Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography–mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography–mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives.

与典型途径不同的新代谢物可以通过集成三种化学信息学工具来识别：BinVestigate，它查询 BinBase 气相色谱-质谱 (GC-MS) 代谢组数据库，以将超过 110,000 个样本中的未知物与生物元数据进行匹配；MS-DIAL 2.0，一种用于高分辨率 GC-MS 或液相色谱-质谱 (LC-MS) 色谱解卷积的软件工具；MS-FINDER 2.0 是一种结构解析程序，除了酶混杂库之外，还结合使用了 14 个代谢组数据库。我们通过注释N-甲基-尿苷单磷酸 (UMP)、溶单半乳糖基-单棕榈酸、N-甲基丙氨酸和两种丙泊酚衍生物来展示我们的工作流程。