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Nucleic Acids Research Advance Access originally published online on May 8, 2009
Nucleic Acids Research 2009 37(Web Server issue):W446-W451; doi:10.1093/nar/gkp325
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Nucleic Acids Research, 2009, Vol. 37, No. suppl_2 W446-W451
© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


Articles

HHomp—prediction and classification of outer membrane proteins

Michael Remmert1,2, Dirk Linke1, Andrei N. Lupas1 and Johannes Söding1,2,*

1Department of Protein Evolution, Max-Planck-Institute for Developmental Biology, Spemannstrasse 35, 72076 Tübingen and 2Gene Center and Center for Integrated Protein Science (CIPSM), Ludwig-Maximilians-University Munich, Feodor-Lynen-Str. 25, 81377 Munich, Germany

*To whom correspondence should be addressed. Tel: +49 2180 76742; Fax: +49 2180 76797; Email: soeding{at}lmb.uni-muenchen.de

Received January 30, 2009. Revised April 16, 2009. Accepted April 20, 2009.

Outer membrane proteins (OMPs) are the transmembrane proteins found in the outer membranes of Gram-negative bacteria, mitochondria and plastids. Most prediction methods have focused on analogous features, such as alternating hydrophobicity patterns. Here, we start from the observation that almost all β-barrel OMPs are related by common ancestry. We identify proteins as OMPs by detecting their homologous relationships to known OMPs using sequence similarity. Given an input sequence, HHomp builds a profile hidden Markov model (HMM) and compares it with an OMP database by pairwise HMM comparison, integrating OMP predictions by PROFtmb. A crucial ingredient is the OMP database, which contains profile HMMs for over 20 000 putative OMP sequences. These were collected with the exhaustive, transitive homology detection method HHsenser, starting from 23 representative OMPs in the PDB database. In a benchmark on TransportDB, HHomp detects 63.5% of the true positives before including the first false positive. This is 70% more than PROFtmb, four times more than BOMP and 10 times more than TMB-Hunt. In Escherichia coli, HHomp identifies 57 out of 59 known OMPs and correctly assigns them to their functional subgroups. HHomp can be accessed at http://toolkit.tuebingen.mpg.de/hhomp.


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