Binding kinetics of ultrasmall gold nanoparticles with proteins

Abstract

Synthetic ultrasmall nanoparticles (NPs) can be designed to interact with biologically active proteins in a controlled manner. However, the rational design of NPs requires a clear understanding of their interactions with proteins and the precise molecular mechanisms that lead to association/dissociation in biological media. Although much effort has been devoted to the study of the kinetics mechanism of protein corona formation on large NPs, the nature of NP-protein interactions in the ultrasmall regime is radically different and poorly understood. Using a combination of experimental and computational approaches, we studied the interactions of a model protein, CrataBL, with ultrasmall gold NPs passivated with p-mercaptobenzoic acid (AuMBA) and glutathione (AuGSH). We have identified this system as an ideal in vitro platform to understand the dependence of binding affinity and kinetics on NP surface chemistry. We found that the structural and chemical complexity of the passivating NP layer leads to quite different association kinetics, from slow and reaction-limited (AuGSH) to fast and diffusion-limited (AuMBA). We also found that the otherwise weak and slow AuGSH-protein interactions measured in buffer solution are enhanced in macromolecular crowded solutions. These findings advance our mechanistic understanding of biomimetic NP-protein interactions in the ultrasmall regime and have implications for the design and use of NPs in the crowded conditions common to all biological media.

Figure 1. Nanoparticles and CrataBL

a, Structure of p-mercaptobenzoic acid (pMBA) and glutathione (GSH) passivating ligands. b, Characterization of NP size and uniformity by dark-field scanning transmission electron microscopy. NPs are approximately 2 nm in core diameter and highly uniform (2.1 ± 0.2 nm). Scale bar, 10 nm. c, UV-visible spectra of NPs. d, Histograms of STEM measurements of nanoparticle diameter. e, Characterization of NP size and uniformity by analytical ultracentrifugation. NPs are ∼ 2 nm in core diameter based on a sedimentation coefficient of ∼ 21 S (cf. ref. [25]). NPs appear reasonably uniform as judged from the widths of their sedimentation coefficient distributions (note these widths are also affected by NP diffusion). f, Left: Surface electrostatic potential of CrataBL scaled from -5 to +5 kT/e (red to blue; calculated with APBS). Middle: surface areas (cyan) corresponding to the 16 Arg⁺ and 5 Lys⁺ residues of the protein. Right: areas corresponding to the 8 Arg⁺ and 2 Lys⁺ residues deemed to be accessible to the solvent (calculated with GetArea).

Figure 2. Steady-state fluorescence quenching of CrataBL with AuMBA and AuGSH as a function of the NaCl concentration

The CrataBL concentration was 2 μM. The lines are a guide to the eye.

Figure 3. Potential sources of heterogeneity of surface binding sites in surface plasmon resonance

a, A protein (green) is represented with three positive charge clusters of different charge densities (shades of blue). The remaining protein surface is assumed to have a uniform distribution of charges. Negatively charged NPs are assumed to bind with different affinities to the different charge clusters. b, The proteins are immobilized in random orientation to a dextran matrix (extended gray lines) by amine coupling. (i) Depending on protein orientation, only certain charge clusters may be exposed to allow binding. (ii) Immobilization to different regions in the dextran matrix may produce different extent of steric hindrance. (iii) Chemical nonuniformity of the matrix may create sub-regions with different charge and pH, which could possibly affect binding. Also represented in (iii) is the fact that NP binding can take place close to the gold surface, leading to an increased signal response. (iv) Binding avidity may result from one NP binding two or more proteins simultaneously. (v) Heterogeneity in NP size and/or surface chemistry may contribute to polydispersity of the binding constants.

Figure 4. NP-protein interactions by surface plasmon resonance

a, Analysis of AuMBA-CrataBL binding traces with the surface-site distribution model. b, The same for AuGSH-CrataBL. Phosphate buffer supplemented with 150 mM NaCl was used as running buffer. AuMBA was injected in the flow at the concentrations of 0.02, 0.05, 0.1, 0.3, 0.5 (2×), 0.7, 1, 2, 5, 10, 20 μM. For AuGSH the concentration range was 0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10, 20 μM. Shown are the experimental traces (green and blue lines), best-fit curves (red lines), and fitting residuals. c, Calculated affinity and rate constant distributions for AuMBA-CrataBL. d, The same for AuGSH-CrataBL. Circled regions indicate the major peaks in the distributions. Integration of the peaks provides the binding parameters K_D, k_on and k_off.

Figure 5. Effect of macromolecular crowding on NP-CrataBL interactions

Steady-state fluorescence quenching of CrataBL with AuMBA and AuGSH in PBS and PBS supplemented with different crowding agents (mass %). Black lines are a guide to the eye.

Figure 6. Molecular modeling and simulation of NP-protein complexation

a, Molecular surface representations of the atom-based (left column) and coarse-graining (right) models of the NPs and protein. b, Molecular surface representations of the NPs (red: −CO₂^‒ groups; blue: −NH₃⁺); despite their identical Au core sizes and coating densities the NPs have slightly different overall diameters and differ substantially in surface chemistry, charge distribution, and topography. c, Potentials of mean force, V, driving NP-protein association (r is the distance between the centers of mass) showing the (loosely-held) pre-bound state 2 and the (tight) bound state 1; dotted line indicates the inferred change of the potential due to the CrataBL/AuGSH interfacial restructuring.