Session E - Uwe Bornscheuer

CV

Uwe Bornscheuer is Professor of Biotechnology and Enzyme Catalysis at the University of Greifswald, Germany. In his research, he uses enzymes for applications in organic synthesis by using rational tools for protein engineering and directed evolution. He also is Editor-in-Chief of the European Journal of Lipid Science and Technology.

1985-1990: Study of Chemistry, University of Hannover, Hannover, Germany
1991-1993: Ph.D. in Chemistry, University of Hannover, Hannover, Germany
1993-1994: Postdoc, University of Nagoya, Nagoya, Japan
1994-1998: Habilitation in Technical Biochemistry, University of Stuttgart, Stuttgart, Germany
since 1999: Professor at University of Greifswald, Greifswald, Germany

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Abstract session E (keynote lecture on May 20, 14:00 h)

Protein Engineering using "Small, but Smart" Mutant Libraries

Henk-Jan Joosten, Bio-Prodict, Nijmegen, The Netherlands

Uwe T. Bornscheuer, Institute of Biochemistry, Greifswald University, Greifswald, Germany

Protein engineering has developed in the past decade to a highly important technology (1,2) to create enzymes with desired properties, but also to understand their function. Whereas initially rational protein design based on detailed analysis of structures was the method of choice, directed evolution became an important alternative. We used information from protein databases to create 'small, but smart' focused protein libraries of enzymes from the a/b-hydrolase fold family using the 3DM database (3). This resulted in enzyme variants with enhanced thermostability or enantioselectivity (4). For the synthesis of chiral amines, we developed an in silico analysis and identified a toolbox of novel (R)-selective transaminases (5) as well as (S)-selective enzymes from a structure-guided search (6). Using a 3DM database of PLP-dependent enzymes (7), we could guide the protein engineering of amine transaminases with extended substrate scope now able to convert bulky ketones into chiral amines (8). More and more protein engineers use a strategy referred to as "smart library design" to improve protein properties. Smart mutant libraries contain a small number of mutants with a high percentage of active clones that have mutations at positions, called hotspots, that are likely to show the desired effect. The quality of a smart library depends on: 1) The selection of hotspots and 2) The prediction of the best amino acid changes at these hotspots.

Recently it was shown that the vast amounts of data nowadays available for protein superfamilies can be used for the prediction of both these steps and, therefore, for the design of high quality smart mutant libraries. 3DM is a protein superfamily analysis platform developed by Bio-Prodict (https://www.bio-prodict.nl/) that integrates many different data types for complete protein superfamilies. Recently, a novel 3DM module called CorNet was released. CorNet is a correlated mutation network analysis tool that combines different superfamily data, such as correlation mutation data, structural data and mutation data extracted from literature. CorNet is specifically designed for the detection of hotspots and for smart library design. With CorNet different enzymes features, such as enantioselectivity, activity and thermostability have been optimized. Comparisons with random designed libraries show that smart libraries designed with CorNet are of high quality, which reduces the number of clones that need to be screened and it increases the chance of finding an enzyme with the desired properties.

[1] Nature, 485, 185-194 (2012).
[2] S. Lutz, U.T. Bornscheuer (Eds.) Protein Engineering Handbook, Wiley-VCH, Weinheim (2009, 2012).
[3] ChemBioChem, 11, 1635-1643 (2010).
[4] Protein Eng. Des. Sel., 23, 903-909 (2010); ChemBioChem, 11, 1861-1866 (2010).
[5] Nature Chem. Biol., 6, 807-813 (2010); Adv. Synth. Catal., 353, 2439-2445 (2011).
[6] ChemCatChem, 5, 150-153 (2013).
[7] Biotechnol. Adv., DOI: 10.1016/j.biotechadv.2014.12.012 (2015).
[8] ChemCatChem, 7, 757-760 (2015).