EPSRC DTP PhD studentship: Mathematical modelling of multi-enzyme cascades

University of Exeter - College of Life and Environmental Sciences

Main supervisor: Dr Nicholas Harmer (University of Exeter)

Co-supervisor:  Prof Jennifer Littlechild (University of Exeter)

Biocatalysis offers an attractive catalytic approach for green chemistry. Biological catalysts operate at moderate temperatures, neutral pH, and without the need for harsh solvents. These catalysts have been adopted, both inside and outside cells, for chemical transformations relevant to pharmaceuticals and fine chemicals.

Multi-enzyme cascades are an attractive extension of this approach: by using multiple enzymes together, several steps can be integrated. Furthermore, linking enzymes often helps to further reduce waste from partial completion of processes or multiple products, and can incorporate steps to regenerate expensive co-factors.

Modelling of these multi-enzyme cascades has traditionally proved challenging. Each step requires several parameters, and good characterisation of the enzymes to identify appropriate equations. Many current approaches adopt a “design of experiments” method to overcome these challenges. We have recently demonstrated the deterministic modelling of a seven enzyme cascade, which highlighted the advantages of this approach. In particular, the modelling results showed unexpected features that have allowed a much better optimisation of the reaction.

This project aims to further develop this work. The project will explore the potential for mathematical approaches to optimise reactions for synthetic biology and sustainable chemistry. This will be combined with experimental reaction cascades both in vivo and in vitro to allow the full model-design-test-interpret cycle to undertaken. Specific aims of the project will be:

  • To explore the mathematical approaches that can be used in multi-enzyme cascades.
  • To demonstrate the use of these in existing and extended cascades, in vitro and in vitro.
  • To extend the range of enzymes/substrates that are suitable for modelling

The student’s role in this project will be to develop advanced modelling approaches for enzyme cascade reactions. Existing data are available to support this modelling, as are well characterised enzymes to generate further data. The student will initially work with the existing data to develop new approaches beyond the modelling that has already been achieved. The aim will be to determine approaches that provide the greatest level of insight and optimise the computation required. The student will work with the investigators, and modelling experts in the University, to explore a wide range of methods. The student will then obtain further experimental data using resources that are already well established in the PI’s lab. These data will demonstrate that the models are truly predictive and valid. Finally, the student will investigate a wider range of substrates and enzymes to extend the existing data, to demonstrate that the modelling approaches are applicable to a wider range of experimental problems. The student will be expected to work only on experimental systems that have been previously validated, to maintain the focus on data modelling.

The student will benefit considerably from the interdisciplinary nature of this project. Exeter is an ideal location for learning modelling, with the expertise of the Centre for Biomedical Modelling and analysis. The student will be encouraged to engage with this centre throughout the PhD. The student will also benefit from the expertise in Biosciences in protein characterisation, which will be considerably enhanced by new experts joining LSI. Finally, the student will benefit from guidance and direction from GSK, and the opportunity to learn more about the priorities of industry.

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