Computational Insight in the Identification of Non-Synonymous Single-Nucleotide Polymorphism Affecting the Structure and Function of Interleukin-4

Background: IL4 is a versatile cytokine essentially known for differentiation, proliferation and cell death in cells. Its dysregulation has been found to be associated with the development of inflammatory disorders.

Objective: The goal of the current investigation is to identify and select non-synonymous single-nucleotide polymorphisms (nsSNPs) in the IL-4 gene by employing computational methods which may have a potential functional impact on the occurrence of disease.

Method and result: Six different nsSNPs were predicted to be deleterious based on the consensus of different algorithms: SIFT, Polyphen2 (Humdiv and HumVar), PredictSNP and SNP&GO. I-mutant and MuPro assessment revealed a decrease in the stability of these mutants except K150M. Modelling was then carried out to build the wild type along with its mutants, followed by superimposition of the wild type with mutants to evaluate the RMSD value, which lies between 0.26 and 0.34. Simulation results of mutant models, along with wild type, showed that four of the mutants (N113Y, A118G, R109W and K150M) deviated most and were unstable. A118G showed a significant deviation from the wild type, while V53A and C123R were stable.

Conclusion: The finding establishes the evidence that the identified six nsSNPs of IL-4 can be the new entrant presenting their candidature for genetic testing.