Protein homology detection by HMM–HMM comparison

MOTIVATION: 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 PROFSIM 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 PROFSIM 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 PROFSIM and 17 times faster than COMPASS.