Department of Pharmacy, University of Salerno, Via Giovanni Paolo II 132, Fisciano 84084, Italy.
Organic Chemistry Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India.
J Org Chem. 2020 Mar 6;85(5):3297-3306. doi: 10.1021/acs.joc.9b03129. Epub 2020 Feb 4.
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., 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 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 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.
量子力学/核磁共振(NMR)方法广泛用于有机化合物的构型分配,通常将一组实验确定的数据(例如,C NMR 化学位移)与所有可能的理论立体异构体的预测值进行比较。在某些情况下,可能会出现多组与特定立体异构体相关的实验数据,并且可以通过组合实验和计算数据来获得准确的立体构型分配。我们在这里介绍了一种基于同时分析、组合和比较所有组实验/计算 C 化学位移的简单方法,以帮助正确分配立体异构体组的构型。比较计算/实验化学位移之间的差异而不是化学位移本身,具有避免校准程序引起的误差、减少系统误差和突出计算数据与实验数据之间最具诊断性差异的优势。该方法应用于一组合成的 cladosporin 立体异构体(cladologs),并进一步在一组 pochonicine 立体异构体上得到验证,在实验数据和计算数据之间获得了正确的对应关系。我们在这里引入了新的 MAE 参数,用于指示实验和计算数据集之间的最佳拟合,以促进立体异构体组的立体化学分配。