Designed active-site library reveals thousands of functional GFP variants

Mutations in a protein active site can lead to dramatic and useful changes in protein activity. The active site, however, is extremely sensitive to mutations due to a high density of molecular interactions, drastically reducing the likelihood of obtaining functional multipoint mutations. We introduce an atomistic and machine-learning-based approach called htFuncLib to design a sequence space in which mutations form low-energy combinations that mitigate the risk from incompatible interactions. We screened 11 million htFuncLib designs that targeted the GFP chromophore-binding pocket and isolated >16,000 unique fluorescent designs encoding as many as eight active-site mutations. Many designs exhibit substantial and useful diversity in stability and activity. By eliminating incompatible active-site mutations, htFuncLib generates a greater diversity of functional sequences than evolutionary or mutational scanning approaches for optimizing enzymes, binders, and other functional proteins.