Investigation of potential targets and mechanisms of naringenin in the treatment of spinal cord injury: A network pharmacology, molecular docking, and molecular dynamics simulation study

Spinal cord injury (SCI) is a disease that causes significant functional impairment and high mortality, imposing a heavy economic burden on patients and society. In this in-silico study, we investigated the potential therapeutic targets and underlying mechanisms of naringenin (NAR) in SCI by integrating network pharmacology, molecular docking, and molecular dynamics (MD) simulation. The intersection of NAR and SCI targets was used to construct a protein–protein interaction network using the STRING database. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Wiki Pathway enrichment analyses were performed using the DAVID bioinformatics resource. Finally, we used molecular docking and MD simulation to study the binding interactions between NAR and the core targets. The results show that the core targets of NAR for spinal cord injury include estrogen receptor 1, AKT serine/threonine kinase 1, B-cell lymphoma 2, PPARG, MAPK8, mechanistic target of rapamycin, protein kinase cAMP-activated catalytic subunit alpha, and HRas proto-oncogene, GTPase. These targets and associated biological processes provide multiple mechanisms supporting NAR’s action. In addition, enrichment analysis indicates that the AMPK, FoxO, and PI3K–Akt–mechanistic target of rapamycin signaling pathways, autophagy, and apoptosis are the main pathways through which NAR acts in SCI. Molecular docking results show that the binding energy between NAR and key proteins ranges from −7.1 to −8.2 kcal/mol, providing a molecular basis for NAR’s treatment of SCI. Molecular dynamics simulation results indicate that the AKT serine/threonine kinase 1–NAR and B-cell lymphoma 2–NAR complexes exhibit good stability. In summary, this study systematically predicts the key targets and signaling pathways through which NAR may act in SCI, providing a theoretical basis for future mechanistic and translational research. However, because the findings are based on computational analyses alone, further in vitro and in vivo validation is required.