Minimizing the risk of deducing wrong natural product structures from NMR data

Burns, Darcy C.; Reynolds, William F.

doi:10.1002/mrc.4933

Cited by 26 publications

(23 citation statements)

References 136 publications

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“…It is interesting to observe that many errors in the literature are introduced by misinterpretation of the spectra obtained using state-of-the-art 2D-techniques. A leading role with respect to this effect, seems to be HMBC-type spectra showing frequent misinterpretations of 2 J (or 4 J)–couplings, as 3 J-couplings necessarily leading to incorrect structure proposals [ 25 ]. This kind of incorrect interpretation of 2D information is frequently preferred against the application of simple spectrum prediction, efficiently showing the inconsistency between the structure proposal and spectral data.…”

Section: Introductionmentioning

confidence: 99%

The Advantage of Automatic Peer-Reviewing of 13C-NMR Reference Data Using the CSEARCH-Protocol

Robien¹

2021

Molecules

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A systematic investigation of the experimental 13C-NMR spectra published in Molecules during the period of 1996 to 2015 with respect to their quality using CSEARCH-technology is described. It is shown that the systematic application of the CSEARCH-Robot-Referee during the peer-reviewing process prohibits at least the most trivial assignment errors and wrong structure proposals. In many cases, the correction of the assignments/chemical shift values is possible by manual inspection of the published tables; in certain cases, reprocessing of the original experimental data might help to clarify the situation, showing the urgent need for a public domain repository. A comparison of the significant key numbers derived for Molecules against those of other important journals in the field of natural product chemistry shows a quite similar level of quality for all publishers responsible for the six journals under investigation. From the results of this study, general rules for data handling, data storage, and manuscript preparation can be derived, helping to increase the quality of published NMR-data and making these data available as validated reference material.

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Section: Introductionmentioning

confidence: 99%

The Advantage of Automatic Peer-Reviewing of 13C-NMR Reference Data Using the CSEARCH-Protocol

Robien¹

2021

Molecules

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“…[1] Some authors, familiar with the contents of the original publication, have applied or quoted this correctly. [2][3][4][5][6][7] Unfortunately, the first easily located publication [8] using the term Crews' rule gives the critical H/C atom ratio as 2 rather than the value of 1 given in the original paper. This error has propagated through the literature [9][10][11][12][13][14][15][16][17][18] and continues to do so to this day.…”

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confidence: 99%

Crews' rule—Still useful but often misquoted

Sidebottom

2021

Magnetic Reson in Chemistry

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“…As an ES determines the structure of an unknown from the set of axioms adopted by the user, [46] another important problem arises-to educate chemists in how to use CASE tools more effectively and reliably when acquiring, processing, and interpreting NMR data used for structure elucidation. An open-access article by Burns and Reynolds [136] devoted to minimizing the risk of deducing wrong natural product structures from NMR data could be strongly recommended to chemists who use both CASE and a manual approach.…”

Section: Case As a Tool For Structure Revision Dereplication And Verificationmentioning

confidence: 99%

Computer Assisted Structure Elucidation (CASE): Current and future perspectives

Elyashberg¹,

Argyropoulos²

2020

Magnetic Reson in Chemistry

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The first efforts for the development of methods for Computer-Assisted Structure Elucidation (CASE) were published more than 50 years ago. CASE expert systems based on one-dimensional (1D) and two-dimensional (2D) Nuclear Magnetic Resonance (NMR) data have matured considerably by now. The structures of a great number of complex natural products have been elucidated and/or revised using such programs. In this article, we discuss the most likely directions in which CASE will evolve. We act on the premise that a synergistic interaction exists between CASE, new NMR experiments, and methods of computational chemistry, which are continuously being improved. The new developments in NMR experiments (long-range correlation experiments, pure-shift methods, coupling constants measurement and prediction, residual dipolar couplings [RDCs]), and residual chemical shift anisotropies [RCSAs], evolution of density functional theory (DFT), and machine learning algorithms will have an influence on CASE systems and vice versa. This is true also for new techniques for chemical analysis (Atomic Force Microscopy [AFM], "crystalline sponge" X-ray analysis, and micro-Electron Diffraction [micro-ED]), which will be used in combination with expert systems. We foresee that CASE will be utilized widely and become a routine tool for NMR spectroscopists and analysts in academic and industrial laboratories. We believe that the "golden age" of CASE is still in the future.

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Minimizing the risk of deducing wrong natural product structures from NMR data

Cited by 26 publications

References 136 publications

The Advantage of Automatic Peer-Reviewing of 13C-NMR Reference Data Using the CSEARCH-Protocol

The Advantage of Automatic Peer-Reviewing of 13C-NMR Reference Data Using the CSEARCH-Protocol

Crews' rule—Still useful but often misquoted

Computer Assisted Structure Elucidation (CASE): Current and future perspectives

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