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PROXIMAL: a method for Prediction of Xenobiotic Metabolism
BACKGROUND: Contamination of the environment with bioactive chemicals has emerged as a potential public health risk. These substances that may cause distress or disease in humans can be found in air, water and food supplies. An open question is whether these chemicals transform into potentially more...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687097/ https://www.ncbi.nlm.nih.gov/pubmed/26695483 http://dx.doi.org/10.1186/s12918-015-0241-4 |
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author | Yousofshahi, Mona Manteiga, Sara Wu, Charmian Lee, Kyongbum Hassoun, Soha |
author_facet | Yousofshahi, Mona Manteiga, Sara Wu, Charmian Lee, Kyongbum Hassoun, Soha |
author_sort | Yousofshahi, Mona |
collection | PubMed |
description | BACKGROUND: Contamination of the environment with bioactive chemicals has emerged as a potential public health risk. These substances that may cause distress or disease in humans can be found in air, water and food supplies. An open question is whether these chemicals transform into potentially more active or toxic derivatives via xenobiotic metabolizing enzymes expressed in the body. We present a new prediction tool, which we call PROXIMAL (Prediction of Xenobiotic Metabolism) for identifying possible transformation products of xenobiotic chemicals in the liver. Using reaction data from DrugBank and KEGG, PROXIMAL builds look-up tables that catalog the sites and types of structural modifications performed by Phase I and Phase II enzymes. Given a compound of interest, PROXIMAL searches for substructures that match the sites cataloged in the look-up tables, applies the corresponding modifications to generate a panel of possible transformation products, and ranks the products based on the activity and abundance of the enzymes involved. RESULTS: PROXIMAL generates transformations that are specific for the chemical of interest by analyzing the chemical’s substructures. We evaluate the accuracy of PROXIMAL’s predictions through case studies on two environmental chemicals with suspected endocrine disrupting activity, bisphenol A (BPA) and 4-chlorobiphenyl (PCB3). Comparisons with published reports confirm 5 out of 7 and 17 out of 26 of the predicted derivatives for BPA and PCB3, respectively. We also compare biotransformation predictions generated by PROXIMAL with those generated by METEOR and Metaprint2D-react, two other prediction tools. CONCLUSIONS: PROXIMAL can predict transformations of chemicals that contain substructures recognizable by human liver enzymes. It also has the ability to rank the predicted metabolites based on the activity and abundance of enzymes involved in xenobiotic transformation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-015-0241-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4687097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46870972015-12-23 PROXIMAL: a method for Prediction of Xenobiotic Metabolism Yousofshahi, Mona Manteiga, Sara Wu, Charmian Lee, Kyongbum Hassoun, Soha BMC Syst Biol Research Article BACKGROUND: Contamination of the environment with bioactive chemicals has emerged as a potential public health risk. These substances that may cause distress or disease in humans can be found in air, water and food supplies. An open question is whether these chemicals transform into potentially more active or toxic derivatives via xenobiotic metabolizing enzymes expressed in the body. We present a new prediction tool, which we call PROXIMAL (Prediction of Xenobiotic Metabolism) for identifying possible transformation products of xenobiotic chemicals in the liver. Using reaction data from DrugBank and KEGG, PROXIMAL builds look-up tables that catalog the sites and types of structural modifications performed by Phase I and Phase II enzymes. Given a compound of interest, PROXIMAL searches for substructures that match the sites cataloged in the look-up tables, applies the corresponding modifications to generate a panel of possible transformation products, and ranks the products based on the activity and abundance of the enzymes involved. RESULTS: PROXIMAL generates transformations that are specific for the chemical of interest by analyzing the chemical’s substructures. We evaluate the accuracy of PROXIMAL’s predictions through case studies on two environmental chemicals with suspected endocrine disrupting activity, bisphenol A (BPA) and 4-chlorobiphenyl (PCB3). Comparisons with published reports confirm 5 out of 7 and 17 out of 26 of the predicted derivatives for BPA and PCB3, respectively. We also compare biotransformation predictions generated by PROXIMAL with those generated by METEOR and Metaprint2D-react, two other prediction tools. CONCLUSIONS: PROXIMAL can predict transformations of chemicals that contain substructures recognizable by human liver enzymes. It also has the ability to rank the predicted metabolites based on the activity and abundance of enzymes involved in xenobiotic transformation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-015-0241-4) contains supplementary material, which is available to authorized users. BioMed Central 2015-12-22 /pmc/articles/PMC4687097/ /pubmed/26695483 http://dx.doi.org/10.1186/s12918-015-0241-4 Text en © Yousofshahi et al. 2015 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 | Research Article Yousofshahi, Mona Manteiga, Sara Wu, Charmian Lee, Kyongbum Hassoun, Soha PROXIMAL: a method for Prediction of Xenobiotic Metabolism |
title | PROXIMAL: a method for Prediction of Xenobiotic Metabolism |
title_full | PROXIMAL: a method for Prediction of Xenobiotic Metabolism |
title_fullStr | PROXIMAL: a method for Prediction of Xenobiotic Metabolism |
title_full_unstemmed | PROXIMAL: a method for Prediction of Xenobiotic Metabolism |
title_short | PROXIMAL: a method for Prediction of Xenobiotic Metabolism |
title_sort | proximal: a method for prediction of xenobiotic metabolism |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687097/ https://www.ncbi.nlm.nih.gov/pubmed/26695483 http://dx.doi.org/10.1186/s12918-015-0241-4 |
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