Reaction Decoder Tool (RDT): extracting features from chemical reactions

Rahman, Syed Asad; Torrance, Gilliean; Baldacci, Lorenzo; Cuesta, Sergio Martínez; Fenninger, Franz; Gopal, Nimish; Choudhary, Saket; May, John W.; Holliday, Gemma L.; Steinbeck, Christoph; Thornton, Janet M.

doi:10.1093/bioinformatics/btw096

Cited by 88 publications

(75 citation statements)

References 15 publications

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“…Here, we evaluate six recently published atom mapping algorithms [10–15]. We compare their predictions for more than five thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D [9].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-017-0223-1) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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“…The current release (release 75 of 30 July 30 2016) features over 600 expert-curated reaction relations. We are currently developing methods to calculate reaction relations for legacy data using curated relations in the ChEBI ontology (6) and computed measures of chemical structure and reaction similarity (21–23). We expect the number of reaction relations to increase significantly in the near future as we continue to check and validate calculated relations.…”

Section: Current Developments In Rheamentioning

confidence: 99%

Updates in Rhea – an expert curated resource of biochemical reactions

Morgat¹,

Lombardot²,

Axelsen³

et al. 2016

Nucleic Acids Res

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Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of expert-curated biochemical reactions designed for the functional annotation of enzymes and the description of metabolic networks. Rhea describes enzyme-catalyzed reactions covering the IUBMB Enzyme Nomenclature list as well as additional reactions, including spontaneously occurring reactions, using entities from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Here we describe developments in Rhea since our last report in the database issue of Nucleic Acids Research. These include the first implementation of a simple hierarchical classification of reactions, improved coverage of the IUBMB Enzyme Nomenclature list and additional reactions through continuing expert curation, and the development of a new website to serve this improved dataset.

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“…Here we describe the introduction of Rhea as the reference vocabulary for enzyme annotation in UniProtKB. This development will significantly increase the utility of UniProtKB for applications such as the integrative analysis of metabolomics and other 'omics data (Kale, et al, 2016;Sud, et al, 2016), as illustrated here, as well as the study of enzyme chemistry and evolution (Rahman, et al, 2016;Tyzack, et al, 2019), the construction and annotation of metabolic models (Cottret, et al, 2018;King, et al, 2016;Moretti, et al, 2016), and the engineering of pathways for biosynthesis and bioremediation (Duigou, et al, 2019). Rhea will also provide a basis to further improve links with other knowledge resources, such as the Gene Ontology (The Gene Ontology Consortium, 2019) and Reactome (Fabregat, et al, 2018), which both plan to use Rhea as the reference for reaction chemistry (Chris Mungall and Peter D'Eustachio, personal communication).…”

Section: Conclusion and Futures Directionsmentioning

confidence: 99%

Enzyme annotation in UniProtKB using Rhea

Morgat

Lombardot

Coudert

et al. 2019

Preprint

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Motivation: To provide high quality computationally tractable enzyme annotation in UniProtKB using Rhea, a comprehensive expert-curated knowledgebase of biochemical reactions which describes reaction participants using the ontology ChEBI (Chemical Entities of Biological Interest). Results:We replaced existing textual descriptions of biochemical reactions in UniProtKB with their equivalents from Rhea, which is now the standard for annotation of enzymatic reactions in UniProtKB. We developed improved search and query facilities for the UniProt website, REST API, and SPARQL endpoint that leverage the chemical structure data, nomenclature, and classification that Rhea and ChEBI provide.Availability and Implementation: UniProtKB at https://www.uniprot.org/; UniProt REST API at https://www.uniprot.org/help/api; UniProt SPARQL endpoint at https://sparql.uniprot.org/sparql; Rhea at https://www.rhea-db.org/.Contact: anne.morgat@sib.swiss

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Reaction Decoder Tool (RDT): extracting features from chemical reactions

Cited by 88 publications

References 15 publications

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

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

Updates in Rhea – an expert curated resource of biochemical reactions

Enzyme annotation in UniProtKB using Rhea

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