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

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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.

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          The interpretation of protein structures: estimation of static accessibility.

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            Prediction of protein stability changes for single-site mutations using support vector machines.

            Accurate prediction of protein stability changes resulting from single amino acid mutations is important for understanding protein structures and designing new proteins. We use support vector machines to predict protein stability changes for single amino acid mutations leveraging both sequence and structural information. We evaluate our approach using cross-validation methods on a large dataset of single amino acid mutations. When only the sign of the stability changes is considered, the predictive method achieves 84% accuracy-a significant improvement over previously published results. Moreover, the experimental results show that the prediction accuracy obtained using sequence alone is close to the accuracy obtained using tertiary structure information. Because our method can accurately predict protein stability changes using primary sequence information only, it is applicable to many situations where the tertiary structure is unknown, overcoming a major limitation of previous methods which require tertiary information. The web server for predictions of protein stability changes upon mutations (MUpro), software, and datasets are available at http://www.igb.uci.edu/servers/servers.html. 2005 Wiley-Liss, Inc.
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              Mechanism of coupled folding and binding of an intrinsically disordered protein.

              Protein folding and binding are analogous processes, in which the protein 'searches' for favourable intramolecular or intermolecular interactions on a funnelled energy landscape. Many eukaryotic proteins are disordered under physiological conditions, and fold into ordered structures only on binding to their cellular targets. The mechanism by which folding is coupled to binding is poorly understood, but it has been hypothesized on theoretical grounds that the binding kinetics may be enhanced by a 'fly-casting' effect, where the disordered protein binds weakly and non-specifically to its target and folds as it approaches the cognate binding site. Here we show, using NMR titrations and (15)N relaxation dispersion, that the phosphorylated kinase inducible activation domain (pKID) of the transcription factor CREB forms an ensemble of transient encounter complexes on binding to the KIX domain of the CREB binding protein. The encounter complexes are stabilized primarily by non-specific hydrophobic contacts, and evolve by way of an intermediate to the fully bound state without dissociation from KIX. The carboxy-terminal helix of pKID is only partially folded in the intermediate, and becomes stabilized by intermolecular interactions formed in the final bound state. Future applications of our method will provide new understanding of the molecular mechanisms by which intrinsically disordered proteins perform their diverse biological functions.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                01 July 2014
                14 May 2014
                14 May 2014
                : 42
                : Web Server issue
                : W314-W319
                Affiliations
                [1 ]Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, UK
                [2 ]ACRF Rational Drug Discovery Centre and Biota Structural Biology Laboratory, St Vincents Institute of Medical Research, Fitzroy, VIC 3065, Australia
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +44 1223 766 033; Fax: +44 1223 766 002; Email: dpires@ 123456dcc.ufmg.br
                Correspondence may also be addressed to Tom L. Blundell. Tel: +44 1223 333628; Fax: +44 1223 766 002; Email: tlb20@ 123456cam.ac.uk
                Article
                10.1093/nar/gku411
                4086143
                24829462
                908a7390-de5b-4731-a837-ab2087e97610
                © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

                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.

                History
                : 29 April 2014
                : 28 April 2014
                : 1 March 2014
                Page count
                Pages: 6
                Categories
                Article
                Custom metadata
                1 July 2014

                Genetics
                Genetics

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