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ABSTRACT: 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 w
SUBMITTER: Venkata Subbiah H
PROVIDER: S-EPMC9247897 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature