(491g) Prediction of Aggregation Potential for Protein/Excipient Systems

Proteins have powerful applications in medicine, and the number of candidate protein drugs is rapidly increasing. However, protein function is very sensitive to conformation. A common problem with protein drugs is aggregation during storage, which renders the drug ineffective and potentially dangerous. One method for preventing protein aggregation is the addition of one or more excipients. The development of models to predict aggregation rates for protein/excipient systems based on structural parameters will enable the design of excipients which more effectively hinder aggregation, while also satisfying many other property targets. This project develops correlations between the properties of a protein and structural parameters of a potential excipients, and the aggregation potential of the solution mixture. These predictive models can then be used within an optimization framework to design novel excipients which improve on the current limited options.

Aggregation rate measurements for various protein/excipient systems was collected from the literature. These data were correlated with basic structural descriptors of the proteins used, such as percent alpha-helical character or the number of disulfide bonds, along with protein surface descriptors, including hydrophobic and ionic surface areas. An initial statistical analysis indicated a correlation between hydrophobic surface area of a protein and the protein's aggregation potential (without excipient). Based on these initial findings, a larger and more consistent data set has been collected. This new data set is being correlated with our structural descriptors to improve the accuracy of our initial correlations to create a model suitable for use within a molecular design algorithm.

Several proteins, including myoglobin, ribonuclease, and calmodulin were mixed with each of a set of selected excipients (trehalose, guanidine hydrochloride, and poly(vinyl pyrrolidone) ) and lyophilized. After lyophilization, the proteins were subjected to an accelerated stability test. The percent aggregation of each protein sample was identified using size exclusion chromatography at four time intervals. For structural description of the excipient molecules, molecular connectivity indices were used. This data was compiled along with the results from the aggregation potential experiments and protein structural and surface information and a set of structure-property correlations were created using this improved data set.

These correlations show a significant relationship between the hydrophobic surface area of the protein, the number of hydrophobic functional groups on the excipient, and the aggregation potential of a protein. These correlations will be used to design novel excipients, which after synthesis and testing could be used to improve protein drug stability.