Design, synthesis, and computational evaluation of ester prodrugs of isoguvacine as potential antiseizure medications

Epilepsy, a neurological disorder affecting millions worldwide, has driven the development of various antiseizure medications (ASMs). Isoguvacine (IGV), a potent and selective agonist of the GABA_A receptor (GABA_AR), has shown potential in the treatment of epilepsy and other neurological disorders. However, its low blood-brain barrier permeability impairs its ability to act effectively within the central nervous system. To address this limitation, two novel ester derivatives of IGV, E7 and E14, were synthesized via Steglich esterification and evaluated through an integrated computational framework comprising density functional theory (DFT) calculations, molecular docking, molecular dynamics (MD) simulations, and in silico ADMET predictions. DFT analysis revealed that esterification significantly modified the electronic properties of IGV, with E14 exhibiting the highest polarizability (225.895 ų) and smallest energy gap (–0.155 eV), indicative of enhanced reactivity. Molecular docking demonstrated that GABA (–8.46 kcal/mol) and IGV (–8.35 kcal/mol) exhibit similar binding affinity and complex stability with GABA_AR, supporting the reliability of our computational approach. MD simulations further confirmed the stability of these complexes, where lower RMSD, RMSF, and Rg values indicated that binding of GABA and IGV did not induce significant conformational changes in the overall receptor structure. Moreover, the derivatives were projected to exhibit optimal intestinal absorption (>90%), oral bioavailability, as well as favorable safety profiles with minimal interaction risks and non-carcinogenic properties. Collectively, these in silico findings highlight the potential of ester prodrug design to overcome the central pharmacokinetic limitations of IGV, with E14 emerging as the most promising ASM candidate for further experimental development in epilepsy therapy. Beyond identifying therapeutic advantages of E14, this study also underscores the broader value of integrated computational approaches as powerful and predictive tools in early-stage drug discovery for neurological disorders.