Literature DB >> 28194563

A Critical Evaluation of the Quality of Published 13C NMR Data in Natural Product Chemistry.

Wolfgang Robien1.   

Abstract

Nuclear Magnetic Resonance spectroscopy contributes very efficiently to the structure elucidation process in organic chemistry. Carbon-13 NMR spectroscopy allows direct insight into the skeleton of organic compounds and therefore plays a central role in the structural assignment of natural products. Despite this important contribution, there is no established and well-accepted workflow protocol utilized during the first steps of interpreting spectroscopic data and converting them into structural fragments and then combining them, by considering the given spectroscopic constraints, into a final proposal of structure. The so-called "combinatorial explosion" in the process of structure generation allows in many cases the generation of reasonable alternatives, which are usually ignored during manual interpretation of the measured data leading ultimately to a large number of structural revisions. Furthermore, even when the determined structure is correct, problems may exist such as assignment errors, ignoring chemical shift values, or assigning lines of impurities to the compound under consideration. An extremely large heterogeneity in the presentation of carbon NMR data can be observed, but, as a result of the efficiency and precision of spectrum prediction, the published data can be analyzed in substantial detail.This contribution presents a comprehensive analysis of frequently occurring errors with respect to 13C NMR spectroscopic data and proposes a straightforward protocol to eliminate a high percentage of the most obvious errors. The procedure discussed can be integrated readily into the processes of submission and peer-reviewing of manuscripts.

Entities:  

Keywords:  13C-NMR/Carbon NMR; Computer-assisted structure elucidation; Isomer generation; Nuclear Magnetic Resonance spectroscopy; Peer-reviewing; Quality of spectroscopic data; Signal assignment; Spectrum prediction; Structure generation; Structure revision

Mesh:

Substances:

Year:  2017        PMID: 28194563     DOI: 10.1007/978-3-319-49712-9_3

Source DB:  PubMed          Journal:  Prog Chem Org Nat Prod        ISSN: 0071-7886


  4 in total

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Review 3.  The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research.

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Journal:  Nat Prod Rep       Date:  2018-07-13       Impact factor: 13.423

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Authors:  Sonja L Knowles; Ngoc Vu; Daniel A Todd; Huzefa A Raja; Antonis Rokas; Qibin Zhang; Nicholas H Oberlies
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  4 in total

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