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Natural products remain one of the major sources of coveted, biologically active compounds. Each isolated compound undergoes biological testing, and its structure is usually established using a set of spectroscopic techniques (NMR, MS, UV-IR, ECD, VCD, etc.). However, the number of erroneously determined structures remains noticeable. Structure revisions are very costly, as they usually require extensive use of spectroscopic data, computational chemistry, and total synthesis. The cost is particularly high when a biologically active compound is resynthesized and the product is inactive because its structure is wrong and remains unknown. In this paper, we propose using Computer-Assisted Structure Elucidation (CASE) and Density Functional Theory (DFT) methods as tools for preventive verification of the originally proposed structure, and elucidation of the correct structure if the original structure is deemed to be incorrect. We examined twelve real cases in which structure revisions of natural products were performed using total synthesis, and we showed that in each of these cases, time-consuming total synthesis could have been avoided if CASE and DFT had been applied. In all described cases, the correct structures were established within minutes of using the originally published NMR and MS data, which were sometimes incomplete or had typos. [ABSTRACT FROM AUTHOR]

Computer‐assisted structure elucidation (CASE) is the class of expert systems that derives molecular structures primarily from one‐dimensional and two‐dimensional nuclear magnetic resonance data. Contemporary CASE systems, including Advanced Chemistry Development/Structure Elucidator (ACD/SE), consider cross‐peaks in heteronuclear multiple bond coherence (HMBC) and correlation spectroscopy (COSY) spectra as two‐ or three‐bond correlations by default. However, four and more bond correlations (nonstandard correlations [NSCs]) could be present in these spectra too. The indiscriminate addition of NSCs to the CASE computations is prohibitively expensive. To address this problem, the ACD/SE program performs a logical analysis of observed correlations and determines the minimum number of NSCs. Guided by this information, a more efficient fuzzy structure generation (FSG) algorithm is subsequently applied. Until now, the FSG algorithm was utilized without any verification of the reliability of found NSCs. Here, we report a verification method for NSCs based on the relationship between NSCs and J‐couplings computed with high accuracy density functional theory (DFT) methods. We used the example of strychnine to show that 41 (32%) of 8‐Hz HMBC cross‐peaks were NSCs and were consistent with 4–6JCH couplings greater than 0.3 Hz. This cutoff value was largely confirmed by the analysis of NSCs in 11 real‐world natural products elucidated by ACD/SE. Additionally, utilizing the example of the CASE study of cleospinol A, we showed that the DFT‐computed J‐couplings of NSCs can distinctively differentiate the correct structure among six proposed isomers. The proposed approach of NSC verification should further improve the robustness of CASE analysis and can help reveal potential problems with reported experimental data. [ABSTRACT FROM AUTHOR]

The state of the art and recent developments in application of nuclear magnetic resonance (NMR) for structure elucidation and identification of small organic molecules are discussed. The recently suggested new two-dimensional (2D)-NMR experiments combined with the advanced instrumentation allow structure elucidation of new organic compounds at a sample amount of less than 10 µg. A pure shift approach that provides 1 H-decoupled proton spectra drastically simplified 1 H and 2D NMR spectra interpretation. The structure elucidation of extremely hydrogen-deficient compounds was dramatically facilitated due to the methodology based on combination of new 2D-NMR experiments providing long-range heteronuclear correlations with computer-assisted structure elucidation (CASE). The capabilities of CASE systems are discussed. The role of NMR-spectrum prediction in structure verification and NMR approaches for qualitative mixture analysis are considered. [ABSTRACT FROM AUTHOR]

Even though NMR has found countless applications in the field of small molecule characterization, there is no standard file format available for the NMR data relevant to structure characterization of small molecules. A new format is therefore introduced to associate the NMR parameters extracted from 1D and 2D spectra of organic compounds to the proposed chemical structure. These NMR parameters, which we shall call NMReDATA (for nuclear magnetic resonance extracted data), include chemical shift values, signal integrals, intensities, multiplicities, scalar coupling constants, lists of 2D correlations, relaxation times, and diffusion rates. The file format is an extension of the existing Structure Data Format, which is compatible with the commonly used MOL format. The association of an NMReDATA file with the raw and spectral data from which it originates constitutes an NMR record. This format is easily readable by humans and computers and provides a simple and efficient way for disseminating results of structural chemistry investigations, allowing automatic verification of published results, and for assisting the constitution of highly needed open‐source structural databases. [ABSTRACT FROM AUTHOR]