Recent advances in the development of dereplication strategies have brought new perspective to speed up natural product screening programs. Here is presented a 13C NMR-based dereplication method dedicated to the chemical profiling of natural metabolite mixtures. Starting from a single 13C NMR analysis and without need for fractionation, the method is based on an algorithm that compares the 13C NMR chemical shifts obtained from the single spectrum of a crude natural extract with a set of predicted NMR data stored in a natural metabolite database. The matching between experimental chemical shifts and predicted data is evaluated by a score function reflecting the probability for a metabolite to be present within the extract. As an example, this method was applied on a crude alkaloid extract obtained from the leaves of Peumus boldus, resulting in the identification of eight major alkaloids including isocorydine, rogersine, boldine, reticuline, coclaurine, laurotetanine, N-methylcoclaurine, and norisocorydine, as well as three monoterpenes including p-cymene, eucalyptol, and α-terpinene.
