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Bioinformatics Advance Access published online on May 23, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl198
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received April 11, 2006
Revised May 10, 2006
Accepted May 18, 2006

Article

Identifying sequence regions undergoing conformational change via predicted continuum secondary structure

Mikael Bodén 1 * and Timothy L. Bailey 2

1 School of Information Technology and Electrical Engineering, QLD 4072, The University of Queensland, Australia
2 Institute for Molecular Bioscience, QLD 4072, The University of Queensland, Australia

* To whom correspondence should be addressed.
Mikael Bodén, E-mail: mikael{at}itee.uq.edu.au


  Abstract

Motivation: Conformational flexibility is essential to the function of many proteins, e.g. catalytic activity. To assist efforts in determining and exploring the functional properties of a protein, it is desirable to automatically identify regions that are prone to undergo conformational changes. It was recently shown that a probabilistic predictor of continuum secondary structure is more accurate than categorical predictors for structurally ambivalent sequence regions, suggesting that such models are suited to characterize protein flexibility.

Results: We develop a computational method for identifying regions that are prone to conformational change directly from the amino acid sequence. The method uses the entropy of the probabilistic output of an 8-class continuum secondary structure predictor. Results for 171 unique amino acid sequences with well-characterized variable structure (identified in the "Macromolecular movements database") indicate that the method is highly sensitive at identifying flexible protein regions, but false positives remain a problem. The method can be used to explore conformational flexibility of proteins (including hypothetical or synthetic ones) whose structure is yet to be determined experimentally.

Availability: The predictor, sequence data and supplementary studies are available at http://pprowler.itee.uq.edu.au/sspred/ and free for academic use.

Associate Editor: Martin Bishop
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