Characterizing Reversible Protein Association at Moderately High Concentration Via Composition-Gradient Static Light...

Area of Science:

• Biochemistry
• Physical Chemistry
• Biophysics

Background:

• Analyzing weakly self-associating macromolecules at high concentrations (above a few g/L) is challenging.
• Thermodynamic nonideality confounds traditional association signal analysis.
• Complex association states further complicate nonideality corrections.

Purpose of the Study:

• To develop a simplified method for accounting for thermodynamic nonideality in composition-gradient static light scattering (CG-MALS).
• To accurately determine the stoichiometry and binding affinity of self-associating proteins in concentrated solutions.
• To establish CG-MALS with nonideality corrections as a key technology for studying macromolecular interactions.

Main Methods:

• Application of a novel, simplified nonideality correction to CG-MALS data.
• Characterization of protein self-association stoichiometry and binding affinity.
• Comparison of results with previous sedimentation equilibrium and dynamic light scattering analyses.

Main Results:

• The simplified nonideality correction effectively accounts for confounding effects in CG-MALS.
• Accurate determination of protein stoichiometry and binding affinity was achieved.
• Results were self-consistent and aligned with prior predictions of self-association.

Conclusions:

• Composition-gradient multi-angle static light scattering with nonideality corrections is a critical technology.
• This method enables robust characterization of associative interactions in concentrated macromolecular solutions.
• The approach simplifies the analysis of complex self-association equilibria.