DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach
Open accessAbstract
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.
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The graph-based signatures concept has proven to be a powerful approach and has been widely applied to the study of protein structure, including how mutations alter protein stability, dynamics and interactions with other molecules.
“Our previously described graph-based signatures concept has proven to be a powerful approach and has been widely applied to the study of protein structure, including how mutations alter protein stability (20,26), dynamics (27) and interactions with other molecules (20,28–34).”
From mCSM-PPI2: predicting the effects of mutations on protein–protein interactions (2019) · cites this paper as [26]
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- Authors
- Pires, D. E. V., Ascher, D. B., & Blundell, T. L.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Pires, D. E. V.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-05-14
- Volume
- 42
- Issue
- W1
- Pages
- W314-W319
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC4086143
- OpenAlex
- W2064488723
- Cited by
- 932
- References
- 25
- Citations by year
- 2026: 68 · 2025: 102 · 2024: 115 · 2023: 102 · 2022: 98 · 2021: 122 · 2020: 93 · 2019: 72 · 2018: 43 · 2017: 46 · 2016: 47 · 2015: 19 · 2014: 3 · 2012: 1
- FWCI
- 15.84
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Funders
- Wellcome Trust (093167, 093167/Z/10/Z)
- Winston Churchill Memorial Trust
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- State Government of Victoria
- National Health and Medical Research Council
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- duets, missense mutations, protein stability, non-synonymous single nucleotide polymorphisms, SDM, consensus forecasts, support vector machine, web server, protein engineering, cancer genomics
- MeSH terms
- Software, Computational Biology, Mutation, Missense, Internet, Protein Stability, Support Vector Machine
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