Protein-Protein Interactions, Clustering, and Rheology for Bovine IgG up to High Concentrations Characterized by Small Angle X-Ray Scattering and Molecular Dynamics Simulations

Abstract

A systematic understanding of intermolecular interactions is necessary for designing concentrated monoclonal and polyclonal antibody solutions with reduced viscosity and enhanced stability. Here, we determine the effects of pH and cosolute on the strength and geometry of short-range anisotropic protein-protein attractions for a polyclonal bovine IgG by comparing intensities [I(q)] obtained from small-angle X-ray scattering to those computed in molecular dynamics simulations with 12-bead models. As our model embodies key features of the protein shape, it can describe the experimental I(q) for solutions of 10-200 mg/mL protein with only a small (<1 k B T) variation in the model's well depth. At high concentration, small changes in the interaction potential produce large increases in clustering given the close interprotein spacing. Reducing the pH below the pI or adding NaCl weakens short-range anisotropic attractions but not enough to remove large reversible oligomers that raise viscosity. In contrast, for arginine added at pH 5.5, a uniform attraction model is sufficient to describe the I(q) that plateaus at low q. With primarily monomers and dimers, the viscosity is reduced relative to the other systems that have larger clusters as described with a model that includes the cluster size distribution.

Temperature Dependence of Protein Solution Viscosity and Protein–Protein Interactions: Insights into the Origins of High-Viscosity Protein Solutions

“…These contributions may include hydrodynamic interactions, short-ranged weak anisotropic interactions, or microstructures, which might be assessed by examining the impact of temperature on solution viscosity under a given solution condition. 33,38,62,63 To quantify the effect of temperature on solution viscosity, the Andrade-Eyring equation was used to determine the values of E a,η and A under a given formulation condition and protein concentration. For the most part, linear relations between ln η and 1/T were observed within the temperature and concentration ranges examined (see below and the Supporting Information).…”

Computational models for studying physical instabilities in high concentration biotherapeutic formulations

“…The resulting CG model was used for calculating the cluster size distribution of the solution, which in turn was used to reproduce the solution viscosity via an empirical equation. 88 This approach predicted reasonably well the changes in viscosity with respect to protein concentrations for both mAbs in most of the tested formulations, as well as for a polyclonal IgG; 198 however, it failed to capture these changes when protein clustering is driven by strong anisotropic interactions. More recently, Izadi et al .…”

“… 85 and Chowdhury et al . 88 , 198 used a 12 CG-site model to evaluate experimental from two different mAbs and a bovine immunoglobulin in various formulation conditions, where the CG-sites interact through a weak short-range attraction and an electrostatic repulsion. Although these reports show that the 12 CG-site model is able to reasonably reproduce the regions of related to the bulk behavior and nearest-neighbor shell (i.e., the low- and intermediate- regions), the addition of a strong attractive potential to the outer CG-sites of the model is required for fitting the data from net attractive formulations.…”

Nano Differential Scanning Fluorimetry-Based Thermal Stability Screening and Optimal Buffer Selection for Immunoglobulin G

“…Protein-protein interactions (PPIs) are known to play a role as a major factor inducing aggregation and high viscosity in antibody formulations [30][31][32]. To elucidate the reasons for the difference in the degree of aggregation and viscosity of IgGs in the sodium acetate and citrate buffers, two measures of colloidal stability, the diffusion interaction parameter (k D ) and the second virial coefficient (A 2 ), were measured by DLS and SLS, respectively (Figure 7).…”