Computational protein stability analysis of SCN1A missense variants reveals domain‐dependent stability patterns
Abstract Objective To determine whether computational protein‐stability predictions discriminate pathogenic from benign SCN1A missense variants, and to characterize the structural distribution of predicted destabilization among pathogenic variants. Methods On an AlphaFold3‐predicted Nav1.1 structure, FoldX, and Rosetta Cartesian ΔΔG were computed for a single ClinVar snapshot of pathogenic/likely‐pathogenic (P/LP) and benign/likely‐benign (B/LB) missense variants and its extension to ClinVar variants of uncertain significance (VUS) and gnomAD v4.1 variants; membrane‐aware RosettaMP was applied to the patch‐clamp subgroup. Pathogenic variants were stratified by functional domain. Results Pathogenic variants were more destabilizing than benign (FoldX 2.61 vs. 0.31 kcal/mol, p = 1.27 × 10−11; ROC‐AUC = 0.760), concordant with Rosetta (ROC‐AUC = 0.697; ρ = 0.660). Destabilization was domain‐dependent: pore (P‐loop/selectivity‐filter) pathogenic variants were depleted of stability‐neutral variants (0.40‐fold; Bonferroni‐adjusted p = 4.3 × 10−7), whereas S4 voltage‐sensor variants were enriched for them (2.32‐fold; p = 0.013). Across ~3300 non‐redundant variants, gnomAD‐common variants resembled benign controls and VUS were intermediate (mean ΔΔG 0.98 kcal/mol; 18.5% strongly destabilizing), with the domain pattern preserved. Among 64 patch‐clamp variants, stability did not separate gain‐ from loss‐of‐function, though gain‐of‐function variants clustered in voltage‐sensing domains and were absent from the pore. Significance Computational stability analysis thus adds a mechanistic layer complementary to the conventional gating‐dysfunction view, distinguishing a destabilized pore‐region subset—for which proteostasis impairment is a candidate, though unproven, mechanism—from a structurally tolerated S4 subset whose pathogenicity is stability‐independent. As a hypothesis‐generating rather than mechanism‐defining approach, this stratification prioritizes candidate variants—including the 18.5% of VUS that are strongly destabilizing—for direct functional and surface‐expression validation in SCN1A‐related epilepsies. Plain Language Summary We used computational modeling to predict how thousands of SCN1A genetic variants influence the stability of the Nav1.1 sodium channel protein. Disease‐causing variants tended to destabilize the protein more than benign variants, and variants in the pore region—where ions flow through the channel—were predominantly destabilizing. This is consistent with loss‐of‐function arising from misfolding and degradation of the channel protein in this subset of variants. By contrast, variants in the voltage‐sensing region were often structurally tolerated, indicating that their disease‐causing effects likely arise through a different mechanism that requires direct functional measurement to define. Accordingly, the analysis nominates a candidate pore‐region subset potentially affected by proteostasis impairment and a complementary stability‐neutral subset warranting functional evaluation.