Combinatorial assembly and design of enzymes

• Published in: bioRxiv
• Main Authors: Lipsh-Sokolik, Rosalie, Khersonsky, Olga, Schroder, Sybrin P, De Boer, Casper, Shlomo Yakir Hoch, Davies, Gideon J, Overkleeft, Hermen S, Fleishman, Sarel J
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 14.12.2022
• Subjects: Enzymes
• DOI: 10.1101/2022.09.17.508230

Design of structurally diverse enzymes is constrained by long-range interactions that are needed for accurate folding. We introduce an atomistic and machine-learning strategy for Combinatorial Assembly and Design of ENZymes, CADENZ, to design fragments that combine with one another to generate diverse, low-energy structures with stable catalytic constellations. We applied CADENZ to endoxylanases and used activity-based protein profiling to recover thousands of active and 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 active enzymes. 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.Competing Interest StatementThe authors have declared no competing interest.Footnotes* Title, abstract and discussion are revised* https://github.com/Fleishman-Lab/CADENZ