Department of Pharmaceutical Chemistry, University of California, San Francisco, California 94158-2517, USA.
Biochemistry. 2010 May 18;49(19):4003-5. doi: 10.1021/bi100445g.
In silico protein-ligand docking methods have proven to be useful in drug design and have also shown promise for predicting the substrates of enzymes, an important goal given the number of enzymes with uncertain function. Further testing of this latter approach is critical because (1) metabolites are on average much more polar than druglike compounds and (2) binding is necessary but not sufficient for catalysis. Here, we demonstrate that docking against the enzymes that participate in the 10 major steps of the glycolysis pathway in Escherichia coli succeeds in identifying the substrates among the top 1% of a virtual metabolite library.
计算机蛋白配体对接方法已被证明在药物设计中非常有用，并且在预测酶的底物方面也显示出了前景，考虑到具有不确定功能的酶数量众多，这是一个重要的目标。进一步测试这种方法是至关重要的，因为 (1) 代谢物的极性平均比类似药物的化合物高得多，以及 (2) 结合对于催化是必要的，但不是充分的。在这里，我们证明了针对大肠杆菌糖酵解途径的 10 个主要步骤中的酶进行对接，可以成功地在虚拟代谢物库的前 1%中识别出底物。
