Why are information-theoretic descriptors powerful predictors of atomic and molecular polarizabilities

IF 2.5 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Modeling Pub Date : 2024-10-03 DOI:10.1007/s00894-024-06162-1
Yilin Zhao, Dongbo Zhao, Shubin Liu, Chunying Rong, Paul W. Ayers
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Abstract

Context

We rationalize the excellent performance of information-theoretic descriptors for predicting atomic and molecular polarizabilities. It seems that descriptors which capture information about the change in valence-shell structure, especially the relative Fisher information measures, are particularly useful. Using this, we can rationalize why the G3 form of the relative Fisher information, which measures the deviation of effective nuclear charge between an atom-in-a-molecule and the reference pro-atom, is especially effective as a predictor of molecular polarizability.

Methods

There are no methods used in this paper, which relies on mathematical derivation and analysis.

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为什么信息论描述符可以有力地预测原子和分子极化率?
背景:我们合理地解释了信息论描述符在预测原子和分子极化率方面的优异表现。捕捉价壳结构变化信息的描述符,尤其是相对费舍尔信息度量,似乎特别有用。利用这一点,我们可以合理地解释为什么相对费舍尔信息的 G3 形式(测量分子中原子与参考原原子之间有效核电荷的偏差)作为分子极化率的预测指标特别有效:本文没有使用任何方法,主要依靠数学推导和分析。
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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