Over the past decades, the interest in designing new enzymes to solve practical challenges in all branches of science and technology has increased notably, most importantly due to large strides made in directed evolution approaches in contrast to more traditional rational design approaches. We will present in this communication a new computational strategy to design novel biocatalysts based on the sum of the best electrostatic properties of different enzymes that show certain catalytic activity on a common reaction.[1-5] The computational protocol has been applied on the re-design of the protein scaffolds from existing promiscuous enzymes. The free energy landscape obtained with QM/MM multiscale methods for proposed new variants predicts measured increased catalytic activity over the original wild-type enzyme. Our computational predictions have been experimentally confirmed by comparing the kinetic data measured with the wild-type and the mutated enzymes. Regardless of the intrinsic limitations, the simplicity of the presented approach offers a new route based on computational technique to (re)design new enzymes.<br/>Recent results obtained in our laboratory oriented towards the design of new enzymes, and in particular for the depolymerization of synthetic polymers such as PET and PU, will be summarized in this communication.

Towards the computation-assisted design of new enzymes for the hydrolysis of synthetic polymers

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