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J Org Chem. 2015 Oct 2;80(19):9371-8. doi: 10.1021/acs.joc.5b01663. Epub 2015 Sep 20.

GIAO C-H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward.

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Instituto de Química Rosario (CONICET), Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario , Suipacha 531, Rosario 2000, Argentina.
Facultad de Química e Ingeniería "Fray Rogelio Bacón", Pontificia Universidad Católica Argentina , Av. Pellegrini 3314, Rosario 2000, Argentina.


The 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.


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