Physicochemical Rules for Identifying Monoclonal Antibodies with Drug-like Specificity

The
ability of antibodies to recognize their target antigens with
high specificity is fundamental to their natural function. Nevertheless,
therapeutic antibodies display variable and difficult-to-predict levels
of nonspecific and self-interactions that can lead to various drug
development challenges, including antibody aggregation, abnormally
high viscosity, and rapid antibody clearance. Here we report a method
for predicting the overall specificity of antibodies in terms of their
relative risk for displaying high levels of nonspecific or self-interactions
at physiological conditions. We find that individual and combined
sets of chemical rules that limit the maximum and minimum numbers
of certain solvent-exposed amino acids in antibody variable regions
are strong predictors of specificity for large panels of preclinical
and clinical-stage antibodies. We also demonstrate how the chemical
rules can be used to identify sites that mediate nonspecific interactions
in suboptimal antibodies and guide the design of targeted sublibraries
that yield variants with high antibody specificity. These findings
can be readily used to improve the selection and engineering of antibodies
with drug-like specificity.