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Fast Methods for Prediction of Aldehyde Oxidase-Mediated Site-of-Metabolism

Aldehyde Oxidase (AO) is an enzyme involved in the metabolism of aldehydes and N-containing heterocyclic compounds. Many drug compounds contain heterocyclic moieties, and AO metabolism has lead to failure of several late-stage drug candidates. Therefore, it is important to take AO-mediated metabolis...

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Autores principales: Montefiori, Marco, Lyngholm-Kjærby, Casper, Long, Anthony, Olsen, Lars, Jørgensen, Flemming Steen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6429535/
https://www.ncbi.nlm.nih.gov/pubmed/30949305
http://dx.doi.org/10.1016/j.csbj.2019.03.003
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author Montefiori, Marco
Lyngholm-Kjærby, Casper
Long, Anthony
Olsen, Lars
Jørgensen, Flemming Steen
author_facet Montefiori, Marco
Lyngholm-Kjærby, Casper
Long, Anthony
Olsen, Lars
Jørgensen, Flemming Steen
author_sort Montefiori, Marco
collection PubMed
description Aldehyde Oxidase (AO) is an enzyme involved in the metabolism of aldehydes and N-containing heterocyclic compounds. Many drug compounds contain heterocyclic moieties, and AO metabolism has lead to failure of several late-stage drug candidates. Therefore, it is important to take AO-mediated metabolism into account early in the drug discovery process, and thus, to have fast and reliable models to predict the site of metabolism (SOM). We have collected a dataset of 78 substrates of human AO with a total of 89 SOMs and 347 non-SOMs and determined atomic descriptors for each compound. The descriptors comprise NMR shielding and ESP charges from density functional theory (DFT), NMR chemical shift from ChemBioDraw, and Gasteiger charges from RDKit. Additionally, atomic accessibility was considered using 2D-SASA and relative span descriptors from SMARTCyp. Finally, stability of the product, the metabolite, was determined with DFT and also used as a descriptor. All descriptors have AUC larger than 0.75. In particular, descriptors related to the chemical shielding and chemical shift (AUC = 0.96) and ESP charges (AUC = 0.96) proved to be good descriptors. We recommend two simple methods to identify the SOM for a given molecule: 1) use ChemBioDraw to calculate the chemical shift or 2) calculate ESP charges or chemical shift using DFT. The first approach is fast but somewhat difficult to automate, while the second is more time-consuming, but can easily be automated. The two methods predict correctly 93% and 91%, respectively, of the 89 experimentally observed SOMs.
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spelling pubmed-64295352019-04-04 Fast Methods for Prediction of Aldehyde Oxidase-Mediated Site-of-Metabolism Montefiori, Marco Lyngholm-Kjærby, Casper Long, Anthony Olsen, Lars Jørgensen, Flemming Steen Comput Struct Biotechnol J Research Article Aldehyde Oxidase (AO) is an enzyme involved in the metabolism of aldehydes and N-containing heterocyclic compounds. Many drug compounds contain heterocyclic moieties, and AO metabolism has lead to failure of several late-stage drug candidates. Therefore, it is important to take AO-mediated metabolism into account early in the drug discovery process, and thus, to have fast and reliable models to predict the site of metabolism (SOM). We have collected a dataset of 78 substrates of human AO with a total of 89 SOMs and 347 non-SOMs and determined atomic descriptors for each compound. The descriptors comprise NMR shielding and ESP charges from density functional theory (DFT), NMR chemical shift from ChemBioDraw, and Gasteiger charges from RDKit. Additionally, atomic accessibility was considered using 2D-SASA and relative span descriptors from SMARTCyp. Finally, stability of the product, the metabolite, was determined with DFT and also used as a descriptor. All descriptors have AUC larger than 0.75. In particular, descriptors related to the chemical shielding and chemical shift (AUC = 0.96) and ESP charges (AUC = 0.96) proved to be good descriptors. We recommend two simple methods to identify the SOM for a given molecule: 1) use ChemBioDraw to calculate the chemical shift or 2) calculate ESP charges or chemical shift using DFT. The first approach is fast but somewhat difficult to automate, while the second is more time-consuming, but can easily be automated. The two methods predict correctly 93% and 91%, respectively, of the 89 experimentally observed SOMs. Research Network of Computational and Structural Biotechnology 2019-03-07 /pmc/articles/PMC6429535/ /pubmed/30949305 http://dx.doi.org/10.1016/j.csbj.2019.03.003 Text en © 2019 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Montefiori, Marco
Lyngholm-Kjærby, Casper
Long, Anthony
Olsen, Lars
Jørgensen, Flemming Steen
Fast Methods for Prediction of Aldehyde Oxidase-Mediated Site-of-Metabolism
title Fast Methods for Prediction of Aldehyde Oxidase-Mediated Site-of-Metabolism
title_full Fast Methods for Prediction of Aldehyde Oxidase-Mediated Site-of-Metabolism
title_fullStr Fast Methods for Prediction of Aldehyde Oxidase-Mediated Site-of-Metabolism
title_full_unstemmed Fast Methods for Prediction of Aldehyde Oxidase-Mediated Site-of-Metabolism
title_short Fast Methods for Prediction of Aldehyde Oxidase-Mediated Site-of-Metabolism
title_sort fast methods for prediction of aldehyde oxidase-mediated site-of-metabolism
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6429535/
https://www.ncbi.nlm.nih.gov/pubmed/30949305
http://dx.doi.org/10.1016/j.csbj.2019.03.003
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