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

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• 作者：Mar铆a M. Zanardi ; Ariel M. Sarotti
• 刊名：Journal of Organic Chemistry
• 出版年：2015
• 出版时间：October 2, 2015
• 年：2015
• 卷：80
• 期：19
• 页码：9371-9378
• 全文大小：743K
• ISSN：1520-6904

文摘

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鈥揌 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.