Objective
Although they have the potential to improve the economic and environmental sustainability of biorefineries, oxidative enzymes have not experienced a complete breakthrough yet in the biobased industries. This is mainly caused by the high cost and long time associated with traditional enzyme engineering methods such as directed evolution. SMARTBOX will develop an advanced computational engineering platform specifically for oxidative enzymes, which can automatically screen for improved enzyme variants with minimal human intervention. This is achieved by implementing several innovations into current computational screening methods, most importantly machine learning, which allows to train the algorithms with experimental results. As this significantly improves computational predictability, the time and costs associated with oxidative enzyme engineering will be reduced 10-fold compared to state-of-the-art (SOTA) directed evolution methods.
Relying on the advanced engineering platform, SMARTBOX will develop the one-enzyme conversion of HMF into FDCA and intermediates, and the one-enzyme conversion of lignin monomers into a potential biobased building block for polycarbonates and vanillin. By adopting a 1-enzyme FDCA production process, the associated production costs and carbon footprint are expected to decrease significantly compared to SOTA chemical oxidation methods. The unique feature of SMARTBOX is that reductive catalytic fractionation (RCF) will be used to selectively produce specific lignin monomers from biomass in near theoretical yields. The structural similarity of the resulting monomers with the SMARTBOX building blocks allows the development of high-yielding processes with only one enzyme. Due to the smart combination between oxidative biocatalysis and RCF, the production of bio-aromatics will proceed with higher yields than the state of the art.
Field of science
- /natural sciences/biological sciences/biochemistry/biomolecules/proteins/enzymes
- /natural sciences/computer and information sciences/artificial intelligence/machine learning
Programme(s)
Topic(s)
Call for proposal
H2020-BBI-JTI-2018
See other projects for this call
Funding Scheme
BBI-RIA - Bio-based Industries Research and Innovation actionCoordinator
9042 Desteldonk Gent
Belgium
Participants (10)
9712CP Groningen
25006 Lleida
1099 085 Lisboa
27100 Pavia
3000 Leuven
4132 Muttenz
3630 Maasmechelen
51373 Leverkusen
1721 Sarpsborg
1024 Ecublens Vd
