Molecular Dynamics as a Precision Therapy: A Perspective on Epileptic Encephalopathies

Epileptic encephalopathies (EEs) are a diverse group of severe neurological disorders characterized by early-onset, drug-resistant seizures, and significant developmental impairment. These complex conditions often stem from genetic variants that disrupt ion channel function, synaptic transmission, or intracellular signaling pathways [1–3]. Despite notable progress in characterizing the genetics of EEs, current pharmacological strategies frequently remain inadequate, necessitating more targeted and personalized approaches to therapy [4]. Recent innovations in genomics and computational biology have highlighted precision medicine as a potential breakthrough in the clinical management of EEs. By focusing on the specific genetic and molecular causes of each patient’s disorder, this approach aims to develop treatments that precisely modulate the aberrant pathways driving epileptogenesis and neurodevelopmental regression [5]. Within this paradigm, molecular dynamics (MD) simulations have emerged as a powerful in silico method for probing how pathological mutations alter protein conformation and function, as well as how different pharmacological agents might selectively interact with these altered targets [6]. Molecular dynamics leverages physics-based algorithms to simulate atomic-level interactions, allowing for the exploration of protein stability, drug-binding affinities, and the effects of particular mutations on drug responsiveness. When integrated with patient-specific genetic data, MD offers a rational strategy for identifying candidate therapies that can be optimized for efficacy and tolerability. Moreover, the incorporation of machine learning and highperformance computing has significantly reduced the time and resources traditionally required for large-scale simulations, making MD increasingly accessible for translational research in rare and complex epilepsies [7, 8]. By bridging clinical genetics and computational modeling, molecular dynamics holds the promise of significantly improving outcomes in drug-resistant epileptic encephalopathies [9]. Targeting pathogenic variants at their molecular root may enable the design of personalized therapies that are more effective than existing broad-spectrum antiseizure medications. This shift toward mechanism-driven, individualized treatment strategies underscores the potential for MD-based approaches to transform the therapeutic landscape of EEs, offering new avenues to mitigate seizure burden and enhance neurodevelopmental trajectoriy