循环-MS:一个闭环端到端的框架,用于质谱结构光.
Jinglong Lin1, Hao Li2, Chengchun Liu1
1School of Materials Science and Engineering, Peking University, Beijing 100871, P. R. China.
Journal of chemical information and modeling
|February 25, 2026
概括
循环-MS通过统一反向和前向预测来增强从质谱 (MS) 数据中的分子结构阐明. 这种可解释的框架提高了用于自动化分析的化学公式和结构特征预测的准确性.
科学领域:
- 计算化学是一种计算化学.
- 分析化学是一种分析化学.
- 结构生物学是结构生物学.
背景情况:
- 质谱 (MS) 对于分子分析至关重要.
- 从多发性硬化谱中阐明复杂的分子结构具有挑战性.
研究的目的:
- 介绍Cycle-MS,这是一个基于MS的结构阐释的端到端框架.
- 提高从光谱中预测分子结构的准确性和解释性.
主要方法:
- 统一反向光谱对分子预测与前向光谱重建.
- 利用循环一致性损失来改进潜在表示.
- 进行可解释性分析,以评估特征优先级.
主要成果:
- 循环-MS在预测原子组成,分子公式,支架和功能组方面表现出更高的准确性.
- 实现分子尺度和关键化学特征的强大恢复.
- 为了化学可信性,优先考虑结构诊断片段而不是非特异的丰富峰值.
结论:
- 循环MS为MS数据提供了一个强大,准确和可解释的框架.
- 实现基于MS的全自动,高精度的结构阐明.
- 推进计算分子结构确定领域.
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