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Bioinformatics Advance Access published online on July 27, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm380
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Comparative modeling without implicit sequence alignments

Andrzej Kolinski * and Dominik Gront

University of Warsaw, Faculty of Chemistry, Pasteura 1 02-093 Warsaw, Poland

*To whom correspondence should be addressed. Dominik Gront, E-mail: dgront{at}chem.uw.edu.pl, kolinski{at}chem.uw.edu.pl


  Abstract

Motivation: The number of known protein sequences is about thousand times larger than the number of experimentally solved three dimensional structures. For more than half of the protein sequences a close or distant structural analog could be identified. The key starting point in a classical comparative modeling is to generate the best possible sequence alignment with a template or templates. With decreasing sequence similarity the number of errors in the alignments increases and these errors are the main causes of the decreasing accuracy of the molecular models generated. Here we propose a new approach to comparative modeling, which does not require the implicit alignment - the model building phase explores geometric, evolutionary and physical properties of a template (or templates).

Results: The proposed method requires prior identification of a template, although the initial sequence alignment is ignored. The model is built using a very efficient reduced representation search engine CABS to find the best possible superposition of the query protein onto the template represented as a three dimensional multi-featured scaffold. The criteria used include: sequence similarity, predicted secondary structure consistency, local geometric features and hydrophobicity profile. For more difficult cases the new method qualitatively outperforms existing schemes of comparative modeling. The algorithm unifies de novo modeling, three dimensional threading and sequence-based methods. The main idea is general and could be easily combined with other efficient modeling tools as Rosetta, UNRES, and others.

Contact: kolinski{at}chem.uw.edu.pl

Associate Editor: Prof. Burkhard Rost

Received on June 6, 2007; revised on June 25, 2007; accepted on July 14, 2007

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