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Automated optimization of the solubility of a hyper-stable α-amylase.

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Greenig, Matthew 
Oeller, Marc 
Atkinson, Misha 
Xu, Xing 

Abstract

Most successes in computational protein engineering to date have focused on enhancing one biophysical trait, while multi-trait optimization remains a challenge. Different biophysical properties are often conflicting, as mutations that improve one tend to worsen the others. In this study, we explored the potential of an automated computational design strategy, called CamSol Combination, to optimize solubility and stability of enzymes without affecting their activity. Specifically, we focus on Bacillus licheniformis α-amylase (BLA), a hyper-stable enzyme that finds diverse application in industry and biotechnology. We validate the computational predictions by producing 10 BLA variants, including the wild-type (WT) and three designed models harbouring between 6 and 8 mutations each. Our results show that all three models have substantially improved relative solubility over the WT, unaffected catalytic rate and retained hyper-stability, supporting the algorithm's capacity to optimize enzymes. High stability and solubility embody enzymes with superior resilience to chemical and physical stresses, enhance manufacturability and allow for high-concentration formulations characterized by extended shelf lives. This ability to readily optimize solubility and stability of enzymes will enable the rapid and reliable generation of highly robust and versatile reagents, poised to contribute to advancements in diverse scientific and industrial domains.

Description

Keywords

enzyme optimization, protein design, protein solubility, alpha-Amylases, Solubility, Enzyme Stability, Protein Engineering, Bacterial Proteins, Mutation, Bacillus licheniformis, Algorithms, Models, Molecular

Journal Title

Open Biol

Conference Name

Journal ISSN

2046-2441
2046-2441

Volume Title

Publisher

The Royal Society
Sponsorship
Horizon Europe UKRI Underwrite ERC (EP/X024733/1)
Royal Society (URF\R1\201461)
European Commission (201461)
M. Ali is supported by a Harding Distinguished Postgraduate Scholarship and M.G. is a Yusuf Hamied Graduate Scholar. P.S. is a Royal Society University Research Fellow (URF\R1\201461). We acknowledge funding from UKRI EPSRC (ERC Starting Grant EP/X024733/1 to P.S.).