The Pro23 to Thr mutation (P23T) in human gamma D-crystallin (HGD) is geographically widespread and associated with congenital cataract. HGD is a monomeric, structural protein found in the eye lens and contains four Greek key motif folds. Recent experiments from the Pande group have shown that the P23T mutant displays increased surface hydrophobicity compared to the wild type (WT) protein with minimal change in the overall protein structure [Pande, A., et al. (2010) <i>Biochemistry</i> 49, 6122-6129]. This increase is believed to result in the observed self-aggregation of the P23T mutant, leading to lens opacity. Characterization of the surface hydrophobicity of the protein is important to understanding protein-protein interactions. Hydropathy scales of individual amino acids have traditionally been used to explain such phenomena. However, surface hydrophobicity is also affected by the chemical and topological heterogeneities and the shape and size-dependence of the ligand interrogating the various regions of the protein surface. In the present work, we employ molecular dynamics (MD) simulations to characterize surfaces of both WT and P23T mutant proteins using two independent techniques. In the first method, we use methane-like Lennard-Jones probe particles in solution with WT and P23T to generate hydrophobicity maps of each protein, allowing us to infer regions with higher aggregation propensity. In the second technique, we use a computationally efficient enhanced sampling method to calculate free energies of cavity formation in benzene and naphthalene shaped probe volumes near the protein surface. These shapes are chosen because phenyl and naphthyl moieties appear in the fluorescent probes used in the experiments to study surface hydrophobicity. We generate ligand binding maps for these probes and compare our results to maps obtained using the first method. These protein surface hydrophobicity characterization techniques based on a fundamental understanding of water near the protein surface have the potential to complement experimental methods leading to the understanding of the aggregation propensity of biomacromolecules.

Quantifying the surface hydrophobicity of human gamma-D crystallin and its cataract-associated P23T mutant using molecular dynamics simulations

249th National Meeting (2015)

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