Bradshaw Richard T, Essex Jonathan W
School of Chemistry, University of Southampton, Highfield Campus , Southampton SO17 1BJ, U.K.
J Chem Theory Comput. 2016 Aug 9;12(8):3871-83. doi: 10.1021/acs.jctc.6b00276. Epub 2016 Jul 29.
Hydration free energy (HFE) calculations are often used to assess the performance of biomolecular force fields and the quality of assigned parameters. The AMOEBA polarizable force field moves beyond traditional pairwise additive models of electrostatics and may be expected to improve upon predictions of thermodynamic quantities such as HFEs over and above fixed-point-charge models. The recent SAMPL4 challenge evaluated the AMOEBA polarizable force field in this regard but showed substantially worse results than those using the fixed-point-charge GAFF model. Starting with a set of automatically generated AMOEBA parameters for the SAMPL4 data set, we evaluate the cumulative effects of a series of incremental improvements in parametrization protocol, including both solute and solvent model changes. Ultimately, the optimized AMOEBA parameters give a set of results that are not statistically significantly different from those of GAFF in terms of signed and unsigned error metrics. This allows us to propose a number of guidelines for new molecule parameter derivation with AMOEBA, which we expect to have benefits for a range of biomolecular simulation applications such as protein-ligand binding studies.
水化自由能（HFE）计算常用于评估生物分子力场的性能和所分配参数的质量。AMOEBA可极化力场超越了传统的静电成对加和模型，预计在预测诸如HFE等热力学量方面比定点电荷模型有更好的表现。最近的SAMPL4挑战在这方面评估了AMOEBA可极化力场，但结果显示比使用定点电荷GAFF模型的结果要差得多。从为SAMPL4数据集自动生成的一组AMOEBA参数开始，我们评估了参数化协议中一系列增量改进的累积效应，包括溶质和溶剂模型的变化。最终，优化后的AMOEBA参数给出的一组结果，在有符号和无符号误差指标方面与GAFF的结果没有统计学上的显著差异。这使我们能够为使用AMOEBA推导新分子参数提出一些指导方针，我们预计这将对一系列生物分子模拟应用（如蛋白质-配体结合研究）有益。
