Identification of Natural Metabolites in Mixture: A Pattern Recognition Strategy Based on 13 C NMR Jane Hubert,* ,† Jean-Marc Nuzillard, † Sylvain Purson, †,‡ Mahmoud Hamzaoui, § Nicolas Borie, † Romain Reynaud, ‡ and Jean-Hugues Renault † † Institut de Chimie Molé culaire de Reims (UMR CNRS 7312), SFR CAP’SANTE, Universite ́ de Reims ChampagneArdenne, Reims, France ‡ Soliance S.A., Pomacle, France § Division of Pharmacognosy and Natural Product Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece ABSTRACT: Because of their highly complex metabolite profile, the chemical characterization of bioactive natural extracts usually requires time-consuming multistep purification procedures to achieve the structural elucidation of pure individual metabolites. The aim of the present work was to develop a dereplication strategy for the identification of natural metabolites directly within mixtures. Exploiting the polarity range of metabolites, the principle was to rapidly fractionate a multigram quantity of a crude extract by centrifugal partition extraction (CPE). The obtained fractions of simplified chemical composition were subsequently analyzed by 13 C NMR. After automatic collection and alignment of 13 C signals across spectra, hierarchical clustering analysis (HCA) was performed for pattern recognition. As a result, strong correlations between 13 C signals of a single structure within the mixtures of the fraction series were visualized as chemical shift clusters. Each cluster was finally assigned to a molecular structure with the help of a locally built 13 C NMR chemical shift database. The proof of principle of this strategy was achieved on a simple model mixture of commercially available plant secondary metabolites and then applied to a bark extract of the African tree Anogeissus leiocarpus Guill. & Perr. (Combretaceae). Starting from 5 g of this genuine extract, the fraction series was generated by CPE in only 95 min. 13 C NMR analyses of all fractions followed by pattern recognition of 13 C chemical shifts resulted in the unambiguous identification of seven major compounds, namely, sericoside, trachelosperogenin E, ellagic acid, an epimer mixture of (+)-gallocatechin and (-)-epigallocatechin, 3,3′-di-O-methylellagic acid 4′-O-xylopyranoside, and 3,4,3′-tri-O-methylflavellagic acid 4′-O-glucopyranoside. N atural extracts from plants and microorganisms still constitute invaluable sources of biologically active metabolites for the development of drugs or cosmetics. 1-3 The major challenge in the search for such metabolites arises from the extreme complexity of plant extracts or culture media which contain a wide diversity of molecules with distinct physical and chemical properties. At present, even if modern analytical and puri fication techniques are routinely available in most laboratories, a considerable work taking several days even several weeks or years is still necessary to isolate and elucidate individual metabolite structures from crude natural extracts. In some cases, time-consuming multistep purification procedures are unavoidable, for instance when the objective is to elucidate the complex molecular structure of a novel compound. In numerous other cases, the systematic purification of individual constituents results in a considerable waste of time. Bioactivity-guided fractionation procedures have been developed to focus only on the fractions or metabolites with a defined biological activity. However, often such approaches are applied to finally rediscover already known compounds. In view of these observations, new methods enabling the identification of natural metabolites directly within mixtures would be very useful. Received: October 7, 2013 Accepted: February 20, 2014 Published: February 20, 2014 Article pubs.acs.org/ac © 2014 American Chemical Society 2955 dx.doi.org/10.1021/ac403223f | Anal. Chem. 2014, 86, 2955-2962