Watching enzymes wiggle- understanding DERA dynamics

Enzymes are protein-based machines that are responsible for efficiently producing all the molecules required by life and, because of their efficiency, find increasing interest for application in industrial chemical synthesis. Holistic understanding of these biocatalysts is currently lacking, limiting their applications, not least because they exhibit complex phenomena such as structural dynamics.

2-deoxyribose-5-phosphate aldolase (DERA) is an enzyme involved in nucleic acid catabolism in bacteria and cellular stress response (including during cancer) in humans - it is of interest both as a drug target and for the biocatalytic synthesis of valuable small molecules such as active pharmaceutical ingredients. The C-terminal tail region of the DERA homolog from E. coli (EcDERA) is highly flexible, and contains a catalytically essential terminal tyrosine residue which must move in and out of the enzyme active site to enable the catalytic cycle. Investigations based on nuclear magnetic resonance spectroscopy (NMR) and molecular dynamics (MD) simulations provided evidence that this motion of the enzyme is essential for its proper function, where the enzyme must transition between ‘closed’ and ‘open’ states. Very limited data is available on how this motion responded to mutations, and which intermolecular interactions are responsible for modulating its speed to ensure it lines up with the catalytic rate.

In this project, we will conduct wet-lab experiments to provide data about necessary residues in the EcDERA C-terminal tail for catalytic competence, which will be both advised by and compared to dry-lab MD simulations of the enzyme’s dynamics. The combined sequence/dynamics/activity data-set will be analysed by an explainable AI model to produce a robust hypothesis for correlating these three features, and further unravelling the functional role of dynamics in this enzyme. Overall, these results will expand possibilities for rational engineering of dynamics motions to improve or otherwise modulate this medicinally and technologically important enzyme, and will contribute to the growing number of investigations into the role of dynamics in the function of enzymes.

The recruited student will start in the wet-lab to learn molecular cloning, enzyme expression and activity assays, working closely together with another MEP and PhD in the LevesonGower group (Month 1 and 2). The student then will move to the dry-lab to perform MD simulations and design and test the library of mutants (Months 3-6 Sostaric and Leveson-Gower groups). The resulting data analysed with explainable AI at the conclusion of the project (Months 6-8 Dumancic group).