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Improved detection of homologous membrane proteins by inclusion of information from topology predictions

¹ Stockholm Bioinformatics Center, SCFAB, Stockholm University, SE-10691, Stockholm, Sweden
² Torhoutse steenweg 238, Brügge 8200, Belgium
³ Stockholm Bioinformatics Center, Department of Bichemistry and Biophysics, Stockholm University, SE-10691 Stockholm, Sweden

Reprint requests to: Arne Elofsson, Stockholm Bioinformatics Center, Stockholm University, SCFAB, SE-10691 Stockholm, Sweden; e-mail: arne{at}sbc.su.se; fax: 46-8-5537-8214.

A total of 20%–25% of the proteins in a typical genome are helical membrane proteins. The transmembrane regions of these proteins have markedly different properties when compared with globular proteins. This presents a problem when homology search algorithms optimized for globular proteins are applied to membrane proteins. Here we present modifications of the standard Smith-Waterman and profile search algorithms that significantly improve the detection of related membrane proteins. The improvement is based on the inclusion of information about predicted transmembrane segments in the alignment algorithm. This is done by simply increasing the alignment score if two residues predicted to belong to transmembrane segments are aligned with each other. Benchmarking over a test set of G-protein-coupled receptor sequences shows that the number of false positives is significantly reduced in this way, both when closely related and distantly related proteins are searched for.

Keywords: Membrane proteins; topology prediction; bioinformatics; homology search; threading

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