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利用 SMD 溶剂化方法和半经验电子结构方法提高溶剂化能预测。

Improving solvation energy predictions using the SMD solvation method and semiempirical electronic structure methods.

机构信息

Department of Chemistry, University of Copenhagen, Copenhagen, Denmark.

Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.

出版信息

J Chem Phys. 2018 Sep 14;149(10):104102. doi: 10.1063/1.5047273.

Abstract

The PM6 implementation in the GAMESS program is extended to elements requiring -integrals and interfaced with the conducter-like polarized continuum model of solvation, including gradients. The accuracy of aqueous solvation energies computed using AM1, PM3, PM6, and DFT tight binding (DFTB) and the Solvation Model Density (SMD) continuum solvation model is tested using the Minnesota Solvation Database data set. The errors in SMD solvation energies predicted using Neglect of Diatomic Differential Overlap (NDDO)-based methods are considerably larger than when using density functional theory (DFT) and HF, with root mean square error (RMSE) values of 3.4-5.9 (neutrals) and 6-15 kcal/mol (ions) compared to 2.4 and ∼5 kcal/mol for HF/6-31G(d). For the NDDO-based methods, the errors are especially large for cations and considerably higher than the corresponding conductor-like screening model results, which suggests that the NDDO/SMD results can be improved by re-parameterizing the SMD parameters focusing on ions. We found that the best results are obtained by changing only the radii for hydrogen, carbon, oxygen, nitrogen, and sulfur, and this leads to RMSE values for PM3 (neutrals: 2.8/ions: ∼5 kcal/mol), PM6 (4.7/∼5 kcal/mol), and DFTB (3.9/∼5 kcal/mol) that are more comparable to HF/6-31G(d) (2.4/∼5 kcal/mol). Although the radii are optimized to reproduce aqueous solvation energies, they also lead more accurate predictions for other polar solvents such as dimethyl sulfoxide, acetonitrile, and methanol, while the improvements for non-polar solvents are negligible.

摘要

在 GAMESS 程序中,PM6 的实现扩展到需要 - 积分的元素,并与包括梯度在内的类似导体的极化连续体溶剂模型接口。使用 AM1、PM3、PM6 和密度泛函紧束缚(DFTB)和溶剂化模型密度(SMD)连续体溶剂化模型计算的水溶液溶剂化能的准确性使用明尼苏达溶剂化数据库数据集进行测试。使用基于忽略二原子微分重叠(NDDO)的方法预测的 SMD 溶剂化能的误差明显大于使用密度泛函理论(DFT)和 HF 的误差,中性的均方根误差(RMSE)值为 3.4-5.9(中性)和 6-15 kcal/mol(离子),而 HF/6-31G(d) 的 RMSE 值为 2.4 和 ∼5 kcal/mol。对于基于 NDDO 的方法,阳离子的误差特别大,并且明显高于相应的类似导体屏蔽模型的结果,这表明可以通过重新参数化 SMD 参数来改进 NDDO/SMD 结果,重点关注离子。我们发现,通过仅改变氢、碳、氧、氮和硫的半径,就可以获得最佳结果,这导致 PM3(中性:2.8/离子:∼5 kcal/mol)、PM6(4.7/∼5 kcal/mol)和 DFTB(3.9/∼5 kcal/mol)的 RMSE 值更接近 HF/6-31G(d)(2.4/∼5 kcal/mol)。虽然半径是优化的,以重现水溶液溶剂化能,但它们也导致其他极性溶剂如二甲亚砜、乙腈和甲醇的更准确预测,而对非极性溶剂的改进可以忽略不计。

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