Assessment of Methodology and Chemical Group Dependences in the Calculation of the pKa for Several Chemical Groups
Assessment of Methodology and Chemical Group Dependences in the Calculation of the pKa for Several Chemical Groups
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评估几种化学基团 pKa 计算中的方法和化学基团依赖性
DOI：
10.1021/acs.jctc.7b00587
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发表时间：
2017
影响因子：
5.5
通讯作者：
Morihashi Kenji
中科院分区：
文献类型：
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作者：
Matsui Toru;Shigeta Yasuteru;Morihashi Kenji
我们基于我们以前的方案[Matsui；Phys]，研究了在质子化氨基酸中发现的某些化学基团的酸解离常数(PKavalue)计算中各种计算方法的依赖性。化学。化学。太棒了。2012年，14,4181−4187]。通过改变量子化学(QC)方法(Hartree-Fock(HF)和微扰理论，以及复合方法，或密度泛函理论中的交换相关泛函)、基组、溶剂化模型和溶剂模型中使用的空穴，我们对大约2,200种组合进行了详尽的测试，以找到其中pKa值的最佳组合。在测试的参数中，与其他因素相比，基组和空穴的选择对重现实验值是最关键的。对于基组，从实验值测得的平均绝对误差(MAE)来看，弥散函数的包含对羧基、硫醇和苯酚基团是相当重要的。在各种腔体模型中，在Pauling、Klamt和UFF定义的腔体模型中，UFF定义的腔体是最好的选择，从而产生最小的MAE。关于QC方法，混合离散傅里叶变换和距离分离离散傅立叶变换总是比纯离散傅立叶变换和高频傅立叶变换提供更好的结果。结果发现，LC-ϖ-PbE/6-31+G(D)与PCMSMD/UFF相结合可提供最好的pKa值估计，MAE在0.15pka单位以内。
We have investigated the dependencies of various computational methods in the calculation of acid dissociation constants (pKavalues) of certain chemical groups found in protonatable amino acids based on our previous scheme [Matsui; Phys. Chem. Chem. Phys. 2012, 14, 4181−4187]. By changing the quantum chemical (QC) method (Hartree–Fock (HF) and perturbation theory, and composite methods, or exchange–correlation functionals in density functional theory (DFT)), basis sets, solvation models, and the cavities used in the solvent models, we have exhaustively tested about 2,200 combinations to find the best combination for pKaestimation among them. Of the tested parameters, the choice of the basis set and cavity is the most crucial to reproduce experimental values compared to other factors. Concerning the basis set, the inclusion of diffuse functions is quite important for carboxyl, thiol, and phenol groups judging from the mean absolute errors (MAEs) measured from the experimental values. Of the cavity models, between the Pauling, Klamt, and the universal force field (UFF) definitions, the UFF defined cavity is the best choice, resulting in the smallest MAEs. Concerning the QC methods, hybrid DFTs and range-separated DFTs always provide better results than pure DFTs and HF. As a result, we found that LC-ϖPBE/6-31+G(d) with PCM-SMD/UFF provides the best pKaestimation with a MAE within 0.15 pKaunits.