Publication details

Computational design of enzymes for biotechnological applications

Authors

PLANAS IGLESIAS Joan MARQUES Sérgio Manuel PINTO VIDAL Felipe Augusto MUSIL Miloš ŠTOURAČ Jan DAMBORSKÝ Jiří BEDNÁŘ David

Year of publication 2021
Type Article in Periodical
Magazine / Source BIOTECHNOLOGY ADVANCES
MU Faculty or unit

Faculty of Science

Citation
Web https://www.sciencedirect.com/science/article/pii/S0734975021000021?via%3Dihub
Doi http://dx.doi.org/10.1016/j.biotechadv.2021.107696
Keywords Biocatalyst; Catalytic efficiency; Computational enzyme design; Enzyme biotechnologies; Protein engineering; Protein dynamics; Software; Solubility; Stability
Description Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.
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