Projektbeschreibung
Künstliche Enzyme der nächsten Generation
Natürliche Enzyme stellen leistungsstarke Katalysatoren mit hoher Effizienz und Selektivität dar und werden in vielen industriellen Prozessen eingesetzt. Forschende wenden eine Methode an, die als gerichtete Evolution bekannt ist. Sie ahmt durch die Erzeugung verschiedener Enzymvarianten die natürliche Evolution nach, um die Eigenschaften von Enzymen auf die jeweiligen Bedürfnisse abzustimmen. Diejenigen mit den gewünschten Merkmalen werden dann ausgewählt. Das vom Europäischen Forschungsrat finanzierte Projekt ProFF zielt darauf ab, die Herausforderungen der gerichteten Evolution durch die Einführung biochemischer Computer zu bewältigen, welche relevante genetische Informationen einbinden. Diese Computer sollen die gerichtete Evolution vielseitiger und schneller bewerkstelligen sowie komplexe Probleme lösen können. Letztendlich zielt diese Forschung auf die Entwicklung der benötigten molekularen Werkzeuge für die programmierbare Auswahl der nächsten Generation katalytischer Werkzeuge, die in nicht natürlichen Umgebungen funktionieren, ab.
Ziel
Natural enzymes are awesome catalysts, in terms of their catalytic efficiency, selectivity, control mechanisms, etc. Revamped as laboratory or industrial tools, they have allowed more than a few breakthroughs, such as PCR, next generation sequencing or green chemistry. The next revolution will be brought by a new generation of extensively modified “enzymatic” catalysts working in non-natural environments, possibly build from non-natural chemistries and targeting an unlimited range of non-natural functions. However, their design is still an arduous process; computational design lacks precision while the combinatorial approach, directed evolution, is limited by labor-intensive or ad hoc selection stages.
We will remove the selection bottleneck in directed evolution by introducing biochemical computers able to perform this step autonomously. Based on recent developments in DNA-based molecular programming, these molecular scouts will be co-compartmentalized with genetic libraries into billions of individual compartments in micrometric emulsions. At each generation and in each droplet, after expression of the genotype, these molecular programs will autonomously: i- evaluate the phenotypic signature of a candidate, ii- integrate this information into a predefined scoring function and iii- propagate the relevant genetic information according to this score.
The programmability of this approach will make directed evolution versatile, faster, and able to address more challenging problems. The evolution dynamics itself become tunable, offering new perspectives on the fitness landscape of biopolymer catalysts. A quantitative in silico model will be built and integrated in a computer-assisted tool for the fast set-up of in vitro experiments and tuning of the various experimental knobs. Overall, we will close a virtuous circle by evolving the molecular tools enabling the programmable selection of the next generation of catalytic tools.
Wissenschaftliches Gebiet
- social sciencespolitical sciencespolitical transitionsrevolutions
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural scienceschemical sciencescatalysisbiocatalysis
- natural sciencesbiological sciencesmolecular biologymolecular evolution
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteinsenzymes
Programm/Programme
Thema/Themen
Finanzierungsplan
ERC-COG - Consolidator GrantGastgebende Einrichtung
75794 Paris
Frankreich