Investigation of key pathogenic mechanisms and potential intervention targets of <i>Eucommia ulmoides</i> in the treatment of sarcopenia based on network pharmacology and molecular docking technology

<sec><strong>Objective</strong> This study aims to identify molecular targets and potential mechanisms of action of <i>Eucommia ulmoides</i> in the treatment of sarcopenia through network pharmacology and bioinformatics analysis. </sec><sec><strong>Methods</strong> The active components of <i>E. ulmoides</i> with a drug similarity score of ≥0.18 and an oral bioavailability of ≥30% were screened from the TCMSP platform, and the target genes of active compounds were determined from the DrugBank database. Using the lateral femoral muscle sample dataset GSE1428 from the GEO database, differentially expressed genes (DEGs) were identified using GEO2R with |logFC| &gt;0.5 and <i>p</i> &lt; 0.05 as the criteria, and candidate molecular targets were determined through Venn diagrams. Enrichment analyses of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were carried out. Protein–protein interaction (PPI) networks and transcription factor (TF)-DEG-miRNA networks were constructed using the STRING tool and DMNC algorithm to screen key genes. </sec><sec><strong>Results</strong> Twenty-eight active compounds of <i>E. ulmoides</i>, involving 217 genes, were identified in the TCMSP database. The Venn diagram presents 13 common genes. KEGG pathway analysis showed that differentially expressed genes (DEGs) were mainly enriched in multiple signaling pathways. Finally, the key module and key gene HSPB1 were determined through PPI network and TF-DEG-miRNA network analysis. Molecular docking showed that the affinity of HSPB1 with quercetin was –9.1, and the binding force was strong. </sec><sec><strong>Conclusions</strong> HSPB1 can be used as a novel predictive biomarker for sarcopenia. <i>E. ulmoides</i> may exert therapeutic effects on sarcopenia through targeting HSPB1 via multiple pathways. </sec>

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Journal
Aging Research
Published
2025-03-01
DOI
https://doi.org/10.26599/agr.2025.9340050
Primary Topic
Rheumatoid Arthritis Research and Therapies
Type
article
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article

Investigation of key pathogenic mechanisms and potential intervention targets of Eucommia ulmoides in the treatment of sarcopenia based on network pharmacology and molecular docking technology

Zhaoshi Bai, Lingxiang Chen, Siwen Liu, Qiang Wei et al.
Aging Research
Rheumatoid Arthritis Research and Therapies
article

Investigation of key pathogenic mechanisms and potential intervention targets of Eucommia ulmoides in the treatment of sarcopenia based on network pharmacology and molecular docking technology

Zhaoshi Bai, Lingxiang Chen, Siwen Liu, Qiang Wei, Yuejiao Zhong, Bin Zhou
article en

Abstract

<sec><strong>Objective</strong> This study aims to identify molecular targets and potential mechanisms of action of <i>Eucommia ulmoides</i> in the treatment of sarcopenia through network pharmacology and bioinformatics analysis. </sec><sec><strong>Methods</strong> The active components of <i>E. ulmoides</i> with a drug similarity score of ≥0.18 and an oral bioavailability of ≥30% were screened from the TCMSP platform, and the target genes of active compounds were determined from the DrugBank database. Using the lateral femoral muscle sample dataset GSE1428 from the GEO database, differentially expressed genes (DEGs) were identified using GEO2R with |logFC| &gt;0.5 and <i>p</i> &lt; 0.05 as the criteria, and candidate molecular targets were determined through Venn diagrams. Enrichment analyses of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were carried out. Protein–protein interaction (PPI) networks and transcription factor (TF)-DEG-miRNA networks were constructed using the STRING tool and DMNC algorithm to screen key genes. </sec><sec><strong>Results</strong> Twenty-eight active compounds of <i>E. ulmoides</i>, involving 217 genes, were identified in the TCMSP database. The Venn diagram presents 13 common genes. KEGG pathway analysis showed that differentially expressed genes (DEGs) were mainly enriched in multiple signaling pathways. Finally, the key module and key gene HSPB1 were determined through PPI network and TF-DEG-miRNA network analysis. Molecular docking showed that the affinity of HSPB1 with quercetin was –9.1, and the binding force was strong. </sec><sec><strong>Conclusions</strong> HSPB1 can be used as a novel predictive biomarker for sarcopenia. <i>E. ulmoides</i> may exert therapeutic effects on sarcopenia through targeting HSPB1 via multiple pathways. </sec>

Aging ResearchVol. 3(1)
Jiangsu Cancer Hospital (CN)
Openalex Percentile: Top 55%
Rheumatoid Arthritis Research and Therapies
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