NMR calculation as a helpful tool in structure elucidation

SAROTTI, A. M.; GRIMBLAT, N.; ZANARDI, M. M.

Santa Fe

Taller; III Taller de Resonancia Magnética ?NMR and EPR at the forefront of research?; 2016

Sistema Nacional de Resonancia Magnética

The total synthesis of natural products is one of the most beautiful and exciting chemistry areas, lying somewhere between a fine art and a hard science. The enterprises are often hard and fraught with difficulties and detours. Eventually, after a considerable investment of time, money, and man-power the synthetic target is accomplished. However, surprisingly often such an exciting moment quickly moves to frustration once a mismatch between the NMR data of the synthesized compound and the natural product is detected.Incorrectly assigned natural products are not uncommon, even in the golden age of NMR. High molecular complexity, human errors, signal ambiguity and sample impurities can be pointed to as the most common sources of misassignments. Hundreds of structural revisions have been published in the last decades, ranging from profound connectivity to subtle (but not least) stereochemical errors. Considering that the discrepancies are often detected after total synthesis of the originally proposed (wrong) structure, it is not unreasonable to assume that the real molecular architecture of many reported natural products remains unknown.Modern computational chemistry has significantly contributed to prevent these mistakes. We have developed to tools wich allow to interpret the correlation between experimental and calculated NMR data contributing to the structural assignment.The DP4 probability is one of the most sophisticated and popular approaches for the stereochemical assignment of organic molecules using GIAO NMR chemical shift calculations when only one set of experimental data is available. In order to improve the performance of the method, we have developed a modified probability (DP4+), whose main differences from the original DP4 are the inclusion of unscaled data and the use of higher levels of theory for the NMR calculation procedure. With these modifications, a significant improvement in the overall performance was achieved, providing accurate and confident results in establishing the stereochemistry of 48 challenging isomeric compounds.1The structural validation problem using quantum chemistry approaches (confirm or reject a candidate structure) has been tackled with artificial neural network (ANN) mediated multidimensional pattern recognition from experimental and calculated 2D C−H COSY. In order to identify subtle errors (such as regio- or stereochemical), more than 400 ANNs have been built and trained, and the most efficient in terms of classification ability were successfully validated in challenging real examples of natural product misassignments.2