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Sequence homolog-based molecular engineering for shifting the enzymatic pH optimum
Fuqiang Ma1, Yuan Xie1, Manjie Luo1
1State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Synthetic and Systems Biotechnology
|October 25, 2017
Summary
Protein engineering can now shift enzyme pH optima using a novel sequence analysis strategy. This method identifies key amino acids, enabling the creation of more efficient enzymes for synthetic biology applications.
Area of Science:
- Biotechnology
- Synthetic Biology
- Enzyme Engineering
Background:
- Cell-free synthetic biology relies on enzyme adaptation for efficient artificial systems.
- Protein engineering tailors enzyme properties, but altering pH optimum is difficult.
Purpose of the Study:
- To develop a novel protein engineering strategy for shifting enzymatic pH optima.
- To identify key amino acid residues influencing pH optimum evolution in GH11 xylanases.
Main Methods:
- Sequence homolog-based analysis using artificial neural networks (ANNs) and least absolute shrinkage and selection operator (Lasso).
- Site-directed mutagenesis of a thermophilic xylanase from *Caldicellulosiruptor bescii*.
- Structural analysis of mutated enzymes.
Main Results:
- Five amino acids related to pH optimum evolution were identified.
- Four mutations shifted pH optima towards acidic conditions without loss of activity or stability.
- A combined mutant (M31) decreased pH optimum by 1.5 units and enhanced activity below pH 5.0.
- Mutations were distant from the active site, suggesting a regulatory 'hot zone'.
Conclusions:
- A statistical sequence analysis method efficiently modulates enzymatic pH optima.
- This approach facilitates the design of optimized enzymes for cell-free synthetic biology.
- Identified mutation sites offer a new strategy for enzyme pH regulation.
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