Objective To identify the potential molecular mechanisms mediating the role of Lycium barbarum polysaccharides (LBPs) in optic nerve regeneration (ONR) through an integrated approach that combines network pharmacology, single-cell RNA sequencing, and molecular docking.

Methods The monosaccharide composition of LBPs was systematically characterized, and potential target genes of each LBPs component were predicted using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), SwissTargetPrediction, and SuperPred databases. Disease-related targets associated with ONR were retrieved from the Online Mendelian Inheritance in Man (OMIM) and GeneCards databases. A protein-protein interaction (PPI) network of the overlapping targets was established via the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and a “drug-disease-target” regulatory network was constructed using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the Metascape platform to elucidate the potential signaling pathways through which LBPs mediate ONR. Seurat software was used to analyze mouse retinal single-cell RNA sequencing data (GSE137398) retrieved from the Gene Expression Omnibus (GEO) database to evaluate the expression distribution and cellular heterogeneity of the core PPI network targets across different retinal cell clusters. Molecular docking analysis was performed to verify the binding affinity between the core monosaccharide components of LBPs and the key regulatory targets identified from the PPI network.

Results A total of 329 predicted targets associated with LBPs monosaccharide components and 8 930 ONR-related targets were identified, yielding 272 overlapping targets. PPI network analysis identified heat shock protein 90 α family class A member 1 (HSP90AA1), heat shock protein 90 α family class B member 1 (HSP90AB1), mitogen-activated protein kinase 3 (MAPK3), hypoxia-inducible factor 1 subunit alpha (HIF1A), nuclear factor kappa B subunit 1 (NFKB1), and mechanistic target of rapamycin kinase (MTOR) as the top six core targets ranked by degree value. Drug-disease-target network topology analysis indicated that xylose, α-L-arabinose, β-D-glucosamine, galactose, and α-D-mannose were the top five principal monosaccharide components with the highest connectivity. GO enrichment analysis showed that the overlapping targets were mainly involved in positive regulation of the extracellular signal-regulated kinase 1/2 (ERK1/2) cascade, positive regulation of MAPK activity, cellular response to hypoxia, negative regulation of inflammatory response, and cytosolic calcium ion release. KEGG analysis demonstrated significant enrichment in the HIF-1, neurotrophin, MAPK, phosphoinositide 3-kinase-protein kinase B (PI3K-Akt), calcium, cyclic adenosine monophosphate (cAMP), rat sarcoma virus (Ras), sphingolipid, and relaxin signaling pathways. Single-cell transcriptomic analysis revealed distinct expression patterns of the six core targets across retinal ganglion cell (RGC) subpopulations, with Hsp90aa1 and Hsp90ab1 broadly expressed, whereas Mapk3 and Hif1a exhibited relatively enriched expression in specific clusters. Molecular docking between the five core monosaccharide components and the six core targets showed binding energies ranging from − 4.3 to − 6.9 kcal/mol. β-D-glucosamine demonstrated comparatively favorable binding affinities toward several core targets, particularly MAPK3, NFKB1, HSP90AA1, and HSP90AB1, whereas xylose and α-L-arabinose exhibited higher network connectivity but relatively weaker predicted binding affinities.

Conclusion The monosaccharide components of LBPs may participate in ONR through multiple candidate targets, particularly HSP90AA1, HSP90AB1, MAPK3, HIF1A, NFKB1, and MTOR, and may involve the HIF-1, neurotrophin, MAPK, and PI3K-Akt signaling pathways. These findings provide a basis for further experimental validation of the potential mechanisms of LBPs in ONR.