Xifeng Jiannao pill mitigates MPTP-induced neuronal apoptosis by reducing inflammation and oxidative stress via MAPK signaling

Xifeng Jiannao Pill (XFJNP), a traditional Chinese medicine formulation, has been shown to alleviate clinical symptoms in patients with Parkinson's disease (PD). However, the underlying mechanisms remain unclear. Therefore, this study employs network pharmacology and molecular biology to investigate the potential therapeutic mechanisms of XFJNP. Firstly, network pharmacology is utilized to screen the major active ingredients and potential targets of XFJNP in the treatment of PD. Following this, pathway enrichment analysis is conducted to gain insights into the underlying mechanisms. Secondly, an MPP⁺-induced SH-SY5Y cell model and an MPTP-induced PD mouse model to investigate the therapeutic effects and potential mechanisms of XFJNP on PD. By assessing apoptosis, oxidative stress (OS), inflammation, activation of the MAPK pathway, and conducting behavioral tests in mice, we aimed to elucidate the efficacy and underlying mechanisms of XFJNP in treating PD. Network pharmacology analysis indicates that the MAPK signaling pathway holds a key position in mediating the therapeutic effects of XFJNP for PD. In basic experimental studies, XFJNP significantly enhanced the survival rate of MPP⁺-induced SH-SY5Y cells in vitro, reduced OS and inflammation levels, and increased the expression of tyrosine hydroxylase (TH) protein. In the MPTP-induced PD mouse model, XFJNP effectively improved motor function and reduced the loss of dopaminergic (DA) neurons. Mechanistic studies suggest that XFJNP may mitigate OS and inflammatory responses in the substantia nigra by inhibiting the excessive activation of ERK, JNK, and p38 in the MAPK signaling pathway. Based on the results of network pharmacology analysis and experimental validation, XFJNP displays profound neuroprotective efficacy by modulating the MAPK signaling cascade, markedly diminishing neuroinflammation and mitigating OS-triggered apoptosis of DA neurons in PD models.