Investigation and computational prediction of gating pore currents in Na_V1.2 mutations across clinical phenotypes.

Authors

Ahmed Eltokhi, Eslam Elhanafy, Jing Li, Tamer M Gamal El-Din

Published in

PNAS nexus. Volume 5. Issue 7. Pages pgag230. Epub Jul 02, 2026.

Abstract

Voltage sensor domains (VSDs) are integral and common regions within voltage-gated ion channels that play a crucial role in cellular signaling and excitability. Each VSD comprises four transmembrane segments (S1-S4) per domain. The transmembrane segment S4 contains positively charged amino acid residues at every third position, which serve as the channel's gating charges. Over the last decade, it has been shown that these gating charges are the target of many pathological mutations. This study investigates three gating-charge mutations in domain I of the Na_V1.2 channel (R220G, R223I, and R223Q) identified in patients with distinct clinical phenotypes. The three mutations showed differential gating pore current (I _gp) amplitudes with distinct voltage dependence. To elucidate the molecular basis for the differential I _gp observed among these mutants, we performed microsecond-scale molecular dynamics (MD) simulations and a comprehensive analysis of the state-dependent interaction network within VSD_I across WT and mutant conformational states. The results showed that cation-π interactions between the S4 gating charges and the hydrophobic residue in S2 are the main forces that prevent VSD from leaking I _gp. Hydrophobic interactions represent the second line of defense against VSD leaking, preventing gating pore formation by maintaining structural integrity across different conformations. Salt-bridge interactions and hydrogen bonds are important stabilizing forces; however, within the VSD, their contribution appears to be less significant than that of cation-π and hydrophobic interactions. Predicting and identifying I _gp as a potential shared pathophysiology across diverse clinical presentations may guide the design of targeted therapeutic strategies.

PMID:
42416924
Bibliographic data and abstract were imported from PubMed on 08 Jul 2026.

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