A novel strategy for screening new natural products by a combination of reversed-phase liquid chromatography fractionation and 13C NMR pattern recognition: the discovery of new anti-cancer flavone dimers from Dysosma versipellis (Hance)

Natural products have been a rich source for drug discovery. However, the traditional process of discovering new bioactive natural products is generally labor-intensive and time-consuming, and the known natural products are frequently rediscovered. In this work, we present a new screening strategy for the discovery of new natural products by a combination of reversed-phase liquid chromatography (RPLC) and 13C NMR pattern recognition. The known compounds were first recognized by 13C NMR clustering analysis and on-line 13C NMR database matching. The unrecognized 13C NMR clusters and HPLC peaks were possibly new natural products and then further subjected to targeted isolation and purification for structural elucidation. Thus, this method may win a higher hit rate of new natural products than the traditional process. As an example, we analyzed a cytotoxic sample extracted from roots of Dysosma versipellis (Hance) by RPLC fractionation followed by 13C NMR clustering analysis. As a result, 7 13C NMR clusters were recognized as 7 known compounds including 5 podophyllotoxins and 2 flavones corresponding to 7 HPLC peaks by comparison with reported NMR data. One unrecognized 13C NMR block including at least three unrecognized NMR clusters gave us clues for new natural products, guiding the following targeted isolation and purification, which resulted in the discovery of 6 new flavone dimers podoverine D, E, F, G, H and I together with the known podoverine A. Interestingly, these new flavone dimers expressed potential cytotoxicity to several cancer cells in vitro. To the best of our knowledge, this is the first document to demonstrate a RPLC fractionation-13C NMR pattern recognition strategy to rapidly discovery new natural products. It is an important advancement for natural product identification and metabolomic analysis.