通过分子静电势的变形描述化学反应过程中化学键的变化

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Modeling Pub Date : 2025-01-03 DOI:10.1007/s00894-024-06239-x
Olga Żurowska, Artur Michalak
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引用次数: 0

摘要

本文从变形密度(Δr)和MEP变形(ΔMEP)两个方面分析了模型反应(i)乙烯+丁二烯环加成反应,(ii)原型SN2反应Cl−+ CH3Cl, (iii)水辅助HCN/CNH异构化反应,(iv) CO + HF→C(O)HF的电子结构沿本构反应坐标(IRC)路径的变化。主要目的是进一步研究ΔMEP作为化学键描述符的效用,并比较Δr和ΔMEP所得到的图像。两种方法都清楚地表明,电子结构的主要变化发生在TS区。对于中性物质的反应,ΔMEP图与基于Δρ的图完全一致,导致中性产物在碎片之间没有大的电荷转移。在具有大电子密度位移的反应中,ΔMEP图以电荷转移为主,比Δr图更清楚地表明电荷转移。方法采用ADF软件包进行计算。Becke-Perdew交换相关函数与具有Becke-Johnson阻尼的grime色散校正(D3版)一起使用。应用了ADF程序中定义的Slater TZP基集。对所分析的反应,通过频率计算确定并验证了平稳点,并确定了IRC。进一步分析了反应物、TS、生成物的结构,以及反应力的最小值和最大值对应的点。对于每个点,考虑两个片段,A和B,对应于反应物。变形密度计算为系统AB的电子密度与A和B的密度之和之差,\(\Delta \rho \left(r\right)= {\rho }^{AB}\left(r\right)-{\rho }^{A}\left(r\right){-\rho }^{B}\left(r\right),\)与ETS-NOCV方法中的碎片定义相同。相应的,MEP中的变形确定为\(\Delta V\left(r\right)={V}^{AB}\left(r\right)- {V}^{A}\left(r\right)- {V}^{B}\left(r\right)\)。
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Description of changes in chemical bonding along the pathways of chemical reactions by deformation of the molecular electrostatic potential

Context

The analysis of the changes in the electronic structure along intrinsic reaction coordinate (IRC) paths for model reactions: (i) ethylene + butadiene cycloaddition, (ii) prototype SN2 reaction Cl + CH3Cl, (iii) HCN/CNH isomerization assisted by water, (iv) CO + HF → C(O)HF was performed, in terms of changes in the deformation density (Δr) and the deformation of MEP (ΔMEP). The main goal was to further examine the utility of the ΔMEP as a descriptor of chemical bonding, and to compare the pictures resulting from Δr and ΔMEP. Both approaches clearly show that the main changes in the electronic structure occur in the TS region. The ΔMEP picture is fully consistent with that based on Δρ for the reactions of the neutral species leading to the neutral products without large charge transfer between the fragments. In the case of reactions with large electron density displacements, the ΔMEP picture is dominated by charge transfer leading to more clear indication of charge shifts than the analysis of Δr.

Methods

All the calculations were performed using the ADF package. The Becke–Perdew exchange–correlation functional was used with the Grimme’s dispersion correction (D3 version) with Becke-Johnson damping. The Slater TZP basis sets defined within the ADF program were applied. For the analysed reactions, the stationary points were determined and verified by frequency calculations, and the IRC was determined. Further analysis was performed for the structures of reactants, TS, products, and the points corresponding to the minimum and maximum of the reaction force. For each point, two fragments, A and B, corresponding to the reactants were considered. The deformation density was calculated as the difference between the electron density of the system AB and the sum of densities of A and B, \(\Delta \rho \left(r\right)= {\rho }^{AB}\left(r\right)-{\rho }^{A}\left(r\right){-\rho }^{B}\left(r\right),\) with the same fragment definition as in the ETS-NOCV method. Correspondingly, deformation in MEP was determined as \(\Delta V\left(r\right)={V}^{AB}\left(r\right)- {V}^{A}\left(r\right)- {V}^{B}\left(r\right)\).

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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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