Department of Chemistry, National Dong Hwa University, Shoufeng, Hualien 97401, Taiwan.
Department of Life Science and Institute of Biotechnology, National Dong Hwa University, Shoufeng, Hualien 97401, Taiwan.
Sci Rep. 2017 Jan 6;7:40053. doi: 10.1038/srep40053.
The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r = 0.928-0.988, = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pK values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r = 0.967, = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.
N-甲基-D-天冬氨酸受体（NMDAR）亚基 GluN1 的甘氨酸结合位点是神经退行性疾病的潜在药物靶点。为了预测 NMDAR GluN1-配体结合亲和力，生成了一种使用配体和蛋白质构象集合以及定制的支持向量机（SVM）-基于模型的新型组合集合对接方案，以选择对接构象并预测对接评分。通过 SVM-Pose 模型预测的构象 RMSD 值与观察值非常吻合（n=30，r=0.928-0.988，=0.894-0.954，RMSE=0.002-0.412，s=0.001-0.214），通过 SVM-Score 预测的 pK 值与训练样本（n=24，r=0.967，=0.899，RMSE=0.295，s=0.170）和测试样本（n=13，q=0.894，RMSE=0.437，s=0.202）的观察值非常吻合。当进行各种统计验证时，开发的 SVM-Pose 和 SVM-Score 模型始终满足最严格的标准。模拟测试证明了这种新型对接方案的可预测性。总的来说，这种准确的新型组合集合对接方案可用于预测 NMDAR GluN1-配体的结合亲和力，从而促进药物发现。
