Mass spectrometry guided strategy based on feature fragment ions for guided-separation on quinoline alkaloids from root barks of Dictamnus dasycarpus / 中国中药杂志

The root bark of Dictamnus dasycarpus is one of common traditional Chinese medicines (TCMs). Quinoline alkaloids are one of the main active substances in this TCM and possess many biological activities including anti-titumor, anti-inflammation, anti-bacteria, anti-oxidation, and anti-platelet aggregation activities. In this study, eight quinoline alkaloids 1-8 were firstly separated from the root barks of D. dasycarpus. It was difficult to isolate more quinoline alkaloids from the remaining fraction 8 in D. dasycarpus by this conventional chemical separation, so the target analysis method combined LC-MS guided-separation of quinoline alkaloids from fraction 8 was established. MS/MS fragmentation patterns of eight quinoline alkaloids reference standard compounds 1-8 were studied by ultra-performance liquid chromatography-electrospary ionization-mass spectrometry (UPLC-ESI-MS/MS). Based on the feature fragment ion 200, the parent ion scan mode was established for the target analysis of quinoline alkaloids in fraction 8. Finally, 8-methoxyflindersine (9) and N-metilatanina (10) were discovered and isolated quickly from fraction 8 guided by LC-MS, and their structures were identified by NMR and MS. Among them, compound 10 was isolated from the genus Dictamnus for the first time. These results indicated that this method is not only quick and sensitive for analyzing the quinoline alkaloids, but also to effectively guided-separate this kind of alkaloids in the root barks of D. dasycarpus.

Strategy of Discovering Active Ingredient in Traditional Chinese Medicine under Guidance of Network Pharmacology / 世界科学技术-中医药现代化

Network pharmacology is an emerging discipline based on the Disease-Gene-Drug multilevel network. And it has been used to forecast the drug targets and improve the efficiency of drug discovery. Its research ideas are similar to the overall efficacy of traditional Chinese medicine (TCM), which attracts more and more medical re-searchers to look for the joint point of TCM and network pharmacology. A series of approaches on disease-related genes, predicting the information of target and active ingredients of TCM emerge. In this paper, the network pharma-cology research tools, databases and their applications were summarized and introduced. This paper also proposed scientific strategies to separate active ingredients of TCM using network pharmacology, so as to improve the efficiency and speed of finding active ingredients of TCM.