DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach

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ID: 302504
2014
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Abstract
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.
Reference Key
openalex_W2064488723 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Douglas E. V. Pires, David B. Ascher, T.L. Blundell
Journal Nucleic Acids Research
Year 2014
DOI
10.1093/nar/gku411
URL
https://academic.oup.com/nar/article-pdf/42/W1/W314/17423556/gku411.pdf
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