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

Comprehensive understanding of the molecular composition in Chinese baijiu is of a 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, lack of the related database makes corresponding LC-MS data difficult to be annotated. Therefore, a Chinese baijiu compound database (CBDB) containing 5709 compounds was constructed based on literatures 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 MS/MS spectrum. In total 468 compounds were identified in six Chinese baijiu samples by searching LCMS-CBDB. Further, database enhancement strategies were proposed based on biological transformations and theoretical homologue expansion, which allows the identification of new compounds. Four monoglycerides were successfully identified and validated using the extended CBDB, three of them were reported in baijiu for the first time.