Computational insights into the antiepileptic potential of hydantoin derivatives: A synergistic approach using network pharmacology, molecular docking, and density functional theory

BACKGROUND: Epilepsy is a chronic neurological disorder marked by recurrent seizures, and nearly one-third of patients remain drug-resistant despite the availability of multiple antiepileptic drugs (AEDs). This unmet need emphasizes the urgency for discovering novel therapeutic agents. OBJECTIVE: The present study employs an in silico approach to investigate the antiepileptic potential of newly synthesized compounds by integrating computational techniques. MATERIALS AND METHODS: Molecular docking, protein–protein interaction (PPI) network analysis, network pharmacology, and density functional theory (DFT) calculations were applied. Docking was used to evaluate the binding affinity of compounds against epilepsy-associated targets. PPI analysis was conducted to identify key protein interactions involved in synaptic transmission, whereas DFT calculations optimized molecular structures and provided insights into their electronic properties. RESULTS: Molecular docking revealed that Compound 10 exhibited the strongest binding affinity, with a docking score of −9.5 kcal/mol against epilepsy-related proteins. PPI network analysis identified metabotropic glutamate receptors (GRM1, GRM3, GRM4, GRM5, GRM7, and GRM8) as critical modulators of synaptic transmission and neuronal plasticity. DFT calculations showed ΔE values ranging from 0.181 eV to 0.199 eV, suggesting high reactivity due to small energy gaps. CONCLUSION: This study highlights the potential of synthetic compounds as novel antiepileptic agents and demonstrates the power of in silico approaches in accelerating drug discovery. The findings provide a cost-effective strategy to identify lead compounds, optimize their molecular properties, and guide the development of innovative therapeutic options for epilepsy management.