基于量子化学的电子电离质谱对环境化学品的预测
Helge Hecht1, Wudmir Y Rojas1, Zargham Ahmad1
1RECETOX, Faculty of Science, Masaryk University, Kotlářská 2, Brno 602 00, Czech Republic.
Analytical chemistry
|August 7, 2024
概括
生成in silico质谱有助于化合物识别,但目前的计算方法对环境化学品的准确性有限. 预测的光谱很少与实验数据相匹配,这凸显了模拟碎片化途径的差距.
科学领域:
- 计算化学计算化学
- 环境科学 环境科学
- 分析化学 分析化学
背景情况:
- 缺乏实验性电子电离高分辨率质谱,阻碍了化合物识别.
- 在 silico 质谱生成可以支持注释工作流程,特别是对于缺乏参考光谱的化学品,如环境污染物.
研究的目的:
- 介绍一个开源的,半自动化的工作流程,用于使用QCxMS软件预测70 eV的电子电离高分辨率质谱 (EI HRMS).
- 为了评估EI HRMS对367种环境化学品的预测准确度,与实验参考光谱相比.
主要方法:
- 开发并应用了一个开源的,半自动化工作流程,用于in silico EI HRMS预测.
- 使用QCxMS软件进行70 eV的光谱预测.
- 通过比较367种环境化学品的计算光谱与实验获得的参考光谱来评估预测准确性.
主要成果:
- 预测准确度与分子灵活性,可旋转键数和负电子原子数负相关.
- 很少有化合物达到足够的预测准确度,可以直接用于光谱匹配工作流程 (平均得分为428).
- 预测光谱中最丰富的离子很少与实验光谱相匹配,表明模拟和经验碎片化之间的分歧.
结论:
- 开发的工作流提供了in silico EI HRMS预测,但在环境化学品的光谱匹配中直接应用时,其准确性有限.
- 计算碎片化途径不能完全捕捉经验反应机制,需要进一步改进预测模型.
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