背景:单核苷酸多态性(SNP)在影响个体对疾病的易感性方面具有至关重要的功能,并且还决定了个体对不同治疗方案的反应。本研究旨在使用不同的计算方法预测和表征溶菌酶C(LYZC)基因的有害错义非同义SNP(nsSNP)。LyzC是一种重要的抗微生物肽,能够破坏细菌的肽聚糖层,导致渗透休克和细胞死亡。首先通过SIFT和PolyPhenv2工具分析nsSNP。预测为有害的nsSNPs然后通过其他硅片工具进行评估-SNAP,PROVEAN,博士-SNP,SNPs&GO。通过I-突变体3.0和ConSurf进一步检查这些SNP。使用GeneMANIA和STRING工具研究LYZC基因的相互作用网络。NetSurfP2.0用于预测LyzC蛋白的二级结构。通过HOPE分析研究了变异对蛋白质结构特征的影响。通过SWISS-MODEL网络服务器预测野生型和变体的结构,使用XenoPlot软件进行能量最小化。TM-align工具用于预测均方根偏差(RMSD)和模板建模(TM)得分。
结果:八个错义nsSNPs(T88N,I74T,F75I,D67H,W82R,D85H,R80C,和R116S)被发现可能有害。I-突变体3.0确定变体降低了蛋白质的稳定性。ConSurf预测rs121913547、rs121913549和rs387906536nsSNP是保守的。相互作用网络工具表明LYZC蛋白与乳铁蛋白(LTF)相互作用。HOPE工具分析了野生型和变体之间的物理化学性质的差异。TM-align工具预测了对齐分数,发现蛋白质折叠是相同的。PyMOL用于可视化变体与野生型的叠加。
结论:本研究确定了LYZC基因的有害错义nsSNP,可用于进一步的实验分析。这些高风险nsSNP可用作诊断和治疗干预的分子靶标。
BACKGROUND: Single-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.
RESULTS: Eight
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.
CONCLUSIONS: This
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.