Methods of remote homology detection can be combined to increase coverage by 10% in the midnight zone.
BACKGROUND
A recent development in sequence-based remote homologue detection is the introduction of profile-profile comparison methods. These are more powerful than previous technologies and can detect potentially homologous relationships missed by structural classifications such as CATH and SCOP. As structural classifications traditionally act as the gold standard of homology this poses a challenge in benchmarking them.


RESULTS
We present a novel approach which allows an accurate benchmark of these methods against the CATH structural classification. We then apply this approach to assess the accuracy of a range of publicly available methods for remote homology detection including several profile-profile methods (COMPASS, HHSearch, PRC) from two perspectives. First, in distinguishing homologous domains from non-homologues and second, in annotating proteomes with structural domain families. PRC is shown to be the best method for distinguishing homologues. We show that SAM is the best practical method for annotating genomes, whilst using COMPASS for the most remote homologues would increase coverage. Finally, we introduce a simple approach to increase the sensitivity of remote homologue detection by up to 10%. This is achieved by combining multiple methods with a jury vote.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Reid
Adam James
AJ
Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK. reid@bioichem.ucl.ac.uk
Yeats
Corin
C
Orengo
Christine Anne
CA
D000465:Algorithms; D000595:Amino Acid Sequence; D019143:Evolution, Molecular; D008969:Molecular Sequence Data; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid