Planta Med 2015; 81 - PZB3
DOI: 10.1055/s-0035-1556552

Dissemination of original NMR data enhances the reproducibility of natural product research

GF Pauli 1, 2, JB Friesen 1, 2, M Niemitz 3, J Bisson 1, DC Lankin 1, C Soldi 4, 5, JT Shaw 4, DJ Tantillo 4, SN Chen 1, 2, JB McAlpine 1, 2
  • 1Dept. of Med. Chemistry & Pharmacognosy
  • 2Inst. for Tuberculosis Research, Coll. Pharmacy, UIC, 833 S. Wood St., Chicago (IL), USA
  • 3PERCH Solutions Ltd., Puijonkatu 24 B 5, Kuopio, Finland
  • 4Dept. of Chemistry, University of CA-Davis, 1 Shields Avenue, Davis (CA) USA
  • 5Univ. Fed. de Santa Catarina, Campus de Curitibanos, Rod. Ulysses Gaboardi, Km 3, Curitibanos – SC, 89520 – 000, Brazil

The acquisition of 1D 1H NMR (HNMR) spectra is one of earliest steps in characterizing natural products and other organic molecules. For publication, HNMR information usually is “converted” into a table format, and sometimes spectral plots are provided. However, this transformation is lossy and frequently insufficient for unambiguous dereplication. This ambiguity can even lead to structural revision, such as in the recent case of aquatolide (1), a sesquiterpene lactone from Asteriscus aquaticus. Our study demonstrates that public dissemination of original (digital) HNMR data (FIDs) can be a powerful means of enhancing the reproducibility of structural assignments and, thus, any downstream biological studies. Using the archived 800 MHz HNMR spectrum, and employing a semi-automated quantum mechanics-driven spectral analysis (HiFSA), we were able to rule out the initial assignment (1a), confirm the revision (1b), and achieve the full interpretation of the HNMR fingerprints. Using additional examples of constitutional and diastereomeric isomers which exhibit complex and near-identical HNMR spectra, we show that the public sharing of original HNMR data (FIDs) is not only essential for robust structural assignments, but can enhance the reproducibility of research with bioactive natural products and other organic molecules simply and productively.

Acknowledgement: We appreciate the diligent help of Michael J. Di Maso, UofCA Davis, with NMR data management.