title: Protein homology detection by HMM-HMM comparison.
abstract: BACKGROUND
  Protein homology detection and sequence alignment are at the basis of protein structure prediction, function prediction and evolution.
  
  
  RESULTS
  We have generalized the alignment of protein sequences with a profile hidden Markov model (HMM) to the case of pairwise alignment of profile HMMs. We present a method for detecting distant homologous relationships between proteins based on this approach. The method (HHsearch) is benchmarked together with BLAST, PSI-BLAST, HMMER and the profile-profile comparison tools PROF_SIM and COMPASS, in an all-against-all comparison of a database of 3691 protein domains from SCOP 1.63 with pairwise sequence identities below 20%.Sensitivity: When the predicted secondary structure is included in the HMMs, HHsearch is able to detect between 2.7 and 4.2 times more homologs than PSI-BLAST or HMMER and between 1.44 and 1.9 times more than COMPASS or PROF_SIM for a rate of false positives of 10%. Approximately half of the improvement over the profile-profile comparison methods is attributable to the use of profile HMMs in place of simple profiles. Alignment quality: Higher sensitivity is mirrored by an increased alignment quality. HHsearch produced 1.2, 1.7 and 3.3 times more good alignments ('balanced' score >0.3) than the next best method (COMPASS), and 1.6, 2.9 and 9.4 times more than PSI-BLAST, at the family, superfamily and fold level, respectively.Speed: HHsearch scans a query of 200 residues against 3691 domains in 33 s on an AMD64 2GHz PC. This is 10 times faster than PROF_SIM and 17 times faster than COMPASS.
authors.affiliation: Department of Protein Evolution, Max-Planck-Institute for Developmental Biology Spemannstrasse 35, D-72076 Tübingen, Germany. johannes.soeding@tuebingen.mpg.de
authors.forename: Johannes
authors.initials: J
authors.lastname: Söding
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D003198:Computer Simulation; D008390:Markov Chains; D008956:Models, Chemical; D015233:Models, Statistical; D008969:Molecular Sequence Data; D011506:Proteins / Q000032:analysis / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D012984:Software
chemical_list: D011506:Proteins