Department of Physics and Astronomy, University of Tennessee , Knoxville, Tennessee 37996, United States.
J Chem Theory Comput. 2017 Feb 14;13(2):916-925. doi: 10.1021/acs.jctc.6b00968. Epub 2017 Jan 26.
Biological cell membranes are responsible for a range of structural and dynamical phenomena crucial, which are crucial to a cell's well-being and its associated functions. Due to the complexity of cell membranes, lipid bilayer systems are often used as biomimetic models. These systems have led to significant insights into vital membrane phenomena such as domain formation, passive permeation, and protein insertion. Experimental observations of membrane structure and dynamics are, however, limited in resolution, both spatial and temporal. Importantly, computer simulations are starting to play a more prominent role in interpreting experimental results, enabling a molecular understanding of lipid membranes. In particular, the synergy between scattering experiments and simulations offers opportunities for new discoveries in membrane physics, as the length and time scales probed by molecular dynamics (MD) simulations parallel those of experiments. Here, we describe a coarse-grained MD simulation approach that mimics neutron scattering data from large unilamellar lipid vesicles over a range of bilayer rigidities. Specifically, we simulate vesicle form factors and membrane thickness fluctuations determined from small angle neutron scattering (SANS) and neutron spin echo (NSE) experiments, respectively. Our simulations accurately reproduce trends from experiments and lay the groundwork for studies of more complex membrane systems.
生物细胞膜负责一系列结构和动力学现象，这些现象对细胞的健康及其相关功能至关重要。由于细胞膜的复杂性，脂质双层系统通常被用作仿生模型。这些系统为重要的膜现象提供了重要的见解，如域形成、被动渗透和蛋白质插入。然而，膜结构和动力学的实验观察在空间和时间分辨率上都受到限制。重要的是，计算机模拟开始在解释实验结果方面发挥更突出的作用，使人们能够从分子水平理解脂质膜。特别是，散射实验和模拟之间的协同作用为膜物理的新发现提供了机会，因为分子动力学 (MD) 模拟所探测的长度和时间尺度与实验平行。在这里，我们描述了一种粗粒化 MD 模拟方法，该方法模拟了从中性原子散射实验中获取的大单层脂质囊泡在一系列双层刚性范围内的数据。具体来说，我们模拟了从小角中子散射 (SANS) 和中子自旋回波 (NSE) 实验分别确定的囊泡形态因子和膜厚度波动。我们的模拟准确地再现了实验趋势，为更复杂的膜系统研究奠定了基础。
