Speaker
Description
Voltage-gated sodium channels are central to neuronal excitability and are major therapeutic targets, yet their functional behavior emerges from highly heterogeneous and dynamically fluctuating pore microenvironments that are difficult to characterize using static structural models alone. In particular, local ion hydration and coordination motifs within the pore can vary substantially over time, potentially modulating energetic sensitivity in ways that are not fully captured by classical force fields. Here, we present a reproducible classical-to-quantum workflow for identifying and prioritizing quantum-relevant microstates in the pore of the human Nav1.7 sodium channel. Using an explicit-solvent molecular dynamics simulation, we extract time-resolved descriptors of the local pore microenvironment, including sodium ion hydration number, oxygen coordination, and spatial occupancy within a protein-centered pore region. These descriptors are used to classify distinct microenvironmental microstates and to construct a qualitative joint-occupancy landscape that highlights recurrent hydration–coordination motifs without invoking fully converged free-energy surfaces. We demonstrate how this ensemble-based microstate analysis can be used to select representative structural clusters for subsequent quantum mechanical treatment, thereby reducing the dimensionality and computational cost of high-level electronic structure calculations such as density functional theory or variational quantum eigensolver (VQE) approaches. Conceptual quantum sensitivity illustrations are included to clarify how different hydration microstates may lead to divergent electronic energetics, motivating targeted quantum refinement. Rather than providing definitive thermodynamic or conductive predictions, this work establishes a practical and extensible framework for bridging long-timescale classical simulations with focused quantum calculations in ion channels. The proposed methodology is broadly applicable to other membrane proteins where transient microenvironmental heterogeneity is expected to play a functional role.
