Investigating the functional and structural effect of non-synonymous single nucleotide polymorphisms in the cytotoxic T-lymphocyte antigen-4 gene: An in-silico study

The cytotoxic T-lymphocyte antigen-4 (CTLA4) is essential in controlling T cell activity within the immune system. Thus, uncovering the molecular dynamics of single nucleotide polymorphisms (SNPs) within the CTLA4 gene is critical. We identified the non-synonymous SNPs (nsSNPs), examined their impact on protein stability, and identified the protein sequences associated with them in the human CTLA4 gene. There were 3134 SNPs (rsIDs) in our study. Out of these, 186 missense variants (5.93%), 1491 intron variants (47.57%), and 91 synonymous variants (2.90%), while the remaining SNPs were unspecified. We utilized SIFT, PolyPhen-2, PROVEAN, and SNAP for identifying deleterious nsSNPs, and SNPs&GO, PhD SNP, and PANTHER for verifying risk nsSNPs in the CTLA4 gene. Following SIFT analysis, six nsSNPs were identified as deleterious and reporting second and third nsSNPs as probably damaging and one as benign, respectively. From upstream analysis, rs138279736, rs201778935, rs369567630, and rs376038796 were found to be deleterious, probably damaging, and disease associated. ConSurf predicted conservation scores for four nsSNPs, and Project Hope suggested that all mutations could disrupt protein interactions. Furthermore, mCSM and DynaMut2 analyses indicated a decrease in ΔΔG stability for the mutants. GeneMANIA and STRING networks highlighted correlations with CD86 and CD80 genes. Finally, MD simulation revealed consistent fluctuation in RMSD and RMSF, consequently Rg, hydrogen bonds, and PCA in the mutant proteins compared with wild-type, which might alter the functional and structural stability of CTLA4 protein. The current comprehensive study shows how various nsSNPs in the CTLA4 gene can modify the structural and functional characteristics of the protein, potentially influencing the pathogenesis of diseases in humans. Further, experimental studies are needed to analyze the effect of these nsSNPs on the susceptibility of pathological phenotype populations.