论文标题
小离子半径限制时间步长3分子动力学模拟
Small ionic radii limit time step in Martini 3 molecular dynamics simulations
论文作者
论文摘要
除其他改进外,Martini 3粗粒力场通过持续使用各种珠子类型和尺寸来更准确地描述了蛋白质口袋和通道的溶剂化。在这里,我们表明Na $^+$和Cl $^ - $离子的表示为“ Tiny”(TQ5)珠子将可访问的时间步长限制为25 fs。相比之下,使用马提尼酒2,没有蛋白质的脂质双层系统可能会达到30-40 fs。该限制与需要长时间平衡时间的脂质混合物相关。我们得出了分子动力学(MD)中时间整合不稳定性的定量动力学模型,这是时间步长,离子浓度和质量,系统大小和仿真时间的函数。通过此模型,我们证明了离子 - 水相互作用是生理条件下不稳定性的主要来源,然后是离子离子相互作用。我们表明,增加离子质量使得可以使用高达40 fs的时间步骤对静态平衡特性以及脂质和离子扩散系数等动态量的影响最小。增加代表离子的珠子的大小(从而改变其水合)也允许更长的时间步骤。 Martini 3模拟中更大的时间步骤的使用导致对配置空间的更有效探索。每当采样效率至关重要时,MD模拟崩溃的动力学模型可用于确定最大允许的时间步长。
Among other improvements, the Martini 3 coarse-grained force field provides a more accurate description of the solvation of protein pockets and channels through the consistent use of various bead types and sizes. Here, we show that the representation of Na$^+$ and Cl$^-$ ions as "tiny" (TQ5) beads limits the accessible time step to 25 fs. By contrast, with Martini 2, time steps of 30-40 fs were possible for lipid bilayer systems without proteins. This limitation is relevant for, e.g., phase separating lipid mixtures that require long equilibration times. We derive a quantitative kinetic model of time-integration instabilities in molecular dynamics (MD) as a function of time step, ion concentration and mass, system size, and simulation time. With this model, we demonstrate that ion-water interactions are the main source of instability at physiological conditions, followed closely by ion-ion interactions. We show that increasing the ionic masses makes it possible to use time steps up to 40 fs with minimal impact on static equilibrium properties and on dynamical quantities such as lipid and ion diffusion coefficients. Increasing the size of the bead representing the ions (and thus changing their hydration) also permits longer time steps. The use of larger time steps in Martini 3 simulations results in a more efficient exploration of configuration space. The kinetic model of MD simulation crashes can be used to determine the maximum allowed time step whenever sampling efficiency is critical.