GeneORator: a novel and high-throughput method for the synthetic biology-based improvement of any enzyme

Lead Research Organisation: University of Liverpool
Department Name: Functional and Comparative Genomics

Abstract

Enzymes have significant uses in biotechnology, for instance as components of 'biological' washing powders. The total enzyme market is large, some $8Bn per year.
Natural enzymes are normally very poor. We can improve them by changing their sequences. However, this still scales as powers of their size: for 14 residues the number is greater than the lifetime in s of the known Universe (~100,000,000,000,000,000). We have a new method that allows one to do this additively (for 14 residues it is just 280 examples). This allows us to study the possible variants MUCH more effectively; with one enzyme we have made a variant that is 1210 times quicker than the starting enzyme.

However, we now need to show that this was not a 'fluke' by demonstrating our methods on a series of other enzymes, and, as well as automating our methods using robots, this is what this project will do. This should get us to a state where we can attract sufficient investment to commercial our discoveries properly.
 
Description Autoencoders that use SMILES as inputs can return three kinds of outputs: (i) the correct SMILES output mirroring the input and/or translating into the input molecular structure (referred to as "perfect"), (ii) an incorrect output of a molecule different from the input but that is still legal SMILES (hence will return a valid molecule), referred to as "good", and (iii) a molecule that is simply not legal SMILES. In practice, our VAE after training returned more than 95% valid SMILES in the test (holdout) set, so those that were invalid could simply be filtered out without significant loss of performance.
Exploitation Route This opens up a considerable area of chemical exploration, even in the absence of any knowledge of bioactivities.
Sectors Digital/Communication/Information Technologies (including Software)

 
Title METHODS FOR PRODUCTION OF ERGOTHIONEINE 
Description The present invention relates to microbial factories, in particular yeast factories, for production of ergothioneine. Also provided are methods for producing ergothioneine in a yeast cell, as well as useful nucleic acids, polypeptides, vectors and host cells. 
IP Reference WO2020221795 
Protection Patent granted
Year Protection Granted 2020
Licensed No
Impact The present invention relates to microbial factories, in particular yeast factories, for production of ergothioneine. Also provided are methods for producing ergothioneine in a yeast cell, as well as useful nucleic acids, polypeptides, vectors and host cells. Ergothioneine (ERG) (2-mercaptohistidine trimethylbetaine, (2S)-3-(2-Thioxo-2,3-dihydro-1 H-imidazol-4-yl)-2-(trimethylammonio)propanoate) is a naturally occurring antioxidant that can be found universally in plants and mammals; it possess