A self-feedback network based on liquid chromatography-quadrupole-time of flight mass spectrometry for system identification of β-carboline alkaloids in Picrasma quassioides

Profiling chemical components in herbs by mass spectrometry is a challenging work because of the lack of standard compounds, especially for position isomers. This paper provides a strategy based on a self-feedback network of mass spectra (MS) data to identify chemical constituents in herbs by liquid chromatography-quadrupole-time of flight mass spectrometry without compound standards. Components sharing same skeleton were screened and all ions were classified into a database. All candidates were connected by the selected bridging ions to establish a primary MS network. Benefited from such a network, it is feasible to characterize sequentially the structures of all diagnostic ions and candidates once single component has been de novo identified. Taking Picrasma quassioides as an example, the primary network of β-carbolines was established with 65 ions (selected from 76 β-carbolines), each of which appeared at least in four compounds. Once an alkaloid has been identified, its logical ions could feedback into primary network to build pathways with other unknown compounds. Moreover, the position of the substituent groups could be deduced through the secondary metabolic pathways of alkaloids (plant secondary metabolism). The network therefore can be utilized for identification of unknown compounds and even their position isomers.