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Bioinformatics 2007 23(2):e219-e224; doi:10.1093/bioinformatics/btl310
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Structural Bioinformatics

Using an alignment of fragment strings for comparing protein structures

Iddo Friedberg 1,*,{dagger}, Tim Harder 1,{dagger}, Rachel Kolodny 2,3, Einat Sitbon 4, Zhanwen Li 1 and Adam Godzik 1

1 Program in Bioinformatics and Systems Biology, Burnham Institute for Medical Research La Jolla, CA, USA
2 Department of Biochemistry and Molecular Biophysics Columbia University, New York NY, USA
3 Howard Hughes Medical Institute USA
4 Department of Molecular Genetics, The Weizmann Institute Rehovot, Israel

*To whom correspondence should be addressed.


  Abstract

Motivation: Most methods that are used to compare protein structures use three-dimensional (3D) structural information. At the same time, it has been shown that a 1D string representation of local protein structure retains a degree of structural information. This type of representation can be a powerful tool for protein structure comparison and classification, given the arsenal of sequence comparison tools developed by computational biology. However, in order to do so, there is a need to first understand how much information is contained in various possible 1D representations of protein structure.

Results: Here we describe the use of a particular structure fragment library, denoted here as KL-strings, for the 1D representation of protein structure. Using KL-strings, we develop an infrastructure for comparing protein structures with a 1D representation. This study focuses on the added value gained from such a description. We show the new local structure language adds resolution to the traditional three-state (helix, strand and coil) secondary structure description, and provides a high degree of accuracy in recognizing structural similarities when used with a pairwise alignment benchmark. The results of this study have immediate applications towards fast structure recognition, and for fold prediction and classification.

Contact: idoerg{at}burnham.org

Supplementary information: http://iddo-friedberg.org/ECCB06-supplement

{dagger}The authors wish it to be known that, in their opinion the first two authors should be regarded as joint First Authors.


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