Molecular Docking Studies ofAnti-Epileptic Drugs forTheir Novel Targeting Potential: A Revie
Epilepsy is a chronic neurological condition that affects millions of people worldwide and has serious effects on their social, economic, and general well-being. Its complex etiology includes genetic predisposition and acute insults, which cause abnormalities in glutamatergic and GABAergic transmission and result in neuronal hyperexcitability. In addition to seizures, epilepsy is linked to somatic co-morbidities, cognitive impairment, and mental health issues. However, a third of patients continue to show little improvement with current therapies. Using in silico-docking analysis, drug discovery can be done more quickly and affordably. This review explores the role of molecular docking in identifying potential antiepileptic drug candidates by focusing on common targets such as ion channels (sodium, calcium, potassium), GABA system (receptors and GABA transaminase), glutamate system (NMDA and AMPA receptors), carbonic anhydrase, and novel targets like SV2A, cannabinoid receptors, mitochondrial proteins, inflammatory pathways, and endogenous transporters. Molecular docking enables rational drug design, virtual screening, binding affinity prediction, and mode of action elucidation by shedding light on the atomic-level interactions between small compounds and target proteins. To sum up, understanding the intricate molecular pathways behind epilepsy and employing molecular docking to identify innovative medications that target these systems have potential for enhancing therapeutic outcomes. To get these putative therapeutic candidates closer to clinical use, additional experimental validation is needed. These initiatives ultimately seek to improve the quality of life for people with epilepsy by offering more efficient and specialized therapy alternatives.
Authors
- A. Madhu (ORCID: https://orcid.org/0000-0001-8809-8556)
Publication Details
- Journal
- African Journal of Biomedical Research
- Published
- 2025-01-22
- DOI
- https://doi.org/10.53555/ajbr.v28i1s.6350
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00