Efficient protein engineering by combining computational design and directed evolution

The use of enzymes in industrial catalysis can result in large environmental benefits. Enzymes often have a high activity and specificity and thereby are able to convert raw materials efficiently into products. However, enzymes are usually not stable enough to be used in industrial processes. This thesis describes the FRESCO method, which was developed to design more stable enzyme variants. This computational approach calculates the 3D structures of mutant enzymes and predicts their stability. It subsequently designs more stable mutant enzymes, which are tested experimentally. Using this method, more stable variants of a haloalkane dehalogenase and a limonene epoxide hydrolase were designed, which could be used at 20 to 30°C higher temperatures without unfolding. The analogous CASCO approach was used to design limonene epoxide hydrolase variants with a higher enantioselectivity. This resulted in the discovery of different mutants that were able to produce either enantiomer of a range of epoxides with high selectivity. Such high selectivity is often required for the synthesis of active pharmaceutical ingredients. Both FRESCO and CASCO were able to discover improved variants after screening only 50 to 200 mutants, which is a significant improvement compared to other approaches. Furthermore, the 3D structures of the improved variants were elucidated. A comparison between the predicted and elucidated structure revealed that the employed methods accurately the 3D structures of mutants. The developed FRESCO and CASCO methods will allow for more efficient protein engineering in the future.