  Immunogenicity is a major problem during the development of biotherapeutics
since it can lead to rapid clearance of the drug and adverse reactions. The
challenge for biotherapeutic design is therefore to identify mutants of the
protein sequence that minimize immunogenicity in a target population whilst
retaining pharmaceutical activity and protein function. Current approaches are
moderately successful in designing sequences with reduced immunogenicity, but
do not account for the varying frequencies of different human leucocyte antigen
alleles in a specific population and in addition, since many designs are
non-functional, require costly experimental post-screening. Here we report a
new method for de-immunization design using multi-objective combinatorial
optimization that simultaneously optimizes the likelihood of a functional
protein sequence at the same time as minimizing its immunogenicity tailored to
a target population. We bypass the need for three-dimensional protein structure
or molecular simulations to identify functional designs by automatically
generating sequences using probabilistic models that have been used previously
for mutation effect prediction and structure prediction. As proof-of-principle
we designed sequences of the C2 domain of Factor VIII and tested them
experimentally, resulting in a good correlation with the predicted
immunogenicity of our model.
