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Computer-Assisted Structure Elucidation (CASE) using a combination of 1D and 2D NMR data has been available for a number of years. These algorithms can be considered as “logic machines” capable of deriving all plausible structures from a set of structural constraints or “axioms”, defined by the spectral data and associated chemical information or prior knowledge. CASE programs allow the spectroscopist not only to determine structures from the spectral data but also to study the dependence of the proposed structure on changes to the set of axioms. In this article we describe the application of the ACD/Structure Elucidator expert system to resolve the conflict between two different hypothetical hexacyclinol structures derived by different researchers from the NMR spectra of this complex natural product. It has been shown that the combination of algorithms for both structure elucidation and structure validation delivered by the expert system enables the identification of the most probable structure as well as the associated chemical shift assignments.

During the process of molecular structure elucidation the selection of the most probable structural hypothesis may be based on chemical shift prediction. The prediction is carried out using either empirical or quantum-mechanical (QM) methods. When QM methods are used, NMR prediction commonly utilizes the GIAO option of the DFT approximation. In this approach the structural hypotheses are expected to be investigated by scientist. In this article we hope to show that the most rational manner by which to create structural hypotheses is actually by the application of an expert system capable of deducing all potential structures consistent with the experimental spectral data and specifically using 2D NMR data. When an expert system is used the best structure(s) can be distinguished using chemical shift prediction, which is best performed either by an incremental or neural net algorithm. The time-consuming QM calculations can then be applied, if necessary, to one or more of the 'best' structures to confirm the suggested solution.

The reliable determination of stereocenters contained within chemical structures usually requires utilization of NMR data, chemical derivatization, molecular modeling, quantum-mechanical (QM) calculations and, if available, X-ray analysis. In this article, we show that the number of stereoisomers which need to be thoroughly verified, can be significantly reduced by the application of NMR chemical shift calculation to the full stereoisomer set of possibilities using a fragmental approach based on HOSE codes. The applicability of this suggested method is illustrated using experimental data published for a series of complex chemical structures

In silico prediction of small molecules properties is widely used in todays industry and academia. Particularly, NMR spectra are predicted by a variety of software packages. Two main approaches are used: •Database-based. Compounds are compared against a database, the result is calculated using data for close structural relatives found in the dataset. •Regression-based. Experimental database is used to calculate parameters of non-linear regression. Chemical shift is represented as a non-linear function of some variables which describe characteristic features of a molecule of interest.

The elucidated structure of asperjinone, a natural product isolated from thermophilic Aspergillus terreus, was revised using the expert system Structure Elucidator. The reliability of the revised structure was confirmed using 180 structures containing the (3,3-dimethyloxiran-2-yl)methyl fragment as a basis for comparison and whose chemical shifts contradict the suggested structure.

This review considers the application of CASE systems to a series of examples in which the original structures were later revised. We demonstrate how the chemical structure could be correctly elucidated if 2D NMR data were available and the expert system Structure Elucidator was employed. We will also demonstrate that if only 1D NMR spectra from the published articles were used then simply the empirical calculation of 13C chemical shifts for the hypothetical structures frequently enables a researcher to realize that the structural hypothesis is likely incorrect. We also analyze a number of erroneous structural suggestions made by highly qualified and skilled chemists. The investigation of these mistakes is very instructive and has facilitated a deeper understanding of the complicated logical-combinatorial process for deducing chemical structures.The multiple examples of the application of Structure Elucidator for resolving mis-assigned structures has shown that the program can serve as a flexible scientific tool which assists chemists in avoiding pitfalls and obtaining the correct solution to a structural problem in an efficient manner. Chemical synthesis clearly still plays an important role in molecular structure elucidation. The multi-step process requires the structure elucidation of all intermediate structures at each step, for which spectroscopic methods are commonly used. Consequently, the application of a CASE system would be very helpful even in those cases when chemical synthesis is the crucial evidence to identify the correct structure. We also believe that the utilization of CASE systems will frequently reduce the number of compounds requiring synthesis.

The accuracy of 13C chemical shift prediction by both DFT GIAO quantum-mechanical (QM) and empirical methods was compared using 205 structures for which experimental and QM-calculated chemical shifts were published in the literature. For these structures, 13C chemical shifts were calculated using HOSE code and neural network (NN) algorithms developed within our laboratory. In total, 2531 chemical shifts were analyzed and statistically processed. It has been shown that, in general, QM methods are capable of providing similar but inferior accuracy to the empirical approaches, but quite frequently they give larger mean average error values. For the structural set examined in this work, the following mean absolute errors (MAEs) were found: MAE(HOSE) = 1.58 ppm, MAE(NN) = 1.91 ppm and MAE(QM) = 3.29 ppm. A strategy of combined application of both the empirical and DFT GIAO approaches is suggested. The strategy could provide a synergistic effect if the advantages intrinsic to each method are exploited.

Structure elucidation using 2D NMR data and application of traditional methods of structure elucidation is known to fail for certain problems. In this work it is shown that Computer-Assisted Structure Elucidation (CASE) methods are capable of solving such problems. We conclude that it is now impossible to evaluate the capabilities of novel NMR experimental techniques in isolation from expert systems developed for processing fuzzy, incomplete and contradictory information obtained from 2D NMR spectra.