Exploring neuroprotective effects of PP2 in ischemic stroke via bioinformatics and experimental validation

Background: Ischemic stroke is a leading cause of mortality and disability worldwide, yet effective therapeutic options remain limited. In this study, bioinformatics analyses were used to identify potential therapeutic targets and small-molecule compounds for ischemic stroke. A mouse model of cerebral ischemia was subsequently used to validate their neuroprotective efficacy.

Methods: Bioinformatics methods were used to analyze and identify key signaling pathways and hub genes associated with ischemic stroke. Additionally, the Connectivity Map (CMap) database was queried to identify potential small-molecule compounds for ischemic stroke treatment. Finally, a middle cerebral artery occlusion/reperfusion (MCAO/R) mouse model was employed to further evaluate the neuroprotective effects of the identified compounds.

Results: GO and KEGG pathway enrichment analyses revealed that key signaling pathways such as TNF, NF-κB, and IL-17 play crucial roles in ischemic stroke. PPI network analysis identified five hub genes-IL-1β, IL-6, ICAM-1, Jun, and Fos-all closely associated with neuroinflammatory responses. The small-molecule compound PP2, a selective Src kinase inhibitor, was identified by CMap database. In the MCAO/R mouse model, PP2 exhibited significant neuroprotective effects. It reduced infarct volume and brain edema and improved neurological function. Mechanistically, PP2 inhibited Src phosphorylation, thereby suppressing the NF-κB signaling pathway and reducing levels of pro-inflammatory cytokines, including TNF-α, IL-1β, and IL-6.

Conclusion: This study identifies Src kinase as a promising therapeutic target for ischemic stroke and highlights the value of bioinformatics in drug discovery and mechanistic research.

Bioinformatics analysis; NF-κB pathway; PP2; neuroprotective; src inhibitor.