Pathogenic predictions of non-synonymous variants and their impacts: A computational assessment of ARHGEF6 gene

Abstract

Introduction: ARHGEF6, a key member and activator of RhoGTPases family that is involved in G-Protein Coupled receptor (GPCR) pathway and stimulate Rho dependent signals in the brain, and mutations in this gene can cause intellectual disability (ID) in Human. Therefore, we aimed to study the consequences of ARHGEF6 non-synonymous mutations by using advanced computational methods.

Methods: Classification of the genetic mutations in ARHGEF6 gene was performed according to Ensembl Genome Database and data mining was done using ensemble tools. The functional and disease effect of missense mutations, and pathogenic characteristics of amino acid substitutions of ARHGEF6 were analyzed using eleven diversified computational tools and servers.

Results: Overall, 47 ARHGEF6 non-synonymous (NS) variants were predicted to be deleterious by SIFT, Polyphen2 and PROVEAN scores. Above that, SNPs&GO and PhD SNP were further graded 21 customarily pathogenic NS-variants. Protein stability analysis resulted in the significant change in terms of △△G of most identified NS-variants, except K609I. Seven variants were analyzed to be located on most potential domain RhoGEF/DH, whereas the remaining 14 were distributed on CH, SH3, PH and BP domains. Furthermore, pathogenic effects of mutations on protein was presented with different parameters using MutPred2 and PROJECT HOPE. Additionally, STRING network data predicted GIT2 and PARVB as most interacted partners of ARHGEF6.

Conclusion: These findings can be supportive of genotype-phenotype research as well as the development in pharmacogenetics studies. Finally, this study revealed a significance of computational methods to figure out highly pathogenic genomic variants linked with the structural and functional relationship of ARHGEF6 protein.

Keywords: Computational methods, ARHGEF6, Intellectual disability, Missense mutation