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Title: Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D

Abstract

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, many algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy ofmore » the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.« less

Authors:
ORCiD logo [1];  [1];  [1];  [1];  [1];  [1]
  1. University of Luxembourg, Belvaux (Luxembourg). Luxembourg Centre for Systems Biomedicine
Publication Date:
Research Org.:
University of Luxembourg, Belvaux (Luxembourg)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25); USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1424907
Grant/Contract Number:  
SC0010429
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Cheminformatics
Additional Journal Information:
Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 1758-2946
Publisher:
Chemistry Central Ltd.
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 97 MATHEMATICS AND COMPUTING; Atom mapping; Metabolic network reconstruction; Automation; RDT; DREAM; AutoMapper; CLCA; MWED; ICMAP; Recon 3D

Citation Formats

Preciat Gonzalez, German A., El Assal, Lemmer R. P., Noronha, Alberto, Thiele, Ines, Haraldsdóttir, Hulda S., and Fleming, Ronan M. T. Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D. United States: N. p., 2017. Web. doi:10.1186/s13321-017-0223-1.
Preciat Gonzalez, German A., El Assal, Lemmer R. P., Noronha, Alberto, Thiele, Ines, Haraldsdóttir, Hulda S., & Fleming, Ronan M. T. Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D. United States. doi:10.1186/s13321-017-0223-1.
Preciat Gonzalez, German A., El Assal, Lemmer R. P., Noronha, Alberto, Thiele, Ines, Haraldsdóttir, Hulda S., and Fleming, Ronan M. T. Wed . "Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D". United States. doi:10.1186/s13321-017-0223-1. https://www.osti.gov/servlets/purl/1424907.
@article{osti_1424907,
title = {Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D},
author = {Preciat Gonzalez, German A. and El Assal, Lemmer R. P. and Noronha, Alberto and Thiele, Ines and Haraldsdóttir, Hulda S. and Fleming, Ronan M. T.},
abstractNote = {The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, many algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.},
doi = {10.1186/s13321-017-0223-1},
journal = {Journal of Cheminformatics},
number = 1,
volume = 9,
place = {United States},
year = {2017},
month = {6}
}

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    Works referencing / citing this record:

    Refining carbon flux paths using atomic trace data
    journal, November 2013


    PubChem Substance and Compound databases
    journal, September 2015

    • Kim, Sunghwan; Thiessen, Paul A.; Bolton, Evan E.
    • Nucleic Acids Research, Vol. 44, Issue D1
    • DOI: 10.1093/nar/gkv951

    EC-BLAST: a tool to automatically search and compare enzyme reactions
    journal, January 2014

    • Rahman, Syed Asad; Cuesta, Sergio Martinez; Furnham, Nicholas
    • Nature Methods, Vol. 11, Issue 2
    • DOI: 10.1038/nmeth.2803

    A community-driven global reconstruction of human metabolism
    journal, March 2013

    • Thiele, Ines; Swainston, Neil; Fleming, Ronan M. T.
    • Nature Biotechnology, Vol. 31, Issue 5
    • DOI: 10.1038/nbt.2488

    Computational Assignment of the EC Numbers for Genomic-Scale Analysis of Enzymatic Reactions
    journal, December 2004

    • Kotera, Masaaki; Okuno, Yasushi; Hattori, Masahiro
    • Journal of the American Chemical Society, Vol. 126, Issue 50
    • DOI: 10.1021/ja0466457

    CLCA: Maximum Common Molecular Substructure Queries within the MetRxn Database
    journal, December 2014

    • Kumar, Akhil; Maranas, Costas D.
    • Journal of Chemical Information and Modeling, Vol. 54, Issue 12
    • DOI: 10.1021/ci5003922

    Accurate Atom-Mapping Computation for Biochemical Reactions
    journal, October 2012

    • Latendresse, Mario; Malerich, Jeremiah P.; Travers, Mike
    • Journal of Chemical Information and Modeling, Vol. 52, Issue 11
    • DOI: 10.1021/ci3002217

    Stereochemically Consistent Reaction Mapping and Identification of Multiple Reaction Mechanisms through Integer Linear Optimization
    journal, December 2011

    • First, Eric L.; Gounaris, Chrysanthos E.; Floudas, Christodoulos A.
    • Journal of Chemical Information and Modeling, Vol. 52, Issue 1
    • DOI: 10.1021/ci200351b

    Reactant pairs and reaction organization patterns produced by a new rule-based approach
    journal, August 2018

    • Vazquez-Hernandez, Carlos; Loza, Antonio; Gutierrez-Rios, Rosa-Maria
    • BMC Research Notes, Vol. 11, Issue 1
    • DOI: 10.1186/s13104-018-3724-8

    KEGG: Kyoto Encyclopedia of Genes and Genomes
    journal, January 2000

    • Kanehisa, Minoru; Goto, Susumu
    • Nucleic Acids Research, Vol. 28, Issue 1, p. 27-30
    • DOI: 10.1093/nar/28.1.27

    MOESM3 of Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D
    dataset, June 2017

    • Gonzalez, German Preciat; El Assal, Lemmer; Noronha, Alberto
    • Figshare-Supplementary information for journal article at DOI: 10.1186/s13321-017-0223-1, 1 zip file (103.34 MB)
    • DOI: 10.6084/m9.figshare.c.3803623_d3

    MOESM4 of Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D
    dataset, June 2017


    MOESM1 of Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D
    dataset, June 2017

    • Gonzalez, German Preciat; El Assal, Lemmer; Noronha, Alberto
    • figshare-Supplementary information for journal article at DOI: 10.1186/s13321-017-0223-1, 1 PDF file (96.94 kB)
    • DOI: 10.6084/m9.figshare.c.3803623_d1

    Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D
    dataset, June 2017

    • Gonzalez, German Preciat; El Assal, Lemmer; Noronha, Alberto
    • Figshare-Supplementary information for journal article at DOI: 10.1186/s13321-017-0223-1, 5 files
    • DOI: 10.6084/m9.figshare.c.3803623

    MOESM2 of Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D
    dataset, June 2017

    • Gonzalez, German Preciat; El Assal, Lemmer; Noronha, Alberto
    • Figshare-Supplementary information for journal article at DOI: 10.1186/s13321-017-0223-1, 1 CSV (178.87 kB)
    • DOI: 10.6084/m9.figshare.c.3803623_d2

    Comparative evaluation of open source software for mapping between metabolite identifiers in metabolic network reconstructions: application to Recon 2
    journal, January 2014

    • Haraldsdóttir, Hulda S.; Thiele, Ines; Fleming, Ronan MT
    • Journal of Cheminformatics, Vol. 6, Issue 1
    • DOI: 10.1186/1758-2946-6-2

    MOESM5 of Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D
    code, June 2017

    • Preciat Gonzalez, German; El Assal, Lemmer; Noronha, Alberto
    • figshare-Supplementary information for journal article at DOI: 10.1186/s13321-017-0223-1, 1 MLX file (7.26 kB)
    • DOI: 10.6084/m9.figshare.c.3803623_d5

    Description of several chemical structure file formats used by computer programs developed at Molecular Design Limited
    journal, May 1992

    • Dalby, Arthur; Nourse, James G.; Hounshell, W. Douglas
    • Journal of Chemical Information and Modeling, Vol. 32, Issue 3
    • DOI: 10.1021/ci00007a012

    MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases
    journal, January 2012

    • Kumar, Akhil; Suthers, Patrick F.; Maranas, Costas D.
    • BMC Bioinformatics, Vol. 13, Issue 1
    • DOI: 10.1186/1471-2105-13-6

    Algorithm for Reaction Classification
    journal, October 2013

    • Kraut, Hans; Eiblmaier, Josef; Grethe, Guenter
    • Journal of Chemical Information and Modeling, Vol. 53, Issue 11
    • DOI: 10.1021/ci400442f

    The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013
    journal, November 2012

    • Hastings, Janna; de Matos, Paula; Dekker, Adriano
    • Nucleic Acids Research, Vol. 41, Issue D1
    • DOI: 10.1093/nar/gks1146

    The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases
    journal, November 2011

    • Caspi, R.; Altman, T.; Dreher, K.
    • Nucleic Acids Research, Vol. 40, Issue D1
    • DOI: 10.1093/nar/gkr1014

    LMSD: LIPID MAPS structure database
    journal, January 2007

    • Sud, M.; Fahy, E.; Cotter, D.
    • Nucleic Acids Research, Vol. 35, Issue Database
    • DOI: 10.1093/nar/gkl838

    Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks
    journal, November 2016


    13C Metabolic Flux Analysis
    journal, July 2001


    Reaction Decoder Tool (RDT): extracting features from chemical reactions
    journal, February 2016


    Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
    journal, August 2011

    • Schellenberger, Jan; Que, Richard; Fleming, Ronan M. T.
    • Nature Protocols, Vol. 6, Issue 9
    • DOI: 10.1038/nprot.2011.308

    HMDB: the Human Metabolome Database
    journal, January 2007

    • Wishart, D. S.; Tzur, D.; Knox, C.
    • Nucleic Acids Research, Vol. 35, Issue Database
    • DOI: 10.1093/nar/gkl923

    Automatic reaction mapping and reaction center detection
    journal, March 2013

    • Chen, William Lingran; Chen, David Z.; Taylor, Keith T.
    • Wiley Interdisciplinary Reviews: Computational Molecular Science, Vol. 3, Issue 6
    • DOI: 10.1002/wcms.1140

    Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota
    journal, November 2016

    • Magnúsdóttir, Stefanía; Heinken, Almut; Kutt, Laura
    • Nature Biotechnology, Vol. 35, Issue 1
    • DOI: 10.1038/nbt.3703

    Open Babel: An open chemical toolbox
    journal, October 2011

    • O'Boyle, Noel M.; Banck, Michael; James, Craig A.
    • Journal of Cheminformatics, Vol. 3, Issue 1
    • DOI: 10.1186/1758-2946-3-33

    Reactant pairs and reaction organization patterns produced by a new rule-based approach
    journal, August 2018

    • Vazquez-Hernandez, Carlos; Loza, Antonio; Gutierrez-Rios, Rosa-Maria
    • BMC Research Notes, Vol. 11, Issue 1
    • DOI: 10.1186/s13104-018-3724-8