Suh Donghyuk, Schwartz Renana, Gupta Prashant Kumar, Zev Shani, Major Dan T, Im Wonpil
Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania 18015, United States.
Department of Chemistry, Israel National Institute of Energy Storage (INIES) and Institute for Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 5290002, Israel.
J Chem Theory Comput. 2025 Feb 25;21(4):2118-2128. doi: 10.1021/acs.jctc.4c01691. Epub 2025 Feb 14.
Enzymes play crucial roles in all biological systems by catalyzing a myriad of chemical reactions. These reactions range from simple one-step processes to intricate multistep cascades. Predicting mechanistically appropriate binding modes along a reaction pathway for substrate, product, and all reaction intermediates and transition states is a daunting task. To address this challenge, special docking programs like EnzyDock have been developed. Yet, running such docking simulations is complicated due to the nature of multistep enzyme processes. This work presents CHARMM-GUI , a web-based cyberinfrastructure designed to streamline the preparation and running of EnzyDock docking simulations. The development of has been achieved through integration of existing CHARMM-GUI modules, such as , , and . In addition, new functionalities have been developed to facilitate a one-stop preparation of multistate and multiscale docking systems and enable interactive and intuitive ligand modifications and flexible protein residues selections. A simple setup related to multiligand docking is automatized through intuitive user interfaces. offers support for standard classical docking and QM/MM docking with CHARMM built-in semiempirical engines. Automated consensus restraints for incorporating experimental knowledge into the docking are facilitated via a maximum common substructure algorithm. To illustrate the robustness of , we conducted docking simulations of three enzyme systems: dihydrofolate reductase, SARS-CoV-2 M, and the diterpene synthase CotB2. In addition, we have created four tutorial videos about these systems, which can be found at https://www.charmm-gui.org/demo/enzydock. is expected to be a valuable and accessible web-based tool that simplifies and accelerates the setup process for multistate docking for enzymes.
酶通过催化无数化学反应在所有生物系统中发挥关键作用。这些反应范围从简单的一步过程到复杂的多步级联反应。预测底物、产物以及所有反应中间体和过渡态在反应途径上符合机理的结合模式是一项艰巨的任务。为应对这一挑战,已开发出诸如EnzyDock等特殊的对接程序。然而,由于多步酶促过程的性质,运行此类对接模拟很复杂。这项工作展示了CHARMM - GUI,这是一个基于网络的网络基础设施,旨在简化EnzyDock对接模拟的准备和运行。通过整合现有的CHARMM - GUI模块,如[此处原文缺失具体模块名称]、[此处原文缺失具体模块名称]和[此处原文缺失具体模块名称],实现了[此处原文缺失具体指代内容]的开发。此外,还开发了新功能,以促进多状态和多尺度对接系统的一站式准备,并实现交互式和直观的配体修饰以及灵活的蛋白质残基选择。通过直观的用户界面实现了与多配体对接相关的简单设置自动化。CHARMM - GUI支持使用CHARMM内置的半经验引擎进行标准经典对接和QM/MM对接。通过最大公共子结构算法促进了将实验知识纳入对接的自动一致性约束。为说明CHARMM - GUI的稳健性,我们对三种酶系统进行了对接模拟:二氢叶酸还原酶、SARS-CoV-2 M和二萜合酶CotB2。此外,我们制作了关于这些系统的四个教程视频,可在https://www.charmm-gui.org/demo/enzydock上找到。CHARMM - GUI有望成为一个有价值且易于使用的基于网络的工具,简化并加速酶多状态对接的设置过程。