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多频谱 ModiFinder 站点定位性能性能

Mohammad Reza Zare Shahneh¹, James Pyke², Emma E Rennie²

¹Department of Computer Science and Engineering, University of California Riverside, 900 University Avenue, Riverside, California 92521, United States.

Journal of the American Society for Mass Spectrometry

|April 9, 2025

概括

这项研究增强了ModiFinder,这是一种用于识别质谱 (MS/MS) 数据中的化学修饰的工具. 通过整合来自多个碰撞能量和添加物的光谱,研究人员提高了化合物定位的准确性.

科学领域:

分析化学分析化学
计算化学计算化学
生物化学生物化学

背景情况:

双重质谱 (MS/MS) 对于小分子识别至关重要,但许多光谱仍然未被分配.
像ModiFinder这样的现有计算工具可以预测化学修饰地点,但由于数据不足和注释模两可,它们面临限制.
非定位的代谢学实验产生了大量的MS/MS数据,需要改进识别策略.

研究的目的:

为了研究将MS/MS光谱从多重碰撞能量和质谱学引证纳入ModiFinder的定位精度的影响.
评估补充的光谱信息是否可以克服当前修改地点预测工具的局限性.
扩大ModiFinder的实用性,用于识别更广泛的修改小分子.

主要方法:

利用了来自Agilent Technologies的2150种化合物的大型数据集,比以前的数据集大得多.
通过结合使用各种碰撞能量获得的MS/MS光谱来评估ModiFinder的性能.
评估了包括不同质谱学引证在修改地点预测的准确性上的影响.

主要成果:

结合来自多个碰撞能量和的光谱,明显提高了ModiFinder本地化化学修饰的能力.
改进的方法扩大了可以准确预测修饰点的化合物范围.
通过整合补充的光谱数据,ModiFinder工具的整体性能得到了显著提高.

结论:

整合MS/MS光谱来自不同的碰撞能量和引物是一个有效的策略,以提高计算修改站点预测.
这种方法显著提高了在复杂的小分子混合物中识别化学变化的准确性和范围.
这些发现为在非目标质谱实验中进行更全面的结构阐明铺平了道路.

关键词:

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