(713h) Protein-Protein Interactions to Model Protein Aggregation and Solubility

Protein-Protein Interactions to Model Protein Aggregation and Solubility

S. Hedberg*, A. Quigley*, J.Y.Y Heng*, D.R. Williams* and J. Liddell**

*Surface and Particle Engineering Laboratory                     **Research and Development

Department of Chemical Engineering                                     Fujifilm Diosynth Biotechnologies

Imperial College London, SW7 2BY,                                          Billingham, TS23 1LH, United  Kingdom

United Kingdom

ABSTRACT

Protein-protein molecular interactions are known to be involved in protein solution aggregation behaviour which are known to be common issue for the manufacturing of therapeutic proteins such as mAbs. A lot of effort has been made for a better understanding of aggregation, however the mechanisms leading to protein aggregation are still not fully understood. The osmotic second virial coefficient B₂₂ is a fundamental physiochemical property that describes protein-protein interactions solution, which can be a useful tool to predict aggregation propensity of proteins.

One way of predicting aggregation propensity and aggregation kinetics is self-interaction chromatography (SIC), which recently have shown to be a promising tool for not only aggregation but also solubility, crystallisation and phase behaviour of proteins. This work combines experimental work to determine B₂₂, aggregation and solubility as well as the use of currently known models in literature and new suggested models built on thermodynamic principles to fit to the experimental data.

The experimental part of the study focuses on estimating B₂₂ using SIC for a number of model proteins and therapeutics mAbs. These have been determined using a wide range of different solution conditions. For the same conditions aggregation data has been determined using SEC and solubility data.

There are a number of models available in the literature already that correlates solubility and B₂₂ for a number of model proteins [1-3]. These models have been applied to fit the experimental data to find the best overall models. The best fitting solubility models were shown to exhibit very similar inverse trends to the aggregation data plotted with B₂₂ for the same proteins. The results from these studies enabled us evaluate how the models were created to thus establish a link between B₂₂ and aggregation.

In summary this work hopes to lead to a better insight into the mechanisms of aggregation by directly comparing the experimental B₂₂ data and relating these to the thermophysical properties that governing this protein solution behaviour. The creation of this new model will enable a fast way to identify successful therapeutic candidates for the downstream and formulation processes.

REFERENCES

1.            Franco, L. and Pessôa Filho, P.d.A. (2013) On the Relationship between the Solubility of Proteins and the Osmotic Second Virial Coefficient. Brazilian Journal of Chemical Engineering. 30(1): p. 95-104.

2.            Haas, C., Drenth, J., and Wilson, W.W. (1999) Relation between the Solubility of Proteins in Aqueous Solutions and the Second Virial Coefficient of the Solution. The Journal of Physical Chemistry B. 103(14): p. 2808-2811.

3.            Ruppert, S., Sandler, S., and Lenhoff, A. (2001) Correlation between the Osmotic Second Virial Coefficient and the Solubility of Proteins. Biotechnology Progress. 17(1): p. 182-187.