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Localized structural frustration for evaluating the impact of sequence variants

Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype–genotype associations. Protein structures pr...

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Detalles Bibliográficos
Autores principales: Kumar, Sushant, Clarke, Declan, Gerstein, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5137452/
https://www.ncbi.nlm.nih.gov/pubmed/27915290
http://dx.doi.org/10.1093/nar/gkw927
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author Kumar, Sushant
Clarke, Declan
Gerstein, Mark
author_facet Kumar, Sushant
Clarke, Declan
Gerstein, Mark
author_sort Kumar, Sushant
collection PubMed
description Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype–genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events.
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spelling pubmed-51374522016-12-06 Localized structural frustration for evaluating the impact of sequence variants Kumar, Sushant Clarke, Declan Gerstein, Mark Nucleic Acids Res Computational Biology Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype–genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events. Oxford University Press 2016-12-01 2016-10-18 /pmc/articles/PMC5137452/ /pubmed/27915290 http://dx.doi.org/10.1093/nar/gkw927 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Computational Biology
Kumar, Sushant
Clarke, Declan
Gerstein, Mark
Localized structural frustration for evaluating the impact of sequence variants
title Localized structural frustration for evaluating the impact of sequence variants
title_full Localized structural frustration for evaluating the impact of sequence variants
title_fullStr Localized structural frustration for evaluating the impact of sequence variants
title_full_unstemmed Localized structural frustration for evaluating the impact of sequence variants
title_short Localized structural frustration for evaluating the impact of sequence variants
title_sort localized structural frustration for evaluating the impact of sequence variants
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5137452/
https://www.ncbi.nlm.nih.gov/pubmed/27915290
http://dx.doi.org/10.1093/nar/gkw927
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