Authors: Guido F. Pauli , Shao-Nong Chen, David C. Lankin, Jonathan Bisson , Ryan J. Case, Lucas R. Chadwick, Tanja Gödecke, Taichi Inui, Aleksej Krunic, Birgit U. Jaki, James B. McAlpine, Shunyan Mo, José G. Napolitano, Jimmy Orjala, Juuso Lehtivarjo, Samuli-Petrus Korhonen, Matthias Niemitz
Journal: Journal of Natural Products (RoMEO status: White) 77(6), 1473-1487, (2014)
Subjects: Pharmacognosy Phytochemistry NMR Spin simulation
The present study demonstrates the importance of adequate precision when reporting the δ and J parameters of frequency domain 1H NMR (HNMR) data. Using a variety of structural classes (terpenoids, phenolics, alkaloids) from different taxa (plants, cyanobacteria), this study develops rationales that explain the importance of enhanced precision in NMR spectroscopic analysis and rationalizes the need for reporting Δδ and ΔJ values at the 0.1–1 ppb and 10 mHz level, respectively. Spectral simulations paired with iteration are shown to be essential tools for complete spectral interpretation, adequate precision, and unambiguous HNMR-driven dereplication and metabolomic analysis. The broader applicability of the recommendation relates to the physicochemical properties of hydrogen (1H) and its ubiquity in organic molecules, making HNMR spectra an integral component of structure elucidation and verification. Regardless of origin or molecular weight, the HNMR spectrum of a compound can be very complex and encode a wealth of structural information that is often obscured by limited spectral dispersion and the occurrence of higher order effects. This altogether limits spectral interpretation, confines decoding of the underlying spin parameters, and explains the major challenge associated with the translation of HNMR spectra into tabulated information. On the other hand, the reproducibility of the spectral data set of any (new) chemical entity is essential for its structure elucidation and subsequent dereplication. Handling and documenting HNMR data with adequate precision is critical for establishing unequivocal links between chemical structure, analytical data, metabolomes, and biological activity. Using the full potential of HNMR spectra will facilitate the general reproducibility for future studies of bioactive chemicals, especially of compounds obtained from the diversity of terrestrial and marine organisms.