Interactions between functionalized noble-metal particles in aqueous solution are central to applications relying on controlled equilibrium association. Herein we obtain the potentials of mean force (PMF) for pair-interactions between functionalized gold nanoparticles (AuNPs) in physiological saline, based upon > 1000-ns experiments in silico of all-atom model systems under equilibrium and nonequilibrium conditions. Four types of functionalization are built by coating the globular Au144 cluster each with 60 thiolate groups: GS-AuNP (glutathionate), PhS-AuNP (thiophenol), CyS-AuNP (cysteinyl), and p-APhS-AuNP (para-aminothiophenol), which are, respectively, negatively charged, hydrophobic (neutral-nonpolar), hydrophilic (neutral-polar), and positively charged at neutral pH. The results confirm the behaviour expected of neutral (hydrophilic or hydrophobic) particles in dilute aqueous environment, but the PMF curves demonstrate that the charged AuNPs interact with one another in a unique way — mediated by H2O molecules and electrolyte (Na+,Cl−) — in a physiological environment. In the case of two GS-AuNPs, the excess, neutralizing Na+ ions form a mobile (or ‘dynamic’) cloud of enhanced concentration between like-charged GS-AuNPs, inducing a moderate attraction (~ 25-kT) between them. And, to a lesser degree, for a pair of p-APhS-AuNPs, the excess, neutralizing Cl− ions (less mobile than Na+) also form a cloud of higher concentration between the two like-charged p-APhS-AuNPs, inducing weaker yet significant attractions (~ 12-kT). In the combination of one GS- and one p-APhS-AuNP, the direct, attractive Coulombic force is completely screened out while the solvation effects give rise to moderate repulsion between the two unlike-charged AuNPs.
The free energy of adsorption of proteins onto nanoparticles offers an insight into the biological activity of these particles in the body, but calculating these energies is challenging at the atomistic resolution. In addition, structural information of the proteins may not be readily available. In this work, we demonstrate how information about adsorption affinity of proteins onto nanoparticles can be obtained from first principles with minimum experimental input. We use a multiscale model of protein–nanoparticle interaction to evaluate adsorption energies for a set of 59 human blood serum proteins on gold and titanium dioxide (anatase) nanoparticles of various sizes. For each protein, we compare the results for 3D structures derived from experiments to those predicted computationally from amino acid sequences using the I-TASSER methodology and software. Based on these calculations and 2D and 3D protein descriptors, we develop statistical models for predicting the binding energy of proteins, enabling the rapid characterization of the affinity of nanoparticles to a wide range of proteins.
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