Premium
The Crucial Role of Methodology Development in Directed Evolution of Selective Enzymes
Author(s) -
Qu Ge,
Li Aitao,
AcevedoRocha Carlos G.,
Sun Zhoutong,
Reetz Manfred T.
Publication year - 2020
Publication title -
angewandte chemie international edition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.831
H-Index - 550
eISSN - 1521-3773
pISSN - 1433-7851
DOI - 10.1002/anie.201901491
Subject(s) - directed evolution , saturated mutagenesis , directed molecular evolution , mutagenesis , rational design , computational biology , in silico , protein engineering , biochemical engineering , computer science , combinatorial chemistry , chemistry , biology , gene , biochemistry , enzyme , engineering , mutation , genetics , mutant
Directed evolution of stereo‐, regio‐, and chemoselective enzymes constitutes a unique way to generate biocatalysts for synthetically interesting transformations in organic chemistry and biotechnology. In order for this protein engineering technique to be efficient, fast, and reliable, and also of relevance to synthetic organic chemistry, methodology development was and still is necessary. Following a description of early key contributions, this review focuses on recent developments. It includes optimization of molecular biological methods for gene mutagenesis and the design of efficient strategies for their application, resulting in notable reduction of the screening effort (bottleneck of directed evolution). When aiming for laboratory evolution of selectivity and activity, second‐generation versions of Combinatorial Active‐Site Saturation Test (CAST) and Iterative Saturation Mutagenesis (ISM), both involving saturation mutagenesis (SM) at sites lining the binding pocket, have emerged as preferred approaches, aided by in silico methods such as machine learning. The recently proposed Focused Rational Iterative Site‐specific Mutagenesis (FRISM) constitutes a fusion of rational design and directed evolution. On‐chip solid‐phase chemical gene synthesis for rapid library construction enhances library quality notably by eliminating undesired amino acid bias, the future of directed evolution?