Novel protein kinase C (nPKC) family member, Protein kinase C epsilon (PKCε) is an AKC kinase superfamily member. It is associated with neurological and metabolic diseases as well as human cancer. 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 nsSNPs impact on protein dynamics. Twenty-nine in silico tools were applied to determine nsSNPs’ 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 on 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 on the hinge region. PKCε nsSNPs have an association with oncogenicity and its expression dysregulation is responsible for poor overall survival. Understanding nsSNPs 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.
Protein kinase C iota (PKCɩ) is a novel protein containing 596 amino acids and is also a member of atypical kinase family. The role of PKCɩ has been explored in neurodegenerative diseases, neuroblastoma, ovarian and pancreatic cancers. Single nucleotide polymorphisms (SNPs) have not been studied in PKCɩ till date. The purpose of the current study is to scrutinize the deleterious missense variants in PKCɩ and determine the effect of these variants on stability and dynamics of the protein. The structure of protein PKCɩ was predicted for the first time and post translational modifications were determined. Genetic variants of PKCɩ 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.
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.
Breast cancer is one of the most common causes of fatalities in females globally. Rising cases of drug resistance against existing chemotherapeutics are great problem. To address this issue, there is a need to find appropriate biomarker that could be used to detect cancer at early stages, so drug resistance development can be avoided. Protein Kinase C iota (PKCɩ), an AGC kinase, has an oncogenic role in cancers and its expression and SNPs have been reported to be associated with the cancer development. So, the study aims were to examine the expression of PKCɩ, Protein Kinase B (AKT), Suppressor of cytokine signaling 3 (SOC3), Vascular endothelial growth factor (VEGF), Krupple like factor 3 (KLF3), Tumor protein D52 (TPD52), Hypoxia inducible factor (HIF1α) and microRNA-124 (miR-124) in breast cancer and association of PKCɩ variants (G34W & F66Y) with breast cancer.: Genetic expression assay was performed through real time PCR, whereas the genotypic association of PKCɩ SNPs with breast cancer was accomplished through Tetra-ARMS PCR. The overall expression levels of PKCɩ, AKT, SOC3, VEGF, HIF1α and TPD52 were elevated in patients as compared to control whereas the expression levels of miR-124 and KLF3 were lowered in patients. Positive association of variant G34W (TT) of PKCɩ with breast cancer has been explored while no association of variant F66Y with breast cancer was found. Hence, the results suggest that PKCɩ and related genes can serve as the potential biomarkers for the early-diagnosis and prognosis of breast cancer.
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