Ensemble-based enzyme design can recapitulate the effects of laboratory directed evolution in silico

• Published in: Nature communications 2020-09, Vol.11 (1), p.4808-4808, Article 4808
• Main Authors: Broom, Aron, Rakotoharisoa, Rojo V., Thompson, Michael C., Zarifi, Niayesh, Nguyen, Erin, Mukhametzhanov, Nurzhan, Liu, Lin, Fraser, James S., Chica, Roberto A.
• Format: Article
• Language: English
• Subjects: 631/114/469; 631/45/603; 631/535/1266; 82/80; BASIC BIOLOGICAL SCIENCES; Humanities and Social Sciences; multidisciplinary; Science; Science (multidisciplinary)
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-020-18619-x

The creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we use room-temperature X-ray crystallography to study changes in the conformational ensemble during evolution of the designed Kemp eliminase HG3 ( k cat / K M 146 M −1 s −1 ). We observe that catalytic residues are increasingly rigidified, the active site becomes better pre-organized, and its entrance is widened. Based on these observations, we engineer HG4, an efficient biocatalyst ( k cat / K M 103,000 M −1 s −1 ) containing key first and second-shell mutations found during evolution. HG4 structures reveal that its active site is pre-organized and rigidified for efficient catalysis. Our results show how directed evolution circumvents challenges inherent to enzyme design by shifting conformational ensembles to favor catalytically-productive sub-states, and suggest improvements to the design methodology that incorporate ensemble modeling of crystallographic data. Kemp eliminases are artificial enzymes that catalyze the concerted deprotonation and ring-opening of benzisoxazoles. Here, the authors use room-temperature X-ray crystallography to investigate changes to the conformational ensemble of the Kemp eliminase HG3 along a directed evolutionary trajectory, and develop an experimentally guided, ensemble-based computational enzyme design procedure.