QSAR模型用于在不同温度下对各种挥发性有机化合物进行臭氧化
Ali Azimi1, Shahin Ahmadi2, Marjan Jebeli Javan2
1Department of Chemistry, Science and Research Branch, Islamic Azad University Tehran Iran.
RSC advances
|March 8, 2024
概括
开发挥发性有机化合物 (VOC) 氧化速率常数的预测模型对于大气化学至关重要. 本研究引入了一种新的定量结构-活性关系 (QSAR) 模型,使用准SMILES和温度来准确预测这些反应速率.
科学领域:
- 大气化学 大气化学
- 环境科学 环境科学
- 计算化学计算化学
背景情况:
- 评估大气中挥发性有机化合物 (VOC) 的命运和持久性,需要了解它们与臭氧 (kO) 的氧化速率常数.
- 对kO值的实验性确定是有限的,昂贵的,耗时的,需要预测建模方法.
研究的目的:
- 开发可靠的定量结构-活性关系 (QSAR) 模型,用于预测149种挥发性有机化合物的臭氧反应速率常数 (kO).
- 将温度作为实验条件纳入QSAR框架,使用准SMILES方法.
主要方法:
- 使用简化分子输入线输入系统 (SMILES) 与温度 (准SMILES) 结合生成混合最佳描述符.
- 使用CORAL软件构建预测QSAR模型,探索各种目标函数和相关性方法.
- 研究了相关性强度指数 (CII) 对模型可预测性的影响.
主要成果:
- 在广泛的温度范围内 (178-409 K) 开发了302 kO值的准确和预测性QSAR模型.
- 最好的模型实现了高性能,R2值为0.9834 (列车),0.9276 (校准) 和0.9136 (验证).
- 确定了促进增加log kO的关键结构特征,包括双键的存在,素的缺失和特定的碳邻居代码.
结论:
- 开发的基于准SMILES的QSAR模型为预测VOC氧化速率常数提供了可靠和有效的方法.
- 包括温度和相关性强度指数显著改善了模型的可预测性.
- 已识别的结构性促进剂提供了有关VOC大气氧化控制机制的见解.
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