Here we develop a
mechanism of protein optimization using a computational
approach known as “genetic programming”. We developed
an algorithm called Protein Optimization Engineering Tool (POET).
Starting from a small library of literature values, the use of this
tool allowed us to develop proteins that produce four times more MRI
contrast than what was previously state-of-the-art. Interestingly,
many of the peptides produced using POET were dramatically different
with respect to their sequence and chemical environment than existing
CEST producing peptides, and challenge prior understandings of how
those peptides function. While existing algorithms for protein engineering
rely on divergent evolution, POET relies on convergent evolution and
consequently allows discovery of peptides with completely different
sequences that perform the same function with as good or even better
efficiency. Thus, this novel approach can be expanded beyond developing
imaging agents and can be used widely in protein engineering.