This study aims to identify molecular targets and potential mechanisms of action of Eucommia ulmoides in the treatment of sarcopenia through network pharmacology and bioinformatics analysis.

The active components of E. ulmoides 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| >0.5 and p < 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.

Twenty-eight active compounds of E. ulmoides, 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.

HSPB1 can be used as a novel predictive biomarker for sarcopenia. E. ulmoides may exert therapeutic effects on sarcopenia through targeting HSPB1 via multiple pathways.