使用MAGMa对质谱数据进行自动复合标注。

Q3 Physics and Astronomy Mass spectrometry Pub Date : 2014-08-01 DOI:10.5702/massspectrometry.S0033
L. Ridder, J. V. D. van der Hooft, S. Verhoeven
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引用次数: 56

摘要

采用MAGMa软件对CASMI 2013大赛的16个MS/MS数据集进行了质谱碎片数据自动标注。第一类(分子式作业)提交了8个溶液,第二类(分子结构作业)提交了12个溶液。每个挑战的MS/MS峰与PubChem中候选分子的计算机生成的子结构相匹配,从而产生用于候选排名的惩罚分数。在提交的12个类别2的溶液中,有6个正确的化学结构获得了最高分,而3个分子排在前5名之外。第一类提交的排名靠前的分子式均正确。此外,我们还展示了MAGMa对剩余挑战的回顾性结果。MAGMa算法的成功应用需要包含相关的候选分子,应用适当的质量公差以及候选分子的足够程度的硅碎片化。此外,还讨论了候选列表穷竭性的影响和基于子结构的评分的局限性。
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Automatic Compound Annotation from Mass Spectrometry Data Using MAGMa.
The MAGMa software for automatic annotation of mass spectrometry based fragmentation data was applied to 16 MS/MS datasets of the CASMI 2013 contest. Eight solutions were submitted in category 1 (molecular formula assignments) and twelve in category 2 (molecular structure assignment). The MS/MS peaks of each challenge were matched with in silico generated substructures of candidate molecules from PubChem, resulting in penalty scores that were used for candidate ranking. In 6 of the 12 submitted solutions in category 2, the correct chemical structure obtained the best score, whereas 3 molecules were ranked outside the top 5. All top ranked molecular formulas submitted in category 1 were correct. In addition, we present MAGMa results generated retrospectively for the remaining challenges. Successful application of the MAGMa algorithm required inclusion of the relevant candidate molecules, application of the appropriate mass tolerance and a sufficient degree of in silico fragmentation of the candidate molecules. Furthermore, the effect of the exhaustiveness of the candidate lists and limitations of substructure based scoring are discussed.
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来源期刊
Mass spectrometry
Mass spectrometry Physics and Astronomy-Instrumentation
CiteScore
1.90
自引率
0.00%
发文量
3
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