Journal Article

pGenTHREADER and pDomTHREADER: new methods for improved protein fold recognition and superfamily discrimination

Anna Lobley, Michael I. Sadowski and David T. Jones

in Bioinformatics

Volume 25, issue 14, pages 1761-1767
Published in print July 2009 | ISSN: 1367-4803
Published online May 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp302
pGenTHREADER and pDomTHREADER: new methods for improved protein fold recognition and superfamily discrimination

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Motivation: Generation of structural models and recognition of homologous relationships for unannotated protein sequences are fundamental problems in bioinformatics. Improving the sensitivity and selectivity of methods designed for these two tasks therefore has downstream benefits for many other bioinformatics applications.

Results: We describe the latest implementation of the GenTHREADER method for structure prediction on a genomic scale. The method combines profile–profile alignments with secondary-structure specific gap-penalties, classic pair- and solvation potentials using a linear combination optimized with a regression SVM model. We find this combination significantly improves both detection of useful templates and accuracy of sequence-structure alignments relative to other competitive approaches. We further present a second implementation of the protocol designed for the task of discriminating superfamilies from one another. This method, pDomTHREADER, is the first to incorporate both sequence and structural data directly in this task and improves sensitivity and selectivity over the standard version of pGenTHREADER and three other standard methods for remote homology detection.

Contact: d.jones@cs.ucl.ac.uk

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  5202 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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