A Classical-to-Quantum Selection Workflow for Hydration Microstate Identification in the Nav1.7 Sodium Channel Pore

Voltage-gated sodium channels such as Nav1.7 control neuronal excitability and pain signaling, yet their narrow pores create heterogeneous Na hydration environments that can challenge fixed-charge molecular dynamics (MD) descriptions. Here we present a classical-to-quantum workflow to identify and prioritize structurally distinct Na hydration-coordination microstates within the Nav1.7 pore for downstream quantum mechanical refinement. Using explicit-solvent MD sampling, we define a protein-centered cylindrical pore region and compute time-resolved descriptors of pore hydration and Na inner-shell coordination using a distance-based criterion (3.2 Å Na-O cutoff). We classify Na configurations into chemically interpretable coordination microstates based on inner-shell ligand identity: water-only (W), mixed protein-water (PW), and protein-only (P). In an analyzed window of 20 frames spanning approximately 2 ns, the pore remains persistently hydrated while Na coordination is dominated by water-dominated states with a resolvable subpopulation of protein-contact configurations. The resulting representative snapshots provide quantum-ready starting structures for subsequent electronic-structure refinement (e.g., DFT or VQE) focused on local ion-ligand effects in confined ion-channel environments. In this manuscript we demonstrate the selection and classification workflow on an analyzed window of 20 frames (~2 ns) and do not report microstate-resolved quantum energies.