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

The Journal of Organic Chemistry
María M Zanardi, Ariel M Sarotti

Abstract

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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Citations

Aug 2, 2017·International Journal of Environmental Research and Public Health·Zhijian LiuGuoqing Cao
Sep 25, 2018·Natural Product Reports·Marialuisa MennaOrazio Taglialatela-Scafati
May 31, 2019·Organic & Biomolecular Chemistry·Kristaps ErmanisJonathan M Goodman
Jul 10, 2019·Magnetic Resonance in Chemistry : MRC·Leonid B Krivdin
Jan 9, 2020·Magnetic Resonance in Chemistry : MRC·Carlos Cobas
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Oct 31, 2020·Archives of Pharmacal Research·Chung Sub KimTae Hyun Lee
Jul 25, 2021·Chemistry & Biodiversity·Peng JiangBing-You Yang
Aug 17, 2020·Accounts of Chemical Research·Maribel O MarcarinoAriel M Sarotti
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Dec 17, 2016·Organic Letters·Nicolás GrimblatAriel M Sarotti
Oct 13, 2021·Journal of Chemical Theory and Computation·Marcelo T de OliveiraCristina A Barboza

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