Dang Na Le, Hughes Tyler B, Krishnamurthy Varun, Swamidass S Joshua
Department of Pathology and Immunology, Washington University School of Medicine, Campus Box 8118, 660 S. Euclid Ave, St. Louis, MO 63110, USA.
Bioinformatics. 2016 Oct 15;32(20):3183-3189. doi: 10.1093/bioinformatics/btw350. Epub 2016 Jun 20.
Uridine diphosphate glucunosyltransferases (UGTs) metabolize 15% of FDA approved drugs. Lead optimization efforts benefit from knowing how candidate drugs are metabolized by UGTs. This paper describes a computational method for predicting sites of UGT-mediated metabolism on drug-like molecules.
XenoSite correctly predicts test molecule's sites of glucoronidation in the Top-1 or Top-2 predictions at a rate of 86 and 97%, respectively. In addition to predicting common sites of UGT conjugation, like hydroxyl groups, it can also accurately predict the glucoronidation of atypical sites, such as carbons. We also describe a simple heuristic model for predicting UGT-mediated sites of metabolism that performs nearly as well (with, respectively, 80 and 91% Top-1 and Top-2 accuracy), and can identify the most challenging molecules to predict on which to assess more complex models. Compared with prior studies, this model is more generally applicable, more accurate and simpler (not requiring expensive quantum modeling).
The UGT metabolism predictor developed in this study is available at http://swami.wustl.edu/xenosite/p/ugt CONTACT: : swamidass@wustl.eduSupplementary information: Supplementary data are available at Bioinformatics online.
尿苷二磷酸葡萄糖醛酸转移酶（UGTs）参与了15%的美国食品药品监督管理局（FDA）批准药物的代谢过程。了解候选药物如何被UGTs代谢有助于先导化合物的优化工作。本文描述了一种预测类药物分子上UGT介导的代谢位点的计算方法。
XenoSite分别以86%和97%的准确率在Top-1或Top-2预测中正确预测测试分子的葡萄糖醛酸化位点。除了预测UGT结合的常见位点，如羟基，它还能准确预测非典型位点（如碳原子）的葡萄糖醛酸化。我们还描述了一种简单的启发式模型，用于预测UGT介导的代谢位点，其表现几乎相同（Top-1和Top-2准确率分别为80%和91%），并且可以识别出预测难度最大的分子，以便评估更复杂的模型。与先前的研究相比，该模型更具通用性、更准确且更简单（不需要昂贵的量子建模）。
本研究中开发的UGT代谢预测器可在http://swami.wustl.edu/xenosite/p/ugt获取。联系方式：swamidass@wustl.edu。补充信息：补充数据可在《生物信息学》在线获取。
