Evidence map›Paper›PMID 42243247›Full record

ArticleScientific reports2026

Mechanism of Artemisia annua active component quercetin in treating psoriasis by regulating ferroptosis.

Ke Xu, Fangrong Liu, Min Li, Yuntong Wang, Fengming Hu, Jian Gong, Xiongfei Ding

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

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ke Xu *Dermatology Hospital of Jiangxi Province, Nanchang, 330001, Jiangxi, China.
Fangrong Liu *Jiangxi University of Chinese Medicine, Nanchang, 330004, Jiangxi, China.
Min LiThe Fifth People's Hospital of Hainan Province, Haikou, 570206, Hainan, China.
Yuntong WangYiwu Traditional Chinese Medicine Hospital, Jinhua, 322000, Zhejiang, China.
Fengming HuDermatology Hospital of Jiangxi Province, Nanchang, 330001, Jiangxi, China.
Jian GongDermatology Hospital of Jiangxi Province, Nanchang, 330001, Jiangxi, China. 360189641@qq.com.
Xiongfei DingDermatology Hospital of Jiangxi Province, Nanchang, 330001, Jiangxi, China. 944689845@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to investigate the mechanism by which active components of Artemisia annua modulate ferroptosis in the treatment of psoriasis vulgaris through an integrated approach combining network pharmacology, molecular docking, and in vivo validation. Therapeutic targets of Artemisia annua active components and psoriasis vulgaris-related genes were retrieved from the TCMSP and GeneCards databases, respectively. Common targets were identified using Venn analysis. Protein-protein interaction (PPI) networks were constructed using Cytoscape, with core targets extracted via the CytoHubba plugin. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. Ferroptosis-related genes were acquired from the FerrDb database. Molecular docking assessed the binding affinity between key active components and critical targets. In vivo experiments using an imiquimod (IMQ)-induced psoriasis-like mouse model were conducted to validate the network pharmacology predictions. Network pharmacology identified 22 active components of Artemisia annua, 202 potential targets, and 1,312 psoriasis-related genes, yielding 96 common targets. Further analysis revealed 485 ferroptosis-related genes, with 26 overlapping targets associated with 17 active components. PPI network analysis indicated TP53(P53), IL6, and IL1B as core targets. Quercetin, kaempferol, and luteolin were identified as the primary active components. Molecular docking demonstrated strong binding affinity between quercetin and TP53(P53). In vivo experiments showed that quercetin significantly alleviated psoriatic-like skin lesions, increased epidermal glutathione (GSH) levels, reduced Fe²⁺ accumulation and reactive oxygen species (ROS) production, and improved mitochondrial morphology. Furthermore, quercetin downregulated the protein and mRNA expression of P53, SAT1, and ALOX15. This study demonstrates that quercetin is the major active component of Artemisia annua responsible for mediating epidermal ferroptosis in psoriasis treatment. Experimental results indicate that quercetin alleviates the inflammatory response in psoriasis by inhibiting epidermal ferroptosis, a process that may be associated with the regulation of the P53/SAT1/ALOX15 signaling pathway.

Indexed as

Artemisia annuaFerroptosisPsoriasisQuercetinAnimalsDisease Models, AnimalHumansImiquimodMiceMolecular Docking SimulationNetwork PharmacologyProtein Interaction MapsImiquimodQuercetinArtemisia annuaFerroptosisNetwork pharmacologyP53/SAT1/ALOX15 pathwayPsoriasisQuercetin

Identifiers

PMID42243247
PMCPMC13478214

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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.