Enzymes are proteins catalysing almost all reactions required for cellular life and, when defective, they can cause severe pathologies. For example, in humans, alpha-galactosidase (a-GAL) deficiency, a condition affecting up to 1 in 3000 newborn known as Fabry’s disease (FD), causes life threatening damage to heart and kidneys. Since these diseases are usually caused by inherited genomic mutations, they cannot be cured, but they can be treated using Enzyme Replacement Therapies (ERTs), which consist of the injection of a recombinant version of the affected enzymes into patients. Unfortunately, ERTs have limitations; recombinant enzymes have lower enzymatic activity compared to the human wild- type versions, are unstable in blood, are poorly absorbed by human cells, and often trigger an immune response. Moreover, manufacturing therapeutic enzymes is extremely expensive because standard mammalian cell-based expression systems have low yield.
Developing effective therapeutic enzymes requires design methods able to discover new amino acid sequences that can encode the same catalytic function, while optimising the therapeutic properties of the molecule. Then, these enzymes must be converted into highly optimised DNA triplets, called codons, to maximise expression and yield in host organisms that can grow in inexpensive media. With the increasing incidence of enzymatic deficiencies and current treatments costing up to £400K per year per patient, it is crucial to establish effective methods to perform these tasks and implement a platform for effective and sustainable production of therapeutic enzymes.
Here we aim at developing the computational and experimental methods required for engineering and manufacturing designer enzymes. We will use deep generative machine learning (ML) to design and codon optimise new enzymes, which will then be rapidly built and tested at scale using the lab automation platform available at the University of Edinburgh (UoE). As a proof of concept, we will build the largest library of human a-GAL enzymes, to identify more effective therapeutic enzymes for Fabry’s disease.