Determination of deleterious single-nucleotide polymorphisms of human LYZ C gene: an in silico study

Abstract

BackgroundSingle-nucleotide polymorphisms (SNPs) have a crucial function in affecting the susceptibility of individuals to diseases and also determine how an individual responds to different treatment options. The present study aimed to predict and characterize deleterious missense nonsynonymous SNPs (nsSNPs) of lysozyme C (LYZ C) gene using different computational methods. Lyz C is an important antimicrobial peptide capable of damaging the peptidoglycan layer of bacteria leading to osmotic shock and cell death. The nsSNPs were first analyzed by SIFT and PolyPhen v2 tools. The nsSNPs predicted as deleterious were then assessed by other in silico tools — SNAP, PROVEAN, PhD-SNP, and SNPs & GO. These SNPs were further examined by I-Mutant 3.0 and ConSurf. GeneMANIA and STRING tools were used to study the interaction network of the LYZ C gene. NetSurfP 2.0 was used to predict the secondary structure of Lyz C protein. The impact of variations on the structural characteristics of the protein was studied by HOPE analysis. The structures of wild type and variants were predicted by SWISS-MODEL web server, and energy minimization was carried out using XenoPlot software. TM-align tool was used to predict root-mean-square deviation (RMSD) and template modeling (TM) scores. ResultsEight missense nsSNPs (T88N, I74T, F75I, D67H, W82R, D85H, R80C, and R116S) were found to be potentially deleterious. I-Mutant 3.0 determined that the variants decreased the stability of the protein. ConSurf predicted rs121913547, rs121913549, and rs387906536 nsSNPs to be conserved. Interaction network tools showed that LYZ C protein interacted with lactoferrin (LTF). HOPE tool analyzed differences in physicochemical properties between wild type and variants. TM-align tool predicted the alignment score, and the protein folding was found to be identical. PyMOL was used to visualize the superimposition of variants over wild type. ConclusionThis study ascertained the deleterious missense nsSNPs of the LYZ C gene and could be used in further experimental analysis. These high-risk nsSNPs could be used as molecular targets for diagnostic and therapeutic interventions.