从其电子电离质谱推断分析物的名义分子质量
Arun S Moorthy1, Anthony J Kearsley2, William G Mallard1
1Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States.
Analytical chemistry
|August 23, 2023
概括
从电子电离质谱准确预测分子质量至关重要. 结合三个算法 - - 峰值解释方法 (PIM),简单搜索热门名单方法 (SS-HM) 和代混合搜索热门名单方法 (iHS-HM) - - 当预测一致时,准确度超过99%.
科学领域:
- 分析化学 分析化学
- 计算化学的计算化学
- 频谱学是一种光谱学.
背景情况:
- 精确的分子质量测定对于识别未知的化合物至关重要.
- 电子电离质谱法 (EIMS) 是一种常见的技术,但推断分子质量可能具有挑战性.
- 从EIMS数据中预测分子质量的现有方法有局限性.
研究的目的:
- 从EIMS数据中预测名义分子质量的三个不同的算法的性能.
- 评估这些算法单独和组合的有效性.
- 确定用于分子质量识别的综合预测的可靠性.
主要方法:
- 使用峰值解释方法 (PIM) 来评估分子离子峰值的概率.
- 简单的搜索热门名单方法 (SS-HM) 和代的混合搜索热门名单方法 (iHS-HM) 使用了质谱图书馆搜索.
- 在大型数据集 (19,074个有机分子,162种药物) 上对外部质谱库进行了测试.
主要成果:
- 单个算法的精度为91% (PIM),89% (SS-HM) 和74% (iHS-HM).
- 结合预测显著提高了准确性和可靠性.
- 当所有三种方法都产生了相同的预测时 (33%的病例),准确率超过99%.
结论:
- 评估的算法为EIMS的分子质量预测提供了有价值的工具.
- 结合PIM,SS-HM和iHS-HM,为高可靠性分子质量确定提供了一个强大的方法.
- 这些方法提高了质谱数据的实用性,用于化合物识别.
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