Planta Med 2014; 80 - P2O6
DOI: 10.1055/s-0034-1395001

Natural products spectral database: An innovative platform for rapid identification

K Stathopoulou 1, D Benaki 1, LH Tseng 2, P Dvortsak 2, G Lambrinidis 1, A Grote 2, E Humpfer 2, H Schaefer 2, V Dumontet 4, G Fouche 5, M Hamburger 3, AL Skaltsounis 1, M Spraul 2, E Mikros 1
  • 1Department of Pharmacognosy & Natural Products Chemistry and Pharmaceutical Chemistry, Faculty of Pharmacy, University of Athens, Zografou, 15771, Greece
  • 2Bruker BioSpin GmbH, 76287 Rheinstetten, Germany
  • 3Division of Pharmaceutical Biology, University of Basel, Klingelbergstrasse 50, 4056 Basel, Switzerland
  • 4Centre de Recherche de Gif, Institut de Chimie des Substances Naturelles, C.N.R.S., 91198 Gif-sur-Yvette Cedex, France
  • 5Biosciences, CSIR, PO Box 395, Pretoria 0001, South Africa

A major difficulty in the natural products field is the lack of standardized spectral libraries for plant extracts and plant-derived compounds. A highly innovative aim of the project under the acronym AgroCos (FP7) is the generation of NMR and LC-MS data spectral libraries of extracts and pure compounds derived from plants originating from major biodiversity hotspots in Europe, Africa, Latin America, and the Asia-Pacific regions. Standardized protocols (sample preparation, spectra acquisition procedure, data processing) were followed to allow comparison of spectra and common statistics and a state-of-the-art technology platform has been developed. Prior to any measurement, a set of control-optimization tests was performed regarding the instrumental performance (temperature calibration, long stability test, homogeneity of magnetic field). All optimization tests were carried out with standard shielded samples of sucrose and CD3OD (99.8%). The NMR spectroscopic dataset from 800 pure compounds and extracts has been processed within the spectral database. Five different spectra have been acquired for each pure compound, 1D, COSY, HSQC, HMBC, J-res and J-res-F2-projection. All pure compounds have been characterized and labeled with atom numbers according to IUPAC nomenclature. Statistical routines have been created for evaluation and classification of acquired spectroscopic data. The statistical analysis based on MatLab routines includes basic and advanced Statistics, PCA, LDA, PLS, statistical tests (T-test, ANOVA, etc.) and STOCSY. In addition detailed metadata information, such as taxonomy, plant part, location, harvesting date, etc., and biological activity is provided. The designed spectral base includes several tools that enable the visual inspection for large spectral numbers, the definition of similarity or identity of pure compounds spectra in extract spectra, providing thus a powerful dereplication platform.

Acknowledgements: This study has been carried out with the financial support of the Commission of the European Community, Framework Program 7, specific cooperation program Theme 2 'FOOD, AGRICULTURE AND FISHERIES, AND BIOTECHNOLOGY'.

Keywords: Database, natural products, NMR, LC-MS, dereplication