Determination and structural characterization of ravidasvir metabolites by LC coupled to triple quadrupole linear ion trap MS: Application to pharmacokinetics and phase I metabolism in rats.
Mohamed Mohamed Yousri KaddahWael TalaatMaha A El DemellawyPublished in: Biomedical chromatography : BMC (2021)
Hepatitis C virus (HCV) is an infectious disease that has become a global clinical issue because of its significant morbidity and mortality. Novel anti-hepatitis C drugs are continuously developed to decrease the pervasiveness of the infection globally. A synthetic ravidasvir, benzimidazole-naphthylene-imidazole derivatives, has been used as an anti-HCV drug. This study determined the metabolites of ravidasvir and its pharmacokinetics in rats using information-dependent acquisition and multiple reaction monitoring scanning modes in linear ion trap LC-MS/MS instrument, respectively. Two time-programming linear-gradient chromatographic methods were employed using a Kinetex C18 column (50 × 3 mm, 2.6 μm) and a Luna HILIC column (100 × 4.6 mm, 3 μm) for the qualitative and quantitative determination of ravidasvir and its metabolites, respectively. In silico prediction where sites in a molecule are susceptible to metabolism by cytochrome P450 was implemented, which helped in proposing the metabolic pathway of ravidasvir. The most dominant metabolite in rat liver microsomal samples was oxidative ravidasvir, where one O-demethylated metabolite and eight isomers of the oxidative ravidasvir metabolites were identified. The study provides essential data for proposing the metabolic pathway and successfully applied it to determine the pharmacokinetics of ravidasvir in rat plasma.
Keyphrases
- hepatitis c virus
- ms ms
- solid phase extraction
- liquid chromatography
- mass spectrometry
- human immunodeficiency virus
- high resolution
- simultaneous determination
- infectious diseases
- molecular docking
- tandem mass spectrometry
- high performance liquid chromatography
- oxidative stress
- emergency department
- adverse drug
- health information
- molecular dynamics simulations
- electron microscopy
- gas chromatography
- neural network
- antiretroviral therapy