Assess aggregation risk at higher protein concentrations with G22

Significance of the Topic

Weak nonspecific protein interactions can compromise colloidal stability, especially at high concentrations typical for biopharmaceutical formulations. Early detection of aggregation risk using light scattering parameters such as kD, B22, and the Kirkwood-Buff integral G22 helps streamline drug development and ensure product quality.

Objectives and Study Overview

This application note demonstrates the use of the G22 parameter measured with the Uncle platform to assess aggregation propensity of alpha-chymotrypsinogen and a monoclonal antibody across a range of protein concentrations and buffer conditions. The goal is to compare kD, B22 and G22 metrics and highlight G22’s sensitivity to high-concentration crowding effects.

Methodology and Instrumentation

A calibration with toluene established instrument constants. Alpha-chymotrypsinogen (25.7 kDa) and Adalimumab (144 kDa) were prepared in citrate, phosphate, and acetate buffers with or without NaCl over pH 3.5–7. Samples at 14–100 mg/mL were analyzed in triplicate on the Uncle platform using simultaneous static (SLS) and dynamic light scattering (DLS) acquisitions. Scattering intensities were converted to R90/K ratios, then to kD, B22 or G22 depending on concentration range and validity criteria.

Main Results and Discussion

• Alpha-chymotrypsinogen in phosphate buffer displayed positive slopes of R90/K and positive G22, indicating attractive interactions enhanced by salt.
• In acetate buffer without salt, G22 became negative at high concentrations, reflecting net repulsion and improved colloidal stability.
• Adalimumab in its formulation showed negative G22 throughout the tested range, confirming net-repulsive interactions unsuitable for B22 analysis at these concentrations.

Benefits and Practical Applications

By integrating kD, B22, and G22 measurements in a single experiment using minimal sample volume (9 µL), researchers can rapidly screen formulation conditions, predict aggregation risk at industrial concentrations, and optimize buffer composition early in development.

Future Trends and Opportunities

• Applying computational design to predict and modulate high-concentration interactions.
• Extending G22 analysis to complex biologics and multi-component formulations.
• Automating high-throughput formulation screening for personalized medicine.

Conclusion

The Uncle platform’s capability to measure G22 alongside kD and B22 offers a comprehensive toolkit for assessing colloidal stability across low and high protein concentrations. This approach enables informed formulation strategies to mitigate aggregation risk in biopharmaceutical development.

Instrumentation Used

• Unchained Labs Uncle platform with fluorescence, SLS, and DLS detection.
• Calibration standard: toluene for scattering intensity.

References

1. O’Brien CJ, Blanco MA, Costanzo JA et al. Modulating non-native aggregation and electrostatic protein-protein interactions with computationally designed single-point mutations. Protein Eng Des Sel. 2016;29(6):231-243.
2. Woldeyes MA, Rubio CC, Furst EM, Roberts CJ. Predicting protein interactions of concentrated globular protein solutions using colloidal models. J Phys Chem B. 2017;121:4756-4767.