SOURCE-LINKED INTELLIGENCE

Enzyme Mimicking by Metabolite-Metal Nanozymes with Exceptional Operational Stability

CORDIS · observation · Publication date unknown

sites, analogous to the organization of covalently bound residues and metal ions in conventional enzymes. The proposed work will involve advanced experimental and computational techniques, including artificial intelligence-driven predictive modelling based on functional, structural, and mechanistic data, to identify, optimize, and test the new nanozymes in various relevant application scenarios. Through this comprehensive study, we will not only identify and characterize highly efficient nanozymes, but also gain fundamental insights into the evolution of natural enzymes and design principles of catalytic nanomaterials. This high-risk/high-gain project has the potential to revolutionize the mimicking of enzymatic catalysis and develop robust, highly efficient, cost-effective, and eco-friendly catalytic assemblies. Self-Assembly, Bio-inspired Materials, Nanotechnology, Molecular Recognition, Metabolite-Metal, Association, Enzyme Mimicking, Catalysis

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recordType

award

status

SIGNED

region

EU

value

2776000

unit

EUR