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Computational approach towards identification of pathogenic missense mutations in AMELX gene and their possible association with amelogenesis imperfecta

Amelogenin gene (AMEL-X) encodes an enamel protein called amelogenin, which plays a vital role in tooth development. Any mutations in this gene or the associated pathway lead to developmental abnormalities of the tooth. The present study aims to analyze functional missense mutations in AMEL-X genes...

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Autores principales: Shivani, Narendra, Smiline-Girija, Aseervatham Selvi, Paramasivam, Arumugam, Vijayashree-Priyadharsini, Jayaseelan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Shiraz University 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382399/
https://www.ncbi.nlm.nih.gov/pubmed/32802900
http://dx.doi.org/10.22099/mbrc.2020.35413.1456
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author Shivani, Narendra
Smiline-Girija, Aseervatham Selvi
Paramasivam, Arumugam
Vijayashree-Priyadharsini, Jayaseelan
author_facet Shivani, Narendra
Smiline-Girija, Aseervatham Selvi
Paramasivam, Arumugam
Vijayashree-Priyadharsini, Jayaseelan
author_sort Shivani, Narendra
collection PubMed
description Amelogenin gene (AMEL-X) encodes an enamel protein called amelogenin, which plays a vital role in tooth development. Any mutations in this gene or the associated pathway lead to developmental abnormalities of the tooth. The present study aims to analyze functional missense mutations in AMEL-X genes and derive an association with amelogenesis imperfecta. The information on missense mutations of human AMEL-X gene was collected from Ensembl database (https://asia.ensembl.org). Three different computational tools viz., SIFT, PolyPhen and PROVEAN were used to identify the deleterious or pathogenic forms of mutations in the gene studied. I-Mutant Suit was used to identify the stability of the proteins identified as deleterious by the three tools. Further, MutPred analysis revealed the pathogenicity of these mutations. Among 96 missense variants reported in AMEL-X gene, 18 were found to be deleterious using the three prediction tools (SIFT, PolyPhen and PROVEAN). When these variants were subjected to protein stability analysis, about 14 missense variants showed decreased stability whereas the other 8 variants showed increased stability. Further, these variants were analyzed using MutPred which identified 9 variants to be highly pathogenic. ExAC database revealed that all the pathogenic mutations had a minor allele frequency less than 0.01. The in silico analysis revealed highly pathogenic mutations in amelogenin gene which could have a putative association with amelogenesis imperfecta. These mutations should be screened in patients for early diagnosis of susceptibility to AI.
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spelling pubmed-73823992020-08-13 Computational approach towards identification of pathogenic missense mutations in AMELX gene and their possible association with amelogenesis imperfecta Shivani, Narendra Smiline-Girija, Aseervatham Selvi Paramasivam, Arumugam Vijayashree-Priyadharsini, Jayaseelan Mol Biol Res Commun Original Article Amelogenin gene (AMEL-X) encodes an enamel protein called amelogenin, which plays a vital role in tooth development. Any mutations in this gene or the associated pathway lead to developmental abnormalities of the tooth. The present study aims to analyze functional missense mutations in AMEL-X genes and derive an association with amelogenesis imperfecta. The information on missense mutations of human AMEL-X gene was collected from Ensembl database (https://asia.ensembl.org). Three different computational tools viz., SIFT, PolyPhen and PROVEAN were used to identify the deleterious or pathogenic forms of mutations in the gene studied. I-Mutant Suit was used to identify the stability of the proteins identified as deleterious by the three tools. Further, MutPred analysis revealed the pathogenicity of these mutations. Among 96 missense variants reported in AMEL-X gene, 18 were found to be deleterious using the three prediction tools (SIFT, PolyPhen and PROVEAN). When these variants were subjected to protein stability analysis, about 14 missense variants showed decreased stability whereas the other 8 variants showed increased stability. Further, these variants were analyzed using MutPred which identified 9 variants to be highly pathogenic. ExAC database revealed that all the pathogenic mutations had a minor allele frequency less than 0.01. The in silico analysis revealed highly pathogenic mutations in amelogenin gene which could have a putative association with amelogenesis imperfecta. These mutations should be screened in patients for early diagnosis of susceptibility to AI. Shiraz University 2020-06 /pmc/articles/PMC7382399/ /pubmed/32802900 http://dx.doi.org/10.22099/mbrc.2020.35413.1456 Text en This is an Open Access article distributed under the terms of the Creative Commons Attribution License, (http://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Shivani, Narendra
Smiline-Girija, Aseervatham Selvi
Paramasivam, Arumugam
Vijayashree-Priyadharsini, Jayaseelan
Computational approach towards identification of pathogenic missense mutations in AMELX gene and their possible association with amelogenesis imperfecta
title Computational approach towards identification of pathogenic missense mutations in AMELX gene and their possible association with amelogenesis imperfecta
title_full Computational approach towards identification of pathogenic missense mutations in AMELX gene and their possible association with amelogenesis imperfecta
title_fullStr Computational approach towards identification of pathogenic missense mutations in AMELX gene and their possible association with amelogenesis imperfecta
title_full_unstemmed Computational approach towards identification of pathogenic missense mutations in AMELX gene and their possible association with amelogenesis imperfecta
title_short Computational approach towards identification of pathogenic missense mutations in AMELX gene and their possible association with amelogenesis imperfecta
title_sort computational approach towards identification of pathogenic missense mutations in amelx gene and their possible association with amelogenesis imperfecta
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382399/
https://www.ncbi.nlm.nih.gov/pubmed/32802900
http://dx.doi.org/10.22099/mbrc.2020.35413.1456
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