Molecular Graphics Lab, Department of Molecular Biology, MB-112, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037-1000, United States.
J Med Chem. 2012 Jan 26;55(2):623-38. doi: 10.1021/jm2005145. Epub 2012 Jan 13.
In modeling ligand-protein interactions, the representation and role of water are of great importance. We introduce a force field and hydration docking method that enables the automated prediction of waters mediating the binding of ligands with target proteins. The method presumes no prior knowledge of the apo or holo protein hydration state and is potentially useful in the process of structure-based drug discovery. The hydration force field accounts for the entropic and enthalpic contributions of discrete waters to ligand binding, improving energy estimation accuracy and docking performance. The force field has been calibrated and validated on a total of 417 complexes (197 training set; 220 test set), then tested in cross-docking experiments, for a total of 1649 ligand-protein complexes evaluated. The method is computationally efficient and was used to model up to 35 waters during docking. The method was implemented and tested using unaltered AutoDock4 with new force field tables.
在建模配体-蛋白质相互作用时,水的表示和作用非常重要。我们引入了一种力场和水合对接方法,使自动预测介导配体与靶蛋白结合的水成为可能。该方法假定没有apo 或 holo 蛋白水合状态的先验知识,在基于结构的药物发现过程中具有潜在的用途。水合力场考虑了离散水对配体结合的熵和焓贡献,提高了能量估计的准确性和对接性能。该力场已在总共 417 个复合物(197 个训练集;220 个测试集)上进行了校准和验证,然后在交叉对接实验中进行了测试,总共评估了 1649 个配体-蛋白质复合物。该方法计算效率高,在对接过程中最多可模拟 35 个水分子。该方法使用未修改的 AutoDock4 和新的力场表进行了实现和测试。