Understanding mechanisms of

Background: Methods: This work used ultracentrifugation to extract the PSELNs and characterized them using transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and dynamic light scattering (DLS). Proteomics and metabolomics were used to analyze the components of the PSELNs, and the Herb database was used to screen for active metabolites. The OMIM and TTD databases were used to analyze active metabolites, and we further speculated that they may have anti-breast cancer (BC) activity. Network pharmacology was used to analyze the possible mechanisms of the PSELNs against BC, mainly including protein-protein interaction (PPI) network analysis for potential targets, gene ontology (GO) for analyzing biological processes, and Kyoto Encyclopedia of Genes and Genomes (KEGG) for analyzing related signaling pathways. After that, the related data of BC was retrieved from the GEO database, and the clinical expression and survival prognosis of the key genes screened by network pharmacology were analyzed by bioinformatics. Molecular docking and Molecular dynamics (MD) simulation were used to verify the binding of active metabolites in the PSELNs with their targets. Finally, the CCK-8 method was used to validate the inhibitory effect of the PSELNs on BC. Results: Firstly, TEM, NTA, and DLS confirmed that the PSELNs were successfully isolated. Then, Proteomics identified 18 protein components from the PSELNs, including ATP synthase subunit alpha, protein Ycf2, and Mannose/silica acid binding lectin. Metabolomics identified 357 metabolic components from the PSELNs and further screened 23 active metabolites by oral bioavailability (OB), including Sedanolide, Baicalein, and 6-Gingerol, etc. By analyzing 23 active metabolites, it was speculated that the PSELNs may have pharmacological activity against BC. After that, network pharmacology was used to screen 23 key targets of the PSELNs against BC. KEGG and GO enrichment analysis showed that the MAPK signaling pathway, PI3k-Akt signaling pathway, and AMPK signaling pathway were involved in the anti-BC effect of the PSELNs. Through bioinformatics analysis of 23 key targets in BC clinical samples, it was found that, except for ESR1, which was significantly upregulated, CAV1, FGF2, and PPARG were all significantly downregulated. The expression levels of 4 targets were positively correlated with survival status. These 4 targets were validated by molecular docking and MD simulation with active metabolites in the PSELNs, and it was found that the binding of sedanolide and ESR1, Baicalein and PPARG, and 6-Gingerol and ESR1 can remain stable. Finally, The inhibitory effect of the PSELNs on BC cells (MDA-MB-231) was validated by the CCK-8 method. Conclusion: This was the first time that the PSELNs have been studied against cancer. It was verified that they have anti-BC activity, and the mechanism may be related to targets such as ESR1 and PPARG, regulated by active metabolites in the PSELNs. This work laid a foundation and reference for more follow-up related research studies.