Evidence map›Paper›PMID 38772711›Full record

ReviewJournal of separation science2024

Update on chiral recognition mechanisms in separation science.

Gerhard K E Scriba

Abstract readReview
In one paragraph

Review in Journal of separation science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Cyclodextrins as Chiral Selectors in Capillary Electromigration Techniques.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  6. Recognition Mechanisms of Chiral Selectors: An Overview.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
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

1 author.

Gerhard K E ScribaDepartment of Pharmaceutical/Medicinal Chemistry, Friedrich Schiller University, Jena, Germany.ORCID https://orcid.org/0000-0003-2950-060X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The stereospecific analysis of chiral molecules is an important issue in many scientific fields. In separation sciences, this is achieved via the formation of transient diastereomeric complexes between a chiral selector and the selectand enantiomers driven by molecular interactions including electrostatic, ion-dipole, dipole-dipole, van der Waals or π-π interactions as well as hydrogen or halogen bonds depending on the nature of selector and selectand. Nuclear magnetic resonance spectroscopy and molecular modeling methods are currently the most frequently applied techniques to understand the selector-selectand interactions at a molecular level and to draw conclusions on the chiral separation mechanism. The present short review summarizes some of the recent achievements for the understanding of the chiral recognition of the most important chiral selectors combining separation techniques with molecular modeling and/or spectroscopic techniques dating between 2020 and early 2024. The selectors include polysaccharide derivatives, cyclodextrins, macrocyclic glycopeptides, proteins, donor-acceptor type selectors, ion-exchangers, crown ethers, and molecular micelles. The application of chiral ionic liquids and chiral deep eutectic solvents, as well as further selectors, are also briefly addressed. A compilation of all published literature on chiral selectors has not been attempted.

Indexed as

analytical enantioseparationchiral recognition mechanismchiral selectorcomplexation

Identifiers

PMID38772711
PMCPMC12964351

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.