Computational exploration and design of HHDH variants with novel synthetically useful functionalities

Estévez-Gay, Miquel
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Enzymes are the best catalysts. They are the main catalysts in cells and have been exposed to millions of years of natural evolution by including random mutations in their sequence and posterior selection. Some enzymes show extreme catalytic rates, selectivity, or stability, but not all are suitable for industrial or pharmaceutical applications. Their use in industrial contents would be very advantageous, thanks to the fact that enzymes are naturally biodegradable molecules, work in water-based solvents, and are non-toxic. These properties are critical for a suitable future for the new generations. It is crucial to design enzymes for catalyzing industrially relevant reactions. One enzyme family with significant usage in the pharmaceutical industry is Halohydrin Dehalogenasses (HHDH). These enzymes convert (S)-4-chloro-3-hydroxybutyrate into ethyl (R)-4-cyano- 3-hydroxybutyrate, a precursor of statin drugs that need to be enantiomerically pure. Not all HHDHs can perform this catalysis due to their inability to accept the substrate (they have a limited substrate scope), and insufficient enantioselectivity, stability, or activity. The design of new enzymes that display good properties in the selected industrial environment is nowadays possible, thanks to the experimental Directed Evolution technique. Still, this protocol mutates residues randomly. The effect of the mutations is not rationalized and usually requires the production and screening of multiple (thousands) variants, which has a high cost associated. Computational protocols, based, for instance, on Molecular Dynamics (MD) simulations, allow for rationalizing the effect of the introduced mutations onto the ensemble of conformations that the enzymes can explore. Still, analyzing MD simulation outputs can be challenging, and there is no gold standard that gives good results and is computationally feasible. From these MD simulations, the identification of which amino acid positions need to be changed to enhance a given property is also not straightforward. In this thesis, a novel pipeline for analyzing the variance obtained during the MD simulations and the accessible tunnels has been developed and is described in Chapter 4. This new protocol was applied to explore the tunnels in all HHDH families, compare the results with the reported features of each HHDH, and propose new mutagenesis sites (Chapter 5). Chapter 6 describes the newly discovered D-family HHDHs and some proposed variants from Prof. Anett Schallmey’s group, and the thermal stability mechanism is unveiled. Finally, in Chapter 7, the most evolved variant generated via Directed Evolution, i.e., HheC R18, is experimentally and computationally characterized to rationalize the effect of the randomly introduced mutations and how these affect the stability, oligomerization, cooperativity, and catalytic parameters of the HHDH enzyme. ​
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