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Influence of PRKCE non-synonymous variants on protein dynamics and functionality

Khushbukhat Khan, Hania Shah, Areeba Rehman, Yasmin Badshah, Naeem Mahmood Ashraf, Maria Shabbir

2022Human Molecular Genetics23 citationsDOI

Abstract

Novel protein kinase C (nPKC) family member, protein kinase C epsilon (PKCε) is an AGC kinase superfamily member. It is associated with neurological and metabolic diseases as well as human cancers. No study so far has been conducted to identify genetic variations and their effect on PKCε folding and functioning. The present study aimed to identify mutational hotspots in PKCε and disease-causing non-synonymous variants (nsSNPs) along with the investigation of nsSNP impact on protein dynamics. Twenty-nine in silico tools were applied to determine nsSNP deleteriousness, their impact on protein dynamics and disease association, along with the prediction of PKCε post-translational modification (PTM) sites. The present study's outcomes indicated that most nsSNPs were concentrated in the PKCε hinge region and C-terminal tail. Most pathogenic variants mapped to the kinase domain. Regulatory domain variants influenced PKCε interaction with molecular players whereas kinase domain variants were predicted to impact its phosphorylation pattern and protein-protein interactions. Most PTM sites were mapped to the hinge region. PKCε nsSNPs have an association with oncogenicity and its expression dysregulation is responsible for poor overall survival. Understanding nsSNP structural impact is a primary step necessary for delineating the relationship of genetic level differences with protein phenotype. The obtained knowledge can eventually help in disease diagnosis and therapy design.

Topics & Concepts

BiologyIn silicoProtein kinase CGeneticsProtein kinase domainPhenotypeProtein kinase AKinaseGenetic associationGeneProtein domainComputational biologyBioinformaticsSingle-nucleotide polymorphismGenotypeMutantBioinformatics and Genomic NetworksGenomics and Rare DiseasesProtein Kinase Regulation and GTPase Signaling