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Computational prediction of the pKas of small peptides through Conceptual DFT descriptors

机译:通过概念DFT描述符计算小肽PKA的计算预测

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摘要

The experimental pKa of a group of simple amines have been plotted against several Conceptual DFT descriptors calculated by means of different density functionals, basis sets and solvation schemes. It was found that the best fits are those that relate the pKa of the amines with the global hardness I/through the MN12SX density functional in connection with the Def2TZVP basis set and the SMD solvation model, using water as a solvent. The parameterized equation resulting from the linear regression analysis has then been used for the prediction of the pKa of small peptides of interest in the study of diabetes and Alzheimer disease. The accuracy of the results is relatively good, with a MAD of 0.36 units of pICa. (c) 2017 Elsevier B.V. All rights reserved.
机译:已经绘制了一组简单胺的实验PKA,其涉及通过不同密度函数,基集和溶剂化方案计算的几个概念DFT描述符。 结果发现,最好的配合是将胺的PKA与全局硬度I /通过MN12SX密度与DEF2TZVP基础组和SMD溶剂化模型相关的那些,使用水作为溶剂。 从线性回归分析产生的参数化方程已经用于预测对糖尿病和阿尔茨海默病的研究的小肽的PKA。 结果的准确性相对较好,MAD为0.36单位的PICA。 (c)2017 Elsevier B.v.保留所有权利。

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