A Combined Ligand- and Structure-Based Virtual Screening To Identify Novel NaV1.2 Blockers: In Vitro Patch Clamp...

Area of Science:

• Neuroscience
• Pharmacology
• Computational Chemistry

Background:

• Epilepsy is a neurological disorder characterized by recurrent seizures due to abnormal brain electrical activity.
• Voltage-gated sodium channels (NaVs) are crucial for neuronal function and implicated in epilepsy pathogenesis.
• Targeting specific NaV subtypes, like hNaV1.2 in the brain, offers a potential therapeutic strategy.

Purpose of the Study:

• To discover novel anticonvulsant compounds targeting the brain subtype hNaV1.2.
• To validate computational models for virtual screening of potential NaV inhibitors.
• To assess the in vitro and in vivo efficacy of identified compounds.

Main Methods:

• Development and validation of ligand-based QSAR and structure-based docking models.
• Virtual screening of the DrugBank database using the developed computational models.
• In vitro electrophysiological evaluation using patch-clamp technique on hNaV1.2 channels.
• In vivo assessment of anticonvulsant activity in the GASH/Sal audiogenic seizure model.

Main Results:

• Montelukast, Novobiocin, and Cinnarizine were identified as inhibitors of hNaV1.2 channels.
• All three compounds demonstrated inhibition of hNaV1.2 channels in patch-clamp experiments.
• Two of the compounds exhibited promising anticonvulsant activity in an animal model of audiogenic seizures.

Conclusions:

• The combined ligand- and structure-based modeling approach is effective for identifying NaV inhibitors.
• Montelukast, Novobiocin, and Cinnarizine show potential as starting points for new antiseizure drug development.
• Further research into these compounds could lead to novel epilepsy treatments targeting NaV channels.