Abstract

Acyl glucuronidation is an important Phase II biotransformation, which is an efficient detoxification mechanism for the metabolism of carboxylic acid group-containing drugs. However, the reactivity of acyl glucuronide (AG) metabolites associated with short half-lives may be an indication of idiosyncratic drug toxicity.The degradation half-lives of AGs elucidate several important reactions such as hydrolysis, acyl migration and covalent binding to proteins. Prediction of degradation half-life using computational methods is a promising alternative approach to costly and time-consuming experiments, enabling a priori evaluation of the properties of drug candidates during the drug design process.The main objective of the present study was to develop a linear model for the quantitative prediction of half-lives of acyl glucuronidated drug-like compounds. The proposed model revealed that the number of total quaternary carbons, the complexity of the ring in the compound, Sanderson electronegativities, and dipole moment of the compound are important molecular features in predicting the half-life of an AG.The rigorously validated model can contribute to a better understanding of molecular features of these drugs to predict degradation half-lives.

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