Accelerating Enzyme Evolution: Computational Methods for Optimizing Mutations

Computational methods play a crucial role in accelerating enzyme evolution by predicting effective mutations and identifying optimal solutions within the local sequence space. Combining different computational strategies allows for wider sampling and optimization, minimizing experimental efforts and significantly speeding up the enzyme evolution process. This review article summarizes key advancements in computational methods for enzyme engineering, focusing on strategies that combine different approaches for improved accuracy and efficiency.

Here are some review articles that discuss the development of computational methods for enzyme evolution:

1. 'Computational methods for enzyme engineering' by M. J. Harms and F. H. Arnold (Current Opinion in Structural Biology, 2019)
2. 'Computational methods for protein engineering' by J. A. Maguire and J. M. Titchmarsh (Current Opinion in Chemical Biology, 2019)
3. 'Computational methods for enzyme design' by M. R. Bedbrook and F. H. Arnold (Current Opinion in Biotechnology, 2012)
4. 'Computational approaches to enzyme design: current state and future directions' by J. B. Siegel and D. Baker (Current Opinion in Chemical Biology, 2011)