Laboratory of Organic Chemistry, Wageningen University, Dreijenplein 8, 6703 HB Wageningen, The Netherlands.
Chemphyschem. 2013 Apr 2;14(5):990-5. doi: 10.1002/cphc.201201085. Epub 2013 Feb 21.
The pKa of the conjugate acids of alkanolamines, neurotransmitters, alkaloid drugs and nucleotide bases are calculated with density functional methods (B3LYP, M08-HX and M11-L) and ab initio methods (SCS-MP2, G3). Implicit solvent effects are included with a conductor-like polarizable continuum model (CPCM) and universal solvation models (SMD, SM8). G3, SCS-MP2 and M11-L methods coupled with SMD and SM8 solvation models perform well for alkanolamines with mean unsigned errors below 0.20 pKa units, in all cases. Extending this method to the pKa calculation of 35 nitrogen-containing compounds spanning 12 pKa units showed an excellent correlation between experimental and computational pKa values of these 35 amines with the computationally low-cost SM8/M11-L density functional approach.
用密度泛函方法（B3LYP、M08-HX 和 M11-L）和从头算方法（SCS-MP2、G3）计算了烷醇胺、神经递质、生物碱药物和核苷酸碱基的共轭酸的 pKa。用导体相似极化连续模型（CPCM）和通用溶剂化模型（SMD、SM8）包含了隐溶剂效应。在所有情况下，G3、SCS-MP2 和 M11-L 方法与 SMD 和 SM8 溶剂化模型相结合，对于烷醇胺的 pKa 计算，平均未签名误差低于 0.20 pKa 单位，表现良好。将该方法扩展到 35 种含氮化合物的 pKa 计算，涵盖了 12 个 pKa 单位，这些胺的实验和计算 pKa 值之间具有极好的相关性，这是通过计算成本低的 SM8/M11-L 密度泛函方法实现的。
