FASTEN, ERC-2022-CoG-101088032


European Research Council (ERC) – Consolidator Grant: “Fast yet accurate routine rational design of novel enzymes” (FASTEN, ERC-2022-CoG-101088032). Total: 1.996,250€. Period: 2023-2028

  • RESEARCH YEAR 2023-2028
  • Funding 1.996,250€


Life could not be sustained without the presence of enzymes, which are responsible for accelerating all the chemical reactions that take place in our body in a biologically compatible timescale. Enzymes present other advantageous features such as high specificity and selectivity, plus they operate under very mild biological conditions. Inspired by these extraordinary characteristics, many scientists wondered about the possibility of designing new enzymes for industrially-relevant targets. The development of highly efficient and environmentally friendly enzyme-catalyzed processes has many socio-economic benefits associated. Unfortunately, none of the current enzyme design strategies is able to rapidly design tailor-made enzymes at a reduced cost. This is limiting the general application of enzyme catalysis in industrial contexts, and thus the chemical manufacturing competitiveness. The goal of this project is to develop a fast yet accurate computational enzyme design approach for allowing the routine design highly efficient enzymes. The groundbreaking nature of DEEPLeaZYME relies on the combination of computational chemistry, deep learning, graph theory, and computational geometry for capturing the complexity of enzyme catalysis. The project is based on the development of a deep learning-based computational protocol able to properly capture the chemical steps and conformational changes that take place along the catalytic itinerary. Active site and distal activity-enhancing mutations are predicted based on correlation and coevolutionary-based guidelines, and the catalytic potential of the new designs is estimated by means of geometry-based oracles. This new computational approach will be validated with the design of enzymes presenting complex conformational dynamics and multi-step mechanisms. The final experimental evaluation of many of the designs will finally reveal the potential of this new approach for the fast routinary design of industrially-relevant enzymes.