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

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.

Possible prognostic impact of PKCι genetic variants in prostate cancer.

BACKGROUND: Single nucleotide polymorphisms (SNPs) have been linked with prostate cancer (PCa) and have shown potential as prognostic markers for advanced stages. Loss of function mutations in PKCι have been linked with increased risk of malignancy by enhancing tumor cell motility and invasion. We have evaluated the impact of two coding region SNPs on the PKCι gene (PRKCI) and their prognostic potential. METHODS: Genotypic association of non-synonymous PKCι SNPs rs1197750201 and rs1199520604 with PCa was determined through tetra-ARMS PCR. PKCι was docked with interacting partner Par-6 to determine the effect of these variants on PKCι binding capabilities. Molecular dynamic simulations of PKCι docked with Par-6 were performed to determine variant effects on PKCι protein interactions. The possible impact of changes in PKCι protein interactions on epithelial cell polarity was hypothesized. RESULTS: PKCι rs1199520604 mutant genotype TT showed association with PCa (p = 0.0055), while rs1197750201 mutant genotype AA also showed significant association with PCa (P = 0.0006). The binding interaction of PKCι with Par-6 was altered for both variants, with changes in Van der Waals energy and electrostatic energy of docked structures. CONCLUSION: Genotypic analysis of two non-synonymous PKCι variants in association with PCa prognosis was performed. Both variants in the PB1 domain showed potential as a prognostic marker for PCa. In silico analysis of the effect of the variants on PKCι protein interactions indicated they may be involved in PCa progression through aberration of epithelial cell polarity pathways.

Investigation of UTR Variants by Computational Approaches Reveal Their Functional Significance in PRKCI Gene Regulation.

Single nucleotide polymorphisms (SNPs) are associated with many diseases including neurological disorders, heart diseases, diabetes, and different types of cancers. In the context of cancer, the variations within non-coding regions, including UTRs, have gained utmost importance. In gene expression, translational regulation is as important as transcriptional regulation for the normal functioning of cells; modification in normal functions can be associated with the pathophysiology of many diseases. UTR-localized SNPs in the PRKCI gene were evaluated using the PolymiRTS, miRNASNP, and MicroSNIper for association with miRNAs. Furthermore, the SNPs were subjected to analysis using GTEx, RNAfold, and PROMO. The genetic intolerance to functional variation was checked through GeneCards. Out of 713 SNPs, a total of thirty-one UTR SNPs (three in 3' UTR region and twenty-nine in 5' UTR region) were marked as ≤2b by RegulomeDB. The associations of 23 SNPs with miRNAs were found. Two SNPs, rs140672226 and rs2650220, were significantly linked with expression in the stomach and esophagus mucosa. The 3' UTR SNPs rs1447651774 and rs115170199 and the 5' UTR region variants rs778557075, rs968409340, and 750297755 were predicted to destabilize the mRNA structure with substantial change in free energy (∆G). Seventeen variants were predicted to have linkage disequilibrium with various diseases. The SNP rs542458816 in 5' UTR was predicted to put maximum influence on transcription factor binding sites. Gene damage index(GDI) and loss of function (o:e) ratio values for PRKCI suggested that the gene is not tolerant to loss of function variants. Our results highlight the effects of 3' and 5' UTR SNP on miRNA, transcription and translation of PRKCI. These analyses suggest that these SNPs can have substantial functional importance in the PRKCI gene. Future experimental validation could provide further basis for the diagnosis and therapeutics of various diseases.

Impact of deleterious missense PRKCI variants on structural and functional dynamics of protein.

Protein kinase C iota (PKCÉ©) is a novel protein containing 596 amino acids and is also a member of atypical kinase family. The role of PKCÉ© has been explored in neurodegenerative diseases, neuroblastoma, ovarian and pancreatic cancers. Single nucleotide polymorphisms (SNPs) have not been studied in PKCÉ© till date. The purpose of the current study is to scrutinize the deleterious missense variants in PKCÉ© and determine the effect of these variants on stability and dynamics of the protein. The structure of protein PKCÉ© was predicted for the first time and post translational modifications were determined. Genetic variants of PKCÉ© were retrieved from ENSEMBL and only missense variants were further analyzed because of its linkage with diseases. The pathogenicity of missense variants, effect on structure and function of protein, association with cancer and conservancy of the protein residues were determined through computational approaches. It is observed that C1 and the pseudo substrate region has the highest number of pathogenic SNPs. Variations in the kinase domain of the protein are predicted to alter overall phosphorylation of the protein. Molecular dynamic simulations predicted noteworthy change in structural and functional dynamics of the protein because of these variants. The study revealed that nine deleterious variants can possibly contribute to malfunctioning of the protein and can be associated with diseases. This can be useful in diagnostics and developing therapeutics for diseases related to these polymorphisms.