Prediction and Reduction of the Aggregation of Monoclonal Antibodies. Issue 8 (21st April 2017) - van der Kant, Rob; Karow-Zwick, Anne R.; Van Durme, Joost; Blech, Michaela; Gallardo, Rodrigo; Seeliger, Daniel; Aßfalg, Kerstin; Baatsen, Pieter; Compernolle, Griet; Gils, Ann; Studts, Joey M.; Schulz, Patrick; et al.
Abstract: Protein aggregation remains a major area of focus in the production of monoclonal antibodies. Improving the intrinsic properties of antibodies can improve manufacturability, attrition rates, safety, formulation, titers, immunogenicity, and solubility. Here, we explore the potential of predicting and reducing the aggregation propensity of monoclonal antibodies, based on the identification of aggregation-prone regions and their contribution to the thermodynamic stability of the protein. Although aggregation-prone regions are thought to occur in the antigen binding region to drive hydrophobic binding with antigen, we were able to rationally design variants that display a marked decrease in aggregation propensity while retaining antigen binding through the introduction of artificial aggregation gatekeeper residues. The reduction in aggregation propensity was accompanied by an increase in expression titer, showing that reducing protein aggregation is beneficial throughout the development process. The data presented show that this approach can significantly reduce liabilities in novel therapeutic antibodies and proteins, leading to a more efficient path to clinical studies. Graphical Abstract: Highlights: Antibody aggregation continues to challenge the development of monoclonal antibodies for therapeutic applications. In the current manuscript, we apply our understanding of the interrelatedness of protein structure and aggregation and the particular role of aggregation gatekeeper residues to predict and engineer the solubility of monoclonal antibodies. This represents a novel rational approach to predict and redesign the solubility of monoclonal antibodies, an approach that could represent a significant improvement in the quality and safety of candidate selection during therapeutic antibody development.