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DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach
Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, acc...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086143/ https://www.ncbi.nlm.nih.gov/pubmed/24829462 http://dx.doi.org/10.1093/nar/gku411 |
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author | Pires, Douglas E.V. Ascher, David B. Blundell, Tom L. |
author_facet | Pires, Douglas E.V. Ascher, David B. Blundell, Tom L. |
author_sort | Pires, Douglas E.V. |
collection | PubMed |
description | Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and predict their effects on protein stability. Despite the diversity of available computational methods in the literature, none has proven accurate and dependable on its own under all scenarios where mutation analysis is required. Here we present DUET, a web server for an integrated computational approach to study missense mutations in proteins. DUET consolidates two complementary approaches (mCSM and SDM) in a consensus prediction, obtained by combining the results of the separate methods in an optimized predictor using Support Vector Machines (SVM). We demonstrate that the proposed method improves overall accuracy of the predictions in comparison with either method individually and performs as well as or better than similar methods. The DUET web server is freely and openly available at http://structure.bioc.cam.ac.uk/duet. |
format | Online Article Text |
id | pubmed-4086143 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-40861432014-12-01 DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach Pires, Douglas E.V. Ascher, David B. Blundell, Tom L. Nucleic Acids Res Article Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and predict their effects on protein stability. Despite the diversity of available computational methods in the literature, none has proven accurate and dependable on its own under all scenarios where mutation analysis is required. Here we present DUET, a web server for an integrated computational approach to study missense mutations in proteins. DUET consolidates two complementary approaches (mCSM and SDM) in a consensus prediction, obtained by combining the results of the separate methods in an optimized predictor using Support Vector Machines (SVM). We demonstrate that the proposed method improves overall accuracy of the predictions in comparison with either method individually and performs as well as or better than similar methods. The DUET web server is freely and openly available at http://structure.bioc.cam.ac.uk/duet. Oxford University Press 2014-07-01 2014-05-14 /pmc/articles/PMC4086143/ /pubmed/24829462 http://dx.doi.org/10.1093/nar/gku411 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/3.0/ 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Pires, Douglas E.V. Ascher, David B. Blundell, Tom L. DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach |
title | DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach |
title_full | DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach |
title_fullStr | DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach |
title_full_unstemmed | DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach |
title_short | DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach |
title_sort | duet: a server for predicting effects of mutations on protein stability using an integrated computational approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086143/ https://www.ncbi.nlm.nih.gov/pubmed/24829462 http://dx.doi.org/10.1093/nar/gku411 |
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