ArticleChemical research in toxicology2021
GLORYx: Prediction of the Metabolites Resulting from Phase 1 and Phase 2 Biotransformations of Xenobiotics.
Article in Chemical research in toxicology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.
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Who cites it
75 citing papers in PubMed.
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- A Novel Workflow for Fast Elucidation of Drug Metabolites for Screening-Combining In Silico Metabolite Prediction With Trapped Ion Mobility QTOF-MS.Drug testing and analysis · 2026Article
- Comprehensive Profiling of Human Urinary Mercapturic Acid Conjugates Associated with Exposure to Reactive Chemical Species Using Enzymatic Deacetylation and High-Resolution Mass Spectrometry.Analytical chemistry · 2026Article
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- Therapeutic Applications of Natural Products in Biomedicine and Pharmacotherapy.Life (Basel, Switzerland) · 2026Review
- Comprehensive metabolic profiling of the new designer stimulant MDPiHP-in vitro and in vivo identification of potential biomarkers for detection in human samples.Analytical and bioanalytical chemistry · 2026Article
- Identification of Metabolites of the Dietary Supplement Ingredient 5α-Hydroxy-Laxogenin.Drug testing and analysis · 2026Article
15 more citing papers are in PubMed but not listed here.
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4 authors.
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Abstract
Predicting the structures of metabolites formed in humans can provide advantageous insights for the development of drugs and other compounds. Here we present GLORYx, which integrates machine learning-based site of metabolism (SoM) prediction with reaction rule sets to predict and rank the structures of metabolites that could potentially be formed by phase 1 and/or phase 2 metabolism. GLORYx extends the approach from our previously developed tool GLORY, which predicted metabolite structures for cytochrome P450-mediated metabolism only. A robust approach to ranking the predicted metabolites is attained by using the SoM probabilities predicted by the FAME 3 machine learning models to score the predicted metabolites. On a manually curated test data set containing both phase 1 and phase 2 metabolites, GLORYx achieves a recall of 77% and an area under the receiver operating characteristic curve (AUC) of 0.79. Separate analysis of performance on a large amount of freely available phase 1 and phase 2 metabolite data indicates that achieving a meaningful ranking of predicted metabolites is more difficult for phase 2 than for phase 1 metabolites. GLORYx is freely available as a web server at https://nerdd.zbh.uni-hamburg.de/ and is also provided as a software package upon request. The data sets as well as all the reaction rules from this work are also made freely available.
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