KCNQ2 Anticonvulsant Program

Target Identification

Our program targets KCNQ2 (Kv7.2) voltage-gated potassium channels, which play a critical role in regulating neuronal excitability. Mutations in the KCNQ2 gene are associated with benign familial neonatal seizures (BFNS) and early-onset epileptic encephalopathy.

Approach

We employ a combination of structure-based drug design, molecular dynamics simulations, and AI-enhanced virtual screening to identify novel modulators of KCNQ2 channels. Our computational pipeline integrates:

• Cryo-EM structure analysis of Kv7.2 channel
• Molecular dynamics simulations for binding site characterization
• Deep learning-based virtual screening of compound libraries
• ADMET prediction for lead optimization

Current Status

The program has progressed to the candidate stage with a lead compound showing favorable selectivity and safety profiles in preclinical models.

Key Milestones

• Target validation: Confirmed KCNQ2 gain-of-function mutations as therapeutic target
• Lead identification: Virtual screening identified 15 novel chemotypes
• Lead optimization: Structure-activity relationship studies yielded compound C2C-047
• Candidate selection: C2C-047 selected as preclinical candidate based on efficacy and safety