Abstract
Epilepsy is a chronic neurological disorder caused by irregular electrical activity in the brain. To manage this disorder effectively, it is imperative to identify potential pharmacological targets and to understand the pathophysiology of epilepsy in depth. This research aimed to identify promising leads from a library of 1,2,4-triazine-6Hindolo[ 2,3-b]quinoline derivatives and optimize them using in silico and dynamic processes. We used computational studies to examine 1,2,4-Triazine-6H-indolo[2,3-b]quinoline derivatives. Some methods were used to strengthen the stability of binding sites, including Docking, ADMET, IFD, MMGBSA, Density Functional Theory (DFT), and Molecular Dynamics. HRSN24 and HRSN34 exhibited promising pharmacokinetic and pharmacodynamic characteristics compared to standard drugs (Carbamazepine and Phenytoin) and a co-crystal ligand (Diazepam). Both HRSN24 and HRSN34 presented notable Glide Xp docking scores (-4.528 and -4.633 Kcal/mol), IFD scores (-702.22 and -700.3 Kcal/mol), and MMGBSA scores (-45.71 and -14.46 Kcal/mol). HRSN24 was selected for molecular dynamics and DFT analysis. During MD, HRSN24 identified LYS21, GLY22, ASP24, ARG26, VAL53, MET55, and SER308 as the most important amino acid residues for hydrophobic interactions. A DFT computation was performed to determine the physicochemical properties of HRSN24, revealing a total energy of -1362.28 atomic units, a HOMO value of -0.20186, and a LUMO value of -0.01915. Based on computational modelling techniques, an array of 1,2,4-triazine-6H-indolo [2,3-b]quinoline derivatives were evaluated for their anti-convulsant properties. A stable compound within the GABAA receptor was identified by HRSN24, suggesting its affinity as an anti-convulsant.
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