Evidence map›Paper›PMID 38784459›Full record

ArticleRSC medicinal chemistry2024

Structure-based virtual screening of unbiased and RNA-focused libraries to identify new ligands for the HCV IRES model system.

Elisabeth Kallert, Laura Almena Rodriguez, Jan-Åke Husmann, Kathrin Blatt, Christian Kersten

Abstract read
In one paragraph

Article in RSC medicinal chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Comparative Evaluation of Explicit Solvent Models for RNA-Ligand Docking.Journal of chemical information and modeling · 2026
    Article
  2. Article
  3. Article
  4. 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

5 authors.

Elisabeth KallertInstitute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany kerstec@uni-mainz.de.ORCID https://orcid.org/0009-0005-3209-0375
Laura Almena RodriguezInstitute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany kerstec@uni-mainz.de.ORCID https://orcid.org/0009-0007-8602-9603
Jan-Åke HusmannInstitute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany kerstec@uni-mainz.de.ORCID https://orcid.org/0009-0007-9978-4587
Kathrin BlattInstitute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany kerstec@uni-mainz.de.ORCID https://orcid.org/0009-0005-0203-2019
Christian KerstenInstitute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Staudingerweg 5 55128 Mainz Germany kerstec@uni-mainz.de.ORCID https://orcid.org/0000-0001-9976-7639

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Targeting RNA including viral RNAs with small molecules is an emerging field. The hepatitis C virus internal ribosome entry site (HCV IRES) is a potential target for translation inhibitor development to raise drug resistance mutation preparedness. Using RNA-focused and unbiased molecule libraries, a structure-based virtual screening (VS) by molecular docking and pharmacophore analysis was performed against the HCV IRES subdomain IIa. VS hits were validated by a microscale thermophoresis (MST) binding assay and a Förster resonance energy transfer (FRET) assay elucidating ligand-induced conformational changes. Ten hit molecules were identified with potencies in the high to medium micromolar range proving the suitability of structure-based virtual screenings against RNA-targets. Hit compounds from a 2-guanidino-quinazoline series, like the strongest binder, compound 8b with an EC

Identifiers

PMID38784459
PMCPMC11110755

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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.