Adsorption of binding peptides on ZnO - towards a quantitative understanding of organic-inorganic interactions

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Bio-hybrid ZnO/peptide materials present peculiar photochemical and optoelectronic properties. Their fabrication relies on the "materials recognition" capability of the peptides, which bind selectively to specific ZnO crystal facets and thus dictate the materials microstructure and properties. With the ultimate goal to develop a rational protocol for engineering the peptide sequences in order to steer the fabrication of ZnO/peptide hybrids with desired properties, in this project we aim at a fundamental understanding of the peptides' materials recognition capability and the origin of a materials-selective binding strength. To reach this goal we will perform precise quantification of the interactions between non-polar ZnO crystal facets and peptides in terms of binding affinity (free energy) and molecular structure. To this aim we will employ a large variety of experimental techniques and combine them with quantitatively accurate molecular modelling. Non-polar (10-10) ZnO binding sequences will be selected via phage-display and their interactions to ZnO crystal surfaces will be characterized amongst other techniques by point mutations of their amino acid sequences. Binding sites will be characterized via NMR. The binding affinity will be evaluated via Quartz-Crystal-Microbalance, Isothermal Titration Calorimetry, AFM force spectroscopy and Surface Plasmon Resonance methods. Simulations will employ state-of-the art advanced sampling molecular dynamics (MD) methods based on metadynamics, replica-exchange with solute tempering and steered MD. The simulations will deliver theoretical estimates of the free energy of binding that can be directly compared to the experimentally determined ones. These methods will also predict structural changes associated with the process of peptide adsorption on ZnO surfaces, that can be compared with experimental results of NMR, Circular Dichroism and Infrared spectroscopy. The complementary and mutually supportive simulation and experimental approaches will help shed light on the peptides' recognition capability in a way that we expect to be transferable to other material/peptide systems, eventually enabling a knowledge-based design of inorganic-binding peptides with tailored binding strengths.