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Nucleic Acids Research 2005 33(16):5343-5353; doi:10.1093/nar/gki842
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Published online 20 September 2005

© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oxfordjournals.org

Article

Gibbs sampling and helix-cap motifs

Erik Kruus1,*, Peter Thumfort1, Chao Tang1,2,3 and Ned S. Wingreen1,4

1NEC Laboratories America, Inc. 4 Independence Way, Princeton, NJ 08544, USA 2Department of Biopharmaceutical Sciences, California Institute for Quantitative Biomedical Research UCSF Box 2540 University of California San Francisco San Francisco, CA 94143-2540, USA 3Department of Biochemistry and Biophysics, California Institute for Quantitative Biomedical Research UCSF Box 2540 University of California San Francisco San Francisco, CA 94143-2540, USA 4Department of Molecular Biology, Princeton University Princeton, NJ 08544-1014, USA

*To whom correspondence should be addressed. Tel: +1 609 951 2628; Fax: +1 609 951 2482; Email: kruus{at}nec-labs.com

Received April 13, 2005. Revised August 8, 2005. Accepted August 30, 2005.

Protein backbones have characteristic secondary structures, including {alpha}-helices and ß-sheets. Which structure is adopted locally is strongly biased by the local amino acid sequence of the protein. Accurate (probabilistic) mappings from sequence to structure are valuable for both secondary-structure prediction and protein design. For the case of {alpha}-helix caps, we test whether the information content of the sequence–structure mapping can be self-consistently improved by using a relaxed definition of the structure. We derive helix-cap sequence motifs using database helix assignments for proteins of known structure. These motifs are refined using Gibbs sampling in competition with a null motif. Then Gibbs sampling is repeated, allowing for frameshifts of ±1 amino acid residue, in order to find sequence motifs of higher total information content. All helix-cap motifs were found to have good generalization capability, as judged by training on a small set of non-redundant proteins and testing on a larger set. For overall prediction purposes, frameshift motifs using all training examples yielded the best results. Frameshift motifs using a fraction of all training examples performed best in terms of true positives among top predictions. However, motifs without frameshifts also performed well, despite a roughly one-third lower total information content.

Correspondence may also be addressed to Ned S. Wingreen. Tel: +1 609 258 8476; Fax: +1 609 258 8616; Email: wingreen{at}molbio.princeton.edu


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