Exploring the Antiamoebic Potential of Zonisamide and Perampanel against Naegleria fowleri : Insights from In Vitro and Docking Studies

High Resolution Image Download MS PowerPoint Slide Naegleria fowleri, the etiological agent of PAM, is a thermophilic amoeba with a high mortality rate with limited therapeutic options. Current treatments involve multidrug regimens with high toxicity with variable efficacy. This study explores the repurposing potential of two central nervous system drugs, Zonisamide and Perampanel against N. fowleri, integrating cell-based assays and in silico docking analyses to predict efficacy and mechanistic pathways. In vitro assays demonstrated significant amoebicidal activity by both compounds, Perampanel reduced trophozoite viability by 87.5%, and Zonisamide by 77.3% at 200 μg/mL. Cytotoxicity assays exhibited low to moderate cytotoxicity on human-derived HeLa and SH-SY5Y cell lines, confirming therapeutic selectivity. Further investigations revealed that both drugs induced programed cell death (PCD), confirmed via fluorescence microscopy, and significantly elevated reactive oxygen species, implicating oxidative stress as a likely mechanism of action. AutoDock Vina scores integrated with GNN-based scoring functions AK-Score2 revealed high binding affinities of both compounds to four essential N. fowleri targets, NfCYP51, cathepsin B, serine carboxypeptidase, and Rab family GTPase with Perampanel showing the highest integrated binding energy score at −5.797 kcal/mol with NfCYP51. This integrative study demonstrates the antiamoebic activity of Zonisamide and Perampanel, supported by in vitro efficacy, selectivity, and molecular docking analyses. These findings support their candidacy for further development as PAM therapeutics. Beyond the scientific results, the approach aligns with Sustainable Development Goal 3 (Good Health and Well-being) by promoting innovative, accessible treatment strategies for neglected diseases and with SDG 9 (industry, innovation, and infrastructure) through the use of computational drug repurposing technologies.