Evidence map›Paper›PMID 42346097›Full record

ArticleCells2026

Structure-Based Virtual Screening and Mechanistic Characterization of Methotrexate and Selinexor as Potent Anti-Melanogenic Agents via Multi-Pathway Suppression of MITF.

Zhongwei Zhang, Huiran Li, Zhonglan Shi, Xuan Bai, Peipei Yin, Lingguang Yang

Abstract read
In one paragraph

Article in Cells, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Zhongwei ZhangJiangxi Key Laboratory of Natural Microbial Medicine Research, School of Pharmacy, Yichun University, Yichun 336000, China.
Huiran LiJiangxi Key Laboratory of Natural Microbial Medicine Research, School of Pharmacy, Yichun University, Yichun 336000, China.
Zhonglan ShiJiangxi Key Laboratory of Natural Microbial Medicine Research, School of Pharmacy, Yichun University, Yichun 336000, China.
Xuan BaiJiangxi Key Laboratory of Natural Microbial Medicine Research, School of Pharmacy, Yichun University, Yichun 336000, China.
Peipei YinJiangxi Key Laboratory of Natural Microbial Medicine Research, School of Pharmacy, Yichun University, Yichun 336000, China.
Lingguang YangJiangxi Key Laboratory of Natural Microbial Medicine Research, School of Pharmacy, Yichun University, Yichun 336000, China.ORCID 0000-0002-0584-0178

Funding

Graduate Innovation Special Fund Project of Jiangxi Province YC2025-S807Jiangxi Province Major Discipline Academic and Technical Leaders Training Project 20243BCE51140Key Research and Development Project of Yichun City, Jiangxi Province 2024ZDYFJH01National Natural Science Foundation of China 32560225Natural Science Foundation of Jiangxi Province 20242BAB20270
6 · The paper itself

Abstract

Tyrosinase is a pivotal therapeutic target for hyperpigmentation disorders, yet current inhibitors frequently exhibit limited potency and suboptimal safety. Here, we employed structure-based virtual screening of an FDA-approved drug library against a refined human tyrosinase homology model, identifying methotrexate and selinexor as potent anti-melanogenic candidates. Both compounds markedly suppressed cellular tyrosinase activity and melanin synthesis (IC

Indexed as

MethotrexateMicrophthalmia-Associated Transcription FactorTriazolesCell Line, TumorCyclic AMPDrug Evaluation, PreclinicalHumansMelaninsMelanogenesisMonophenol MonooxygenaseSignal TransductionCyclic AMPMelaninsMethotrexateMicrophthalmia-Associated Transcription FactorMITF protein, humanMonophenol MonooxygenaseTriazolesdrug repurposingmelanogenesisMITFtyrosinase inhibitorvirtual screening

Identifiers

PMID42346097
PMCPMC13296867

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.