4.7 Article

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

期刊

JOURNAL OF ORGANIC CHEMISTRY
卷 80, 期 19, 页码 9371-9378

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.joc.5b01663

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资金

  1. UNR [BIO 316]
  2. ANPCyT [PICT 2011-0255, PICT-2012-0970]
  3. CONICET [PIP 11220130100660CO, 3759/13]

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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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