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Open Access Highly Accessed Technical Note

GPCRTree: online hierarchical classification of GPCR function

Matthew N Davies1*, Andrew Secker2, Mark Halling-Brown3, David S Moss3, Alex A Freitas2, Jon Timmis4, Edward Clark4 and Darren R Flower1

Author Affiliations

1 The Jenner Institute, University of Oxford, Compton, Newbury, Berkshire, RG20 7NN, UK

2 Department of Computing and Centre for BioMedical Informatics, University of Kent, Canterbury, Kent, CT2 7NF, UK

3 Department of Crystallography, Birkbeck College, University of London, Malet Street, London, WC1E 7HX, UK

4 Departments of Computer Science and Electronics, University of York, Heslington, York, YO10 5DD, UK

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BMC Research Notes 2008, 1:67  doi:10.1186/1756-0500-1-67

Published: 21 August 2008

Abstract

Background

G protein-coupled receptors (GPCRs) play important physiological roles transducing extracellular signals into intracellular responses. Approximately 50% of all marketed drugs target a GPCR. There remains considerable interest in effectively predicting the function of a GPCR from its primary sequence.

Findings

Using techniques drawn from data mining and proteochemometrics, an alignment-free approach to GPCR classification has been devised. It uses a simple representation of a protein's physical properties. GPCRTree, a publicly-available internet server, implements an algorithm that classifies GPCRs at the class, sub-family and sub-subfamily level.

Conclusion

A selective top-down classifier was developed which assigns sequences within a GPCR hierarchy. Compared to other publicly available GPCR prediction servers, GPCRTree is considerably more accurate at every level of classification. The server has been available online since March 2008 at URL: http://igrid-ext.cryst.bbk.ac.uk/gpcrtree/ webcite.