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![Technical Aspect of the Automated Synthesis and Real-Time Kinetic Evaluation of [11C]SNAP-7941](/_next/image?url=https%3A%2F%2Fcloudfront.jove.com%2FCDNSource%2Fteasers%2F59557.jpg&w=3840&q=50)
Technical Aspect of the Automated Synthesis and Real-Time Kinetic Evaluation of [11C]SNAP-7941
Published on: April 28, 2019
New insights into quetiapine metabolism using molecular networking
Brendan Le Daré1,2, Pierre-Jean Ferron3, Pierre-Marie Allard4
1INSERM, INRAE, CHU Rennes, Institut NuMeCan (Nutrition, Metabolism and Cancer), PREVITOX Network, Univ Rennes, 35033, Rennes, France. brendan.le.dare@chu-rennes.fr.
Abstract:
Metabolism is involved in both pharmacology and toxicology of most xenobiotics including drugs. Yet, visualization tools facilitating metabolism exploration are still underused, despite the availibility of pertinent bioinformatics solutions. Since molecular networking appears as a suitable tool to explore structurally related molecules, we aimed to investigate its interest in in vitro metabolism exploration. Quetiapine, a widely prescribed antipsychotic drug, undergoes well-described extensive metabolism, and is therefore an ideal candidate for such a proof of concept. Quetiapine was incubated in metabolically competent human liver cell models (HepaRG) for different times (0 h, 3 h, 8 h, 24 h) with or without cytochrom P450 (CYP) inhibitor (ketoconazole as CYP3A4/5 inhibitor and quinidine as CYP2D6 inhibitor), in order to study its metabolism kinetic and pathways. HepaRG culture supernatants were analyzed on an ultra-high performance liquid chromatography coupled with tandem mass spectrometry (LC-HRMS/MS). Molecular networking approach on LC-HRMS/MS data allowed to quickly visualize the quetiapine metabolism kinetics and determine the major metabolic pathways (CYP3A4/5 and/or CYP2D6) involved in metabolite formation. In addition, two unknown putative metabolites have been detected. In vitro metabolite findings were confirmed in blood sample from a patient treated with quetiapine. This is the first report using LC-HRMS/MS untargeted screening and molecular networking to explore in vitro drug metabolism. Our data provide new evidences of the interest of molecular networking in drug metabolism exploration and allow our in vitro model consistency assessment.
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