The favorable interaction between proteins and nanoparticles has sparked potential applications of nanotechnology in medicine, and the unique electronic and chemical properties of nanoparticles also provide novel strategies for protein-related therapeutics. The formation of the biocorona has attracted substantial interest over the past decades. For instance, as a potential drug delivery mechanism, protein-coated nanoparticles can improve biocompatibility and increase targeting ability. However, the mechanistic details of protein-nanoparticle interactions remain poorly understood. For example, it is currently impossible to predict the orientation and structure of proteins on the nanoparticle surface, as well as the fate of the biocorona in vivo. Since the composition of the biocorona determines the biological response, identifying and stabilizing the biocorona seems critical for the further development of applications in biological system. In this study, we investigated the physicochemical properties of protein interactions with gold nanoparticles (AuNPs). Firstly, we developed an NMR-based approach for measuring the stoichiometry of protein adsorption to AuNPs, which can be generally applied to globular proteins of different size. Quantitative analysis enabled us to create a protein binding model that involves an initial association, structure reorientation and irreversible adsorption. Secondly, we measured the protein hydrogen-deuterium exchange rates and found that they were unperturbed in the presence of AuNPs, suggesting that proteins retain their globular structure upon adsorption. Finally, we investigated the electrostatic contribution to binding, and we identified a dynamically changing surface in which the factors of net charge, binding affinity and protein size play distinct roles at different phases.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-1608 |
| Date | 07 May 2016 |
| Creators | Wang, Ailin |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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