Breaking Down Nature’s Catalysts Complexity

Enzymes are remarkable biological catalysts with intricately organized active sites that are perfectly tailored to stabilize the transition states of specific reactions. This sophisticated design is further enhanced by the dynamic nature of enzymes, which can adopt multiple conformations during their reaction cycle. We have developed a strategy able to properly consider the perfect preorganization of enzymatic catalytic pockets and also their ability to change conformation. This has been achieved by tunning the 2024 Nobel Prize awarded AlphaFold2 neural network to estimate the ensemble of conformations [1] combined with physics-based approaches. We have studied several industrially relevant enzymes, including squalene hopene cyclases for the industrial production of the fragrance Ambroxide [2], unspecific peroxygenases for the selective oxygenation of organic substrates [3], and Halohydrin Dehalogenases for epoxide ring-opening reactions. [4] Drawing inspiration from Nature and leveraging our developed Shortest Path Map tool [5] to analyze complex conformational networks of natural enzymes, we successfully designed efficient stand-alone tryptophan synthases for the production of indole derivatives.[6]