Sodium Channel

Voltage-gated sodium channels (Nav) are crucial for neuronal excitability and are implicated in various diseases, including pain and cardiac arrhythmias. Current research focuses on developing computational models, particularly machine learning approaches like Random Forests and Support Vector Machines, to predict drug interactions with specific Nav channels (e.g., Nav1.5, Nav1.7, Nav1.8, Nav1.9, and hERG) and design safer drugs with reduced cardiotoxicity. This work is significant because it accelerates drug discovery and development by identifying potential drug candidates and mitigating risks associated with off-target effects, ultimately improving therapeutic efficacy and patient safety.