Prediction of the hydration levels
of protein cavities
and active
sites is important to both mechanistic analysis and ligand design.
Due to the unique microscopic environment of these buried water molecules,
a polarizable model is expected to be crucial for an accurate treatment
of protein internal hydration in simulations. Here we adapt a nonequilibrium
candidate Monte Carlo approach for conducting grand canonical Monte
Carlo simulations with the Drude polarizable force field. The GPU
implementation enables the efficient sampling of internal cavity hydration
levels in biomolecular systems. We also develop an enhanced sampling
approach referred to as B-walking, which satisfies
detailed balance and readily combines with grand canonical integration
to efficiently calculate quantitative binding free energies of water
to protein cavities. Applications of these developments are illustrated
in a solvent box and the polar ligand binding site in trypsin. Our
simulation results show that including electronic polarization leads
to a modest but clear improvement in the description of water position
and occupancy compared to the crystal structure. The B-walking approach enhances the range of water sampling in different
chemical potential windows and thus improves the accuracy of water
binding free energy calculations.