Quantum Hydration-Coordination Microstate Classification in the Nav1.7 Pore: A Framework for Future Refinement

Voltage-gated sodium channels are central to electrical excitability, and Nav1.7 is a major therapeutic target implicated in pain disorders and sensory signaling. Within the channel pore, permeating Na+ ions experience dynamically fluctuating hydration and coordination environments that may influence local ion-protein interactions. Identifying chemically distinct coordination states from molecular dynamics (MD) simulations is an important prerequisite for future higher-level electronic structure investigations. In this study, we present a reproducible workflow for identifying and classifying Na+ hydration-coordination microstates in the Nav1.7 pore using explicit-solvent molecular dynamics simulations. A geometrically defined pore region was used to quantify pore hydration and Na+ inner-shell coordination based on a 3.2 & Aring; Na-O distance criterion. Na+ configurations were classified according to ligand identity into water-only (W), mixed protein-water (PW), and protein-only (P) microstates. Analysis of a 2 ns proof-of-principle simulation revealed a persistently hydrated pore environment, with Na+ coordination dominated by water-rich states and a smaller but distinct population of protein-contact configurations. These observations demonstrate that local coordination environments are chemically heterogeneous and cannot be fully described by hydration number alone. Representative structures from each microstate class were extracted to provide candidate configurations for future quantum mechanical, Quantum Mechanics/Molecular Mechanics (QM/MM), or density functional theory investigations of ion-ligand interactions in confined pore environments. The present work establishes a transparent and reproducible microstate-selection framework and does not report quantum mechanical energies, free-energy landscapes, or converged microstate populations. More broadly, the workflow provides a practical strategy for reducing complex MD ensembles into chemically interpretable coordination states suitable for subsequent higher-level analysis.