Abstract

IBRAHIM, Muhammad Tukur et al. Molecular Modelling, Docking and Pharmacokinetic Studies of N-Arylidenequinoline-3-Carbohydrazides Analogs as Novel β-Glucuronidase Inhibitors. J. Mex. Chem. Soc [online]. 2020, vol.64, n.1, pp.30-40.  Epub Dec 31, 2020. ISSN 1870-249X.  https://doi.org/10.29356/jmcs.v64i1.1025.

Quantitative structure-activity relationships (QSAR) modelling on 30 N-Arylidenequinoline-3-carbohydrazides analogs was performed using Multi-Linear Regression (MLR) analysis adopting Genetic Function Algorithm (GFA) method. Semi empirical method using PM6 basis set was used for complete geometry optimization of the data set. The best model was chosen based on its statistical fit due to it good internal and external validations. From the Williams plot, it can be inferred that the reported model can make prediction of new compounds that are not within the data set. The molecular docking study showed that, the most active chemical in the data set was better than the standard β-glucuronidase inhibitor both in terms of binding scores and the amino acid residues that interacted with the drug and β-glucuronidase enzyme. The Pharmacokinetic studies indicated that none of the chemicals violated any of the condition set by the Lipinski′s Rule of five which confirm the bioavailability of these chemicals. The results these findings give room for designing novel β-glucuronidase inhibitors that are highly effective.

Keywords : Molecular modeling; docking; GFA; β-glucuronidase.

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