Higher Accuracy Achieved for Protein-Ligand Binding Pose Prediction by Elastic Network Model-Based Ensemble Docking
Higher Accuracy Achieved for Protein-Ligand Binding Pose Prediction by Elastic Network Model-Based Ensemble Docking
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通过基于弹性网络模型的集成对接实现了更高准确度的蛋白质-配体结合姿势预测
DOI：
10.1021/acs.jcim.9b01168
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发表时间：
2020-05
影响因子：
5.6
通讯作者：
Li Guohui
中科院分区：
文献类型：
--
作者：
Wang Anhui;Zhang Yuebin;Chu Huiying;Liao Chenyi;Zhang Zhichao;Li Guohui
分子对接在预测受体-配体相互作用中起着不可或缺的作用，其中蛋白质受体通常保持刚性，而配体被视为柔性。由于蛋白质固有的柔性，载脂蛋白受体的结合口袋在与配体结合时可能发生显著的构象重排，这限制了对接预测的准确性。在这里，我们提出了一个迭代的各向异性网络模型（iterANM）为基础的合奏对接方法，产生多个全息样受体结构从载脂蛋白受体，并将蛋白质的灵活性对接。在由233种化学上不同的CDK 2抑制剂组成的验证数据集中，与使用来自分子动力学（MD）模拟的单一载脂蛋白受体构象或构象系综的那些相比，基于iterANM的系综对接实现了更高的再现天然样结合姿势的能力。iterANM产生的top5排序的结合位姿内的预测成功率可以通过用分子力学-Poisson Boltzmann/表面积（MMPBSA）方法重新排序来进一步提高。在具有58种CDK 2抑制剂的较小数据集中，与基于柔性受体的对接程序AutoDockFR和其他受体构象生成方法相比，基于iterANM的集成显示出更高的成功率。此外，由十种不同的受体/配体组合组成的额外的对接测试表明，iterANM是稳健地适用于不同的受体结构。这些结果表明，基于iterANM的系综对接作为一个准确，高效，实用的框架来预测具有灵活性的受体的配体的结合模式。
Molecular docking plays an indispensable role in predicting the receptor-ligand interactions in which the protein receptor is usually kept rigid while the ligand is treated as being flexible. Due to the inherent flexibility of proteins, the binding pocket of apo receptors might undergo significant conformational rearrangement upon ligand binding, which limits the prediction accuracy of docking. Here, we present an iterative Anisotropic Network Model (iterANM)-based ensemble docking approach which generates multiple holo-like receptor structures starting from the apo receptor and incorporates protein flexibility into docking. In a validation dataset consisting of 233 chemically diverse CDK2 inhibitors, the iterANM-based ensemble docking achieves higher capacity to reproduce native-like binding poses compared with those using single apo receptor conformation or conformational ensemble from molecular dynamics (MD) simulations. The prediction success rate within top5-ranked binding poses produced by iterANM can further be improved through re-ranking with the molecular mechanics-Poisson Boltzmann/surface area (MMPBSA) method. In a smaller dataset with 58 CDK2 inhibitors, the iterANM-based ensemble shows higher success rate compared with the flexible-receptor-based docking procedure AutoDockFR and other receptor conformation generation approaches. Further, an additional docking test consisting of ten diverse receptor/ligand combinations shows that the iterANM is robustly applicable for different receptor structures. These results suggest the iterANM-based ensemble docking as an accurate, efficient, and practical framework to predict the binding mode of a ligand for receptors with flexibility.
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