Abstract
Protein engineering and formulation optimization strategies can be taken to minimize protein aggregation in the biopharmaceutical industry. Short-term stability measures such as the midpoint transition temperature (Tm) for global unfolding provide convenient surrogates for longer-term (e.g., 2-year) degradation kinetics, with which to optimize formulations on practical time-scales. While successful in some cases, their limitations have not been fully evaluated or understood. Tm values are known to correlate with chemical degradation kinetics for wild-type granulocyte colony stimulating factor (GCSF) at pH 4-5.5. However, we found previously that the Tm of an antibody Fab fragment only correlated with its rate of monomer loss at temperatures close to the Tm. Here we evaluated Tm, the fraction of unfolded protein (fT) at temperature T, and two additional short-term stability measures, for their ability to predict the kinetics of monomer and bioactivity loss of wild-type GCSF and four variants, at 37 °C, and in a wide range of formulations. The GCSF variants introduced one to three mutations, giving a range of conformational stabilities spanning 7.8 kcal mol-1. We determined the extent to which the formulation rank order differs across the variants when evaluated by each of the four short-term stability measures. All correlations decreased as the difference in average Tm between each pair of GCSF variants increased. The rank order of formulations determined by Tm was the best preserved, with R2-values >0.7. Tm-values also provided a good predictor (R2 = 0.73) of the aggregation rates, extending previous findings to include GCSF variant-formulation combinations. Further analysis revealed that GCSF aggregation rates at 37 °C were dependent on the fraction unfolded at 37 °C (fT37), but transitioned smoothly to a constant baseline rate of aggregation at fT37 < 10-3. A similar function was observed previously for A33 Fab formulated by pH, ionic strength, and temperature, without excipients. For GCSF, all combinations of variants and formulations fit onto a single curve, suggesting that even single mutations destabilized by up to 4.8 kcal mol-1, are insufficient to change significantly the baseline rate of aggregation under native conditions. The baseline rate of aggregation for GCSF under native conditions was 66-fold higher than that for A33 Fab, highlighting that they are a specific feature of each native protein structure, likely to be dependent on local surface properties and dynamics.
Highlights
Minimizing protein aggregation remains a major challenge to the biopharmaceutical industry
6.0, 50 mM sodium phosphate pH 7.0, 50 mM 4-(2-hydroxyethyl)piperazine-1ethanesulfonic acid (HEPES) pH 8.0, predict the kinetics of monomer loss from aggregation? Would these apply to the kinetics for loss of bioactivity? Given the potential of protein engineering to modify aggregation kinetics, how well do formulation rankings for one variant predict those of other related variants? Do aggregation mechanisms depend on formulation conditions, and how do these changes impact on the predictive power of short-term stability measures?
granulocyte colony stimulating factor (GCSF) is already known to be most stable at low pH,[11,12] we aimed deliberately to represent a wide range of stabilities and even potentially different aggregation mechanisms
Summary
Minimizing protein aggregation remains a major challenge to the biopharmaceutical industry. It can occur during protein expression,[1] downstream processing (e.g., chromatography[2] and ultrafiltration/diafiltration3), and during storage,[4] with aggregates treated as potentially immunogenic impurities.[5]. It remains a major challenge to predict molecular variants and formulation excipients that improve stability, and minimize aggregation. The design process for formulation is typically semiempirical, making use of the generally observed effects of commonly used excipients, and has more recently made use of high-throughput screening in combination with design of experiments.[7] To speed development, formulation screens often depend on simple short-term stability measures to create an initial rank-ordering, prior to more resource-intensive (Tonset), or midpoint transition temperature (Tm) for global conformational unfolding, as well as the onset temperature at which aggregates are first detected (Tagg)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
