Polarizable Atomic Multipole Solutes in a Generalized Kirkwood Continuum.
Polarizable Atomic Multipole Solutes in a Generalized Kirkwood Continuum.
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DOI：
10.1021/ct7001336
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发表时间：
2007-10
影响因子：
5.5
通讯作者：
M. Schnieders;J. Ponder
中科院分区：
文献类型：
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作者：
M. Schnieders;J. Ponder
广义玻恩（GB）模型的连续静电是一个分析近似的泊松方程用于预测的溶剂化自由能的溶质的大小从小的有机分子到大分子复合物的静电分量。基于柯克伍德关于任意电荷分布溶质溶剂化自由能静电分量的解析结果，提出了一个新的连续静电模型。不同于GB，这是有限的单极子，我们的广义柯克伍德（GK）模型可以治疗溶质静电的永久和诱导原子多极矩的任意程度的任何组合表示。在这里，我们将GK模型应用于新开发的原子多极优化能量学生物分子应用（AMOEBA）力场，该力场包括通过四极的永久原子多极，并通过诱导偶极子处理极化。GK梯度的推导，这使得能量最小化或分子动力学的一个AMOEBA溶质在GK连续。对于一系列的55种蛋白质，GK静电溶剂化自由能相比，极化多极泊松-玻尔兹曼（PMPB）模型，并产生一个平均无符号的相对差异为0.9%。此外，GK的反应场与PMPB模型的反应场相当，如在预测该测试集中每种蛋白质的总溶剂化偶极矩时平均无符号相对差异为2.7%所示。GK相对于真空AMOEBA计算所需的CPU时间约为3倍，使其适合于需要大量配置空间采样的应用。
The generalized Born (GB) model of continuum electrostatics is an analytic approximation to the Poisson equation useful for predicting the electrostatic component of the solvation free energy for solutes ranging in size from small organic molecules to large macromolecular complexes. This work presents a new continuum electrostatics model based on Kirkwood's analytic result for the electrostatic component of the solvation free energy for a solute with arbitrary charge distribution. Unlike GB, which is limited to monopoles, our generalized Kirkwood (GK) model can treat solute electrostatics represented by any combination of permanent and induced atomic multipole moments of arbitrary degree. Here we apply the GK model to the newly developed Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field, which includes permanent atomic multipoles through the quadrupole and treats polarization via induced dipoles. A derivation of the GK gradient is presented, which enables energy minimization or molecular dynamics of an AMOEBA solute within a GK continuum. For a series of 55 proteins, GK electrostatic solvation free energies are compared to the Polarizable Multipole Poisson-Boltzmann (PMPB) model and yield a mean unsigned relative difference of 0.9%. Additionally, the reaction field of GK compares well to that of the PMPB model, as shown by a mean unsigned relative difference of 2.7% in predicting the total solvated dipole moment for each protein in this test set. The CPU time needed for GK relative to vacuum AMOEBA calculations is approximately a factor of 3, making it suitable for applications that require significant sampling of configuration space.