"Virtual patch clamp analysis" for predicting the functional significance of pathogenic variants in sodium channels.

OBJECTIVE:Opening of voltage-gated sodium channels is crucial for neuronal depolarization. Proper channel opening and influx of Na+ through the ion pore, is dependent upon binding of Na+ ion to a specific amino-acid motif (DEKA) within the pore. In this study we used molecular dynamic simulations, an advanced bioinformatic tool, to research the dysfunction caused by pathogenic variants in SCN1a, SCN2a and SCN8a genes. METHOD:Molecular dynamic simulations were performed in six patients: three patients with Dravet syndrome (p.Gly177Ala,p.Ser259Arg and p.Met1267Ile, SCN1a), two patients with early onset drug resistant epilepsy(p.Ala263Val, SCN2a and p.Ile251Arg, SCN8a), and a patient with autism (p.Thr155Ala, SCN2a). After predicting the 3D-structure of mutated proteins by homology modeling, time dependent molecular dynamic simulations were performed, using the Schrödinger algorithm. The opening of the sodium channel, including the detachment of the sodium ion to the DEKA motif and pore diameter were assessed. Results were compared to the existent patch clamp analysis in four patients, and consistency with clinical phenotype was noted. RESULTS:The Na+ ion remained attached to DEKA filter longer when compared to wild type in the p.Gly177Ala, p.Ser259Arg,SCN1a, and p.Thr155Ala, SCN2a variants, consistent with loss-of-function. In contrast, it detached quicker from DEKA than wild type in the p.Ala263Val,SCN2a variant, consistent with gain-of-function. In the p.Met1267Ile,SCN1a variant, detachment from DEKA was quicker, but pore diameter decreased, suggesting partial loss-of-function. In the p.Leu251Arg,SCN8a variant, the pore remained opened longer when compared to wild type, consistent with a gain-of-function. The molecular dynamic simulation results were consistent with the existing patch-clamp analysis studies, as well as the clinical phenotype. SIGNIFICANCE:Molecular dynamic simulation can be useful in predicting pathogenicity of variants and the disease phenotype, and selecting targeted treatment based on channel dysfunction. Further development of these bioinformatic tools may lead to "virtual patch-clamp analysis".