Computational strategies for understanding the molecular basis of biochemical and biocatalytic processes
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Enzymes are molecules that play a crucial role in many biological and chemical processes. To understand how they work and how to design enzymes with specific functions, it is important to study their molecular structure and dynamics. However, it can be difficult to capture the transient nature of these processes, so combining experimental techniques with computational methods can provide an atomistic view to explain the molecular basis of biological processes.
This thesis focuses on using computational techniques, such as molecular dynamics simulations and quantum mechanics, to explore the molecular basis of biochemical and biocatalytic processes. The goal is to understand enzymatic properties such as allostery, cofactor specificity, and catalytic activity, and use this knowledge to design new enzyme variants.
The thesis is divided into three results chapters. In the first chapter (Chapter 4), the focus is on understanding the molecular basis of allosteric regulation in the enzyme Imidazole Glycerol Phosphate Synthase (IGPS). By characterizing the molecular details of the allosteric activation of IGPS in the ternary complex, it was possible to identify the hidden states relevant for IGPS catalytic activity. In the next results chapter (Chapter 5), we designed a computational protocol to unravel the molecular mechanism of the enantioselective N-H insertion in P411 enzyme variants. By exploring the molecular basis of this enzymatic transformation and elucidating the role of key mutations, it was possible to generate a biocatalytic platform for enantiodivergent C-N bond formation. In the last results chapter (Chapter 6), we rationalized the molecular basis of cofactor specificity in engineered formate dehydrogenase variants. By studying the kinetic efficiency with the non-natural NADP+ cofactor, specificity towards the non-natural NADP+ cofactor, and affinity towards the substrate formate, it was possible to understand how to design enzymes with specific cofactor preferences.
Overall, this thesis demonstrates the importance of understanding enzyme function at the molecular level in order to design enzyme variants with specific functions. The use of computational techniques allows for a more detailed understanding of enzymatic mechanisms and provides a valuable tool for designing novel enzymes with improved properties
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