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分子酸度:密度泛函反应理论中的信息论方法的精确描述。

Molecular acidity: An accurate description with information-theoretic approach in density functional reactivity theory.

机构信息

Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research, (Ministry of Education of China), College of Chemistry and Chemical Engineering, Hunan Normal University, Changsha, Hunan, 410081, People's Republic of China.

School of Pharmaceutical and Chemical Engineering, Taizhou University, 1139 Shifu Road, Linhai, Zhejiang, 318000, People's Republic of China.

出版信息

J Comput Chem. 2018 Jan 15;39(2):117-129. doi: 10.1002/jcc.25090. Epub 2017 Oct 26.

DOI:10.1002/jcc.25090
PMID:29076175
Abstract

Molecular acidity is one of the important physiochemical properties of a molecular system, yet its accurate calculation and prediction are still an unresolved problem in the literature. In this work, we propose to make use of the quantities from the information-theoretic (IT) approach in density functional reactivity theory and provide an accurate description of molecular acidity from a completely new perspective. To illustrate our point, five different categories of acidic series, singly and doubly substituted benzoic acids, singly substituted benzenesulfinic acids, benzeneseleninic acids, phenols, and alkyl carboxylic acids, have been thoroughly examined. We show that using IT quantities such as Shannon entropy, Fisher information, Ghosh-Berkowitz-Parr entropy, information gain, Onicescu information energy, and relative Rényi entropy, one is able to simultaneously predict experimental pKa values of these different categories of compounds. Because of the universality of the quantities employed in this work, which are all density dependent, our approach should be general and be applicable to other systems as well. © 2017 Wiley Periodicals, Inc.

摘要

分子酸度是分子系统的重要物理化学性质之一,但在文献中,其准确计算和预测仍然是一个未解决的问题。在这项工作中,我们建议利用信息论(IT)方法中的量在密度泛函反应理论中,并从全新的角度提供对分子酸度的准确描述。为了说明这一点,我们彻底研究了五类酸性系列,即单取代和双取代苯甲酸、单取代苯亚磺酸、苯硒酸、苯酚和烷羧酸。我们表明,使用 IT 量,如香农熵、费希尔信息、Ghosh-Berkowitz-Parr 熵、信息增益、Onicescu 信息能量和相对 Renyi 熵,能够同时预测这些不同类别化合物的实验 pKa 值。由于这项工作中使用的量是普遍的,都是密度依赖的,因此我们的方法应该是通用的,也适用于其他系统。

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