Evidence map›Paper›PMID 32364661›Full record

ArticleAngewandte Chemie (International ed. in English)2020

Magnetically Induced Alignment of Natural Products for Stereochemical Structure Determination via NMR.

Niels Karschin, Klaus Wolkenstein, Christian Griesinger

Abstract read
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
  2. Theory of Field-Dependent NMR Shifts in Paramagnetic Molecules.Journal of chemical theory and computation · 2025
    Article
  3. Benchmark of Density Functional Theory in the Prediction ofJournal of chemical theory and computation · 2025
    Article
  4. Review
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Niels KarschinDepartment for NMR-based Structural Biology, Max-Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077, Göttingen, Germany.ORCID 0000-0002-5890-8842
Klaus WolkensteinDepartment for NMR-based Structural Biology, Max-Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077, Göttingen, Germany.ORCID 0000-0003-0944-6247
Christian GriesingerDepartment for NMR-based Structural Biology, Max-Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077, Göttingen, Germany.ORCID 0000-0002-1266-4344

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anisotropic NMR has gained increasing popularity to determine the structure and specifically the configuration of small, flexible, non-crystallizable molecules. However, it suffers from the necessity to dissolve the analyte in special media such as liquid crystals or polymer gels. Generally, small degrees of alignment are also caused by an anisotropic magnetic susceptibility of the molecule, for example, induced by aromatic moieties. For this mechanism, the alignment can be predicted via density functional theory. Here we show that both residual dipolar couplings and residual chemical shift anisotropies can be acquired from natural products without special sample preparation using magnetically induced alignment. On the two examples of the novel natural product gymnochrome G and the alkaloid strychnine, these data, together with the predicted alignment, yield the correct configuration with high certainty.

Indexed as

MagneticsAnisotropyBiological ProductsMagnetic Resonance SpectroscopyStereoisomerismBiological Productsanisotropic NMR parametersconfiguration determinationdensity functional calculationsmagnetically induced alignmentNMR spectroscopy

Identifiers

PMID32364661
PMCPMC7540557

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.