Molecular-level understanding of the adsorption mechanism of a graphite-binding peptide at the water/graphite interface
journal contributionposted on 14.01.2016, 13:52 authored by M.J. Penna, M. Mijajlovic, C. Tamerler, Mark Biggs
The association of proteins and peptides with inorganic material has vast technological potential. An understanding of the adsorption of peptides at liquid/solid interfaces on a molecular-level is fundamental to fully realising this potential. Combining our prior work along with the statistical analysis of 100+ molecular dynamics simulations of adsorption of an experimentally identified graphite binding peptide, GrBP5, at the water/graphite interface has been used here to propose a model for the adsorption of a peptide at a liquid/solid interface. This bottom-up model splits the adsorption process into three reversible phases: biased diffusion, anchoring and lockdown. Statistical analysis highlighted the distinct roles played by regions of the peptide studied here throughout the adsorption process: the hydrophobic domain plays a significant role in the biased diffusion and anchoring phases suggesting that the initial impetus for association between the peptide and the interface may be hydrophobic in origin; aromatic residues dominate the interaction between the peptide and the surface in the adsorbed state and the polar region in the middle of the peptide affords a high conformational flexibility allowing strongly interacting residues to maximise favourable interactions with the surface. Reversible adsorption was observed here, unlike in our prior work focused on a more strongly interacting surface. However, this reversibility is unlikely to be seen once the peptide–surface interaction exceeds 10 kcal mol 1.
M.J.P. gratefully acknowledges receipt of an Australian Postgraduate Award (APA) from The University of Adelaide. M.M. is similarly grateful for the postdoctoral fellowship part-funding from The University of Adelaide. The support of the Australian Research Council (DP130101714) is also acknowledged. The supercomputing resources for this work were provided by eResearchSA and both the NCI National Facility at the Australian National University and the iVEC Facility at Murdoch University under the National Merit Allocation Scheme.