Department of Chemistry, University of Florida, Gainesville, Florida 32611, USA.
Institute of Physics, Federal University of Mato Grosso do Sul, Campo Grande, MS 79070-900, Brazil.
J Chem Phys. 2018 Aug 21;149(7):072338. doi: 10.1063/1.5027379.
Redox processes are important in chemistry, with applications in biomedicine, chemical analysis, among others. As many redox experiments are also performed at a fixed value of pH, having an efficient computational method to support experimental measures at both constant redox potential and pH is very important. Such computational techniques have the potential to validate experimental observations performed under these conditions and to provide additional information unachievable experimentally such as an atomic level description of macroscopic measures. We present the implementation of discrete redox and protonation states methods for constant redox potential Molecular Dynamics (CEMD), for coupled constant pH and constant redox potential MD (C(pH,E)MD), and for Replica Exchange MD along the redox potential dimension (E-REMD) on the AMBER software package. Validation results are presented for a small system that contains a single heme group: -acetylmicroperoxidase-8 (NAcMP8) axially connected to a histidine peptide. The methods implemented allow one to make standard redox potential (E) predictions with the same easiness and accuracy as p predictions using the constant pH molecular dynamics and pH-REMD methods currently available on AMBER. In our simulations, we can correctly describe, in agreement also with theoretical predictions, the following behaviors: when a redox-active group is reduced, the p of a near pH-active group increases because it becomes easier for a proton to be attached; equivalently, when a pH-active group is protonated, the standard redox potential (E) of an adjacent redox-active group rises. Furthermore, our results also show that E-REMD is able to achieve faster statistical convergence than CEMD or C(pH,E)MD. Moreover, computational benchmarks using our methodologies show high-performance of GPU (Graphics Processing Unit) accelerated calculations in comparison to conventional CPU (Central Processing Unit) calculations.
氧化还原过程在化学中很重要，其应用包括生物医学、化学分析等。由于许多氧化还原实验也是在固定 pH 值下进行的，因此拥有一种有效的计算方法来支持恒氧化还原电位和 pH 值下的实验测量非常重要。这种计算技术有可能验证在这些条件下进行的实验观察，并提供无法通过实验获得的额外信息，例如宏观测量的原子水平描述。我们在 AMBER 软件包上实现了用于恒氧化还原电位分子动力学 (CEMD) 的离散氧化还原和质子化状态方法、用于耦合恒 pH 和恒氧化还原电位 MD (C(pH,E)MD) 的方法，以及用于氧化还原电位维度的复制交换 MD (E-REMD)。为包含单个血红素基团的小系统：-乙酰化微过氧化物酶-8 (NAcMP8) 轴向连接到组氨酸肽，提出了验证结果。所实现的方法允许使用与当前在 AMBER 上可用的恒 pH 分子动力学和 pH-REMD 方法一样轻松和准确地进行标准氧化还原电位 (E) 预测。在我们的模拟中，我们可以正确描述，也与理论预测一致，以下行为：当一个氧化还原活性基团被还原时，一个接近 pH 活性基团的 pH 值增加，因为更容易附着一个质子；同样，当一个 pH 活性基团被质子化时，相邻氧化还原活性基团的标准氧化还原电位 (E) 上升。此外，我们的结果还表明，E-REMD 能够比 CEMD 或 C(pH,E)MD 更快地实现统计收敛。此外，使用我们的方法学进行的计算基准测试表明，与传统的中央处理单元 (CPU) 计算相比，图形处理单元 (GPU) 加速计算具有高性能。
