Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland21201, United States.
Lilly Biotechnology Center, San Diego, California92121, United States.
J Chem Theory Comput. 2022 Dec 13;18(12):7510-7527. doi: 10.1021/acs.jctc.2c00586. Epub 2022 Nov 15.
Constant pH molecular dynamics (MD) simulations sample protonation states on the fly according to the conformational environment and user specified pH conditions; however, the current accuracy is limited due to the use of implicit-solvent models or a hybrid solvent scheme. Here, we report the first GPU-accelerated implementation, parametrization, and validation of the all-atom continuous constant pH MD (CpHMD) method with particle-mesh Ewald (PME) electrostatics in the Amber22 engine. The titration parameters for Asp, Glu, His, Cys, and Lys were derived for the CHARMM c22 and Amber ff14sb and ff19sb force fields. We then evaluated the PME-CpHMD method using the asynchronous pH replica-exchange titration simulations with the c22 force field for six benchmark proteins, including BBL, hen egg white lysozyme (HEWL), staphylococcal nuclease (SNase), thioredoxin, ribonuclease A (RNaseA), and human muscle creatine kinase (HMCK). The root-mean-square deviation from the experimental p's of Asp, Glu, His, and Cys is 0.76 pH units, and the Pearson's correlation coefficient for the p shifts with respect to model values is 0.80. We demonstrated that a finite-size correction or much enlarged simulation box size can remove a systematic error of the calculated p's and improve agreement with experiment. Importantly, the simulations captured the relevant biology in several challenging cases, e.g., the titration order of the catalytic dyad Glu35/Asp52 in HEWL and the coupled residues Asp19/Asp21 in SNase, the large p upshift of the deeply buried catalytic Asp26 in thioredoxin, and the large p downshift of the deeply buried catalytic Cys283 in HMCK. We anticipate that PME-CpHMD will offer proper pH control to improve the accuracies of MD simulations and enable mechanistic studies of proton-coupled dynamical processes that are ubiquitous in biology but remain poorly understood due to the lack of experimental tools and limitation of current MD simulations.
恒 pH 分子动力学 (MD) 模拟根据构象环境和用户指定的 pH 条件实时采样质子化状态;然而,由于使用隐式溶剂模型或混合溶剂方案,目前的准确性受到限制。在这里,我们报告了第一个在 Amber22 引擎中使用 GPU 加速实现、参数化和验证全原子连续恒 pH MD (CpHMD) 方法与粒子网格 Ewald (PME) 静电的方法。针对 CHARMM c22 和 Amber ff14sb 和 ff19sb 力场,我们推导了 Asp、Glu、His、Cys 和 Lys 的滴定参数。然后,我们使用带有 c22 力场的异步 pH 复制交换滴定模拟对六个基准蛋白(包括 BBL、鸡卵清溶菌酶 (HEWL)、金黄色葡萄球菌核酸酶 (SNase)、硫氧还蛋白、核糖核酸酶 A (RNaseA) 和人肌肉肌酸激酶 (HMCK))进行了 PME-CpHMD 方法的评估。Asp、Glu、His 和 Cys 的实验 p 值的均方根偏差为 0.76 pH 单位,模型值的 p 偏移的 Pearson 相关系数为 0.80。我们证明,有限尺寸修正或更大的模拟盒尺寸可以消除计算 p 值的系统误差,并提高与实验的一致性。重要的是,模拟在几个具有挑战性的情况下捕捉到了相关的生物学,例如,HEWL 中催化二联体 Glu35/Asp52 的滴定顺序和 SNase 中 Asp19/Asp21 的偶联残基、硫氧还蛋白中深埋的催化 Asp26 的大 p 上移以及 HMCK 中深埋的催化 Cys283 的大 p 下移。我们预计 PME-CpHMD 将提供适当的 pH 控制,以提高 MD 模拟的准确性,并能够对质子偶联动力学过程进行机制研究,这些过程在生物学中普遍存在,但由于缺乏实验工具和当前 MD 模拟的限制,这些过程仍未得到很好的理解。