Gold nanoparticles (AuNPs) associate strongly with proteins when used as a nanoscale drug carrier in vivo. It is recognized that the structure and function of a protein can be affected upon surface adsorption. To understand the structural properties of the adsorbed protein, we developed a residue-based affinity scale obtained from competitive binding to predict the bound orientation of a given protein and therefore its function on AuNP. A total of 20 K13X GB3 variants are generated by mutating the key binding residue K13 into each of the 19 amino acids, and a series of host-guest binding experiments are performed to quantify the affinity scale of each residue for AuNP with NMR spectroscopy. The effects of size, charge, and hydrophobicity of each residue on AuNP-binding are systematically evaluated. Our results show that, for nonpolar residues, the steric size is the dominant factor during competition for an AuNP surface, as the affinity scale decreases linearly with increasing side chain volumes. Importantly, time-resolved 2D NMR indicates the adsorption kinetics and thermodynamics are drastically different for each variant when competition is present. Combined with the surface accessibility of a residue, the affinity scale is applied to predict the binding surface and function of two selected enzymes on an AuNP. With its predictability successfully validated by activity assays, the affinity scale should be widely applicable for guiding the fabrication of AuNP-based nanomedicines using active biomolecules.

Predicting protein function and orientation on a gold nanoparticle surface using a residue-based affinity scale

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