Attractive protein–protein interactions (PPI) in concentrated monoclonal antibody (mAb) solutions may lead to reversible oligomers (clusters) that impact colloidal stability and viscosity. Herein, the PPI are tuned for two mAbs via the addition of arginine (Arg), NaCl, or ZnSO4 as characterized by the structure factor (S eff(q)) with small-angle X-ray scattering (SAXS). The SAXS data are fit with molecular dynamics simulations by placing a physically relevant short-range attractive interaction on selected beads in coarse-grained 12-bead models of the mAb shape. The optimized 12-bead models are then used to differentiate key microstructural properties, including center of mass radial distribution functions (g COM(r)), coordination numbers, and cluster size distributions (CSD). The addition of cosolutes results in more attractive S eff(q) relative to the no cosolute control for all systems tested, with the most attractive systems showing an upturn at low q. Only the All1 model with an attractive site in each Fab and Fc region (possessing Fab–Fab, Fab–Fc, and Fc–Fc interactions) can reproduce this upturn, and the corresponding CSDs show the presence of larger clusters compared to the control. In general, for models with similar net attractions, i.e., second osmotic virial coefficients, the size of the clusters increases as the attraction is concentrated on a smaller number of evenly distributed beads. The cluster size distributions from simulations are used to improve the understanding and prediction of experimental viscosities. The ability to discriminate between models with bead interactions at particular Fab and Fc bead sites from SAXS simulations, and to provide real-space properties (CSD and g COM(r)), will be of interest in engineering protein sequence and formulating protein solutions for weak PPI to minimize aggregation and viscosities.

The ability to design and formulate mAbs to minimize attractive interactions at high concentrations is important for protein processing, stability, and administration, particularly in subcutaneous delivery, where high viscosities are often challenging. The strength of protein−protein interactions (PPIs) of an IgG1 and IgG4 monoclonal antibody (mAb) from low to high concentration was determined by static light scattering (SLS) and used to understand viscosity data. The PPI were tuned using NaCl and five organic ionic co-solutes. The PPI strength was quantified by the normalized structure factor S(0)/S(0) HS and Kirkwood−Buff integral G 22 /G 22,HS (HS = hard sphere) determined from the SLS data and also by fits with (1) a spherical Yukawa potential and (2) an interacting hard sphere (IHS) model, which describes attraction in terms of hypothetical oligomers. The IHS model was better able to capture the scattering behavior of the more strongly interacting systems (mAb and/or co-solute) than the spherical Yukawa potential. For each descriptor of PPI, linear correlations were obtained between the viscosity at high concentration (200 mg/mL) and the interaction strengths evaluated both at low (20 mg/mL) and high concentrations (200 mg/mL) for a given mAb. However, the only parameter that provided a correlation across both mAbs was the oligomer mass ratio (m oligomer /m monomer+dimer ) from the IHS model, indicating the importance of self-association (in addition to the direct influence of the attractive PPI) on the viscosity.

A revised version of this manuscript has been accepted in the AIChE Journal [website link] and can be cited as

Oil-in-water emulsions were formed and stabilized at low amphiphile concentrations by combining hydrophilic nanoparticles (NPs) (i.e., bare colloidal silica) with a weakly interacting zwitterionic surfactant, caprylamidopropyl betaine, to generate a high hydrophilic-lipophilic balance. The weak interaction of the NPs with surfactant was quantified with contact angle measurements. Emulsions were characterized by static light scattering to determine the droplet size distributions, optical photography to quantify phase separation due to creaming, and both optical and electron microscopy to determine emulsion microstructure. The NPs and surfactant acted synergistically to produce finer emulsions with a greater stability to coalescence relative to the behavior with either NPs or surfactant alone. As a consequence of the weak adsorption of the highly hydrophilic surfactant on the anionic NPs along with the high critical micelle concentration, an unusually large surfactant concentration was available to adsorb at the oil-water interface and lower the interfacial tension. The synergy for emulsion formation and stabilization for the two amphiphiles was even greater in the case of a high-salinity synthetic seawater aqueous phase. Here, higher NP adsorption at the oil-water interface was caused by electrostatic screening of interactions between (1) NPs and the anionic oil-water interface and (2) between the NPs. This greater adsorption as well as partial flocculation of the NPs provided a more efficient barrier to droplet coalescence.

Understanding protein–protein interactions in concentrated therapeutic monoclonal antibody (mAb) solutions is desirable for improved drug discovery, processing, and administration. Here, we deduce both the net protein charge and the magnitude and geometry of short-ranged, anisotropic attractions of a mAb across multiple concentrations and cosolute conditions by comparing structure factors S(q) obtained from small-angle X-ray scattering experiments with those from molecular dynamics (MD) simulations. The simulations, which utilize coarse-grained 12-bead models exhibiting a uniform van der Waals attraction, uniform electrostatic repulsion, and short-range attractions between specific beads, are versatile enough to fit S(q) of a wide range of protein concentrations and ionic strength with the same charge on each bead and a single anisotropic short-range attraction strength. Cluster size distributions (CSDs) obtained from best fit simulations reveal that the experimental structure is consistent with small reversible oligomers in even low viscosity systems and help quantify the impact of these clusters on viscosity. The ability to systematically use experimental S(q) data together with MD simulations to discriminate between different possible protein–protein interactions, as well as to predict viscosities from protein CSDs, is beneficial for designing mAbs and developing formulation strategies that avoid high viscosities and aggregation at high concentration.

Single-ion conducting polymers such as ionomers are promising battery electrolyte materials, but it is critical to understand how rates and mechanisms of free cation transport depend on the nanoscale aggregation of cations and polymerbound anions. We perform coarse-grained molecular dynamics simulations of ionomer melts to understand cation mobility as a function of polymer architecture, background relative permittivity, and corresponding ionic aggregate morphology. In systems exhibiting percolated ionic aggregates, cations diffuse via stepping motions along the ionic aggregates. These diffusivities can be quantitatively predicted by calculating the lifetimes of continuous association between oppositely charged ions, which equal the time scales of the stepping (diffusive) motions. In contrast, predicting cation diffusivity for systems with isolated ionic aggregates requires another time scale. Our results suggest that to improve conductivity the Coulombic interaction strength should be strong enough to favor percolated aggregates but weak enough to facilitate ion dissociation.

Fluids with competing short-range attractions and long-range repulsions mimic dispersions of chargestabilized colloids that can display equilibrium structures with intermediate range order (IRO), including particle clusters. Using simulations and analytical theory, we demonstrate how to detect cluster formation in such systems from the static structure factor and elucidate links to macrophase separation in purely attractive reference fluids. We find that clusters emerge when the thermal correlation length encoded in the IRO peak of the structure factor exceeds the characteristic lengthscale of interparticle repulsions. We also identify qualitative differences between the dynamics of systems that form amorphous versus micro-crystalline clusters.

Nanoparticle (NP) clusters with diameters ranging from 20 to 100 nm are reversibly assembled from 5 nm gold (Au) primary particles coated with glutathione (GSH) in aqueous solution as a function of pH in the range of 5.4 to 3.8. As the pH is lowered, the GSH surface ligands become partially zwitterionic and form interparticle hydrogen bonds that drive the self-limited assembly of metastable clusters in <1 min. Whereas clusters up to 20 nm in size are stable against cluster-cluster aggregation for up to 1 day, clusters up to 80 nm in size can be stabilized over this period via the addition of citrate to the solution in equal molarity with GSH molecules. The cluster diameter may be cycled reversibly by tuning pH to manipulate the colloidal interactions; however, modest background cluster-cluster aggregation occurs during cycling. Cluster sizes can be stabilized for at least 1 month via the addition of PEG-thiol as a grafted steric stabilizer, where PEG-grafted clusters dissociate back to starting primary NPs at pH 7 in fewer than 3 days. Whereas the presence of excess citrate has little effect on the initial size of the metastable clusters, it is necessary for both the cycling and dissociation to mediate the GSH-GSH hydrogen bonds. In summary, these metastable clusters exhibit significant characteristics of equilibrium self-limited assembly between primary particles and clusters on time scales where cluster-cluster aggregation is not present.