Machine learning for enzyme engineering, selection and design

Abstract Machine learning is a useful computational tool for large and complex tasks such as those in the field of enzyme engineering, selection and design. In this review, we examine enzyme-related applications of machine learning. We start by comparing tools that can identify the function of an en...

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Bibliographic Details
Published in:Protein engineering, design and selection design and selection, 2021-07, Vol.34
Main Authors: Feehan, Ryan, Montezano, Daniel, Slusky, Joanna S G
Format: Article
Language:English
Subjects:
Review
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Summary:Abstract Machine learning is a useful computational tool for large and complex tasks such as those in the field of enzyme engineering, selection and design. In this review, we examine enzyme-related applications of machine learning. We start by comparing tools that can identify the function of an enzyme and the site responsible for that function. Then we detail methods for optimizing important experimental properties, such as the enzyme environment and enzyme reactants. We describe recent advances in enzyme systems design and enzyme design itself. Throughout we compare and contrast the data and algorithms used for these tasks to illustrate how the algorithms and data can be best used by future designers. Graphical Abstract Graphical Abstract
ISSN:1741-0126
1741-0134
DOI:10.1093/protein/gzab019