Project
Decipher cytochrome p450 enzymes (CYPs) by digital tools to produce flavonoids and terpenoids
Plant natural compounds constitute an immense, diverse group of compounds with a wide range of societal applications. Today only a fraction of these plant compounds are used due to their presence in non-domesticated species, low compound yield, seasonal variability leading to volatile prices and competition for land use.
In deCYPher, we want to unlock these compounds for society by creating a reliable and efficient sustainable manufacturing pipeline. The deCYPher project will apply artificial intelligence (AI) and machine learning (ML) techniques to identify plant enzymes and design optimal microbial cell factories for the fermentative bio-based production of oxygenised terpenoids and flavonoids. The project will deliver:
- A pipeline for production of plant natural compounds with applications such as flavour, fragrance, pharmaceutical, biopesticide, phytonutrient or plastic precursor
- development of AI and ML tools for plant enzyme discovery and annotation.
- reduced development time & costs of circular bio-based processes using local, sustainable resources & side/waste streams
- improved consumer & citizen benefits and reflection on societal impact of the convergence of AI & synthetic biology
- enhanced ecosystems & biodiversity by avoiding overexploitation of (endangered) plant species and identification & preservation of key natural plant resources
This project will therefore contribute to the transition to a circular bioeconomy in several sectors. The innovative methods developed in the project can be applied to other plant resources and types of compounds in the future.