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DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data

[Image: see text] Quantum mechanical/nuclear magnetic resonance (NMR) approaches are widely used for the configuration assignment of organic compounds generally comparing one cluster of experimentally determined data (e.g., (13)C NMR chemical shifts) with those predicted for all possible theoretical...

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Autores principales: Lauro, Gianluigi, Das, Pronay, Riccio, Raffaele, Reddy, D. Srinivasa, Bifulco, Giuseppe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997581/
https://www.ncbi.nlm.nih.gov/pubmed/31961156
http://dx.doi.org/10.1021/acs.joc.9b03129
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author Lauro, Gianluigi
Das, Pronay
Riccio, Raffaele
Reddy, D. Srinivasa
Bifulco, Giuseppe
author_facet Lauro, Gianluigi
Das, Pronay
Riccio, Raffaele
Reddy, D. Srinivasa
Bifulco, Giuseppe
author_sort Lauro, Gianluigi
collection PubMed
description [Image: see text] Quantum mechanical/nuclear magnetic resonance (NMR) approaches are widely used for the configuration assignment of organic compounds generally comparing one cluster of experimentally determined data (e.g., (13)C NMR chemical shifts) with those predicted for all possible theoretical stereoisomers. More than one set of experimental data, each related to a specific stereoisomer, may occur in some cases, and the accurate stereoassignments can be obtained by combining the experimental and computed data. We introduce here a straightforward methodology based on the simultaneous analysis, combination, and comparison of all sets of experimental/calculated (13)C chemical shifts for aiding the correct configuration assignment of groups of stereoisomers. The comparison of the differences between the calculated/experimental chemical shifts instead of the shifts themselves led to the advantage of avoiding errors arising from calibration procedures, reducing systematic errors, and highlighting the most diagnostic differences between calculated and experimental data. This methodology was applied on a tetrad of synthesized cladosporin stereoisomers (cladologs) and further corroborated on a tetrad of pochonicine stereoisomers, obtaining the correct correspondences between experimental and calculated sets of data. The new MAE(ΔΔδ) parameter, useful for indicating the best fit between sets of experimental and calculated data, is here introduced for facilitating the stereochemical assignment of groups of stereoisomers.
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spelling pubmed-79975812021-03-29 DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data Lauro, Gianluigi Das, Pronay Riccio, Raffaele Reddy, D. Srinivasa Bifulco, Giuseppe J Org Chem [Image: see text] Quantum mechanical/nuclear magnetic resonance (NMR) approaches are widely used for the configuration assignment of organic compounds generally comparing one cluster of experimentally determined data (e.g., (13)C NMR chemical shifts) with those predicted for all possible theoretical stereoisomers. More than one set of experimental data, each related to a specific stereoisomer, may occur in some cases, and the accurate stereoassignments can be obtained by combining the experimental and computed data. We introduce here a straightforward methodology based on the simultaneous analysis, combination, and comparison of all sets of experimental/calculated (13)C chemical shifts for aiding the correct configuration assignment of groups of stereoisomers. The comparison of the differences between the calculated/experimental chemical shifts instead of the shifts themselves led to the advantage of avoiding errors arising from calibration procedures, reducing systematic errors, and highlighting the most diagnostic differences between calculated and experimental data. This methodology was applied on a tetrad of synthesized cladosporin stereoisomers (cladologs) and further corroborated on a tetrad of pochonicine stereoisomers, obtaining the correct correspondences between experimental and calculated sets of data. The new MAE(ΔΔδ) parameter, useful for indicating the best fit between sets of experimental and calculated data, is here introduced for facilitating the stereochemical assignment of groups of stereoisomers. American Chemical Society 2020-01-21 2020-03-06 /pmc/articles/PMC7997581/ /pubmed/31961156 http://dx.doi.org/10.1021/acs.joc.9b03129 Text en Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Lauro, Gianluigi
Das, Pronay
Riccio, Raffaele
Reddy, D. Srinivasa
Bifulco, Giuseppe
DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data
title DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data
title_full DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data
title_fullStr DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data
title_full_unstemmed DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data
title_short DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data
title_sort dft/nmr approach for the configuration assignment of groups of stereoisomers by the combination and comparison of experimental and predicted sets of data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997581/
https://www.ncbi.nlm.nih.gov/pubmed/31961156
http://dx.doi.org/10.1021/acs.joc.9b03129
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