Accurate Prediction of Glucuronidation of Structurally Diverse Phenolics by Human UGT1A9 Using Combined Experimental and In Silico Approaches

作者：Wu Baojian; Wang Xiaoqiang; Zhang Shuxing; Hu Ming^*

来源：Pharmaceutical Research, 2012, 29(6): 1544-1561.

DOI：10.1007/s11095-012-0666-z

• CoMFA
• CoMSIA
• glucuronidation
• homology modeling
• UGT1A9

Catalytic selectivity of human UGT1A9, an important membrane-bound enzyme catalyzing glucuronidation of xenobiotics, was determined experimentally using 145 phenolics and analyzed by 3D-QSAR methods. %26lt;br%26gt;Catalytic efficiency of UGT1A9 was determined by kinetic profiling. Quantitative structure activity relationships were analyzed using CoMFA and CoMSIA techniques. Molecular alignment of substrate structures was made by superimposing the glucuronidation site and its adjacent aromatic ring to achieve maximal steric overlap. For a substrate with multiple active glucuronidation sites, each site was considered a separate substrate. %26lt;br%26gt;3D-QSAR analyses produced statistically reliable models with good predictive power (CoMFA: q(2) = 0.548, r(2) = 0.949, r (pred) (2) = 0.775; CoMSIA: q(2) = 0.579, r(2) = 0.876, r (pred) (2) = 0.700). Contour coefficient maps were applied to elucidate structural features among substrates that are responsible for selectivity differences. Contour coefficient maps were overlaid in the catalytic pocket of a homology model of UGT1A9, enabling identification of the UGT1A9 catalytic pocket with a high degree of confidence. %26lt;br%26gt;CoMFA/CoMSIA models can predict substrate selectivity and clearance of UGT1A9. Our findings also provide a possible molecular basis for understanding UGT1A9 functions and substrate selectivity.

• 出版日期2012-6