Quantum chemistry calculations and chemical kinetic studies on the tautomeric mechanism of creatinine

IF 2.5 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Yiqing Sun, Xiankai Jiang, Zhenhai Xiong, Junjian Miao
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引用次数: 0

Abstract

Context

Thermal processing of meat typically leads to the formation of heterocyclic aromatic amines (HAAs), a class of highly toxic compounds. Although extensive research has been conducted on HAAs, the precise formation mechanisms of individual HAAs remain incompletely understood, with many critical details yet to be elucidated. Several unresolved aspects concern the number of tautomers of creatinine—the key precursor in HAA formation, the interconversion pathways among these tautomers and the time scales involved, and the equilibrium distribution ratios among the tautomeric forms. Addressing these questions is essential for achieving an accurate understanding of the mechanistic pathways underlying the formation of HAAs.

Methods

All possible tautomers were manually deduced and verified by RDkit, a chemoinformatics toolkit. Geometry optimizations and frequency analyses were performed using density functional theory (DFT). The distribution of various tautomers was evaluated under three different environments—gas phase, ethanol, and water—to simulate real conditions. Calculations were carried out at the B3LYP/def2QZVPP//6-31G(d,p) level of theory, with the polarizable continuum model (PCM) applied for ethanol and water. A similar computational approach to the calculations on distribution was employed to investigate tautomerization mechanisms. Tautomerization kinetics were analyzed within the framework of transition state theory (TST) to determine rate constants for each tautomeric interconversion. Tunneling correction factors (κ) were then calculated to account for quantum mechanical tunneling effects. Subsequently, the corresponding system of differential equations was solved to obtain the time-dependent concentration profiles of each tautomeric species.

Abstract Image

Abstract Image

肌酸酐互变异构机理的量子化学计算及化学动力学研究
肉类的热加工通常会导致形成杂环芳香胺(HAAs),这是一类剧毒化合物。尽管对HAAs进行了广泛的研究,但个体HAAs的确切形成机制仍不完全清楚,许多关键细节尚未阐明。几个尚未解决的问题涉及肌酐的互变异构体的数量,这些互变异构体之间的相互转化途径和涉及的时间尺度,以及互变异构体形式之间的平衡分布比率。解决这些问题对于准确理解HAAs形成的机制途径至关重要。方法采用化学信息学工具RDkit手工推导并验证所有可能的互变异构体。利用密度泛函理论(DFT)进行几何优化和频率分析。在气相、乙醇和水三种不同环境下评估了各种互变异构体的分布,以模拟真实条件。在B3LYP/def2QZVPP//6-31G(d,p)理论水平上进行计算,乙醇和水采用极化连续介质模型(PCM)。采用与分布计算类似的计算方法来研究互变异构机理。在过渡态理论(TST)框架内分析了互变异构化动力学,以确定每个互变异构相互转化的速率常数。然后计算隧道修正因子(κ)以解释量子力学隧道效应。随后,求解相应的微分方程组,得到各互变异构体的浓度随时间的变化曲线。
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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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