Fast yet accurate routine rational design of novel enzymes

Life could not be sustained without the presence of enzymes, which are responsible for accelerating the chemical reactions 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.

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 routine application of enzyme catalysis in industry, 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 of highly efficient enzymes.

FASTEN combines computational chemistry, deep learning, graph theory, and computational geometry for controlling the complexity of enzyme catalysis in a new computational protocol that will 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 co-evolutionary-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 experimental evaluation of many of the designs will finally reveal the potential of this new approach for the fast routinely design of industrially-relevant enzymes.

FASTEN has the potential of making the routine design of enzymes possible, thus improving our current lives and leading to a more sustainable world for our generations.