Using Correlated Monte Carlo Sampling for Efficiently Solving the Linearized Poisson-Boltzmann Equation Over a Broad Range of Salt Concentration.
Using Correlated Monte Carlo Sampling for Efficiently Solving the Linearized Poisson-Boltzmann Equation Over a Broad Range of Salt Concentration.
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DOI：
10.1021/ct9003806
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发表时间：
2010-01-01
影响因子：
5.5
通讯作者：
Simonov, Nikolai A.
中科院分区：
文献类型：
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作者：
Fenley, Marcia O.;Mascagni, Michael;McClain, James;Silalahi, Alexander R. J.;Simonov, Nikolai A.
介电连续或隐式溶剂模型提供了一个显着降低计算成本时，占盐介导的静电相互作用的生物分子浸没在离子环境中。这些模型中，溶剂和离子被取代的介电连续，试图捕捉平均统计效应的离子溶剂，而溶质处理在原子水平的细节。几十年来，三维Poisson-Boltzmann方程（PBE）的解已经成为评估生物分子系统中静电效应的标准隐式溶剂工具，它基于各种确定性数值方法。一些确定性PBE算法有缺点，其中包括缺乏适当评估其精度，离散化引起的几何困难，以及对于某些问题，它们在存储器和计算时间上的成本。我们原来的随机方法解决了这些困难，通过解决PBE使用蒙特卡罗方法（MCM）。这种新的PBE方法能够有效地解决复杂的，多域和盐依赖性的问题，在生物分子连续静电高精度。在这里，我们改进了我们的新的随机方法，通过相关的Monte Carlo（MC）采样，在不同的离子浓度下，通过计算静电势和溶剂化自由能。通过在我们的算法中使用精心构建的相关随机游走，我们实际上可以同时计算包括所有感兴趣的盐浓度下的线性化PBE（LPBE）的标准系统的解。这种方法不仅加快了我们的MCPBE算法，但似乎有成本和精度的优势，以及确定性的方法。我们验证了这种技术的有效性，通过将其应用到两个常见的静电计算：静电势和极性溶剂化自由能的钙结合蛋白质，使用成熟的确定性PBE方法获得类似的结果进行比较。
Dielectric continuum or implicit solvent models provide a significant reduction in computational cost when accounting for the salt-mediated electrostatic interactions of biomolecules immersed in an ionic environment. These models, in which the solvent and ions are replaced by a dielectric continuum, seek to capture the average statistical effects of the ionic solvent, while the solute is treated at the atomic level of detail. For decades, the solution of the three-dimensional Poisson-Boltzmann equation (PBE), which has become a standard implicit-solvent tool for assessing electrostatic effects in biomolecular systems, has been based on various deterministic numerical methods. Some deterministic PBE algorithms have drawbacks, which include a lack of properly assessing their accuracy, geometrical difficulties caused by discretization, and for some problems their cost in both memory and computation time. Our original stochastic method resolves some of these difficulties by solving the PBE using the Monte Carlo method (MCM). This new approach to the PBE is capable of efficiently solving complex, multi-domain and salt-dependent problems in biomolecular continuum electrostatics to high precision. Here we improve upon our novel stochastic approach by simultaneouly computating of electrostatic potential and solvation free energies at different ionic concentrations through correlated Monte Carlo (MC) sampling. By using carefully constructed correlated random walks in our algorithm, we can actually compute the solution to a standard system including the linearized PBE (LPBE) at all salt concentrations of interest, simultaneously. This approach not only accelerates our MCPBE algorithm, but seems to have cost and accuracy advantages over deterministic methods as well. We verify the effectiveness of this technique by applying it to two common electrostatic computations: the electrostatic potential and polar solvation free energy for calcium binding proteins that are compared with similar results obtained using mature deterministic PBE methods.
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影响因子：
3
作者：
DAVIS, ME;MCCAMMON, JA
通讯作者：
MCCAMMON, JA
影响因子：
3.4
作者：
Fujiwara, Shin-Ichi;Amisaki, Takashi
通讯作者：
Amisaki, Takashi
影响因子：
3
作者：
BROOKS, BR;BRUCCOLERI, RE;KARPLUS, M
通讯作者：
KARPLUS, M
影响因子：
5.6
作者：
Bhardwaj, Nitin;Stahelin, Robert V.;Lu, Hui
通讯作者：
Lu, Hui
影响因子：
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作者：
BONDI, A
通讯作者：
BONDI, A