Understanding the rules of life

Bioscience for renewable resources and clean growth

Category: Standard Studentships

Computational predictions of thermostability and binding affinity changes in enzymes

Primary Supervisor

Prof. Paul Cox – University of Portsmouth

Co-Supervisor(s)

Prof. Jonathan W. Essex – University of Southampton

Dr. Gerhard Koenig – University of Portsmouth

Summary

The use of enzymes for chemical synthesis and recycling is often limited by their low thermostability, as many reactions require high temperatures.

Therefore, high performance computing procedures to find mutations that increase protein stability would represent a competitive advantage for the green industry. This project aims at using molecular dynamics simulations to determine the effect of point mutations on the thermostability of different enzymes. The targets include well-characterized examples from the literature (RNAse SA) for benchmarking, and new mutants of plastic-degrading enzymes that are currently being experimentally evaluated at the CEI (e.g., PETase and cutinases). The mutations are simulated in the folded and the unfolded state to determine the relative free energy changes ΔΔG. The folded state is modelled based on the crystal structure of the enzyme, and the unfolded state can be modelled by small peptides in water. Ideally, the simulations will provide a scale that ranks all canonical amino acids in terms of their influence on protein stability. This can be used to train fast bioinformatics approaches. The temperature-dependent data of hydration free energies and conformational entropies of each amino acid type can help to understand the mutation patterns during the evolution of thermophilic organisms.

Another important factor for proper enzyme function is the capability to bind to the substrate at elevated temperatures. Protein-ligand binding is often driven by the hydrophobic effect, which depends on the temperature. Therefore, it is often necessary to optimize the binding pocket to allow substrate binding at high temperatures (e.g., the binding of PET plastics to PETase). Such calculations are already common in computational drug design, so the required tools already exist in computational chemistry, and only have to be modified to optimize the binding pocket instead of the ligand. Possible applications include the design of thermostable enzymes that can degrade plastics for recycling.