Caine Beth A, Bronzato Maddalena, Fraser Torquil, Kidley Nathan, Dardonville Christophe, Popelier Paul L A
Department of Chemistry, University of Manchester, Manchester, UK.
Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester, UK.
Commun Chem. 2020 Feb 12;3(1):21. doi: 10.1038/s42004-020-0264-7.
The accurate prediction of aqueous pK values for tautomerizable compounds is a formidable task, even for the most established in silico tools. Empirical approaches often fall short due to a lack of pre-existing knowledge of dominant tautomeric forms. In a rigorous first-principles approach, calculations for low-energy tautomers must be performed in protonated and deprotonated forms, often both in gas and solvent phases, thus representing a significant computational task. Here we report an alternative approach, predicting pK values for herbicide/therapeutic derivatives of 1,3-cyclohexanedione and 1,3-cyclopentanedione to within just 0.24 units. A model, using a single ab initio bond length from one protonation state, is as accurate as other more complex regression approaches using more input features, and outperforms the program Marvin. Our approach can be used for other tautomerizable species, to predict trends across congeneric series and to correct experimental pK values.
即使对于最成熟的计算机模拟工具而言,准确预测可互变异构化合物的水相pK值也是一项艰巨的任务。由于缺乏对主要互变异构形式的先验知识,经验方法往往难以奏效。在严格的第一性原理方法中,必须对低能互变异构体的质子化和去质子化形式进行计算,通常在气相和溶剂相中都要进行,因此这是一项重大的计算任务。在此,我们报告一种替代方法,该方法可将1,3 - 环己二酮和1,3 - 环戊二酮的除草剂/治疗性衍生物的pK值预测在仅0.24个单位以内。一个使用来自一种质子化状态的单个从头算键长的模型,与使用更多输入特征的其他更复杂的回归方法一样准确,并且优于Marvin程序。我们的方法可用于其他可互变异构的物种,以预测同系物系列的趋势并校正实验pK值。