Evidence map›Paper›PMID 37438485›Full record

ArticleCommunications chemistry2023

Impact of conformation and intramolecular interactions on vibrational circular dichroism spectra identified with machine learning.

Tom Vermeyen, Ana Cunha, Patrick Bultinck, Wouter Herrebout

Abstract read
In one paragraph

Article in Communications chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Induced Chirality and Vibrational Optical Activity in an Ionic-Liquid Anion.Angewandte Chemie (International ed. in English) · 2025
    Article
  3. 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

4 authors.

Tom VermeyenDepartment of Chemistry, University of Antwerp, Groenenborgerlaan 171, Antwerpen, 2020, Belgium. tom.vermeyen@uantwerpen.be.ORCID http://orcid.org/0000-0001-6049-2623
Ana CunhaDepartment of Chemistry, University of Antwerp, Groenenborgerlaan 171, Antwerpen, 2020, Belgium.ORCID http://orcid.org/0000-0001-8996-2860
Patrick BultinckDepartment of Chemistry, Ghent University, Krijgslaan 281, Gent, 9000, Belgium. patrick.bultinck@ugent.be.ORCID http://orcid.org/0000-0003-2766-2672
Wouter HerreboutDepartment of Chemistry, University of Antwerp, Groenenborgerlaan 171, Antwerpen, 2020, Belgium.ORCID http://orcid.org/0000-0002-3167-8944

Funding

Fonds Wetenschappelijk Onderzoek (Research Foundation Flanders) 1160419N
6 · The paper itself

Abstract

Vibrational Circular Dichroism (VCD) spectra often differ strongly from one conformer to another, even within the same absolute configuration of a molecule. Simulated molecular VCD spectra typically require expensive quantum chemical calculations for all conformers to generate a Boltzmann averaged total spectrum. This paper reports whether machine learning (ML) can partly replace these quantum chemical calculations by capturing the intricate connection between a conformer geometry and its VCD spectrum. Three hypotheses concerning the added value of ML are tested. First, it is shown that for a single stereoisomer, ML can predict the VCD spectrum of a conformer from solely the conformer geometry. Second, it is found that the ML approach results in important time savings. Third, the ML model produced is unfortunately hardly transferable from one stereoisomer to another.

Identifiers

PMID37438485
PMCPMC10338531

What OpenQuestion holds

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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.