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Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach

The AKT1 (v-akt murine thymoma viral oncogene homologue 1) kinase is a member of most frequently activated proliferation and survival signaling pathway in cancer. Recently, hyperactivation of AKT1, due to functional point mutation in the pleckstrin homology (PH) domain of AKT1 gene, has been found t...

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Autores principales: Khan, Imran, Ansari, Irfan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5637233/
https://www.ncbi.nlm.nih.gov/pubmed/29114575
http://dx.doi.org/10.1016/j.bbrep.2017.04.013
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author Khan, Imran
Ansari, Irfan A.
author_facet Khan, Imran
Ansari, Irfan A.
author_sort Khan, Imran
collection PubMed
description The AKT1 (v-akt murine thymoma viral oncogene homologue 1) kinase is a member of most frequently activated proliferation and survival signaling pathway in cancer. Recently, hyperactivation of AKT1, due to functional point mutation in the pleckstrin homology (PH) domain of AKT1 gene, has been found to be associated with human colorectal, breast and ovarian cancer. Thus, considering its crucial role in cellular signaling pathway, a functional analysis of missense mutations of AKT1 gene was undertaken in this study. Twenty nine nsSNPs (non-synonymous single nucleotide polymorphism) within coding region of AKT1 gene were selected for our investigation and six SNPs were found to be deleterious by combinatorial predictions of various computational tools. RMSD values were calculated for the mutant models which predicted four substitutions (E17K, E319G, D32E and A255T) to be highly deleterious. The insight of the structural attribute was gained through analysis of, secondary structures, solvent accessibility and intermolecular hydrogen bond analysis which confirmed one missense mutation (E17K) to be highly deleterious nsSNPs. In conclusion, the investigated gene AKT1 has twenty nine SNPs in the coding region and through progressive analysis using different bioinformatics tools one highly deleterious SNP with rs121434592 was profiled. Thus, results of this study can pave a new platform to sort nsSNPs for several important regulatory genes that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case control studies.
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spelling pubmed-56372332017-11-07 Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach Khan, Imran Ansari, Irfan A. Biochem Biophys Rep Research Article The AKT1 (v-akt murine thymoma viral oncogene homologue 1) kinase is a member of most frequently activated proliferation and survival signaling pathway in cancer. Recently, hyperactivation of AKT1, due to functional point mutation in the pleckstrin homology (PH) domain of AKT1 gene, has been found to be associated with human colorectal, breast and ovarian cancer. Thus, considering its crucial role in cellular signaling pathway, a functional analysis of missense mutations of AKT1 gene was undertaken in this study. Twenty nine nsSNPs (non-synonymous single nucleotide polymorphism) within coding region of AKT1 gene were selected for our investigation and six SNPs were found to be deleterious by combinatorial predictions of various computational tools. RMSD values were calculated for the mutant models which predicted four substitutions (E17K, E319G, D32E and A255T) to be highly deleterious. The insight of the structural attribute was gained through analysis of, secondary structures, solvent accessibility and intermolecular hydrogen bond analysis which confirmed one missense mutation (E17K) to be highly deleterious nsSNPs. In conclusion, the investigated gene AKT1 has twenty nine SNPs in the coding region and through progressive analysis using different bioinformatics tools one highly deleterious SNP with rs121434592 was profiled. Thus, results of this study can pave a new platform to sort nsSNPs for several important regulatory genes that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case control studies. Elsevier 2017-04-21 /pmc/articles/PMC5637233/ /pubmed/29114575 http://dx.doi.org/10.1016/j.bbrep.2017.04.013 Text en © 2017 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Khan, Imran
Ansari, Irfan A.
Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach
title Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach
title_full Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach
title_fullStr Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach
title_full_unstemmed Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach
title_short Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach
title_sort prediction of a highly deleterious mutation e17k in akt-1 gene: an in silico approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5637233/
https://www.ncbi.nlm.nih.gov/pubmed/29114575
http://dx.doi.org/10.1016/j.bbrep.2017.04.013
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