Lauro, Gianluigi ; Das, Pronay ; Riccio, Raffaele ; Reddy, D. Srinivasa ; Bifulco, Giuseppe (2020) DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data Journal of Organic Chemistry, 85 (5). pp. 3297-3306. ISSN 0022-3263
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Official URL: http://doi.org/10.1021/acs.joc.9b03129
Related URL: http://dx.doi.org/10.1021/acs.joc.9b03129
Abstract
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., 13C 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 13C 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 MAEΔΔδ 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
Item Type: | Article |
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Source: | Copyright of this article belongs to American Chemical Society |
ID Code: | 121810 |
Deposited On: | 22 Jul 2021 09:24 |
Last Modified: | 22 Jul 2021 09:24 |
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