Establishment of pharmacophore and VolSurf models to predict the substrates of UDP-glucuronosyltransferase1A3

Abstract

1. UDP-glucuronosyltransferase1A3 (UGT1A3) catalyzes glucuronidation of numerous xenobiotics/drugs. Here, we aimed to establish substrate selectivity models for UGT1A3 using the pharmacophore and VolSurf approaches.

2. Fifty structurally diverse substrates of UGT1A3 were collated from the literature. These substrates were divided into training (n = 34) and test sets (n = 16). The pharmacophore model was developed using the Discovery Studio 2.5 software. A user-defined feature (i.e. the glucuronidation site) was included in the program for model generation. The VolSurf model was derived using the VolSurf program implemented in SYBYL 8.0 software.

3. The pharmacophore model consisted of three features (i.e. one glucuronidation site and two hydrogen-bond acceptors). The activities of 81% of test set substrates were adequately predicted (deviated by less than one-log unit) by the model, suggestive of a satisfactory predictive power. The refined VolSurf model based on 22 molecular descriptors was statistically significant (r²= 0.793, q²= 0.606). It also processed a good predictability as the activities of 14 test set compounds were well predicted. The VolSurf model highlighted the chemical features (including large molecule size, hydrophilic regions and hydrogen-bonding groups) contributing to favored glucuronidation by UGT1A3.

4. In conclusion, two predictive 3D-QSAR models (i.e. the pharmacophore and VolSurf models) for UGT1A3 were successfully established. These models contributed to an improved understanding of the substrate preference of UGT1A3 and a more comprehensive prediction of UGT-mediated metabolism.

• Glucuronidation
• pharmacophore
• substrate selectivity
• UGT1A3
• VolSurf

Acknowledgements

The authors are grateful to Jing Fang from NeoTrident Technology for technical supports during the work.

Declaration of interest

This work was supported by the Young Scientist Special Projects in biotechnological and pharmaceutical field of 863 Program (SS2015AA020916).

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.

Supplementary material available online Supplementary Information