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Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations

BACKGROUND: Linking structural effects of mutations to functional outcomes is a major issue in structural bioinformatics, and many tools and studies have shown that specific structural properties such as stability and residue burial can be used to distinguish neutral variations and disease associate...

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Detalles Bibliográficos
Autores principales: Reumers, Joke, Schymkowitz, Joost, Rousseau, Fréderic
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745591/
https://www.ncbi.nlm.nih.gov/pubmed/19758473
http://dx.doi.org/10.1186/1471-2105-10-S8-S9
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author Reumers, Joke
Schymkowitz, Joost
Rousseau, Fréderic
author_facet Reumers, Joke
Schymkowitz, Joost
Rousseau, Fréderic
author_sort Reumers, Joke
collection PubMed
description BACKGROUND: Linking structural effects of mutations to functional outcomes is a major issue in structural bioinformatics, and many tools and studies have shown that specific structural properties such as stability and residue burial can be used to distinguish neutral variations and disease associated mutations. RESULTS: We have investigated 39 structural properties on a set of SNPs and disease mutations from the Uniprot Knowledge Base that could be mapped on high quality crystal structures and show that none of these properties can be used as a sole classification criterion to separate the two data sets. Furthermore, we have reviewed the annotation process from mutation to result and identified the liabilities in each step. CONCLUSION: Although excellent annotation results of various research groups underline the great potential of using structural bioinformatics to investigate the mechanisms underlying disease, the interpretation of such annotations cannot always be extrapolated to proteome wide variation studies. Difficulties for large-scale studies can be found both on the technical level, i.e. the scarcity of data and the incompleteness of the structural tool suites, and on the conceptual level, i.e. the correct interpretation of the results in a cellular context.
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spelling pubmed-27455912009-09-18 Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations Reumers, Joke Schymkowitz, Joost Rousseau, Fréderic BMC Bioinformatics Research BACKGROUND: Linking structural effects of mutations to functional outcomes is a major issue in structural bioinformatics, and many tools and studies have shown that specific structural properties such as stability and residue burial can be used to distinguish neutral variations and disease associated mutations. RESULTS: We have investigated 39 structural properties on a set of SNPs and disease mutations from the Uniprot Knowledge Base that could be mapped on high quality crystal structures and show that none of these properties can be used as a sole classification criterion to separate the two data sets. Furthermore, we have reviewed the annotation process from mutation to result and identified the liabilities in each step. CONCLUSION: Although excellent annotation results of various research groups underline the great potential of using structural bioinformatics to investigate the mechanisms underlying disease, the interpretation of such annotations cannot always be extrapolated to proteome wide variation studies. Difficulties for large-scale studies can be found both on the technical level, i.e. the scarcity of data and the incompleteness of the structural tool suites, and on the conceptual level, i.e. the correct interpretation of the results in a cellular context. BioMed Central 2009-08-27 /pmc/articles/PMC2745591/ /pubmed/19758473 http://dx.doi.org/10.1186/1471-2105-10-S8-S9 Text en Copyright © 2009 Reumers et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Reumers, Joke
Schymkowitz, Joost
Rousseau, Fréderic
Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations
title Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations
title_full Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations
title_fullStr Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations
title_full_unstemmed Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations
title_short Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations
title_sort using structural bioinformatics to investigate the impact of non synonymous snps and disease mutations: scope and limitations
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745591/
https://www.ncbi.nlm.nih.gov/pubmed/19758473
http://dx.doi.org/10.1186/1471-2105-10-S8-S9
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