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Rapid membrane protein topology prediction
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. (Arne Elofsson)
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.ORCID iD: 0000-0002-7115-9751
2011 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1460-2059, Vol. 27, no 9, 1322-1323 p.Article in journal (Refereed) Published
Abstract [en]

State-of-the-art methods for topology of α-helical membrane proteins are based on the use of time-consuming multiple sequence alignments obtained from PSI-BLAST or other sources. Here, we examine if it is possible to use the consensus of topology prediction methods that are based on single sequences to obtain a similar accuracy as the more accurate multiple sequence-based methods. Here, we show that TOPCONS-single performs better than any of the other topology prediction methods tested here, but ~6% worse than the best method that is utilizing multiple sequence alignments. AVAILABILITY AND IMPLEMENTATION: TOPCONS-single is available as a web server from and is also included for local installation from the web site. In addition, consensus-based topology predictions for the entire international protein index (IPI) is available from the web server and will be updated at regular intervals.

Place, publisher, year, edition, pages
2011. Vol. 27, no 9, 1322-1323 p.
National Category
Bioinformatics and Systems Biology
Research subject
Computing Science; Molecular Biotechnology
URN: urn:nbn:se:su:diva-61921DOI: 10.1093/bioinformatics/btr119ISI: 000290331600023OAI: diva2:438639
Swedish Research Council, VR-NT 2009-5072; VR-M 2007-3065EU, FP7, Seventh Framework Programme, 512092; 201924Swedish Foundation for Strategic Research
Available from: 2011-09-05 Created: 2011-09-05 Last updated: 2014-11-10Bibliographically approved
In thesis
1. Application of membrane protein topology prediction
Open this publication in new window or tab >>Application of membrane protein topology prediction
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Membrane proteins often have essential functions in the cell and many are important drug targets, yet only a small fraction of available protein structures are of membrane proteins. Experimental techniques for elucidating membrane protein structures have proven laborious and expensive, opening the field for comparatively inexpensive computational modeling. Topology prediction addresses a sub-problem of structure prediction for α-helical membrane proteins by modeling which parts of the peptide chain are in, and which parts are on either side, of the membrane.

This work describes an algorithm for combining the results of several topology prediction methods to increase prediction accuracy and to quantify prediction reliability, and a faster implementation of the algorithm applicable to large-scale genome data.

Further, topology prediction is applied, together with other sequence-based methods, to detect duplications in membrane proteins in whole genomes. We find more duplications in the genomes of yeast and E. coli than in human, possibly due to the abundance of nonduplicated GPCRs in human. A gene duplication and subsequent fusion event constitute a likely origin for duplicated proteins, yet only for one superfamily, the AcrB Multidrug Efflux Pump, do we find the duplicated unit in its nonduplicated form. This apparent scarcity of nonduplicated forms is confirmed when extending the study to the whole human genome.

Finally, a benchmark study of topology prediction on several comparably large datasets is described. We confirm previous results showing that methods utilizing homology information top the ranking of topology prediction methods. We also see that the separation of membrane proteins from non-membrane proteins has a partially different set of requirements than topology prediction of membrane proteins, and we suggest a pipeline using different methods for these two tasks.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics, Stockholm University, 2011. 65 p.
National Category
Biochemistry and Molecular Biology
Research subject
Biochemistry with Emphasis on Theoretical Chemistry
urn:nbn:se:su:diva-61950 (URN)978-91-7447-324-7 (ISBN)
Public defence
2011-10-14, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 10:00 (English)
At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Manuscript.Available from: 2011-09-22 Created: 2011-09-06 Last updated: 2011-09-19Bibliographically approved

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