In Silico Analysis by Bioinformatics AND Genotyping of P53 Gene In TBI

Abstract

Introduction: Evaluation of the SNPs of p53 by bioinformatics tools, genotyping of p53 gene in TBI patients as compared to controls as well as to evaluate the association of p53 gene polymorphisms with the functional outcome of TBI were the objectives of this study.

Methods: In silico analysis of SNPs of  p53  gene was conducted using its accession IDs and their FASTA amino acid sequences obtained from NCBI . SIFT, Polyphen-2, CADD score, MetaLR and mutation assessor  were the bioinformatics softwares utilized for the study. Protein –protein interaction was assessed by string database.

The influence of the Arginine variant of p53 was investigated in a cohort of 58 adults with mild, moderate, and severe TBI with PCR-RFLP method.

Results: A total of 15761 nsSNPs were filtered and analysed. SIFT analysis of the p53 gene's SNPs found that 63% of the mutations were harmful while 27% were tolerable. According to Polyphen-2 study, 35.42% of SNPs were benign mutations whereas 64.20% of them were harmful. On the basis of the metaLR analysis, 96.2% of the SNPs were determined to have harmful mutations, whereas 2.25% of them were tolerated. The p53 gene showed 7.42% harmful and 91.77% tolerant alterations according to CADD scores. No significant difference was observed between the allelic distribution of genotype variants among cases and controls. The mean value of GCS was highest in patients with CC genotype.

Conclusion: The results propose that p53 gene mutations that are deleterious and its interactions as obtained by the bioinformatics softwares may have a crucial role the pathogenesis of TBI.There was no significant association between p53 gene polymorphism and functional outcome after TBI. However, patients with CC genotype (proline/proline) had less severe injuries, whereas the extent of recovery was maximum in GG-containing genotypes, supported by their longest length of hospital stay.