Evidence map›Paper›PMID 42491949›Full record

ArticlePeerJ2026

Integrated network pharmacology and bioinformatics analysis reveals multi-target mechanisms of HeJie Shengfa Decoction against alopecia areata.

Lingling Zhao, Haixia Mi, Zhaokun Diao, Aikeda Tiemuer, Limin Mou, Jingxuan Yang, Lingmeng Zuo, Chenghui Zhang

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Article in PeerJ, 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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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Lingling Zhao *The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China.
Haixia Mi *Wenzhou People's Hospital (The Wenzhou Third Clinical Institute Affiliated To Wenzhou Medical University), Wenzhou, Zhejiang, China.
Zhaokun DiaoThe Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China.
Aikeda TiemuerThe Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China.
Limin MouThe Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China.
Jingxuan YangThe Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China.
Lingmeng ZuoThe Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China.
Chenghui ZhangXinjiang Uygur Autonomous Region Hospital of Traditional Chinese Medicine, Urumqi, Xinjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Alopecia areata (AA) is a common non-scarring autoimmune disease with a complex pathogenesis, high recurrence rates, and difficulty in achieving a cure. Recent years have seen an increasing focus on both clinical and basic research regarding AA. Hejie Shengfa Decoction (HSD), a traditional Chinese medicine formula, has shown certain efficacy in the clinical treatment of AA, though its underlying mechanisms remain unclear. Methods: In this study, we retrieved the active ingredients of HSD and their associated targets from public databases. We then identified AA-related targets through bioinformatics analysis of publicly available AA datasets. A protein-protein interaction (PPI) network was constructed to generate the HSD-AA action network by integrating drug-specific targets and disease-related targets. Functional enrichment analysis was subsequently performed. To further investigate key genes, three machine learning algorithms-least absolute shrinkage and selection operator (LASSO) regression, support vector machine-recursive feature elimination (SVM-RFE), and Random Forest-were applied Additionally, immune cell infiltration analysis was carried out to examine the roles of these key genes in the local immune microenvironment. Molecular docking and molecular dynamics simulations were employed to assess the binding stability of the active ingredients with the core targets. Results: The results revealed that HSD contains 96 active ingredients and 985 related targets. From the AA dataset, 955 differentially expressed genes and 492 co-expressed modular genes were identified, resulting in 23 intersecting genes after integration. Machine learning algorithms identified four key target genes among these 23. Immune infiltration analysis suggested that HSD could influence the immune microenvironment of AA by modulating the expression of these key targets. Molecular docking and molecular dynamics simulations confirmed strong and stable binding interactions between HSD's main active ingredients-especially quercetin-and the core targets. Conclusion: This study elucidates the potential of HSD as a treatment for AA and provides insights into its mechanisms of action, offering a novel approach for treating AA with multi-targeted traditional Chinese medicine.

Indexed as

Alopecia AreataComputational BiologyDrugs, Chinese HerbalNetwork PharmacologyHumansMolecular Docking SimulationMolecular Dynamics SimulationProtein Interaction MapsDrugs, Chinese HerbalAlopecia areataBioinformaticsHejie Shengfa decoctionNetwork pharmacologyTraditional Chinese medicine

Identifiers

PMID42491949
PMCPMC13378497

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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.