Investigation and Computational Prediction of Gating Pore Currents in NaV1.2 Mutations Across Clinical Phenotypes

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ID: 319412
2026
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Abstract
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. It has 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 NaV1.2 channel (R220G, R223I, R223Q) identified in patients with distinct clinical phenotypes. The three mutations showed differential gating-pore current amplitudes with distinct voltage dependence. To elucidate the molecular basis for the differential Igp observed among these mutants, we performed microsecond-scale molecular dynamics (MD) simulations and a comprehensive analysis of the state-dependent interaction network within VSDI 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 gating-pore current. 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 voltage-sensing domain, their contribution appears to be less significant than that of cation–π and hydrophobic interactions. Predicting and identifying gating pore currents as a potential shared pathophysiology across diverse clinical presentations may guide the design of targeted therapeutic strategies.
Reference Key
openalex_W7167088778 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ahmed Eltokhi, Eslam Elhanafy, Jing Li, Tamer M. Gamal El-Din
Journal PNAS nexus
Year 2026
DOI
10.1093/pnasnexus/pgag230
URL
https://doi.org/10.1093/pnasnexus/pgag230
Keywords Keywords not found

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