Investigating Nav1.6 and Its Potential Therapeutic Applications – American Journal of Student Research

American Journal of Student Research

Investigating Nav1.6 and Its Potential Therapeutic Applications

Publication Date : Dec-12-2025

DOI: 10.70251/HYJR2348.36877894


Author(s) :

Aiden Ashcraft.


Volume/Issue :
Volume 3
,
Issue 6
(Dec - 2025)



Abstract :

Neuropathic pain affects 6.9-10% of the global population, with first-line treatments providing meaningful relief in only ~30% of patients. Trafficking disruption has emerged as a therapeutic strategy for Nav1.7, where peptides disrupting the CRMP2-Nav1.7 interaction reduce channel surface expression and alleviate pain in preclinical models. This approach remains unexplored for Nav1.6 (SCN8A), despite regulatory protein interactions. This study evaluated whether Nav1.6 possesses molecular properties suitable for trafficking-based therapeutic modulation. We integrated transmembrane domain prediction (TMHMM), multiple sequence alignment across five species, protein-protein interaction network analysis (STRING), expression profiling (GTEx), and Hodgkin-Huxley modeling of dorsal root ganglion (DRG) neurons under varying Nav1.6 expression levels (1.0x normal, 1.5x neuropathic, 0.7x reduced, 0.1x knockout). Analysis revealed that MAP1B binding to the Nav1.6 N-terminus prevents endocytosis and controls surface expression, a regulatory mechanism similar to the CRMP2-Nav1.7 system, which has been successfully targeted for Nav1.7-mediated pain. Conservation analysis showed moderate variability in the MAP1B binding region (residues 77-80), contrasting with highly conserved transmembrane domains. Computational modeling demonstrated that ~30% Nav1.6 reduction (0.7x expression) eliminates repetitive firing while preserving normal responsiveness. Experimental MAP1B-Nav1.6 disruption achieves ~40% surface expression reduction, a magnitude that falls within the therapeutic range identified by the modeling, validating trafficking disruption as a therapeutic strategy. GTEx profiling confirmed CNS-enriched expressions. This computational integration predicts trafficking disruption as a therapeutic strategy for Nav1.6, with specific predictions directly testable in neuropathic pain models.