Prediction of Structurally-Determined Coiled-Coil Domains with Hidden Markov Models

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The coiled-coil protein domain is a widespread structural motif known to be involved in a wealth of key interactions in cells and organisms. Coiled-coil recognition and prediction of their location in a protein sequence are important steps for modeling protein structure and function. Nowadays, thanks to the increasing number of experimentally determined protein structures, a significant number of coiled-coil protein domains is available. This enables the development of methods suited to predict the coiled-coil structural motifs starting from the protein sequence. Several methods have been developed to predict classical heptads using manually annotated coiled-coil domains. In this paper we focus on the prediction structurally-determined coiled-coil segments. We introduce a new method based on hidden Markov models that complement the existing methods and outperforms them in the task of locating structurallydefined coiled-coil segments.

Original languageEnglish
Title of host publicationBioinformatics Research and Development : First International Conference, BIRD 2007 Proceedings
EditorsSepp Hochreiter, Roland Wagner
Number of pages11
Publication date2007
ISBN (Print)3-540-71232-1, 978-3-540-71232-9
Publication statusPublished - 2007
Event1st International Conference on Bioinformatics Research and Development, BIRD 2007 - Berlin, Germany
Duration: 12 Mar 200714 Mar 2007


Conference1st International Conference on Bioinformatics Research and Development, BIRD 2007
SeriesLecture Notes in Bioinformatics

    Research areas

  • Coiled-coil domains, Hidden Markov models, Protein structure prediction

ID: 199873053