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XMetDB: an open access database for xenobiotic metabolism
Xenobiotic metabolism is an active research topic but the limited amount of openly available high-quality biotransformation data constrains predictive modeling. Current database often default to commonly available information: which enzyme metabolizes a compound, but neither experimental conditions...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025591/ https://www.ncbi.nlm.nih.gov/pubmed/27651835 http://dx.doi.org/10.1186/s13321-016-0161-3 |
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author | Spjuth, Ola Rydberg, Patrik Willighagen, Egon L. Evelo, Chris T. Jeliazkova, Nina |
author_facet | Spjuth, Ola Rydberg, Patrik Willighagen, Egon L. Evelo, Chris T. Jeliazkova, Nina |
author_sort | Spjuth, Ola |
collection | PubMed |
description | Xenobiotic metabolism is an active research topic but the limited amount of openly available high-quality biotransformation data constrains predictive modeling. Current database often default to commonly available information: which enzyme metabolizes a compound, but neither experimental conditions nor the atoms that undergo metabolization are captured. We present XMetDB, an open access database for drugs and other xenobiotics and their respective metabolites. The database contains chemical structures of xenobiotic biotransformations with substrate atoms annotated as reaction centra, the resulting product formed, and the catalyzing enzyme, type of experiment, and literature references. Associated with the database is a web interface for the submission and retrieval of experimental metabolite data for drugs and other xenobiotics in various formats, and a web API for programmatic access is also available. The database is open for data deposition, and a curation scheme is in place for quality control. An extensive guide on how to enter experimental data into is available from the XMetDB wiki. XMetDB formalizes how biotransformation data should be reported, and the openly available systematically labeled data is a big step forward towards better models for predictive metabolism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-016-0161-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5025591 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-50255912016-09-20 XMetDB: an open access database for xenobiotic metabolism Spjuth, Ola Rydberg, Patrik Willighagen, Egon L. Evelo, Chris T. Jeliazkova, Nina J Cheminform Database Xenobiotic metabolism is an active research topic but the limited amount of openly available high-quality biotransformation data constrains predictive modeling. Current database often default to commonly available information: which enzyme metabolizes a compound, but neither experimental conditions nor the atoms that undergo metabolization are captured. We present XMetDB, an open access database for drugs and other xenobiotics and their respective metabolites. The database contains chemical structures of xenobiotic biotransformations with substrate atoms annotated as reaction centra, the resulting product formed, and the catalyzing enzyme, type of experiment, and literature references. Associated with the database is a web interface for the submission and retrieval of experimental metabolite data for drugs and other xenobiotics in various formats, and a web API for programmatic access is also available. The database is open for data deposition, and a curation scheme is in place for quality control. An extensive guide on how to enter experimental data into is available from the XMetDB wiki. XMetDB formalizes how biotransformation data should be reported, and the openly available systematically labeled data is a big step forward towards better models for predictive metabolism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-016-0161-3) contains supplementary material, which is available to authorized users. Springer International Publishing 2016-09-15 /pmc/articles/PMC5025591/ /pubmed/27651835 http://dx.doi.org/10.1186/s13321-016-0161-3 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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. |
spellingShingle | Database Spjuth, Ola Rydberg, Patrik Willighagen, Egon L. Evelo, Chris T. Jeliazkova, Nina XMetDB: an open access database for xenobiotic metabolism |
title | XMetDB: an open access database for xenobiotic metabolism |
title_full | XMetDB: an open access database for xenobiotic metabolism |
title_fullStr | XMetDB: an open access database for xenobiotic metabolism |
title_full_unstemmed | XMetDB: an open access database for xenobiotic metabolism |
title_short | XMetDB: an open access database for xenobiotic metabolism |
title_sort | xmetdb: an open access database for xenobiotic metabolism |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025591/ https://www.ncbi.nlm.nih.gov/pubmed/27651835 http://dx.doi.org/10.1186/s13321-016-0161-3 |
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