Boschitsch Alexander H, Fenley Marcia O
Continuum Dynamics, Inc. 34 Lexington Ave., Ewing, NJ, 08618.
J Chem Theory Comput. 2011 May 10;7(5):1524-1540. doi: 10.1021/ct1006983.
An adaptive Cartesian grid (ACG) concept is presented for the fast and robust numerical solution of the 3D Poisson-Boltzmann Equation (PBE) governing the electrostatic interactions of large-scale biomolecules and highly charged multi-biomolecular assemblies such as ribosomes and viruses. The ACG offers numerous advantages over competing grid topologies such as regular 3D lattices and unstructured grids. For very large biological molecules and multi-biomolecule assemblies, the total number of grid-points is several orders of magnitude less than that required in a conventional lattice grid used in the current PBE solvers thus allowing the end user to obtain accurate and stable nonlinear PBE solutions on a desktop computer. Compared to tetrahedral-based unstructured grids, ACG offers a simpler hierarchical grid structure, which is naturally suited to multigrid, relieves indirect addressing requirements and uses fewer neighboring nodes in the finite difference stencils. Construction of the ACG and determination of the dielectric/ionic maps are straightforward, fast and require minimal user intervention. Charge singularities are eliminated by reformulating the problem to produce the reaction field potential in the molecular interior and the total electrostatic potential in the exterior ionic solvent region. This approach minimizes grid-dependency and alleviates the need for fine grid spacing near atomic charge sites. The technical portion of this paper contains three parts. First, the ACG and its construction for general biomolecular geometries are described. Next, a discrete approximation to the PBE upon this mesh is derived. Finally, the overall solution procedure and multigrid implementation are summarized. Results obtained with the ACG-based PBE solver are presented for: (i) a low dielectric spherical cavity, containing interior point charges, embedded in a high dielectric ionic solvent - analytical solutions are available for this case, thus allowing rigorous assessment of the solution accuracy; (ii) a pair of low dielectric charged spheres embedded in a ionic solvent to compute electrostatic interaction free energies as a function of the distance between sphere centers; (iii) surface potentials of proteins, nucleic acids and their larger-scale assemblies such as ribosomes; and (iv) electrostatic solvation free energies and their salt sensitivities - obtained with both linear and nonlinear Poisson-Boltzmann equation - for a large set of proteins. These latter results along with timings can serve as benchmarks for comparing the performance of different PBE solvers.
提出了一种自适应笛卡尔网格(ACG)概念,用于快速、稳健地数值求解三维泊松-玻尔兹曼方程(PBE),该方程用于描述大型生物分子以及诸如核糖体和病毒等高电荷多生物分子聚集体的静电相互作用。与常规三维晶格和非结构化网格等竞争网格拓扑相比,ACG具有诸多优势。对于非常大的生物分子和多生物分子聚集体,网格点总数比当前PBE求解器中使用的传统晶格网格所需的网格点总数少几个数量级,从而使终端用户能够在台式计算机上获得准确且稳定的非线性PBE解。与基于四面体的非结构化网格相比,ACG提供了一种更简单的分层网格结构,它自然适用于多重网格,减少了间接寻址需求,并且在有限差分模板中使用的相邻节点更少。ACG的构建以及介电/离子映射的确定简单、快速,并且需要最少的用户干预。通过重新表述问题以在分子内部产生反应场势并在外部离子溶剂区域产生总静电势,消除了电荷奇点。这种方法使网格依赖性最小化,并减轻了在原子电荷位点附近采用精细网格间距的需求。本文的技术部分包含三个部分。首先,描述了ACG及其针对一般生物分子几何结构的构建。接下来,推导了在此网格上对PBE的离散近似。最后,总结了整体求解过程和多重网格实现。给出了基于ACG的PBE求解器获得的结果,包括:(i)嵌入高介电离子溶剂中的包含内部点电荷的低介电球形腔——这种情况下有解析解,从而可以严格评估解的准确性;(ii)嵌入离子溶剂中的一对低介电带电球体,用于计算作为球体中心之间距离函数的静电相互作用自由能;(iii)蛋白质、核酸及其诸如核糖体等更大规模聚集体的表面电势;以及(iv)通过线性和非线性泊松-玻尔兹曼方程获得的一大组蛋白质的静电溶剂化自由能及其盐敏感性。后面这些结果以及计算时间可作为比较不同PBE求解器性能基准。