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基于理论 NMR 相关的结构讨论。

Theoretical NMR correlations based Structure Discussion.

机构信息

Fundaçã Oswaldo Cruz - CDTS, Rio de Janeiro - RJ, Brazil.

出版信息

J Cheminform. 2011 Jul 28;3:27. doi: 10.1186/1758-2946-3-27.

Abstract

The constitutional assignment of natural products by NMR spectroscopy is usually based on 2D NMR experiments like COSY, HSQC, and HMBC. The actual difficulty of the structure elucidation problem depends more on the type of the investigated molecule than on its size. The moment HMBC data is involved in the process or a large number of heteroatoms is present, a possibility of multiple solutions fitting the same data set exists. A structure elucidation software can be used to find such alternative constitutional assignments and help in the discussion in order to find the correct solution. But this is rarely done. This article describes the use of theoretical NMR correlation data in the structure elucidation process with WEBCOCON, not for the initial constitutional assignments, but to define how well a suggested molecule could have been described by NMR correlation data. The results of this analysis can be used to decide on further steps needed to assure the correctness of the structural assignment. As first step the analysis of the deviation of carbon chemical shifts is performed, comparing chemical shifts predicted for each possible solution with the experimental data. The application of this technique to three well known compounds is shown. Using NMR correlation data alone for the description of the constitutions is not always enough, even when including 13C chemical shift prediction.

摘要

通过 NMR 光谱对天然产物进行结构解析通常基于二维 NMR 实验,如 COSY、HSQC 和 HMBC。结构解析问题的实际难度更多地取决于所研究分子的类型,而不是其大小。当涉及 HMBC 数据或存在大量杂原子时,可能会存在多个符合相同数据集的解决方案。结构解析软件可用于找到这些替代结构分配,并帮助进行讨论以找到正确的解决方案。但这种情况很少发生。本文描述了在结构解析过程中使用 WEBCOCON 的理论 NMR 相关数据,而不是用于初始结构分配,而是用于定义 NMR 相关数据可以如何很好地描述建议的分子。该分析的结果可用于决定需要采取哪些进一步的步骤来确保结构分配的正确性。作为第一步,对碳化学位移的偏差进行分析,将每种可能解决方案的预测化学位移与实验数据进行比较。展示了该技术在三个知名化合物中的应用。仅使用 NMR 相关数据来描述结构并不总是足够的,即使包括 13C 化学位移预测也是如此。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57fb/3162559/e02a536fb7e8/1758-2946-3-27-1.jpg

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