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Epilepsy is a debilitating neurological disorder that impacts approximately 50 million people worldwide. The treatment of epilepsy with antiepileptic drugs has not achieved effective seizure management and thus requires new therapeutic options. This study investigated the catechins' affect on epilepsy-related molecular targets using a computational method that combined network pharmacology, molecular docking, and molecular dynamics (MDs) simulation. We fetched 84 catechins-related and 5356 disease-associated targets from various databases, yielding 31 common targets. The protein-protein interaction (PPI) network of 31 common targets identified 10 hub genes, including ALB, INS, brain-derived neurotrophic factor (BDNF), PTGS2, tumor necrosis factor (TNF), IL1B, FOS, IL6, LEP, and FGF2. Further, the functional enrichment analysis revealed that these common targets have a high prevalence in multiple pathways and gene ontology functions. Furthermore, "compound-target" and "compound-gene-pathway" networks were constructed and analyzed. Network pharmacology data show TNF, IL1B, and IL6 could influence epilepsy treatment by regulating several pathways. The Cresset Flare Pro+ docking study unveiled that the lead catechin, epigallocatechin gallate (EGCG), exhibited the highest Lead Finder (LF) dG scores of -10.2, -9.40, and -8.15 kcal/mol against TNF, IL6, and IL1B, respectively. The electrostatic complementarity and Molecular Mechanics with Generalized Born and surface area (MMGBSA) results supported the docking results. Further, the stability of EGCG-bound complexes was analyzed using a 300 ns MD simulation. The principal component analysis yielded promising results for the EGCG-2AZ5 and EGCG-1ALU complexes collective motion. These findings provide computational evidence suggesting that EGCG has a promising scaffold for designing multi-target molecules that could modulate epilepsy, meriting further experimental validation.