Departmento de Ingeniería Mecánica and Centro Científico Tecnológico de Valparaíso (CCTVal), Universidad Técnica Federico Santa María, Valparaíso, Chile.
J Comput Chem. 2019 Jul 5;40(18):1680-1692. doi: 10.1002/jcc.25820. Epub 2019 Mar 19.
Implicit-solvent models are widely used to study the electrostatics in dissolved biomolecules, which are parameterized using force fields. Standard force fields treat the charge distribution with point charges; however, other force fields have emerged which offer a more realistic description by considering polarizability. In this work, we present the implementation of the polarizable and multipolar force field atomic multipole optimized energetics for biomolecular applications (AMOEBA), in the boundary integral Poisson-Boltzmann solver PyGBe. Previous work from other researchers coupled AMOEBA with the finite-difference solver APBS, and found difficulties to effectively transfer the multipolar charge description to the mesh. A boundary integral formulation treats the charge distribution analytically, overlooking such limitations. This becomes particularly important in simulations that need high accuracy, for example, when the quantity of interest is the difference between solvation energies obtained from separate calculations, like happens for binding energy. We present verification and validation results of our software, compare it with the implementation on APBS, and assess the efficiency of AMOEBA and classical point-charge force fields in a Poisson-Boltzmann solver. We found that a boundary integral approach performs similarly to a volumetric method on CPU. Also, we present a GPU implementation of our solver. Moreover, with a boundary element method, the mesh density to correctly resolve the electrostatic potential is the same for standard point-charge and multipolar force fields. Finally, we saw that for binding energy calculations, a boundary integral approach presents more consistent results than a finite difference approximation for multipolar force fields. © 2019 Wiley Periodicals, Inc.
隐溶剂模型被广泛用于研究溶解生物分子中的静电,这些模型使用力场进行参数化。标准力场用点电荷处理电荷分布;然而,出现了其他力场,通过考虑极化率提供了更现实的描述。在这项工作中,我们在边界积分泊松-玻尔兹曼求解器 PyGBe 中实现了用于生物分子应用的极化和多极力场原子多极优化能量学(AMOEBA)。其他研究人员的先前工作将 AMOEBA 与有限差分求解器 APBS 耦合,并发现难以有效地将多极电荷描述转移到网格上。边界积分公式以解析方式处理电荷分布,忽略了这种限制。当感兴趣的数量是从单独计算中获得的溶剂化能的差异时,这一点变得尤为重要,例如在结合能的情况下。我们提出了我们的软件的验证和验证结果,将其与 APBS 上的实现进行了比较,并评估了 AMOEBA 和经典点电荷力场在泊松-玻尔兹曼求解器中的效率。我们发现,边界积分方法在 CPU 上的性能与体积方法相似。此外,我们还提出了我们求解器的 GPU 实现。此外,使用边界元法,正确解析静电势的网格密度对于标准点电荷和多极力场是相同的。最后,我们看到对于结合能计算,边界积分方法比多极力场的有限差分逼近具有更一致的结果。©2019 威立威利公司