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    Computational Methods for the Prediction of the Structure and Interactions of Coiled-Coil Peptides

    Access Status
    Fulltext not available
    Authors
    Gandhi, Neha
    Mancera, Ricardo
    Date
    2008
    Type
    Journal Article
    
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    Citation
    Gandhi, Neha and Mancera, Ricardo. 2008. Computational Methods for the Prediction of the Structure and Interactions of Coiled-Coil Peptides. Current Bioinformatics 3: pp. 149-161.
    Source Title
    Current Bioinformatics
    ISSN
    15748936
    Faculty
    Faculty of Health Sciences
    School of Biomedical Sciences
    URI
    http://hdl.handle.net/20.500.11937/27216
    Collection
    • Curtin Research Publications
    Abstract

    The past several years have seen significant advances in the development of computational methods for the prediction of the structure and interactions of coiled-coil peptides. These methods are generally based on pairwise correlations of amino acids, helical propensity, thermal melts and the energetics of sidechain interactions, as well as statistical patterns based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) techniques. These methods are complemented by a number of public databases that contain sequences, motifs, domains and other details of coiled-coil structures identified by various algorithms. Some of these computational methods have been developed to make predictions of coiled-coil structure on the basis of sequence information; however, structural predictions of the oligomerisation state of these peptides still remains largely an open question due to the dynamic behaviour of these molecules. This review focuses on existing in silico methods for the prediction of coiled-coil peptides of functional importance using sequenceand/or three-dimensional structural data.

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