Open Access

BMC Bioinformatics

, volume 20 , issue 1 , publication number 473

HH-suite3 for fast remote homology detection and deep protein annotation

Martin Steinegger ^{1, 2}

Markus Meier ¹

Milot Mirdita ¹

Harald Vöhringer ^{1, 3}

Stephan J Haunsberger ⁴

Johannes Söding ¹

Hide authors affiliations Show authors affiliations: 4 affiliations

Quantitative and Computational Biology Group, Max-Planck Institute for Biophysical Chemistry, Munich, Germany |

Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA |

European Bioinformatics Institute, Cambridge, United Kingdom |

⁴

Royal College of Surgeons, Dublin, Ireland |

Publication type: Journal Article

Publication date: 2019-09-14

Springer Nature

BMC Bioinformatics

scimago Q1

wos Q1

SJR: 1.190

CiteScore: 6.8

Impact factor: 3.3

ISSN: 14712105

DOI: 10.1186/s12859-019-3019-7

Copy DOI

PubMed ID: 31521110

Biochemistry

Computer Science Applications

Molecular Biology

Structural Biology

Applied Mathematics

Abstract

Background

HH-suite is a widely used open source software suite for sensitive sequence similarity searches and protein fold recognition. It is based on pairwise alignment of profile Hidden Markov models (HMMs), which represent multiple sequence alignments of homologous proteins.

Results

We developed a single-instruction multiple-data (SIMD) vectorized implementation of the Viterbi algorithm for profile HMM alignment and introduced various other speed-ups. These accelerated the search methods HHsearch by a factor 4 and HHblits by a factor 2 over the previous version 2.0.16. HHblits3 is ∼10× faster than PSI-BLAST and ∼20× faster than HMMER3. Jobs to perform HHsearch and HHblits searches with many query profile HMMs can be parallelized over cores and over cluster servers using OpenMP and message passing interface (MPI). The free, open-source, GPLv3-licensed software is available at https://github.com/soedinglab/hh-suite.

Conclusion

The added functionalities and increased speed of HHsearch and HHblits should facilitate their use in large-scale protein structure and function prediction, e.g. in metagenomics and genomics projects.

Found

2 citations

Procter James

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Toshchakov Stepan

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Kravchenko Olesya

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Institute of Protein Research of the Russian Academy of Sciences

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1 citation

Maikova Anna

PhD in Biological/biomedical sciences

9 publications, 299 citations, 2 reviews

h-index: 7

Saint-Petersburg Pasteur Institute

Research interests

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1 citation

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DSc in Biological/biomedical sciences, professor

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Zoological Institute of the Russian Academy of Sciences

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Delft University of Technology

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Moscow Institute of Physics and Technology

Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences

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Malyshev Alexander

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h-index: 3

Lomonosov Moscow State University

Dukhov Research Institute of Automatics

Herzen Moscow Oncology Research Institute

Research interests

Computational chemistry

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Steinegger M. et al. HH-suite3 for fast remote homology detection and deep protein annotation // BMC Bioinformatics. 2019. Vol. 20. No. 1. 473

GOST all authors (up to 50) Copy

Steinegger M., Meier M., Mirdita M., Vöhringer H., Haunsberger S. J., Söding J. HH-suite3 for fast remote homology detection and deep protein annotation // BMC Bioinformatics. 2019. Vol. 20. No. 1. 473

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RIS Copy

TY - JOUR

DO - 10.1186/s12859-019-3019-7

UR - https://doi.org/10.1186/s12859-019-3019-7

TI - HH-suite3 for fast remote homology detection and deep protein annotation

T2 - BMC Bioinformatics

AU - Steinegger, Martin

AU - Meier, Markus

AU - Mirdita, Milot

AU - Vöhringer, Harald

AU - Haunsberger, Stephan J

AU - Söding, Johannes

PY - 2019

DA - 2019/09/14

PB - Springer Nature

IS - 1

VL - 20

PMID - 31521110

SN - 1471-2105

ER -

BibTex

Cite this

BibTex (up to 50 authors) Copy

@article{2019_Steinegger,

author = {Martin Steinegger and Markus Meier and Milot Mirdita and Harald Vöhringer and Stephan J Haunsberger and Johannes Söding},

title = {HH-suite3 for fast remote homology detection and deep protein annotation},

journal = {BMC Bioinformatics},

year = {2019},

volume = {20},

publisher = {Springer Nature},

month = {sep},

url = {https://doi.org/10.1186/s12859-019-3019-7},

number = {1},

pages = {473},

doi = {10.1186/s12859-019-3019-7}

}

Publisher

Springer Nature

Journal

BMC Bioinformatics

scimago Q1

wos Q1

SJR

1.190

CiteScore

6.8

Impact factor

3.3

ISSN

14712105 (Print, Electronic)