Open Access

Bioinformatics, volume 21, issue 7, pages 951-960

Protein homology detection by HMM-HMM comparison

Johannes Söding ¹

Hide authors affiliations Show authors affiliations: 1 affiliation

Department of Protein Evolution, Max-Planck-Institute for Developmental Biology, Spemannstrasse 35, D-72076 Tübingen, Germany. |

Publication type: Journal Article

Publication date: 2004-11-05

Oxford University Press

Journal: Bioinformatics

Quartile SCImago

Quartile WOS

Impact factor: 5.8

ISSN: 13674803, 13674811, 14602059

DOI: 10.1093/bioinformatics/bti125

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Biochemistry

Computer Science Applications

Molecular Biology

Statistics and Probability

Computational Mathematics

Computational Theory and Mathematics

Abstract

Protein homology detection and sequence alignment are at the basis of protein structure prediction, function prediction and evolution.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.

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Söding J. Protein homology detection by HMM-HMM comparison // Bioinformatics. 2004. Vol. 21. No. 7. pp. 951-960.

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Söding J. Protein homology detection by HMM-HMM comparison // Bioinformatics. 2004. Vol. 21. No. 7. pp. 951-960.

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TY - JOUR

DO - 10.1093/bioinformatics/bti125

UR - https://doi.org/10.1093/bioinformatics/bti125

TI - Protein homology detection by HMM-HMM comparison

T2 - Bioinformatics

AU - Söding, Johannes

PY - 2004

DA - 2004/11/05 00:00:00

PB - Oxford University Press

SP - 951-960

IS - 7

VL - 21

SN - 1367-4803

SN - 1367-4811

SN - 1460-2059

ER -

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@article{2004_Söding,

author = {Johannes Söding},

title = {Protein homology detection by HMM-HMM comparison},

journal = {Bioinformatics},

year = {2004},

volume = {21},

publisher = {Oxford University Press},

month = {nov},

url = {https://doi.org/10.1093/bioinformatics/bti125},

number = {7},

pages = {951--960},

doi = {10.1093/bioinformatics/bti125}

}

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Söding, Johannes. “Protein homology detection by HMM-HMM comparison.” Bioinformatics, vol. 21, no. 7, Nov. 2004, pp. 951-960. https://doi.org/10.1093/bioinformatics/bti125.

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Publisher

Oxford University Press

Journal

Bioinformatics

Quartile SCImago

Quartile WOS

Impact factor

5.8

ISSN

13674803 (Print)
13674811 (Electronic)
14602059 (Electronic)