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TOPCONS: consensus prediction of membrane protein topology
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.ORCID iD: 0000-0002-7115-9751
2009 (English)In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 37, no Suppl. 2, W465-W468 p.Article in journal (Refereed) Published
Abstract [en]

TOPCONS (http://topcons.net/) is a web server for consensus prediction of membrane protein topology. The underlying algorithm combines an arbitrary number of topology predictions into one consensus prediction and quantifies the reliability of the prediction based on the level of agreement between the underlying methods, both on the protein level and on the level of individual TM regions. Benchmarking the method shows that overall performance levels match the best available topology prediction methods, and for sequences with high reliability scores, performance is increased by approximately 10 percentage points. The web interface allows for constraining parts of the sequence to a known inside/outside location, and detailed results are displayed both graphically and in text format.

Place, publisher, year, edition, pages
2009. Vol. 37, no Suppl. 2, W465-W468 p.
National Category
Biochemistry and Molecular Biology
Research subject
Biochemistry with Emphasis on Theoretical Chemistry
Identifiers
URN: urn:nbn:se:su:diva-34577DOI: 10.1093/nar/gkp363ISI: 000267889100081PubMedID: 19429891OAI: oai:DiVA.org:su-34577DiVA: diva2:285154
Funder
EU, FP7, Seventh Framework Programme, 512092; 201924Swedish Research CouncilSwedish Foundation for Strategic Research
Available from: 2010-01-11 Created: 2010-01-11 Last updated: 2017-12-12Bibliographically 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
Identifiers
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)
Opponent
Supervisors
Note
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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