The design of structurally diverse enzymes is constrained by long-range interactions that are necessary for accurate folding.
Combinatorial assembly and design of enzymes (CADENZ) is a novel atomistic and machine-learning strategy for designing protein fragments that freely combine to generate diverse, low-energy structures with stable catalytic constellations.
I applied CADENZ to endoxylanases and used activity-based protein profiling to recover thousands of structurally diverse enzymes. Functional designs exhibit high active-site preorganization and more stable and compact packing outside the active site. Implementing these lessons into CADENZ led to a tenfold improved hit rate and >10,000 recovered enzymes, with >80 mutations from any natural one, demonstrating a high level of control over enzyme design principles.
This design-test-learn loop can be applied, in principle, to any modular protein family, yielding huge diversity and general lessons on protein design principles.
