Objective To investigate the targets and mechanisms of Huachansu in alleviating oxaliplatin-induced peripheral neurotoxicity using bioinformatics and network pharmacology. Methods The targets of Huachansu were predicted via SwissTarget Prediction, PharmMapper, and SuperPred databases. Targets associated with oxaliplatin-induced peripheral neurotoxicity were retrieved from GeneCards, OMIM, and Harmonizome 3.0 databases. Combined with differential genes after oxaliplatin treatment from the GEO database, common targets were obtained through intersection analysis. The DAVID database was used for gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment. Core targets were screened via the PPI network and machine learning. Single-cell analysis was performed to explore the specific expression landscape of the core targets. AutoDock and Gromacs were employed for molecular docking and molecular dynamics simulation, with visualization assisted by PyMOL, QtGrace 2.6 and Python 3.7. Results A total of 37 active components of Huachansu were identified (e.g., telocinobufagin, hellebrigenol). Forty-five common targets were obtained. CCND1, PDGFRB, and other core targets were jointly determined by PPI network and machine learning. Molecular docking showed that telocinobufagin and other components exhibited binding energies of < -5 kcal/mol with Cyclin D1 (CCND1) and platelet-derived growth factor receptor beta (PDGFRB). Molecular dynamics simulation confirmed the stable binding between PDGFRB and telocinobufagin. Single-cell analysis suggested that Huachansu targets PDGFRB in stromal cells to reshape the neuro-supportive microenvironment. Conclusion Huachansu exerts neuroprotective effects at the acute OIPN stage by targeting PDGFRB⁺ neural stromal cells and activating the phosphatidylinositol-3-hydroxykinase (PI3K)-protein kinase B (Akt) signaling pathway, providing a theoretical basis for the early prevention of chemotherapy-induced neurotoxicity.

oxaliplatin-induced peripheral neurotoxicity  /  Huachansu  /  network pharmacology  /  machine learning  /  molecular docking  /  molecular dynamics simulation