Original Research ARTICLE
GLORY: Generator of the Structures of Likely Cytochrome P450 Metabolites Based on Predicted Sites of Metabolism
- 1Universität Hamburg, Germany
- 2University of Chemistry and Technology in Prague, Czechia
- 3IDEAconsult, Bulgaria
- 4Plovdiv University "Paisii Hilendarski", Bulgaria
- 5University of Bergen, Norway
Computational prediction of xenobiotic metabolism can provide valuable information to guide the development of drugs, cosmetics, agrochemicals, and other chemical entities. We have previously developed FAME 2, an effective tool for predicting sites of metabolism (SoMs). In this work, we focus on the prediction of the chemical structures of metabolites, in particular metabolites of xenobiotics. To this end, we have developed a new tool, GLORY, which combines SoM prediction with FAME 2 and a new collection of rules for metabolic reactions mediated by the cytochrome P450 enzyme family. GLORY has two modes: MaxEfficiency and MaxCoverage. For MaxEfficiency mode, the use of predicted SoMs to restrict the locations in the molecule at which the reaction rules could be applied was explored. For MaxCoverage mode, the predicted SoM probabilities were instead used to develop a new scoring approach for the predicted metabolites. With this scoring approach, GLORY achieves a recall of 0.83 and can predict at least one known metabolite within the top three ranked positions for 76% of the molecules of a new, manually curated test set. GLORY is freely available as a web server at https://acm.zbh.uni-hamburg.de/glory/, and the datasets and reaction rules are provided in the Supplementary Material.
Keywords: metabolism prediction, metabolite structure prediction, rule-based approach, xenobiotic metabolism, cytochrome P450, Metabolites, Sites of metabolism
Received: 28 Mar 2019;
Accepted: 17 May 2019.
Edited by:Jose L. Medina-Franco, National Autonomous University of Mexico, Mexico
Reviewed by:Angelica Mazzolari, University of Milan, Italy
Anastasia Rudik, Institute of Biomedical Chemistry, Russian Academy of Medical Sciences (RAMS), Russia
Copyright: © 2019 de Bruyn Kops, Stork, Šícho, Kochev, Svozil, Jeliazkova and Kirchmair. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mx. Johannes Kirchmair, University of Bergen, Bergen, 5020, Hordaland, Norway, firstname.lastname@example.org