FreeContact: fast and free software for protein contact prediction from residue co-evolution

Background 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-f...

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Published inBMC bioinformatics Vol. 15; no. 1; p. 85
Main Authors Kaján, László, Hopf, Thomas A, Kalaš, Matúš, Marks, Debora S, Rost, Burkhard
Format Journal Article
LanguageEnglish
Published London BioMed Central 26.03.2014
BioMed Central Ltd
Springer Nature B.V
Subjects
Online AccessGet full text
ISSN1471-2105
1471-2105
DOI10.1186/1471-2105-15-85

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Abstract Background 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software. Results Here, we present FreeContact , a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library “libfreecontact”, complete with command line tool “freecontact”, as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability. Conclusions FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud).
AbstractList 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software.BACKGROUND20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software.Here, we present FreeContact, a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library "libfreecontact", complete with command line tool "freecontact", as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability.RESULTSHere, we present FreeContact, a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library "libfreecontact", complete with command line tool "freecontact", as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability.FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud).CONCLUSIONSFreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud).
Doc number: 85 Abstract Background: 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software. Results: Here, we present FreeContact , a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library "libfreecontact", complete with command line tool "freecontact", as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability. Conclusions: FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud).
20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software. Here, we present FreeContact, a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library "libfreecontact", complete with command line tool "freecontact", as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability. FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud).
Background 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software. Results Here, we present FreeContact, a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library "libfreecontact", complete with command line tool "freecontact", as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability. Conclusions FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud). Keywords: Protein structure prediction, Protein sequence analysis, Fast protein contact prediction, 2D prediction, Open-source software, EVfold, EVcouplings, PSICOV, mfDCA, BioXSD, Debian package
Background 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software. Results Here, we present FreeContact , a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library “libfreecontact”, complete with command line tool “freecontact”, as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability. Conclusions FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud).
Background: 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software. Results: Here, we present FreeContact, a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library "libfreecontact", complete with command line tool "freecontact", as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability. Conclusions: FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud).
20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software. Here, we present FreeContact, a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library "libfreecontact", complete with command line tool "freecontact", as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability. FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud).
ArticleNumber 85
Audience Academic
Author Rost, Burkhard
Hopf, Thomas A
Kalaš, Matúš
Kaján, László
Marks, Debora S
AuthorAffiliation 5 Institute of Advanced Study (TUM-IAS), Lichtenbergstr. 2a, Garching/Munich 85748, Germany
2 Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA
4 Department of Informatics, University of Bergen, Bergen 5008, Norway
1 Department for Bioinformatics and Computational Biology, TU Munich, Boltzmannstraße 3, Garching 85748, Germany
6 WZW – Weihenstephan, Alte Akademie 8, Freising, Germany
3 Computational Biology Unit, Uni Computing, Bergen 5008, Norway
AuthorAffiliation_xml – name: 4 Department of Informatics, University of Bergen, Bergen 5008, Norway
– name: 6 WZW – Weihenstephan, Alte Akademie 8, Freising, Germany
– name: 1 Department for Bioinformatics and Computational Biology, TU Munich, Boltzmannstraße 3, Garching 85748, Germany
– name: 2 Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA
– name: 5 Institute of Advanced Study (TUM-IAS), Lichtenbergstr. 2a, Garching/Munich 85748, Germany
– name: 3 Computational Biology Unit, Uni Computing, Bergen 5008, Norway
Author_xml – sequence: 1
  givenname: László
  surname: Kaján
  fullname: Kaján, László
  organization: Department for Bioinformatics and Computational Biology, TU Munich
– sequence: 2
  givenname: Thomas A
  surname: Hopf
  fullname: Hopf, Thomas A
  organization: Department for Bioinformatics and Computational Biology, TU Munich, Department of Systems Biology, Harvard Medical School
– sequence: 3
  givenname: Matúš
  surname: Kalaš
  fullname: Kalaš, Matúš
  organization: Computational Biology Unit, Uni Computing, Department of Informatics, University of Bergen
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  givenname: Debora S
  surname: Marks
  fullname: Marks, Debora S
  organization: Department of Systems Biology, Harvard Medical School
– sequence: 5
  givenname: Burkhard
  surname: Rost
  fullname: Rost, Burkhard
  email: assistant@rostlab.org
  organization: Department for Bioinformatics and Computational Biology, TU Munich, Institute of Advanced Study (TUM-IAS), Lichtenbergstr. 2a, WZW – Weihenstephan
BackLink https://www.ncbi.nlm.nih.gov/pubmed/24669753$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
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COPYRIGHT 2014 BioMed Central Ltd.
2014 Kaján et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Copyright © 2014 Kaján et al.; licensee BioMed Central Ltd. 2014 Kaján et al.; licensee BioMed Central Ltd.
Copyright_xml – notice: Kaján et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( ) applies to the data made available in this article, unless otherwise stated.
– notice: COPYRIGHT 2014 BioMed Central Ltd.
– notice: 2014 Kaján et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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Issue 1
Keywords EVcouplings
PSICOV
mfDCA
EVfold
2D prediction
Open-source software
Protein structure prediction
BioXSD
Debian package
Protein sequence analysis
Fast protein contact prediction
Language English
License This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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Snippet Background 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated...
20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations...
Background 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated...
Doc number: 85 Abstract Background: 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein...
Background: 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated...
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StartPage 85
SubjectTerms Algorithms
Bioinformatics
Biology
Biomedical and Life Sciences
C plus plus
Colleges & universities
Computational Biology - methods
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Internet service providers
Life Sciences
Methods
Microarrays
Programming languages
Protein Conformation
Protein structure prediction
Proteins
Proteins - chemistry
Proteins - genetics
Public software
Sequence analysis (applications)
Sequence Analysis, Protein - methods
Software
Technology application
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