Construction of Chinese baijiu compound database using text mining and its application in assisting compound identification of liquid chromatography-high-resolution mass spectrometry data

A comprehensive understanding of the molecular composition of Chinese baijiu is of great value for understanding the flavor and improving the quality. Liquid chromatography-mass spectrometry (LC-MS) is a good tool for the analysis of Chinese baijiu. However, the lack of a related database makes it difficult to annotate corresponding LC-MS data. Therefore, a Chinese baijiu compound database (CBDB) containing 5709 compounds was constructed based on literature and text mining, and further, a Chinese baijiu LC-MS database (LCMS-CBDB) was built by endowing each compound with retention time, exact mass, and MS2 information. In total, 468 compounds were identified in six Chinese baijiu samples by searching LCMS-CBDB. Further, 2 database enhancement strategies were proposed based on biological transformation and theoretical homologue expansion. As an example, four monoglycerides were successfully identified and validated using the extended CBDB, and three of them were reported in baijiu for the first time.