A coarse-grained xDLVO model for colloidal protein-protein interactions.

Area of Science:

• Biophysics
• Physical Chemistry
• Biotechnology

Background:

• Protein-protein interactions (PPIs) govern protein solubility, aggregation, and crystallization, crucial for biotechnology.
• Current models, like extended Derjaguin-Landau-Verwey-Overbeek (xDLVO), are limited in quantitative prediction and require experimental fitting.
• Estimating PPIs via the osmotic second virial coefficient (B22) is vital but challenging.

Purpose of the Study:

• To develop an advanced model for predicting protein-protein interactions (PPIs).
• To enhance the quantitative and predictive capabilities of existing PPI models.
• To reduce reliance on experimental fitting for PPI calculations.

Main Methods:

• Developed an extended xDLVO model incorporating coarse-grained protein representation (xDLVO-CG).
• Included an additional ion-protein dispersion interaction term in the model.
• Applied the model to four proteins: lysozyme, subtilisin, bovine serum albumin, and immunoglobulin G1.

Main Results:

• The xDLVO-CG model achieved semi-quantitative agreement with experimental B22 values for four diverse proteins.
• The model provided predictive PPI calculations without needing to fit to experimental data.
• Demonstrated improved accuracy over previous xDLVO models.

Conclusions:

• The xDLVO-CG model represents a significant advancement towards predictive PPI calculations.
• This model offers improved transferability across different protein types.
• Further development of the xDLVO-CG model could enhance control over biotechnological processes involving proteins.