Searching molecular structure databases with tandem mass spectra using CSI:FingerID
Searching molecular structure databases with tandem mass spectra using CSI:FingerID
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DOI：
10.1073/pnas.1509788112
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发表时间：
2015-10-13
影响因子：
11.1
通讯作者：
Boecker, Sebastian
中科院分区：
文献类型：
--
作者：
Duehrkop, Kai;Shen, Huibin;Boecker, Sebastian
代谢物提供了细胞状态的直接功能标志。非靶向代谢组学实验通常依靠串联质谱来鉴定生物样品中的数千种化合物。今天，绝大多数代谢物仍然未知。提出了一种利用小分子串联质谱数据搜索分子结构数据库的方法。我们的方法计算了一个最好地解释未知分子的碎片谱的碎片树。我们使用碎片树，利用机器学习预测未知化合物的分子结构指纹。然后用这个指纹来搜索分子结构数据库，比如PubChem。我们的方法被证明在计算代谢物鉴定的竞争方法上有相当大的改进。
Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin.