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Computational Chemistry Approach in the Assessment of Potential Acyl Glucuronide-Mediated Toxicity
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DOI：10.2174/0113892002401464251121074008.png)
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Abstract
En 中文
Introduction: Acyl glucuronides are common phase II metabolites of xenobiotics and can sometimes contribute to idiosyncratic toxicities. Their reactivity is primarily mediated through acyl migration and/or nucleophilic displacement, and shorter acyl glucuronide half-lives are associated with increased reactivity. This reactivity can lead to metabolite-induced toxicity, posing a significant risk during drug development. Methods: We developed regression models trained on features derived from Density Functional Theory (DFT) calculations to predict the half-lives of acyl glucuronide metabolites. The aim was to provide a computational tool to guide the design of drug candidates with more stable acyl glucuronide metabolites. Results: The best-performing model achieved a strong correlation between predicted and experimental half-lives, with an R-2 of 0.67 on the test set. Predicted half-lives for drugs classified as clinically safe were longer than those for drugs in the warning and withdrawn categories, demonstrating a separation comparable to experimentally measured half-lives. Discussion: The model is sufficiently accurate to support the optimization of acyl glucuronides for longer half-lives. Further analysis indicated that acyl glucuronide stability can be modulated by electron-donating and electron-withdrawing groups, effects that are effectively captured by the model. Conclusion: This modeling approach can be applied during drug discovery to reduce the risk of metabolite-related toxicity by enabling in silico screening of compound modifications and ranking them based on predicted effects on acyl glucuronide half-life.
Keywords:
UGT
acyl glucuronides
glucuronidation
reactivity
stability
bioactivation
thioacyl glutathione
in silico
Journal
C
IF:
1.8
Papers:
45
Citations:
4.3K
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