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In Silico-Based Structural Evaluation to Categorize the Pathogenicity of Mutations Identified in the RAD Class of Proteins
[Image: see text] RAD genes, known as double-strand break repair proteins, play a major role in maintaining the genomic integrity of a cell by carrying out essential DNA repair functions via double-strand break repair pathways. Mutations in the RAD class of proteins show high susceptibility to breas...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034773/ https://www.ncbi.nlm.nih.gov/pubmed/36969410 http://dx.doi.org/10.1021/acsomega.2c07802 |
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author | Anwaar, Aaliya Varma, Ashok K. Baruah, Reshita |
author_facet | Anwaar, Aaliya Varma, Ashok K. Baruah, Reshita |
author_sort | Anwaar, Aaliya |
collection | PubMed |
description | [Image: see text] RAD genes, known as double-strand break repair proteins, play a major role in maintaining the genomic integrity of a cell by carrying out essential DNA repair functions via double-strand break repair pathways. Mutations in the RAD class of proteins show high susceptibility to breast and ovarian cancers; however, adequate research on the mutations identified in these genes has not been extensively reported for their deleterious effects. Changes in the folding pattern of RAD proteins play an important role in protein–protein interactions and also functions. Missense mutations identified from four cancer databases, cBioPortal, COSMIC, ClinVar, and gnomAD, cause aberrant conformations, which may lead to faulty DNA repair mechanisms. It is therefore necessary to evaluate the effects of pathogenic mutations of RAD proteins and their subsequent role in breast and ovarian cancers. In this study, we have used eight computational prediction servers to analyze pathogenic mutations and understand their effects on the protein structure and function. A total of 5122 missense mutations were identified from four different cancer databases, of which 1165 were predicted to be pathogenic using at least five pathogenicity prediction servers. These mutations were characterized as high-risk mutations based on their location in the conserved domains and subsequently subjected to structural stability characterization. The mutations included in the present study were selected from clinically relevant mutants in breast cancer pedigrees. Comparative folding patterns and intra-atomic interaction results showed alterations in the structural behavior of RAD proteins, specifically RAD51C triggered by mutations G125V and L138F and RAD51D triggered by mutations S207L and E233G. |
format | Online Article Text |
id | pubmed-10034773 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-100347732023-03-24 In Silico-Based Structural Evaluation to Categorize the Pathogenicity of Mutations Identified in the RAD Class of Proteins Anwaar, Aaliya Varma, Ashok K. Baruah, Reshita ACS Omega [Image: see text] RAD genes, known as double-strand break repair proteins, play a major role in maintaining the genomic integrity of a cell by carrying out essential DNA repair functions via double-strand break repair pathways. Mutations in the RAD class of proteins show high susceptibility to breast and ovarian cancers; however, adequate research on the mutations identified in these genes has not been extensively reported for their deleterious effects. Changes in the folding pattern of RAD proteins play an important role in protein–protein interactions and also functions. Missense mutations identified from four cancer databases, cBioPortal, COSMIC, ClinVar, and gnomAD, cause aberrant conformations, which may lead to faulty DNA repair mechanisms. It is therefore necessary to evaluate the effects of pathogenic mutations of RAD proteins and their subsequent role in breast and ovarian cancers. In this study, we have used eight computational prediction servers to analyze pathogenic mutations and understand their effects on the protein structure and function. A total of 5122 missense mutations were identified from four different cancer databases, of which 1165 were predicted to be pathogenic using at least five pathogenicity prediction servers. These mutations were characterized as high-risk mutations based on their location in the conserved domains and subsequently subjected to structural stability characterization. The mutations included in the present study were selected from clinically relevant mutants in breast cancer pedigrees. Comparative folding patterns and intra-atomic interaction results showed alterations in the structural behavior of RAD proteins, specifically RAD51C triggered by mutations G125V and L138F and RAD51D triggered by mutations S207L and E233G. American Chemical Society 2023-03-08 /pmc/articles/PMC10034773/ /pubmed/36969410 http://dx.doi.org/10.1021/acsomega.2c07802 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Anwaar, Aaliya Varma, Ashok K. Baruah, Reshita In Silico-Based Structural Evaluation to Categorize the Pathogenicity of Mutations Identified in the RAD Class of Proteins |
title | In Silico-Based
Structural Evaluation to Categorize
the Pathogenicity of Mutations Identified in the RAD Class of Proteins |
title_full | In Silico-Based
Structural Evaluation to Categorize
the Pathogenicity of Mutations Identified in the RAD Class of Proteins |
title_fullStr | In Silico-Based
Structural Evaluation to Categorize
the Pathogenicity of Mutations Identified in the RAD Class of Proteins |
title_full_unstemmed | In Silico-Based
Structural Evaluation to Categorize
the Pathogenicity of Mutations Identified in the RAD Class of Proteins |
title_short | In Silico-Based
Structural Evaluation to Categorize
the Pathogenicity of Mutations Identified in the RAD Class of Proteins |
title_sort | in silico-based
structural evaluation to categorize
the pathogenicity of mutations identified in the rad class of proteins |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034773/ https://www.ncbi.nlm.nih.gov/pubmed/36969410 http://dx.doi.org/10.1021/acsomega.2c07802 |
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