Zhu Kai, Borrelli Kenneth W, Greenwood Jeremy R, Day Tyler, Abel Robert, Farid Ramy S, Harder Edward
Schrodinger Inc., 120 West 45th Street, New York, New York 10036, United States.
J Chem Inf Model. 2014 Jul 28;54(7):1932-40. doi: 10.1021/ci500118s. Epub 2014 Jun 26.
Although many popular docking programs include a facility to account for covalent ligands, large-scale systematic docking validation studies of covalent inhibitors have been sparse. In this paper, we present the development and validation of a novel approach for docking and scoring covalent inhibitors, which consists of conventional noncovalent docking, heuristic formation of the covalent attachment point, and structural refinement of the protein-ligand complex. This approach combines the strengths of the docking program Glide and the protein structure modeling program Prime and does not require any parameter fitting for the study of additional covalent reaction types. We first test this method by predicting the native binding geometry of 38 covalently bound complexes. The average RMSD of the predicted poses is 1.52 Å, and 76% of test set inhibitors have an RMSD of less than 2.0 Å. In addition, the apparent affinity score constructed herein is tested on a virtual screening study and the characterization of the SAR properties of two different series of congeneric compounds with satisfactory success.
尽管许多流行的对接程序都具备处理共价配体的功能，但针对共价抑制剂的大规模系统对接验证研究却很稀少。在本文中，我们展示了一种用于对接和评分共价抑制剂的新方法的开发与验证，该方法包括传统的非共价对接、共价连接点的启发式形成以及蛋白质 - 配体复合物的结构优化。这种方法结合了对接程序Glide和蛋白质结构建模程序Prime的优势，并且在研究其他共价反应类型时无需任何参数拟合。我们首先通过预测38个共价结合复合物的天然结合几何结构来测试此方法。预测构象的平均均方根偏差（RMSD）为1.52 Å，并且测试集中76%的抑制剂的RMSD小于2.0 Å。此外，本文构建的表观亲和力评分在虚拟筛选研究以及对两个不同系列同系化合物的构效关系（SAR）特性表征中进行了测试，均取得了令人满意的结果。
