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使用LSD软件进行小分子结构解析的教程。

Tutorial for the structure elucidation of small molecules by means of the LSD software.

作者信息

Nuzillard Jean-Marc, Plainchont Bertrand

机构信息

UMR CNRS 7312, University of Reims, Reims, France.

出版信息

Magn Reson Chem. 2018 Jun;56(6):458-468. doi: 10.1002/mrc.4612. Epub 2017 Jun 20.

DOI:10.1002/mrc.4612
PMID:28543725
Abstract

Automatic structure elucidation of small molecules by means of the "logic for structure elucidation" (LSD) software is introduced in the context of the automatic exploitation of chemical shift correlation data and with minimal input from chemical shift values. The first step in solving a structural problem by means of LSD is the extraction of pertinent data from the 1D and 2D spectra. This operation requires the labeling of the resonances and of their correlations; its reliability highly depends on the quality of the spectra. The combination of COSY, HSQC, and HMBC spectra results in proximity relationships between nonhydrogen atoms that are associated in order to build the possible solutions of a problem. A simple molecule, camphor, serves as an example for the writing of an LSD input file and to show how solution structures are obtained. An input file for LSD must contain a nonambiguous description of each atom, or atom status, which includes the chemical element symbol, the hybridization state, the number of bound hydrogen atoms and the formal electric charge. In case of atom status ambiguity, the pyLSD program performs clarification by systematically generating the status of the atoms. PyLSD also proposes the use of the nmrshiftdb algorithm in order to rank the solutions of a problem according to the quality of the fit between the experimental carbon-13 chemical shifts, and the ones predicted from the proposed structures. To conclude, some hints toward future uses and developments of computer-assisted structure elucidation by LSD are proposed.

摘要

借助“结构解析逻辑”(LSD)软件对小分子进行自动结构解析,是在自动利用化学位移相关数据且化学位移值输入最少的背景下展开的。利用LSD解决结构问题的第一步是从一维和二维光谱中提取相关数据。此操作需要对共振及其相关性进行标记;其可靠性高度依赖于光谱的质量。COSY、HSQC和HMBC光谱的结合产生了非氢原子之间的邻近关系,这些关系相互关联以构建问题的可能解决方案。一个简单的分子——樟脑,用作编写LSD输入文件的示例,并展示如何获得溶液结构。LSD的输入文件必须包含对每个原子或原子状态的明确描述,其中包括化学元素符号、杂化状态、结合氢原子的数量和形式电荷。在原子状态不明确的情况下,pyLSD程序通过系统地生成原子状态来进行澄清。PyLSD还建议使用nmrshiftdb算法,以便根据实验碳-13化学位移与从所提出结构预测的化学位移之间的拟合质量对问题的解决方案进行排序。最后,针对LSD在计算机辅助结构解析方面未来的应用和发展提出了一些建议。

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