Protein‐spanning water networks and implications for prediction of protein–protein interactions mediated through hydrophobic effects

Hydrophobic effects, often conflated with hydrophobic forces, are implicated as major determinants in biological association and self‐assembly processes. Protein–protein interactions involved in signaling pathways in living systems are a prime example where hydrophobic effects have profound implications. In the context of protein–protein interactions, a priori knowledge of relevant binding interfaces (i.e., clusters of residues involved directly with binding interactions) is difficult. In the case of hydrophobically mediated interactions, use of hydropathy‐based methods relying on single residue hydrophobicity properties are routinely and widely used to predict propensities for such residues to be present in hydrophobic interfaces. However, recent studies suggest that consideration of hydrophobicity for single residues on a protein surface require accounting of the local environment dictated by neighboring residues and local water. In this study, we use a method derived from percolation theory to evaluate spanning water networks in the first hydration shells of a series of small proteins. We use residue‐based water density and single‐linkage clustering methods to predict hydrophobic regions of proteins; these regions are putatively involved in binding interactions. We find that this simple method is able to predict with sufficient accuracy and coverage the binding interface residues of a series of proteins. The approach is competitive with automated servers. The results of this study highlight the importance of accounting of local environment in determining the hydrophobic nature of individual residues on protein surfaces. Proteins 2014; 82:3312–3326. © 2014 Wiley Periodicals, Inc.