An overview of conceptual-DFT based insights into global chemical reactivity of volatile sulfur compounds (VSCs)

IF 3.1 Q2 TOXICOLOGY

Computational Toxicology Pub Date : 2023-12-12 DOI:10.1016/j.comtox.2023.100295

Manjeet Bhatia

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引用次数: 0

Abstract

Volatile sulfur compounds (VSCs) are highly volatile and most frequently associated with oral malodor. The odor quality is associated with the size and shape of the molecule along with stability, hydrogen bonding, extended d-shell electronic behavior, and complicity of d-shell bonding. Chemical reactivity descriptors of VSCs, such as chemical hardness (η), softness (σ), chemical potential (μ), electrophilic index (ω), and electronegativity (χ) are computed at B₃LYP/Aug-cc-PVTZ level of theory from the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) in the light of Koopmans’ approximation. Furthermore, the global reactivity parameters are evaluated from the vertical ionization potential (IP) and electron affinity (EA) to support the results of Koopmans’ theorem. These reactivity parameters offer a quantitative measure of the electronic structure and chemical properties of VSCs, offering insights into their stability, reactivity, and interaction with other molecules. A Python-based application is provided for the rapid calculation of these parameters (GitHub: Link).

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基于概念-DFT 的挥发性硫化合物（VSCs）全球化学反应性洞察概述

挥发性硫化合物(VSCs)是高度挥发性的，最常与口腔异味有关。气味质量与分子的大小和形状以及稳定性、氢键、扩展d壳层电子行为和d壳层键的共合性有关。根据Koopmans近似，从最高已占据分子轨道(HOMO)和最低未占据分子轨道(LUMO)出发，在B3LYP/Aug-cc-PVTZ理论水平上计算了VSCs的化学反应性描述符，如化学硬度(η)、柔软度(σ)、化学势(μ)、亲电指数(ω)和电负性(χ)。此外，利用垂直电离势(IP)和电子亲和力(EA)对整体反应性参数进行了评估，以支持Koopmans定理的结果。这些反应性参数提供了VSCs的电子结构和化学性质的定量测量，提供了对其稳定性、反应性和与其他分子相互作用的见解。提供了一个基于python的应用程序来快速计算这些参数(GitHub: Link)。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computational Toxicology Computer Science-Computer Science Applications

CiteScore

5.50

自引率

0.00%

发文量

审稿时长

56 days

期刊介绍： Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs