使用量子化学方法模拟碰撞诱导解离并列质谱 (CID-MS/MS) 血液暴露基数据库 - 一项试点研究
1Integrated Data Science Laboratory for Metabolomics and Exposomics, Department of Environmental Medicine, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States.
Journal of the American Society for Mass Spectrometry
|August 28, 2025
概括
计算化学生成了121种化学物质的质谱,扩大了暴露组研究的光谱库. 这种方法成功地为81种化合物创建了高质量的光谱,改善了化学物质的识别.
科学领域:
- 计算化学
- 分析化学
- 环境健康
背景情况:
- 由于没有可用的参考标准,许多暴露基数据库中的化学物质缺乏必要的质谱数据.
- 扩展光谱库对于在曝光学研究中准确的化合物识别至关重要.
研究的目的:
- 使用计算化学来生成缺乏实验光谱的化合物的质谱数据.
- 开发和验证可扩展光谱库的可扩展计算框架.
主要方法:
- 使用基于量子化学的软件 (QCxMS) 来生成来自血液暴露基的121种化合物的碰撞诱导解离质谱.
- 开发了一个集成QCxMS与参数选择策略和覆盖标准的计算框架.
- 基于分子结构系统地探索原质异构体和应用序列参数组合.
主要成果:
- 为81种化合物生成高质量的光谱,达到71%的光谱覆盖率.
- 使用相似度评分 (≥700) 和与NIST23库相匹配的碎片离子验证的光谱.
- 证明了优化模拟参数的重要性,并考虑了光谱质量的质量.
结论:
- 开发的工作流提供了一种实用且具有成本效益的策略,以增加血液暴露基数据的质谱数据.
- 这种方法支持光谱图书馆扩展,增强了表达学中的复合注释功能.
- 优化计算方法对于推进环境健康研究中的化学识别至关重要.
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