Predicting Protein Interactions of Concentrated Globular Protein Solutions Using Colloidal Models

Area of Science:

• Biochemistry
• Physical Chemistry
• Protein Science

Background:

• Understanding protein-protein interactions (PPI) is crucial for various biological processes.
• α-chymotrypsinogen A (aCgn) is a model protein for studying protein behavior.
• Protein interactions are influenced by factors like pH and ionic strength.

Purpose of the Study:

• To quantify protein interactions of aCgn across a range of concentrations.
• To investigate the influence of pH and total ionic strength (TIS) on PPI.
• To develop and validate predictive models for PPI behavior.

Main Methods:

• Static light scattering (SLS) was employed to measure excess Rayleigh ratio (R^ex) and osmotic second virial coefficients (B₂₂).
• Colloidal potential of mean force (PMF) models were used to fit experimental data.
• Transition matrix Monte Carlo simulations were utilized to predict high-concentration behavior.

Main Results:

• Repulsive PPI were observed at pH 5, while attractive PPI were seen at pH 7.
• Increasing TIS reduced both repulsive and attractive PPI.
• Simulations quantitatively predicted R^ex at repulsive to slightly attractive PPI conditions.
• Strongly attractive PPI presented prediction challenges due to parameter sensitivity.

Conclusions:

• The study provides quantitative insights into aCgn PPI under varying conditions.
• Predictive models based on PMF and simulations show success for certain interaction regimes.
• Advanced molecular models offer potential for predicting PPI influenced by anisotropic surface charges.