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Bioinformatics Advance Access published online on November 29, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti805
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received August 25, 2005
Revised November 18, 2005
Accepted November 27, 2005

Article

Simshift: identifying structural similarities from NMR chemical shifts

Simon W. Ginzinger 1 * and Johannes Fischer 1

1 LFE Bioinformatik, Institut für Informatik, Ludwig-Maximilians-Universität, München, Amalienstr. 17, D-80333 München, Germany

* To whom correspondence should be addressed.
Simon W. Ginzinger, E-mail: Simon.Ginzinger{at}bio.ifi.lmu.de


  Abstract

Motivation: An important quantity that arises in NMR spectroscopy experiments are chemical shifts. The interpretation of these data is mostly done by human experts; to our knowledge there are no algorithms that predict protein structure from chemical shift sequences alone. One approach to facilitate this process could be to compare two such sequences, where the structure of one protein has already been resolved. Our claim is that NMR-similarity thereby found implies structural similarity of the respective proteins.

Results: We present an algorithm to identify structural similarities of proteins by aligning their associated chemical shift sequences. To evaluate the correctness of our predictions, we propose a benchmark set of protein pairs that have high structural similarity, but low sequence similarity (because with high sequence similarity the structural similarities could easily be detected by a sequence alignment algorithm). We compare our results to those of HHsearch and SSEA and show that our method outperforms both in more than 50% of all cases.


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