013). SNPs &GO (Single nucleotide polymorphism & Gene Ontology), PHD-SNP, (Predictor of Human Deleterious SNP) SNPs & GO, an accurate method that, starting from a protein sequence, can predict whether a mutation is disease-related or not by exploiting the protein functional annotation. SNPs & GO collects in unique framework information derived from protein sequence, evolutionary information, and function as encoded in the Gene Ontology terms, and outperforms other available predictive methods (Calabrese et al., 2009). d) Prediction of Protein stability Two software were used to predict the effect of a missense mutation on the protein’s stability. i. I-Mutant 3.0 http://gpcr2.biocomp.unibo.it/cgi/ predictors/I-Mutant3.0/I-Mutant3.0.cgi This software offers the opportunity to predict automatically protein stability changes upon single-site mutations starting from protein sequence alone or 16 Year 2022 Global Journal of Medical Research Volume XXII Issue IV Version I ( D ) F © 2022 Global Journals Computational Analysis of Possibly Pathogenic Non-Synonymous Single Nucleotide Polymorphisms Variants in HGD Gene