Li Sean, Bohman Björn, Flematti Gavin R, Jayatilaka Dylan
School of Molecular Sciences, The University of Western Australia, 35 Stirling Highway, Crawley, 6009, Australia.
Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Box 190, 23422, Lomma, Sweden.
J Cheminform. 2023 Nov 7;15(1):104. doi: 10.1186/s13321-023-00776-y.
Identifying the molecular formula and fragmentation reactions of an unknown compound from its mass spectrum is crucial in areas such as natural product chemistry and metabolomics. We propose a method for identifying the correct candidate formula of an unidentified natural product from its mass spectrum. The method involves scoring the plausibility of parent candidate formulae based on a parent subformula graph (PSG), and two possible metrics relating to the number of edges in the PSG. This method is applicable to both electron-impact mass spectrometry (EI-MS) and tandem mass spectrometry (MS/MS) data. Additionally, this work introduces the two-dimensional fragmentation plot (2DFP) for visualizing PSGs.
Our results suggest that incorporating information regarding the edges of the PSG results in enhanced performance in correctly identifying parent formulae, in comparison to the more well-accepted "MS/MS score", on the 2016 Computational Assessment of Small Molecule Identification (CASMI 2016) data set (76.3 vs 58.9% correct formula identification) and the Research Centre for Toxic Compounds in the Environment (RECETOX) data set (66.2% vs 59.4% correct formula identification). In the extension of our method to identify the correct candidate formula from complex EI-MS data of semiochemicals, our method again performed better (correct formula appearing in the top 4 candidates in 20/23 vs 7/23 cases) than the MS/MS score, and enables the rapid identification of both the correct parent ion mass and the correct parent formula with minimal expert intervention.
Our method reliably identifies the correct parent formula even when the mass information is ambiguous. Furthermore, should parent formula identification be successful, the majority of associated fragment formulae can also be correctly identified. Our method can also identify the parent ion and its associated fragments in EI-MS spectra where the identity of the parent ion is unclear due to low quantities and overlapping compounds. Finally, our method does not inherently require empirical fitting of parameters or statistical learning, meaning it is easy to implement and extend upon.
Developed, implemented and tested new metrics for assessing plausibility of candidate molecular formulae obtained from HR-MS data.
从质谱图中识别未知化合物的分子式和裂解反应在天然产物化学和代谢组学等领域至关重要。我们提出了一种从质谱图中识别未知天然产物正确候选分子式的方法。该方法包括基于母离子子式图（PSG）对母离子候选分子式的合理性进行评分，以及与PSG中边的数量相关的两种可能的度量标准。此方法适用于电子轰击质谱（EI-MS）和串联质谱（MS/MS）数据。此外，这项工作引入了二维裂解图（2DFP）来可视化PSG。
我们的结果表明，与更被广泛接受的“MS/MS评分”相比，纳入有关PSG边的信息在正确识别母离子分子式方面具有更高的性能，在2016年小分子识别计算评估（CASMI 2016）数据集（正确分子式识别率为76.3%对58.9%）和环境中毒性化合物研究中心（RECETOX）数据集（正确分子式识别率为66.2%对59.4%）上均如此。在将我们的方法扩展以从信息素的复杂EI-MS数据中识别正确候选分子式时，我们的方法再次表现优于MS/MS评分（20/23例中正确分子式出现在前4个候选中，而MS/MS评分为7/23例），并且能够在最少专家干预的情况下快速识别正确的母离子质量和正确的母离子分子式。
即使质量信息不明确，我们的方法也能可靠地识别正确的母离子分子式。此外，如果母离子分子式识别成功，大多数相关的碎片分子式也能被正确识别。我们的方法还可以在EI-MS谱图中识别母离子及其相关碎片，其中由于含量低和化合物重叠导致母离子的身份不明确。最后，我们的方法本质上不需要对参数进行经验拟合或统计学习，这意味着它易于实现和扩展。
开发、实施并测试了用于评估从高分辨质谱（HR-MS）数据获得的候选分子式合理性的新度量标准。
