Department of Pharmacology, University of Texas Southwestern Medical Center at Dallas, 5323 Harry Hines Boulevard, Dallas, Texas 75390-9050, USA.
J Comput Chem. 2011 Dec;32(16):3505-19. doi: 10.1002/jcc.21939. Epub 2011 Sep 22.
In this work, we have evaluated how well the general assisted model building with energy refinement (AMBER) force field performs in studying the dynamic properties of liquids. Diffusion coefficients (D) have been predicted for 17 solvents, five organic compounds in aqueous solutions, four proteins in aqueous solutions, and nine organic compounds in nonaqueous solutions. An efficient sampling strategy has been proposed and tested in the calculation of the diffusion coefficients of solutes in solutions. There are two major findings of this study. First of all, the diffusion coefficients of organic solutes in aqueous solution can be well predicted: the average unsigned errors and the root mean square errors are 0.137 and 0.171 × 10(-5) cm(-2) s(-1), respectively. Second, although the absolute values of D cannot be predicted, good correlations have been achieved for eight organic solvents with experimental data (R(2) = 0.784), four proteins in aqueous solutions (R(2) = 0.996), and nine organic compounds in nonaqueous solutions (R(2) = 0.834). The temperature dependent behaviors of three solvents, namely, TIP3P water, dimethyl sulfoxide, and cyclohexane have been studied. The major molecular dynamics (MD) settings, such as the sizes of simulation boxes and with/without wrapping the coordinates of MD snapshots into the primary simulation boxes have been explored. We have concluded that our sampling strategy that averaging the mean square displacement collected in multiple short-MD simulations is efficient in predicting diffusion coefficients of solutes at infinite dilution.
在这项工作中,我们评估了通用辅助模型构建与能量细化(AMBER)力场在研究液体动力学性质方面的表现。我们预测了 17 种溶剂、5 种水溶液中的有机化合物、4 种水溶液中的蛋白质和 9 种非水溶液中的有机化合物的扩散系数(D)。我们提出并测试了一种有效的采样策略,用于计算溶液中溶质的扩散系数。本研究有两个主要发现。首先,可以很好地预测水溶液中有机溶质的扩散系数:平均无偏差误差和均方根误差分别为 0.137 和 0.171×10(-5) cm(-2) s(-1)。其次,尽管无法预测 D 的绝对值,但对于 8 种有机溶剂、4 种水溶液中的蛋白质和 9 种非水溶液中的有机化合物,均能达到良好的相关性(R(2) = 0.784、R(2) = 0.996、R(2) = 0.834)。我们研究了三种溶剂,即 TIP3P 水、二甲基亚砜和环己烷的温度依赖性行为。探索了主要的分子动力学(MD)设置,例如模拟盒的大小以及是否将 MD 快照的坐标包裹到主模拟盒中。我们得出结论,我们的采样策略,即在多个短 MD 模拟中平均收集的均方位移,在预测无限稀释溶质的扩散系数方面是有效的。