Prediction of deleterious non-synonymous SNPs of human TLR2 gene associated with bacterial meningitis and hearing impairment by computational approach

Palanisamy Manikandan

doi:10.53730/ijhs.v6nS8.12941

Authors

Palanisamy Manikandan
m.palanisamy@mu.edu.sa
Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University, Al Majmaah, 11952, Saudi Arabia

Keywords:

bacterial meningitis, TLR2, gram-positive bacteria, SNPs, SFIT, Polyphen-2, I-mutant, peptide docking

Abstract

Background: Bacterial meningitis is the most serious infection of the central nervous system and often occurs in children under the age of 5 years and leads to hearing loss, learning disabilities. Several studies have reported the genetic variation in a gene that is involved in the innate immune system and affects the susceptibility, severity of bacterial infection during meningitis. Methodology: Hence the present study was performed to insights the single nucleotide polymorphisms in pathogen recognition genes especially those that play an essential role in the innate immune system. Toll-like receptor 2 (TLR2) was selected to analyze the association of TLR2 in bacterial meningitis. The coding and non-coding SNPs of the human TLR2 gene was retrieved from the NCBI database and were subjected to various computational prediction tools including SIFT, PolyPhen-2, Imutnat, to predict the high-risk deleterious SNPs and the effect of single amino acid substitutions and structural and functional impact of these mutations was predicted with project HOPE, SNP-GO tools. Results: The result revealed that among the 501 non-synonymous, 9 deleterious SNPs were sorted by SFIT, Polyphen-2 and I mutant serve with SFIT score, DDG score, and PISC score which are equal to 1.

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