(253bf) Characterizing Protein Hydration to Inform Its Interactions with Ligands and Other Proteins

Protein interactions are crucial in numerous biological processes, including cell signaling, enzymatic function and disease pathology. Since all of biology happens in water, every bio-molecular binding process involves protein-water interactions being disrupted, and replaced by direct interactions between the binding partners. Thus, the key to predicting protein-protein interactions is to be able to accurately characterize the free energetics of protein-water interactions. Estimating protein-water interactions accurately and efficiently, however, has proved to be challenging, because proteins have incredibly complex surfaces that disrupt the inherent structure of water in countless different ways, which depend not only on the chemistry of the underlying protein surface, but also on the precise topography and chemical pattern of amino acids. Here, I will present our recent work on characterizing protein-water interactions using explicit water molecular simulations in conjunction with an unfavorable biasing potential that attempts to displaces water molecules away from the protein hydration shell. As the strength of the biasing potential is increased, protein-water interactions are systematically disrupted, resulting in the formation of cavities in the protein hydration shell. The order in which cavities appear in various regions of the protein contains a wealth of information: regions of the protein that interact weakly with water ought to dewet first, whereas those that are highly hydrophilic should hold on to their hydration waters even at large biasing potentials. Because the regions where cavities first appear have the weakest interactions with water, and correspondingly the highest surface energy, the protein is most likely to interact with other molecules through these regions. Furthermore, the size and the shape of the cavities that spontaneously appear in the protein hydration shell also inform the size and shape of an optimal hydrophobic ligand that will bind most strongly to the protein of interest. Our results could thus inform the design of customized ligands for protein separations using hydrophobic interaction chromatography (HIC).