Evidence map›Paper›PMID 39833227›Full record

ArticleScientific reports2025

Identification of dequalinium as a potent inhibitor of human organic cation transporter 2 by machine learning based QSAR model.

Fumihiro Yamane, Kenji Ikemura, Masayoshi Kondo, Manami Ueno, Masahiro Okuda

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Fumihiro YamaneDepartment of Hospital Pharmacy, School of Pharmaceutical Sciences, Osaka University, Suita, Osaka, 565-0871, Japan.
Kenji IkemuraDepartment of Pharmacy, Osaka University Hospital, 2-15 Yamadaoka, Suita, Osaka, 565-0871, Japan. ikemurak@hp-drug.med.osaka-u.ac.jp.
Masayoshi KondoDepartment of Hospital Pharmacy, School of Pharmaceutical Sciences, Osaka University, Suita, Osaka, 565-0871, Japan.
Manami UenoDepartment of Hospital Pharmacy, School of Pharmaceutical Sciences, Osaka University, Suita, Osaka, 565-0871, Japan.
Masahiro OkudaDepartment of Pharmacy, Osaka University Hospital, 2-15 Yamadaoka, Suita, Osaka, 565-0871, Japan.

Funding

Japan Society for the Promotion of Science 24K09958
6 · The paper itself

Abstract

Human organic cation transporter 2 (hOCT2/SLC22A2) is a key drug transporter that facilitates the transport of endogenous and exogenous organic cations. Because hOCT2 is responsible for the development of adverse effects caused by platinum-based anti-cancer agents, drugs with OCT2 inhibitory effects may serve as prophylactic agents against the toxicity of platinum-based anti-cancer agents. In the present study, we established a machine learning-based quantitative structure-activity relationship (QSAR) model for hOCT2 inhibitors based on the public ChEMBL database and explored novel hOCT2 inhibitors among the FDA-approved drugs. Using our QSAR model, we identified 162 candidate hOCT2 inhibitors among the FDA-approved drugs registered in the DrugBank database. After manual selection and in vitro assays, we found that dequalinium, a quaternary ammonium cation antimicrobial agent, is a potent hOCT2 inhibitor (IC

Indexed as

DequaliniumMachine LearningOrganic Cation Transporter 2Quantitative Structure-Activity RelationshipAntineoplastic AgentsCisplatinHumansOxaliplatinAntineoplastic AgentsCisplatinDequaliniumOrganic Cation Transporter 2OxaliplatinSLC22A2 protein, humanDequaliniumDrug repositioningMachine learningOrganic cation transporter 2Quantitative structure-activity relationship

Identifiers

PMID39833227
PMCPMC11746930

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.