Wilson Michael A, Pohorille Andrew
Exobiology Branch, MS 239-4, NASA Ames Research Center, Moffett Field, CA 94035, USA.
SETI Institute, 189 Bernardo Ave, Suite 200, Mountain View, CA 94043, USA.
Entropy (Basel). 2021 May 6;23(5):571. doi: 10.3390/e23050571.
We use stochastic simulations to investigate the performance of two recently developed methods for calculating the free energy profiles of ion channels and their electrophysiological properties, such as current-voltage dependence and reversal potential, from molecular dynamics simulations at a single applied voltage. These methods require neither knowledge of the diffusivity nor simulations at multiple voltages, which greatly reduces the computational effort required to probe the electrophysiological properties of ion channels. They can be used to determine the free energy profiles from either forward or backward one-sided properties of ions in the channel, such as ion fluxes, density profiles, committor probabilities, or from their two-sided combination. By generating large sets of stochastic trajectories, which are individually designed to mimic the molecular dynamics crossing statistics of models of channels of trichotoxin, p7 from hepatitis C and a bacterial homolog of the pentameric ligand-gated ion channel, GLIC, we find that the free energy profiles obtained from stochastic simulations corresponding to molecular dynamics simulations of even a modest length are burdened with statistical errors of only 0.3 kcal/mol. Even with many crossing events, applying two-sided formulas substantially reduces statistical errors compared to one-sided formulas. With a properly chosen reference voltage, the current-voltage curves can be reproduced with good accuracy from simulations at a single voltage in a range extending for over 200 mV. If possible, the reference voltages should be chosen not simply to drive a large current in one direction, but to observe crossing events in both directions.
我们使用随机模拟来研究最近开发的两种方法的性能,这两种方法用于从单个施加电压下的分子动力学模拟中计算离子通道的自由能分布及其电生理特性,如电流-电压依赖性和反转电位。这些方法既不需要扩散率的知识,也不需要在多个电压下进行模拟,这大大减少了探测离子通道电生理特性所需的计算量。它们可用于根据通道中离子的正向或反向单侧特性(如离子通量、密度分布、反应概率)或其双侧组合来确定自由能分布。通过生成大量随机轨迹,这些轨迹被单独设计用于模拟来自毛喉毒素、丙型肝炎病毒p7以及五聚体配体门控离子通道GLIC的细菌同源物的通道模型的分子动力学穿越统计,我们发现,即使是适度长度的分子动力学模拟对应的随机模拟所获得的自由能分布,其统计误差也仅为0.3千卡/摩尔。即使有许多穿越事件,与单侧公式相比,应用双侧公式也能大幅降低统计误差。通过适当选择参考电压,在超过200毫伏的范围内,从单个电压的模拟中可以高精度地重现电流-电压曲线。如果可能的话,参考电压的选择不应仅仅是为了在一个方向上驱动大电流,而是要观察两个方向上的穿越事件。