Abstract Background Traditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a Polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. Objective To systematically investigate the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays. This study aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. Methods This study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics simulations, MM/PBSA free energy analysis, RT?qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper, followed by topological analysis using Cytoscape. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. Results The results of the CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/Akt, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT?qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. Conclusion This study suggests that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/Akt signaling pathway. These findings provide crucial evidence supporting PA's development as a therapeutic candidate for NB. Key words: Pachymic acid; Network pharmacology; molecular dynamics simulation