In silico analysis of single nucleotide polymorphism (SNP) in human TNF-α gene

The TNF-α gene mutations are seen in many diseases especially inflammatory diseases. Hence, before planning a larger population study, it is advisable to sort out the possible functional SNPs. To accomplish this goal, data available in the dbSNP database and different computer programs can be used. Therefore, this study was undertaken to find the functional nsSNPs (non-synonymous single nucleotide polymorphisms) in TNF-α. Out of the total 169 SNPs, 48 were nsSNPs (non-synonymous single nucleotide polymorphisms), 23 occurred in the mRNA 3′ UTR, 10 occurred in 5′ UTR region, 41 occurred in intronic regions and the rest were other types of SNPs. SIFT and PolyPhen predicted 2 out of 48 nsSNPs as damaging. Among the predicted nsSNPs, rs4645843 and rs1800620 were identified as deleterious and damaging by the SIFT (Sorting Intolerant from Tolerant) and PolyPhen programs. Additionally, I-Mutant and nsSNPAnalyzer showed a decrease in stability for these nsSNPs upon mutation. Protein structural analysis with these amino acid variants was performed by using I-Mutant, Swiss PDB viewer, ANOLEA (Atomic Non-Local Environment Assessment), MUSTER (MUlti-Sources ThreadER) and NOMAD-Ref servers to check their molecular dynamics and energy minimization calculations. This study suggested that P84L and A94T variants of TNF-α could directly or indirectly destabilize the amino acid interactions and hydrogen bond networks thus explaining the functional deviations of protein to some extent.