Adam James Reid1, Corin Yeats, Christine Anne Orengo. 1. Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK. reid@bioichem.ucl.ac.uk
Abstract
MOTIVATION: 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. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: 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. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Sandun Rajapaksa; Dinithi Sumanaweera; Arthur M Lesk; Lloyd Allison; Peter J Stuckey; Maria Garcia de la Banda; David Abramson; Arun S Konagurthu Journal: Bioinformatics Date: 2022-06-24 Impact factor: 6.931
Authors: Alison Cuff; Oliver C Redfern; Lesley Greene; Ian Sillitoe; Tony Lewis; Mark Dibley; Adam Reid; Frances Pearl; Tim Dallman; Annabel Todd; Richard Garratt; Janet Thornton; Christine Orengo Journal: Structure Date: 2009-08-12 Impact factor: 5.006
Authors: Tony E Lewis; Ian Sillitoe; Antonina Andreeva; Tom L Blundell; Daniel W A Buchan; Cyrus Chothia; Alison Cuff; Jose M Dana; Ioannis Filippis; Julian Gough; Sarah Hunter; David T Jones; Lawrence A Kelley; Gerard J Kleywegt; Federico Minneci; Alex Mitchell; Alexey G Murzin; Bernardo Ochoa-Montaño; Owen J L Rackham; James Smith; Michael J E Sternberg; Sameer Velankar; Corin Yeats; Christine Orengo Journal: Nucleic Acids Res Date: 2012-11-30 Impact factor: 16.971