Predicting Protein Interactions of Concentrated Globular Protein Solutions Using Colloidal Models

Protein interactions of α-chymotrypsinogen A (aCgn) were quantified using light scattering from low to high protein concentrations. Static light scattering (SLS) was used to determine the excess Rayleigh ratio (R^ex) and osmotic second virial coefficients (B₂₂) as a function of pH and total ionic strength (TIS). Repulsive (attractive) protein–protein interactions (PPI) were observed at pH 5 (pH 7), with decreasing repulsions (attractions) upon increasing TIS. Simple colloidal potential of mean force models (PMF) that account for short-range nonelectrostatic attractions and screened electrostatic interactions were used to fit model parameters from data for B₂₂ vs TIS at both pH values. The parameters and PMF models from low-concentration conditions were used as the sole input to transition matrix Monte Carlo simulations to predict high concentration R^ex behavior. At conditions where PPI are repulsive to slightly attractive, experimental R^ex data at high concentrations could be predicted quantitatively by the simulations. However, accurate predictions were challenging when PPI were strongly attractive due to strong sensitivity to changes in PMF parameter values. Additional simulations with higher-resolution coarse-grained molecular models suggest an approach to qualitatively predict cases when anisotropic surface charge distributions will lead to overall attractive PPI at low ionic strength, without assumptions regarding electrostatic “patches” or multipole expansions.