Revisiting the Metabolism of Donepezil in Rats Using Non-Targeted Metabolomics and Molecular Networking
<b>Background/Objectives</b>: Although donepezil, a reversible acetylcholinesterase inhibitor, has been in use since 1996, its metabolic characteristics remain poorly characterized. Therefore, this study aims to investigate the in vivo metabolism of donepezil using liquid chromatography–...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Pharmaceutics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4923/17/1/115 |
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| Summary: | <b>Background/Objectives</b>: Although donepezil, a reversible acetylcholinesterase inhibitor, has been in use since 1996, its metabolic characteristics remain poorly characterized. Therefore, this study aims to investigate the in vivo metabolism of donepezil using liquid chromatography–high-resolution mass spectrometry (LC-HRMS) based on a molecular networking (MN) approach integrated with a non-targeted metabolomics approach. <b>Methods</b>: After the oral administration of donepezil (30 mg/kg) in rats, urine, feces, and liver samples were collected for LC-HRMS analysis. Chromatographic and spectrometric data were processed through MN and multivariate data analysis to identify the in vivo metabolites of donepezil. <b>Results</b>: A total of 50 metabolites were characterized, including 23 newly identified metabolites. Donepezil was biotransformed by <i>O-</i>demethylation, <i>N-</i>debenzylation, and hydroxylation, and these metabolites are further conjugated with glucuronic acid and sulfurous acid. <i>N-</i>Desbenzyldonepezil (<b>M4</b>), didesmethyldonepezil (<b>M5</b>), and <i>N-</i>desbenzyldonepezil (<b>M4</b>) were identified as the most abundant metabolites in urine, feces, and liver samples, respectively. <b>Conclusions</b>: The metabolic characteristics of donepezil in rats were comparable to those in humans, indicating that a rat is a reliable model for studying donepezil metabolism. This study indicates that a MN approach combined with a metabolomics approach is a reliable tool to identify unknown metabolites of drugs and drug candidates. |
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| ISSN: | 1999-4923 |