4.4 Review

The Generation and Exploitation of Protein Mutability Landscapes for Enzyme Engineering

Journal

CHEMBIOCHEM
Volume 17, Issue 19, Pages 1792-1799

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/cbic.201600382

Keywords

biocatalysis; enzyme engineering; hotspots; mutability landscapes; mutagenesis

Funding

  1. Division of Earth and Life Sciences of the Netherlands Organisation of Scientific Research (ALW) [820.02.021]
  2. European Research Council under the European Community [242293]
  3. European Union [635595]
  4. European Research Council (ERC) [242293] Funding Source: European Research Council (ERC)

Ask authors/readers for more resources

The increasing number of enzyme applications in chemical synthesis calls for new engineering methods to develop the biocatalysts of the future. An interesting concept in enzyme engineering is the generation of large-scale mutational data in order to chart protein mutability landscapes. These landscapes allow the important discrimination between beneficial mutations and those that are neutral or detrimental, thus providing detailed insight into sequence-function relationships. As such, mutability landscapes are a powerful tool with which to identify functional hotspots at any place in the amino acid sequence of an enzyme. These hotspots can be used as targets for combinatorial mutagenesis to yield superior enzymes with improved catalytic properties, stability, or even new enzymatic activities. The generation of mutability landscapes for multiple properties of one enzyme provides the exciting opportunity to select mutations that are beneficial either for one or for several of these properties. This review presents an overview of the recent advances in the construction of mutability landscapes and discusses their importance for enzyme engineering.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available