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Bioinformatics Advance Access originally published online on November 29, 2005
Bioinformatics 2006 22(4):460-465; 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

SimShift: Identifying structural similarities from NMR chemical shifts

Simon W. Ginzinger * and Johannes Fischer

LFE Bioinformatik, Institut für Informatik, Ludwig-Maximilians-Universität München Amalienstraße 17, D-80333 München, Germany

*To whom correspondence should be addressed.

Motivation: An important quantity that arises in NMR spectroscopy experiments is the chemical shift. 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 similarity of chemical shifts 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 with those of HHsearch and SSEA and show that our method outperforms both in >50% of all cases.

Contact: Simon.Ginzinger{at}bio.ifi.lmu.de

Received on August 25, 2005; revised on November 18, 2005; accepted on November 27, 2005

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