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通过密度泛函理论和泊松-玻尔兹曼连续介质溶剂模型对脂肪族胺、二胺和氨基酰胺进行pKa计算。

pKa calculations of aliphatic amines, diamines, and aminoamides via density functional theory with a Poisson-Boltzmann continuum solvent model.

作者信息

Bryantsev Vyacheslav S, Diallo Mamadou S, Goddard William A

机构信息

Materials and Process Simulation Center, Beckman Institute 139-74, California Institute of Technology, Pasadena, CA 91125, USA.

出版信息

J Phys Chem A. 2007 May 24;111(20):4422-30. doi: 10.1021/jp071040t. Epub 2007 May 1.

Abstract

In order to make reliable predictions of the acid-base properties of macroligands with a large number of ionizable sites such as dendrimers, one needs to develop and validate computational methods that accurately estimate the acidity constants (pKa) of their chemical building blocks. In this article, we couple density functional theory (B3LYP) with a Poisson-Boltzmann continuum solvent model to calculate the aqueous pKa of aliphatic amines, diamines, and aminoamides, which are building blocks for several classes of dendrimers. No empirical correction terms were employed in the calculations except for the free energy of solvation of the proton (H+) adjusted to give the best match with experimental data. The use of solution-phase optimized geometries gives calculated pKa values in excellent agreement with experimental measurements. The mean absolute error is <0.5 pKa unit in all cases. Conversely, calculations for diamines and aminoamides based on gas-phase geometries lead to a mean absolute error >0.5 pKa unit compared to experimental measurements. We find that geometry optimization in solution is essential for making accurate pKa predictions for systems possessing intramolecular hydrogen bonds.

摘要

为了对具有大量可电离位点的大环配体(如树枝状大分子)的酸碱性质进行可靠预测,需要开发并验证能准确估算其化学结构单元酸度常数(pKa)的计算方法。在本文中,我们将密度泛函理论(B3LYP)与泊松-玻尔兹曼连续介质溶剂模型相结合,来计算脂肪族胺、二胺和氨基酰胺的水相pKa,这些都是几类树枝状大分子的结构单元。计算中除了对质子(H+)的溶剂化自由能进行调整以使其与实验数据达到最佳匹配外,未采用任何经验校正项。使用溶液相优化几何结构得到的计算pKa值与实验测量值高度吻合。在所有情况下,平均绝对误差均小于0.5个pKa单位。相反,基于气相几何结构对二胺和氨基酰胺进行的计算与实验测量相比,平均绝对误差大于0.5个pKa单位。我们发现,对于具有分子内氢键的体系,在溶液中进行几何结构优化对于准确预测pKa至关重要。

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