A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene

Abstract

PLCG1 gene is responsible for many T-cell lymphoma subtypes, including peripheral T-cell lymphoma (PTCL), angioimmunoblastic T-cell lymphoma (AITL), cutaneous T-cell lymphoma (CTCL), adult T-cell leukemia/lymphoma along with other diseases. Missense mutations of this gene have already been found in patients of CTCL and AITL. The non-synonymous single nucleotide polymorphisms (nsSNPs) can alter the protein structure as well as its functions. In this study, probable deleterious and disease-related nsSNPs in PLCG1 were identified using SIFT, PROVEAN, PolyPhen-2, PhD-SNP, Pmut, and SNPS&GO tools. Further, their effect on protein stability was checked along with conservation and solvent accessibility analysis by I-mutant 2.0, MUpro, Consurf, and Netsurf 2.0 server. Some SNPs were finalized for structural analysis with PyMol and BIOVIA discovery studio visualizer. Out of the 16 nsSNPs which were found to be deleterious, ten nsSNPs had an effect on protein stability, and six mutations (L411P, R355C, G493D, R1158H, A401V and L455F) were predicted to be highly conserved. Among the six highly conserved mutations, four nsSNPs (R355C, A401V, L411P and L455F) were part of the catalytic domain. L411P, L455F and G493D made significant structural change in the protein structure. Two mutations-Y210C and R1158H had post-translational modification. In the 5’ and 3’ untranslated region, three SNPs, rs139043247, rs543804707, and rs62621919 showed possible miRNA target sites and DNA binding sites. This in silico analysis has provided a structured dataset of PLCG1 gene for further in vivo researches. With the limitation of computational study, it can still prove to be an asset for the identification and treatment of multiple diseases associated with the target gene.

Cross-neutralizing antibody against emerging Omicron subvariants of SARS-CoV-2 in infection-naïve individuals with homologous BNT162b2 or BNT162b2(WT+ BA.4/5) bivalent booster vaccination

“…This was also noted in another study which compared the immune evasion of EG.5.1 and XBB.2.3.2 [13]. GMTs to EG.5.1 and HK.3 differed signi cantly in the BBBB vaccine group which may be due to the L455F mutation in HK.3, a mutation shown by computational analysis to change the protein structure [14]. The greater immune evasion in JN.1 compared to BA.2.86 could be explained by a key mutation L455S in spike protein.…”

In Silico Analysis and In-depth Assessment of a Female Patient with a Missense Mutation in the F12 Gene Associated with Hereditary Angioedema Symptoms: A Case Study

“…3b). Such differences may lead to alterations in the molecular interactions within the protein, disrupting the stability of the position and domain where the mutation was identi ed [29,44,52]. It is interesting to note that our analysis indicates a decrease in protein stability from − 0.54 to -1.63 kcal/mol (Fig.…”

Cross-neutralizing antibody against emerging Omicron subvariants of SARS-CoV-2 in infection-naïve individuals with homologous BNT162b2 or BNT162b2(WT + BA.4/5) bivalent booster vaccination

“…This was also noted in another study which compared the immune evasion of EG.5.1 and XBB.2.3.2 [ 15 ]. GMTs to EG.5.1 and HK.3 differed significantly in the BBBB vaccine group which may be due to the L455F mutation in HK.3, a mutation shown by computational analysis to change the protein structure [ 16 ]. The greater immune evasion in JN.1 compared to BA.2.86 could be explained by a key mutation L455S in spike protein.…”