液晶单体体在EI-MS分析中的特征结构以及在可疑查中的潜在应用
Jing-Jing Feng1, Jian-Xiong Liao1, Qian-Wen Jiang1
1Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain, Guangxi Institute of Botany, Guangxi Zhuang Autonomous Region and Chinese Academy of Sciences, Guilin, 541006, China.
Chemosphere
|May 4, 2024
概括
对液晶单体 (LCM) 的监测至关重要. 新的QSPR模型可以预测LCM质谱,有助于识别具有特定结构特征的环境污染物.
科学领域:
- 环境化学环境化学
- 分析化学 分析化学
- 材料科学 材料科学 材料科学
背景情况:
- 液晶单体 (LCM) 在各种环境中越来越多地被检测到.
- 它们对人类健康和生态系统的潜在不利影响需要有效的监测策略.
- 快速的材料创新使得保持更新的LCM嫌疑人名单具有挑战性.
研究的目的:
- 开发和评估用于预测LCM电子电离 (EI) 质谱的in-silico和QSPR模型.
- 识别LCM的特征结构特征和质谱碎片,以改进可疑的查.
- 为了促进环境样本中新型LCMs的识别.
主要方法:
- 一个in-silico质量碎片化模型的应用.
- 开发和培训使用已发表的LCM质谱的定量结构-活动关系 (QSPR) 模型.
- 分析了1606个LCM的最新可疑名单,以确定特征性结构.
主要成果:
- 在模型显示,EI质谱的预测准确性有限.
- QSPR模型在预测分子离子强度方面取得了可接受的12%绝对误差,但在基峰预测方面遇到了困难.
- 确定了41种特征性结构,其中多基 (85%的LCM) 产生了154种特征性的EI质谱峰值.
结论:
- QSPR建模显示,预测LCM质谱具有前途,有助于环境监测.
- 识别特有的LCM结构,特别是多核,可以帮助检测新的环境污染物.
- 在质谱中监测特定的结构碎片可以促进识别以前未知的LCMs.
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