Woo Hyung-June, Dinner Aaron R, Roux Benoît
Department of Biochemistry, Weill Medical College of Cornell University, New York, New York 10021, USA.
J Chem Phys. 2004 Oct 1;121(13):6392-400. doi: 10.1063/1.1784436.
The grand canonical simulation algorithm is considered as a general methodology to sample the configuration of water molecules confined within protein environments. First, the probability distribution of the number of water molecules and their configuration in a region of interest for biochemical simulations, such as the active site of a protein, is derived by considering a finite subvolume in open equilibrium with a large system serving as a bulk reservoir. It is shown that the influence of the bulk reservoir can be represented as a many-body potential of mean force acting on the atoms located inside the subvolume. The grand canonical Monte Carlo (GCMC) algorithm, augmented by a number of technical advances to increase the acceptance of insertion attempts, is implemented, and tested for simple systems. In particular, the method is illustrated in the case of a pure water box with periodic boundary conditions. In addition, finite spherical systems of pure water and containing a dialanine peptide, are simulated with GCMC while the influence of the surrounding infinite bulk is incorporated using the generalized solvent boundary potential [W. Im, S. Berneche, and B. Roux, J. Chem. Phys. 114, 2924 (2001)]. As a last illustration of water confined in the interior of a protein, the hydration of the central cavity of the KcsA potassium channel is simulated.
巨正则模拟算法被视为一种用于对限制在蛋白质环境中的水分子构型进行采样的通用方法。首先,通过考虑与作为大量储库的大系统处于开放平衡的有限子体积,推导出生化模拟感兴趣区域(如蛋白质活性位点)内水分子数量及其构型的概率分布。结果表明,大量储库的影响可以表示为作用于子体积内原子的多体平均力势。实现了通过若干技术改进增强以提高插入尝试接受率的巨正则蒙特卡罗(GCMC)算法,并针对简单系统进行了测试。特别是,该方法在具有周期性边界条件的纯水盒的情况下进行了说明。此外,使用GCMC模拟了纯水的有限球形系统以及包含二丙氨酸肽的系统,同时使用广义溶剂边界势[W. Im, S. Berneche, and B. Roux, J. Chem. Phys. 114, 2924 (2001)]纳入周围无限大量的影响。作为蛋白质内部受限水的最后一个示例,模拟了KcsA钾通道中心腔的水合作用。