Identifying the Unknowns by Aligning Fragmentation Trees
Identifying the Unknowns by Aligning Fragmentation Trees
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DOI：
10.1021/ac300304u
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发表时间：
2012-04-03
影响因子：
7.4
通讯作者：
Boecker, Sebastian
中科院分区：
文献类型：
--
作者：
Rasche, Florian;Scheubert, Kerstin;Boecker, Sebastian
质谱法可以对小分子进行敏感，自动化和高通量分析。原则上，串联质谱法使我们能够在任何数据库中识别“未知”的小分子，但是对此类数据的自动解释仍处于起步阶段。最近引入了碎裂树，用于对小分子的碎片模式进行自动分析。我们提出了一种基于对齐化合物的碎片树的对齐的这种碎片模式的自动比较的方法。我们仅基于它们的碎片模式聚类，并与已知的化合物类别显示出良好的一致性。碎片模式相似性与分子的化学相似性密切相关。我们提出了一种用于搜索数据库的工具，以获取具有碎片模式的化合物，类似于未知样品化合物。我们将此工具应用于冰岛罂粟的代谢产物。我们的方法允许在任何数据库中都无法找到的小分子进行全自动计算识别。
Mass spectrometry allows sensitive, automated, and high-throughput analysis of small molecules. In principle, tandem mass spectrometry allows us to identify "unknown" small molecules not in any database, but the automated interpretation of such data is in its infancy. Fragmentation trees have recently been introduced for the automated analysis of the fragmentation patterns of small molecules. We present a method for the automated comparison of such fragmentation patterns, based on aligning the compounds' fragmentation trees. We cluster compounds based solely on their fragmentation patterns and show a good agreement with known compound classes. Fragmentation pattern similarities are strongly correlated with the chemical similarity of molecules. We present a tool for searching a database for compounds with fragmentation pattern similar to an unknown sample compound. We apply this tool to metabolites from Icelandic poppy. Our method allows fully automated computational identification of small molecules that cannot be found in any database.