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Consensus engineering of sucrose phosphorylase: the outcome reflects the sequence input
Dirk Aerts1, Tom Verhaeghe, Henk-Jan Joosten
1Department of Biochemical and Microbial Technology, Centre for Industrial Biotechnology and Biocatalysis, Ghent University, Coupure Links 653, B-9000, Ghent, Belgium.
Biotechnology and Bioengineering
|April 25, 2013
Summary
Consensus engineering can enhance protein stability by replacing amino acids. This study developed a method to overcome challenges in highly variable regions, creating functional consensus enzymes with average thermostability.
Area of Science:
- Protein engineering
- Enzyme stability
- Bioinformatics
Background:
- Consensus engineering is a strategy to improve protein stability by selecting consensus amino acids from multiple sequence alignments (MSAs).
- Applying full-length consensus design to enzymes is challenging due to difficulties in defining consensus in highly variable protein regions.
Purpose of the Study:
- To address challenges in full-length consensus enzyme engineering, particularly in highly variable regions.
- To investigate the impact of MSA bias on consensus sequence design and enzyme properties.
- To establish practical guidelines for designing stable consensus enzymes.
Main Methods:
- A novel approach to handle highly variable regions by incorporating sequences from the closest natural homologue.
- Construction of three full-length consensus sucrose phosphorylase (SP) enzymes using different MSAs.
- Analysis of enzyme folding, activity, thermostability, and co-evolution networks.
Main Results:
- The developed method successfully generated functional consensus SP enzymes with approximately 70 mutations compared to natural homologues.
- Consensus enzymes exhibited intact co-evolution networks, a key advantage of full-length design.
- The engineered enzymes displayed intermediate thermostability, outperforming some natural variants but not all.
Conclusions:
- A viable strategy exists for full-length consensus enzyme engineering, even with highly variable regions.
- MSA bias can influence consensus sequence representation, necessitating careful MSA selection.
- The success of consensus enzyme design is relative and depends on the chosen natural enzyme for comparison.
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