Exploring chemical reactivity through a combined conceptual DFT and ELF topology approach

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Modeling Pub Date : 2024-10-03 DOI:10.1007/s00894-024-06144-3
Bastien Courbière, Julien Pilmé
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Abstract

Context

In a proof-of-concept study, we explore how a combined approach using the topology of the electron localization function (ELF) and the condensed dual descriptor (DD) function can guide the optimal orientation between reactants and mimic the potential energy surfaces of molecular systems at the beginning of the chemical pathway. The DD has been chosen for its ability to evaluate the regioselectivity of neutral and soft species and to potentially mimic the interaction energy obtained from the mutual interactions between nucleophilic and electrophilic regions of the building blocks under perturbative theory.

Method

Our method has been illustrated with examples in which the optimal orientation of several systems can be successfully identified. The limitations of the presented model in predicting chemical reactivity are outlined in particular the influence of the selected condensation scheme.

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通过概念 DFT 和 ELF 拓扑相结合的方法探索化学反应性。
背景:在一项概念验证研究中,我们探索了利用电子定位功能(ELF)的拓扑结构和凝聚双描述符(DD)功能的组合方法如何指导反应物之间的最佳取向,以及如何在化学途径的起始阶段模拟分子系统的势能面。之所以选择 DD,是因为它能够评估中性和软性物种的区域选择性,并有可能模拟扰动理论下构件亲核区和亲电区之间相互影响所产生的相互作用能:我们的方法已通过实例进行了说明,在这些实例中,我们成功地确定了几个系统的最佳取向。方法:我们用实例说明了我们的方法,在这些实例中,我们成功地确定了几个系统的最佳取向。我们还概述了所提出的模型在预测化学反应性方面的局限性,特别是所选缩合方案的影响。
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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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