Luchko Tyler, Blinov Nikolay, Limon Garrett C, Joyce Kevin P, Kovalenko Andriy
Department of Physics and Astronomy, California State University, Northridge, Northridge, CA, 91330-8268, USA.
National Institute for Nanotechnology, National Research Council of Canada, 11421 Saskatchewan Dr., Edmonton, AB, T6G 2M9, Canada.
J Comput Aided Mol Des. 2016 Nov;30(11):1115-1127. doi: 10.1007/s10822-016-9947-7. Epub 2016 Sep 1.
Implicit solvent methods for classical molecular modeling are frequently used to provide fast, physics-based hydration free energies of macromolecules. Less commonly considered is the transferability of these methods to other solvents. The Statistical Assessment of Modeling of Proteins and Ligands 5 (SAMPL5) distribution coefficient dataset and the accompanying explicit solvent partition coefficient reference calculations provide a direct test of solvent model transferability. Here we use the 3D reference interaction site model (3D-RISM) statistical-mechanical solvation theory, with a well tested water model and a new united atom cyclohexane model, to calculate partition coefficients for the SAMPL5 dataset. The cyclohexane model performed well in training and testing ([Formula: see text] for amino acid neutral side chain analogues) but only if a parameterized solvation free energy correction was used. In contrast, the same protocol, using single solute conformations, performed poorly on the SAMPL5 dataset, obtaining [Formula: see text] compared to the reference partition coefficients, likely due to the much larger solute sizes. Including solute conformational sampling through molecular dynamics coupled with 3D-RISM (MD/3D-RISM) improved agreement with the reference calculation to [Formula: see text]. Since our initial calculations only considered partition coefficients and not distribution coefficients, solute sampling provided little benefit comparing against experiment, where ionized and tautomer states are more important. Applying a simple [Formula: see text] correction improved agreement with experiment from [Formula: see text] to [Formula: see text], despite a small number of outliers. Better agreement is possible by accounting for tautomers and improving the ionization correction.
经典分子模拟中的隐式溶剂方法经常被用于快速提供基于物理的大分子水合自由能。这些方法对其他溶剂的可转移性较少被考虑。蛋白质和配体建模的统计评估5（SAMPL5）分配系数数据集以及随附的显式溶剂分配系数参考计算提供了对溶剂模型可转移性的直接测试。在这里，我们使用三维参考相互作用位点模型（3D-RISM）统计力学溶剂化理论，结合经过充分测试的水模型和新的联合原子环己烷模型，来计算SAMPL5数据集的分配系数。环己烷模型在训练和测试中表现良好（氨基酸中性侧链类似物的[公式：见原文]），但前提是使用参数化的溶剂化自由能校正。相比之下，使用单一溶质构象的相同协议在SAMPL5数据集上表现不佳，与参考分配系数相比得到[公式：见原文]，这可能是由于溶质尺寸大得多。通过结合分子动力学与3D-RISM（MD/3D-RISM）进行溶质构象采样，与参考计算的一致性提高到了[公式：见原文]。由于我们最初的计算只考虑了分配系数而不是分布系数，溶质采样与实验相比益处不大，在实验中离子化和互变异构状态更为重要。应用简单的[公式：见原文]校正使与实验的一致性从[公式：见原文]提高到了[公式：见原文]，尽管有少数异常值。通过考虑互变异构体并改进电离校正，可以实现更好的一致性。
