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

Abstract

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.

Ecological and Pharmacological Activities of Polybrominated Diphenyl Ethers (PBDEs) from the Indonesian Marine Sponge Lamellodysidea herbacea

“…The carbon atoms C-3 to C-6 were not explicitly assigned for the prediction of the constitutional isomers 1a to 1c due to very similar 13 The averaged deviation of δ( 13 C) for all 12 carbon atoms to the calculated and existing experimental data sets in comparison to our experimental values is given in Figure 5. The results showed that the mean value of 1d was close to the experimental shifts reported for 1d in the literature [49] (Figure 5, bars 6 to 10). Comparison to the calculated values obtained with NMRPredict also preferred constitutional proposals 1d (<1 ppm) over the regioisomers 1a to 1c (>2 ppm).…”

“…In order to elucidate the correct regioisomers, the 1 H and 13 C NMR data were compared to existing NMR data in the literature (Tables 3 and 4). Furthermore, the structures of 1d and 2b were also verified through comparison with predicted 13 C NMR chemical shifts [43][44][45][46] using three different computational approaches: NMRPredict [47], NMRShiftDB [48], and CSEARCH [49]. The 13 C chemical shifts of compound 1d (this work) were compared to predicted values and literature data (the atom numbering of Bowden et al, 2000 [50] was used for all literature data).…”

Taxonomy-Focused Natural Product Databases for Carbon-13 NMR-Based Dereplication

“…Dereplication relies on the comparison between freshly collected spectroscopic data with those from previous studies and stored in a DB. The extraction of experimental MS and NMR data from publications is a tedious process that may result in copy errors and in the exact copy of erroneous structure or data assignments [17]. However, the accumulated knowledge gained of the relationships between molecular structures and measurement outcomes has made it possible to design spectroscopic prediction tools that may replace, to some extent, experimental spectral data by predicted ones [10,18].…”

Sampling CASE Application for the Quality Control of Published Natural Product Structures

“…The methods used can roughly be divided into stochastic (S), deterministic (D), and hybrid (H), with hybrid representing various different combinations of stochastic and deterministic methods. The most prominent methods are fragment assemblers (H) [1][2][3][4][5][6], expert systems (H) [7][8][9], databases of 13 C NMR chemical shifts or neural networks (S) [10][11][12][13], structure generation by reduction (S/H) [14], logic engines (D) [15], stochastic structure generators (S) [16], combinatorial brute force (D) [17][18][19][20][21], combinatorial brute force with restraints (D/H) [22,23], genetic algorithms (S) [24][25][26], simulated annealing (S) [27], convergent structure generation (S) [28,29], evolutionary algorithm (S) [30], fuzzy structure generation (S) [31], and expert systems with DFT (H) [32]. Altogether, 14 different methods were implemented in more than 20 different tools, some of which are freely usable, and many of them have not seen further development by their authors after the first publication.…”

“…Despite of all these efforts, none of these tools has become popular enough to be used for quality control of published structures by a wider community of researchers or journal editors. The 13 C chemical shift-based tools have an outstanding position in this list, as they do not take NMR correlation data into account. They can either map chemical shifts to chemical neighborhoods, which in turn are assembled into a proposed constitution, or determine chemical neighborhoods for each carbon of a proposed constitution and predict a chemical shift.…”