In vitro identification of dapaconazole metabolites and enzymatic phenotyping using human liver microsomes and selective CYP450 inhibitory monoclonal antibodies
DOI:
https://doi.org/10.34119/bjhrv8n3-290Keywords:
dapaconazole, imidazole, in vitro metabolism, microsome, enzymatic phenotyping, inhibitory antibodies, in silico predictionAbstract
Superficial fungal infections have significantly increased in recent decades, becoming one of the most prevalent forms of infection. Fungal resistance to azole compounds has been an important focus of research in recent years. Dapaconazole, a new antifungal imidazole, was developed through radical innovation and has shown efficacy against pathogenic fungi. The objective of this study was to elucidate the main metabolites generated by phase I and phase II metabolism of dapaconazole in vitro, using human (HLM) and rat (RLM) liver microsomes and in silico tools (Meteor Nexus and GastroPlus® softwares). The isoenzymes involved in the process were also investigated by enzyme phenotyping with inhibitory antibodies against CYP450 isoenzymes. The metabolite identification was performed using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). For enzyme phenotyping, a liquid chromatography quadrupole mass spectrometry (LC-MS/MS) method was employed. A total of seven metabolites were found in HLM and RLM, which five (C20H18Cl2F3N2O, C19H16Cl2F3N2O2, C11H11Cl2N2O, C19H16Cl2F3N2O2, C19H14Cl2F3N2O2) were produced by phase I reactions, metabolized by various isoenzymes of the CYP450 (CYP1A1, CYP1A2, CYP2B6, CYP2C8, CYP2C19, CYP2D6, CYP2E1, CYP3A4), one by phase I + II (C25H24Cl2F3N2O8), and one directly by phase II (C25H24Cl2F3N2O7). In silico simulation models were relevant for metabolite identification and proved to be an important complement to in vitro experiments. The essays allowed not only determination, but also the metabolites formation rate. Differences in metabolic formation rates between species were observed, mainly for the conjugated metabolites.
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