Evidence map›Paper›PMID 41778031›Full record

ArticleFrontiers in medicine2026

Network pharmacology, machine learning, and experiments uncover β-sitosterol targeting HSP90AA1 in medicinal-edible black soybean against aging.

Yuanyuan Jia, Jingyi Yang, Qian Chen, Yuting Yang, Wei Min, Dan Luo

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Article in Frontiers in medicine, 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

6 authors.

Yuanyuan Jia *Department of Dermatology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.
Jingyi Yang *Department of Dermatology, Kunshan First People's Hospital, Suzhou, Jiangsu, China.
Qian ChenDepartment of Dermatology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.
Yuting YangDepartment of Dermatology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.
Wei MinDepartment of Dermatology, Kunshan First People's Hospital, Suzhou, Jiangsu, China.
Dan LuoDepartment of Dermatology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Aging involves progressive dysregulation of cellular homeostasis, while current anti-aging agents face limitations in specificity and safety. Black soybean, a medicinal-edible substance, contains various bioactive compounds. This study aims to investigate the anti-aging mechanism of its key component, β-sitosterol, through integrated network pharmacology and machine learning. Methods: Active components and targets of black soybean were acquired from the TCMSP database, while aging-associated genes were obtained from the GeneCards, TTD, and OMIM databases. Venn analysis was applied to intersect the targets. A protein-protein interaction (PPI) network was constructed using the STRING database and visualized with Cytoscape software to identify core targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted via Metascape. A triple-machine-learning strategy (SVM-RFE, RF, LASSO) was employed to further prioritize key targets. Molecular docking was performed to predict the binding affinities. The core targets and mechanisms were validated through Results: Bioinformatics analysis identified 63 overlapping targets between the corresponding targets of black soybean components and aging-associated genes, with protein-protein interaction networks prioritizing HSP90AA1 and BCL2 as core regulators. Molecular docking confirmed β-sitosterol's high-affinity binding to HSP90AA1, primarily through hydrogen bond interactions with the key amino acid residue ILE-214 within its 9-236 region, which is the functional domain responsible for client protein interaction. Experimental validation in cellular models demonstrated β-sitosterol attenuated photoaging markers, restored cell cycle arrest, and enhanced antioxidant defenses. Mechanistically, β-sitosterol upregulated HSP90AA1 expression to stabilize apoptotic regulators (BCL2, p53) and mitigate oxidative damage. Inhibition of HSP90AA1 abolished these effects, establishing its pivotal role. Conclusion: This work reveals that β-sitosterol, a core component of black soybean, combats skin photoaging by targeting the HSP90AA1-mediated stress adaptation and regulating the p53-BCL2 signaling axis. These findings provide a molecular basis for the application of this medicinal-edible substance in anti-aging interventions.

Indexed as

agingblack soybeanHSP90AA1machine learningnetwork pharmacologyβ-sitosterol

Identifiers

PMID41778031
PMCPMC12950797

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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.