Mitigation of reversible self-association and viscosity in a human IgG1 monoclonal antibody by rational, structure-guided Fv engineering

• Published in: mAbs Vol. 8; no. 5; pp. 941 - 950
• Main Authors: Geoghegan, James C, Fleming, Ryan, Damschroder, Melissa, Bishop, Steven M, Sathish, Hasige A, Esfandiary, Reza
• Format: Journal Article
• Language: English
• Published: United States Taylor & Francis 03.07.2016
• Subjects: Antibodies, Monoclonal - chemistry; Humans; Immunoglobulin G - chemistry; Immunoglobulin Variable Region - chemistry; Models, Molecular; Protein Engineering - methods; Viscosity; viscosity; homology modeling; reversible self-association; DLS; Antibody engineering; AC-SINS; monoclonal antibody; antibody developability
• ISSN: 1942-0862; 1942-0870
• DOI: 10.1080/19420862.2016.1171444

Undesired solution behaviors such as reversible self-association (RSA), high viscosity, and liquid-liquid phase separation can introduce substantial challenges during development of monoclonal antibody formulations. Although a global mechanistic understanding of RSA (i.e., native and reversible protein-protein interactions) is sufficient to develop robust formulation controls, its mitigation via protein engineering requires knowledge of the sites of protein-protein interactions. In the study reported here, we coupled our previous hydrogen-deuterium exchange mass spectrometry findings with structural modeling and in vitro screening to identify the residues responsible for RSA of a model IgG1 monoclonal antibody (mAb-C), and rationally engineered variants with improved solution properties (i.e., reduced RSA and viscosity). Our data show that mutation of either solvent-exposed aromatic residues within the heavy and light chain variable regions or buried residues within the heavy chain/light chain interface can significantly mitigate RSA and viscosity by reducing the IgG's surface hydrophobicity. The engineering strategy described here highlights the utility of integrating complementary experimental and in silico methods to identify mutations that can improve developability, in particular, high concentration solution properties, of candidate therapeutic antibodies.