Department of Chemistry , Bar-Ilan University , Ramat-Gan 52900 , Israel.
Hadassah Academic College , 7 Hanevi'im Street , Jerusalem 9101001 , Israel.
J Chem Theory Comput. 2019 Sep 10;15(9):5116-5134. doi: 10.1021/acs.jctc.9b00366. Epub 2019 Aug 27.
Enzymes play a pivotal role in all biological systems. These biomachines are the most effective catalysts known, dramatically enhancing the rate of reactions by more than 10 orders of magnitude relative to the uncatalyzed reactions in solution. Predicting the correct, mechanistically appropriate binding modes for substrate and product, as well as all reaction intermediates and transition states, along a reaction pathway is immensely challenging and remains an unsolved problem. In the present work, we developed an effective methodology for identifying probable binding modes of multiple ligand states along a reaction coordinate in an enzyme active site. The program is called EnzyDock and is a CHARMM-based multistate consensus docking program that includes a series of protocols to predict the chemically relevant orientation of substrate, reaction intermediates, transition states, product, and inhibitors. EnzyDock is based on simulated annealing molecular dynamics and Monte Carlo sampling and allows ligand, as well as enzyme side-chain and backbone flexibility. The program can employ many user-defined constraints and restraints and classical force field potentials, as well as a range of hybrid quantum mechanics-molecular mechanics potentials. Herein, we apply EnzyDock to several different kinds of problems. First, we study two terpene synthase reactions, namely bornyl diphosphate synthase and the bacterial diterpene synthase CotB2. Second, we use EnzyDock to predict reaction coordinate states in a pair of Diels-Alder reactions in the enzymes spirotetronate AbyU and LepI. Third, we study a couple of racemases: the cofactor-dependent serine racemase and the cofactor independent proline racemase. Finally, we study several cases of covalent docking involving the Michael addition reaction. For all systems we predict binding modes that are consistent with available experimental observations, as well as with theoretical modeling studies from the literature. EnzyDock provides a platform for generating mechanistic insight into enzyme reactions, useful and reliable starting points for in-depth multiscale modeling projects, and rational design of noncovalent and covalent enzyme inhibitors.
酶在所有生物系统中都起着关键作用。这些生物机器是已知的最有效的催化剂，通过相对于溶液中非催化反应提高 10 个数量级以上的速率来显著增强反应速率。预测正确的、机械上合适的底物和产物以及所有反应中间体和过渡态的结合模式，沿着反应途径是极具挑战性的，仍然是一个未解决的问题。在本工作中，我们开发了一种有效的方法，用于识别酶活性位点中沿反应坐标的多个配体状态的可能结合模式。该程序称为 EnzyDock，是一种基于 CHARMM 的多态共识对接程序，包括一系列预测底物、反应中间体、过渡态、产物和抑制剂化学相关取向的协议。EnzyDock 基于模拟退火分子动力学和蒙特卡罗采样，并允许配体以及酶侧链和骨架的灵活性。该程序可以采用许多用户定义的约束和限制以及经典的力场势能，以及一系列混合量子力学-分子力学势能。在此，我们将 EnzyDock 应用于几种不同的问题。首先，我们研究了两种萜烯合酶反应，即莰烯二磷酸合酶和细菌二萜合酶 CotB2。其次，我们使用 EnzyDock 预测了酶 spirotetronate AbyU 和 LepI 中的一对 Diels-Alder 反应的反应坐标状态。第三，我们研究了一对消旋酶：依赖辅因子的丝氨酸消旋酶和独立辅因子的脯氨酸消旋酶。最后，我们研究了涉及迈克尔加成反应的几个共价对接案例。对于所有系统，我们预测的结合模式与可用的实验观察结果以及文献中的理论建模研究一致。EnzyDock 为深入了解酶反应提供了一个平台，为深入的多尺度建模项目以及非共价和共价酶抑制剂的合理设计提供了有用且可靠的起点。
