Developing a better-than-nature enzyme platform for biocatalysis applications

Enzymes are used in vast range of commercial applications and are a central pillar of the biotechnology-based
economy in the UK. Despite their high specificity and efficiency, enzymes are unstable and it is difficult/impossible to
rationally manipulate their activity. Existing approaches to alter activity are hugely time-intensive, costly and often
yield only marginal increases in the desired property, at the expense of activity or specificity.
Industrially one would like a small number of platform systems that could be modified to change activity/specificity/
stability, rather than a new natural enzyme for every application. Artificial enzymes are peptides (~80 amino acids)
with catalytic activity. They are small, robust and tuneable, but retain the specificity and efficiency of 'natural'
enzymes. These systems are therefore excellent candidates for creating an idealised platform system since they can
be easily engineered with non-natural chemical groups.
Recent research in fundamental enzymology has illustrated the crucial importance of the flexibility of enzymes in
mediating their function. Tuning the flexibility and dynamics of an enzyme therefore has the potential to be a simple,
rationale route to manipulating activity, without compromising the ideal active site environment that governs catalysis.
This strategy represents a novel approach in enzyme engineering and builds on technology recently developed in
Pudney's lab (UK Patent No. 1604640.1) and technology being developed in partnership with an industrial
biotechnology company, Biocatalysts Ltd.
We plan to develop a tuneable, artificial enzyme that can perform a range of redox chemical reactions and change its
stability, by modulating the flexibility and dynamics of the protein scaffold. To achieve this, we will use novel
structure-based calculations that identify the network of flexible motion in our platform enzyme and how this network
affects the enzyme activity and stability. We will then validate thes e predictions with a new biophysical analysis that
captures information on protein flexibility and dynamics. We will iterate this approach to arrive at a well-developed
platform system that can be tuned across a range of activities and stabilities.