Abstract
It is difficult to predict how antibodies will behave when mixed together, even after each has been independently characterized. Here, we present a statistical mechanical model for the activity of antibody mixtures that accounts for whether pairs of antibodies bind to distinct or overlapping epitopes. This model requires measuring n individual antibodies and their [Formula: see text] pairwise interactions to predict the 2n potential combinations. We apply this model to epidermal growth factor receptor (EGFR) antibodies and find that the activity of antibody mixtures can be predicted without positing synergy at the molecular level. In addition, we demonstrate how the model can be used in reverse, where straightforward experiments measuring the activity of antibody mixtures can be used to infer the molecular interactions between antibodies. Lastly, we generalize this model to analyze engineered multidomain antibodies, where components of different antibodies are tethered together to form novel amalgams, and characterize how well it predicts recently designed influenza antibodies.
Highlights
Antibodies can bind with strong affinity and exquisite specificity to a multitude of antigens
We investigate the specific case of monoclonal antibodies targeting a cancer-causing receptor or the influenza virus and develop a statistical mechanical framework that predicts the effectiveness of a mixture of antibodies
The power of this model lies in its ability to make a large number of predictions based on a limited amount of data
Summary
Antibodies can bind with strong affinity and exquisite specificity to a multitude of antigens. Due to their clinical and commercial success, antibodies are one of the largest and fastest. Modeling the mechanisms of antibody mixtures research/divisions/public-health-sciences-division/ research/computational-biology/mahan-fellowship. Html) from the Fred Hutchinson Cancer Center (TE) and the NIAID of the NIH Nih.gov/) through R01 AI127893 and R01 AI141707 (JBD). JDB is an investigator of the Howard Hughes Medical Institute The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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