Recent advances in rational approaches for enzyme engineering

By K. Steiner, Helmut Schwab. 2012

160 citations recorded by the source corpus.

Enzymes are an attractive alternative in the asymmetric syntheses of chiral building blocks. To meet the requirements of industrial biotechnology and to introduce new functionalities, the enzymes need to be optimized by protein engineering. This article specifically reviews rational approaches for enzyme engineering and de novo enzyme design involving structure-based approaches developed in recent years for improvement of the enzymes’ performance, broadened substrate range, and creation of novel functionalities to obtain products with high added value for industrial applications.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

Evolutionary context-integrated deep sequence modeling for protein engineering (2020, background): “Rational design optimizes the protein properties by making precise site-specific mutations based on detailed knowledge of structure, mechanism, and dynamics [2] .”
Single-sequence protein structure prediction using language models from deep learning (2021, background): “Reducing this cost would enable many practical applications in enzymology and therapeutics including designing new functions 14–16 , raising thermostability 17 , altering pH sensitivity 18 , and increasing compatibility with organic solvents 19 .”
Single-sequence protein structure prediction using language models and deep learning (2022, background): “Fast predictions for large numbers of long proteins would enable many practical applications in enzymology, therapeutics and chemical engineering, including designing new functions 14–16 , raising thermostability 17 , altering pH sensitivity 18 and increasing compatibility with organic solvents 19 .”