Abstract
Enzyme engineering, though pivotal across various biotechnological domains, is often plagued by its time-consuming and labor-intensive nature. This review aims to offer an overview of supportive in silico methodologies for this demanding endeavor. Starting from methods to predict protein structures, to classification of their activity and even the discovery of new enzymes we continue with describing tools used to increase thermostability and production yields of selected targets. Subsequently, we discuss computational methods to modulate both, the activity as well as selectivity of enzymes. Last, we present recent approaches based on cutting-edge machine learning methods to redesign enzymes. With exception of the last chapter, there is a strong focus on methods easily accessible via web-interfaces or simple Python-scripts, therefore readily useable for a diverse and broad community.
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CITATION STYLE
Tripp, A., Braun, M., Wieser, F., Oberdorfer, G., & Lechner, H. (2024, October 16). Click, Compute, Create: A Review of Web-based Tools for Enzyme Engineering. ChemBioChem. John Wiley and Sons Inc. https://doi.org/10.1002/cbic.202400092
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