Water molecules play a key role in many biomolecular systems, particularly when bound at protein–ligand interfaces. However, molecular simulation studies on such systems are hampered by the relatively long time scales over which water exchange between a protein and solvent takes place. Grand canonical Monte Carlo (GCMC) is a simulation technique that avoids this issue by attempting the insertion and deletion of water molecules within a given structure. The approach is constrained by low acceptance probabilities for insertions in congested systems, however. To address this issue, here, we combine GCMC with nonequilibium candidate Monte Carlo (NCMC) to yield a method that we refer to as grand canonical nonequilibrium candidate Monte Carlo (GCNCMC), in which the water insertions and deletions are carried out in a gradual, nonequilibrium fashion. We validate this new approach by comparing GCNCMC and GCMC simulations of bulk water and three protein binding sites. We find that not only is the efficiency of the water sampling improved by GCNCMC but that it also results in increased sampling of ligand conformations in a protein binding site, revealing new water-mediated ligand-binding geometries that are not observed using alternative enhanced sampling techniques.

Water plays an important role in mediating protein-ligand interactions. Water rearrangement upon a ligand binding or modification can be very slow and beyond typical timescales used in molecular dynamics (MD) simulations. Thus, inadequate sampling of slow water motions in MD simulations often impairs the accuracy of the accuracy of ligand binding free energy calculations. Previous studies suggest grand canonical Monte Carlo (GCMC) outperforms normal MD simulations for water sampling, thus GCMC has been applied to help improve the accuracy of ligand binding free energy calculations. However, in prior work we observed protein and/or ligand motions impaired how well GCMC performs at water rehydration, suggesting more work is needed to improve this method to handle water sampling. In

Water molecules play a key role in biomolecular systems, particularly when bound at protein-ligand interfaces. Simulation studies are hampered by the relatively long timescales on which water exchange between protein and solvent can take place. Grand canonical Monte Carlo (GCMC) is a simulation technique which avoids this issue by attempting the direct insertion and deletion of water molecules. GCMC is, however, hampered by low acceptance probabilities for insertions in congested systems. To address this issue, here, we combine GCMC with nonequilibrium candidate Monte Carlo (NCMC) to yield a new method, grand canonical nonequilibrium candidate Monte Carlo (GCNCMC), in which water insertions and deletions are carried out in a gradual, nonequilibrium fashion. We compare GCNCMC and GCMC simulations of bulk water, and three protein binding sites. We find the efficiency of water sampling is improved by GCNCMC, and that increased sampling of bound ligand conformations is also observed.

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Energized nutrient import in bacteria needs the interaction between a TonB-dependent transporter (TBDT) and a TonB protein. The mechanism of energy and signal transfer between these two proteins is not well understood. They belong to two membranes separated by the periplasmic space and possess each a disordered and flexible region. Therefore, the membranes, their distance and geometrical constraints together with the protein dynamics are important factors for deciphering this trans-envelope system. Here we report the first example of the interaction of a TBDT with a TonB protein in the presence of both membranes. By combining molecular dynamics simulations in a membrane model, in vitro and in vivo phenotypic experiments we obtained the comprehensive network of interaction between HasR, a heme/hemophore receptor and its dedicated TonB protein, HasB.