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1 Bioinformatics Unit, Department of Computer Science, University College London, London WC1E 6BT, UK
2 Institute of Cancer Genetics and Pharmacogenomics, Department of Biological Sciences, Brunel University, Uxbridge, Middlesex UB8 3PH, UK
Reprint requests to: David T. Jones, Bioinformatics Unit, Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK; e-mail: d.jones{at}cs.ucl.ac.uk; fax: +44 20 7387 1397.
The elucidation of the domain content of a given protein sequence in the absence of determined structure or significant sequence homology to known domains is an important problem in structural biology. Here we address how successfully the delineation of continuous domains can be accomplished in the absence of sequence homology using simple baseline methods, an existing prediction algorithm (Domain Guess by Size), and a newly developed method (DomSSEA). The study was undertaken with a view to measuring the usefulness of these prediction methods in terms of their application to fully automatic domain assignment. Thus, the sensitivity of each domain assignment method was measured by calculating the number of correctly assigned top scoring predictions. We have implemented a new continuous domain identification method using the alignment of predicted secondary structures of target sequences against observed secondary structures of chains with known domain boundaries as assigned by Class Architecture Topology Homology (CATH). Taking top predictions only, the success rate of the method in correctly assigning domain number to the representative chain set is 73.3%. The top prediction for domain number and location of domain boundaries was correct for 24% of the multidomain set (±20 residues). These results have been put into context in relation to the results obtained from the other prediction methods assessed.
Keywords: Domains; secondary structure; protein folding; sequence analysis; structure prediction
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