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Updated: Apr 30, 2026

Human Liver Microphysiological System for Assessing Drug-Induced Liver Toxicity In Vitro
Published on: January 31, 2022
Cylindrospermopsin toxicokinetics: in silico ADMET modeling, rat and human liver microsome metabolism, and
Antonio Cascajosa-Lira1, Remedios Guzmán-Guillén2, Ana M Cameán1
1Area of Toxicology, Faculty of Pharmacy, University of Sevilla, Seville, Spain.
Abstract:
Cylindrospermopsin is a potent cyanobacterial toxin of growing global concern due to its environmental persistence and broad toxicological profile. Despite increasing evidence of its toxic effects, knowledge of its toxicokinetics remains limited. This study integrates in silico ADMET predictions with in vitro microsomal assays using human and sex-stratified rat liver microsomes to characterize CYN biotransformation. In silico predictions indicated low intestinal absorption, improbable blood-brain barrier (BBB) penetration, minimal binding to plasma proteins, and very limited CYP450-mediated metabolism. However, several potential phase II conjugation routes were identified, with certain metabolites predicted to display altered toxicological properties compared with the parent compound. Complementary in vitro studies in microsomes confirmed the high metabolic stability of CYN, with only modest decreases in toxin concentration observed during incubation (8-15% decrease). Notably, biotransformation was more evident under phase II conditions, particularly glucuronidation and amino acid conjugation. Novel metabolites were detected for the first time by Ultra-High Performance Liquid Chromatography (UHPLC-/MS/MS), including conjugates with cysteine, glycine, taurine, and arginine, as well as with fatty acids. No significant quantitative differences were observed between sexes or species, although qualitative variability in metabolite profiles was detected. These findings provide new insights into the metabolic fate of CYN, underscore the importance of conjugation reactions in its detoxification, and support the application of integrative computational and experimental approaches to improve cyanotoxin risk assessment.
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