Department of Biochemistry and Cellular and Molecular Biology , University of Tennessee , Knoxville , Tennessee 37996 , United States.
UT/ORNL Center for Molecular Biophysics , Oak Ridge , Tennessee 37830 , United States.
J Phys Chem B. 2019 Jun 27;123(25):5189-5195. doi: 10.1021/acs.jpcb.8b11491. Epub 2019 Feb 12.
Ensemble docking in drug discovery or chemical biology uses dynamical simulations of target proteins to generate binding site conformations for docking campaigns. We show that 600 ns molecular dynamics simulations of four G-protein-coupled receptors in their membrane environments generate ensembles of protein configurations that, collectively, are selected by 70?99% of the known ligands of these proteins. Therefore, the process of ligand recognition by conformational selection can be reproduced by combining molecular dynamics and docking calculations. Clustering of the molecular dynamics trajectories, however, does not necessarily identify the protein conformations that are most often selected by the ligands.
在药物发现或化学生物学中,集合对接使用目标蛋白的动力学模拟来生成对接研究的结合位点构象。我们表明,对四种 G 蛋白偶联受体在其膜环境中的 600 纳秒分子动力学模拟,产生了蛋白质构象的集合,这些构象总体上被这些蛋白质的 70%至 99%的已知配体选择。因此,通过结合分子动力学和对接计算,可以再现配体通过构象选择识别的过程。然而,分子动力学轨迹的聚类不一定能识别出最常被配体选择的蛋白质构象。