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

Classification-based strategies to simplify complex traditional Chinese medicine (TCM) researches through liquid chromatography-mass spectrometry in the last decade (2011-2020): Theory, technical route and difficulty

The difficulty of traditional Chinese medicine (TCM) researches lies in the complexity of components, metabolites, and bioactivities. For a long time, there has been a lack of connections among the three parts, which is not conducive to the systematic elucidation of TCM effectiveness. To overcome this problem, a classification-based methodology for simplifying TCM researches was refined from literature in the past 10 years (2011-2020). The theoretical basis of this methodology is set theory, and its core concept is classification. Its starting point is that "although TCM may contain hundreds of compounds, the vast majority of these compounds are structurally similar". The methodology is composed by research strategies for components, metabolites and bioactivities of TCM, which are the three main parts of the review. Technical route, key steps and difficulty are introduced in each part. Two perspectives are highlighted in this review: set theory is a theoretical basis for all strategies from a conceptual perspective, and liquid chromatography-mass spectrometry (LC-MS) is a common tool for all strategies from a technical perspective. The significance of these strategies is to simplify complex TCM researches, integrate isolated TCM researches, and build a bridge between traditional medicines and modern medicines. Potential research hotspots in the future, such as discovery of bioactive ingredients from TCM metabolites, are also discussed. The classification-based methodology is a summary of research experience in the past 10 years. We believe it will definitely provide support and reference for the following TCM researches.

A new cinnamamide derivative and two new β-carboline alkaloids from the stems of Picrasma quassioides

Picrasamide A (1), a new cinnamamide derivative, together with two new β-carboline alkaloids (2 and 3) and five known β-carboline alkaloids (4-8) were isolated from the stems of Picrasma quassioides (D. Don) Benn. Their structures were elucidated by detailed analyses of UV, IR, HRESIMS, and NMR data. Compound 1 was the first case of cinnamamide derivative from genus Picrasma. The AChE inhibitory activity and the antimicrobial activity of 1-8 were assessed. In addition, preliminary structure-activity relationships of these β-carboline alkaloids on the AChE inhibitory activity and antimicrobial activity were proposed.

Identification and screening of cardiac glycosides in Streptocaulon griffithii using an integrated data mining strategy based on high resolution mass spectrometry

The present study was designed to develop a practical strategy to tackle the problem of lacking standard compounds and limited references for identifying structure-related compounds in Streptocaulon griffithii Hook. f., especially those in trace concentrations, with a focus on antitumor activity. The cardiac glycosides (CGs)-enriched part was determined using in vitro bioactive assays in three cancer cell lines and then isolated using macroporous resins. The MS and MS/MS data were acquired using a high performance liquid chromatography coupled with hybrid quadrupole-time of flight (HPLC-Q-TOF-MS) system. To acquire data of trace compound in the extract, a multiple segment program was applied to modify the HPLC-Q-TOF-MS method. A mass defect filter (MDF) approach was employed to make a primary MS data filtration. Utilizing a MATLAB program, the redundant peaks obtained by imprecise MDF template calculated with limited references were excluded by fragment ion classification, which was based on the ion occurrence number in the MDF-filtered total ion chromatograms (TIC). Additionally, the complete cleavage pathways of CG aglycones were proposed to assist the structural identification of 29 common fragment ions (CFIs, ion occurrence number ≥ 5) and diagnostic fragment ions (DFIs, ion occurrence number < 5). As a result, 30 CGs were filtered out from the MDF results, among which 23 were identified. This newly developed strategy may provide a rapid and effective tool for identifying structure-related compounds in herbal medicines.