A step change in the modelling of enzymatic catalysis

Lead Research Organisation: University of Manchester
Department Name: Chemistry

Abstract

A deep understanding of enzymatic processes requires an atomic-level description, which is often beyond the reach of experimental techniques but can be achieved through synergy with computational chemistry. This purely computational project proposes a step change in the modelling of an enzyme's active site by building on the foundations laid by a novel force field method called FFLUX[1]. This method is based on the best modern definition of an atom inside a molecular system[2]. FFLUX uses machine learning to train these atoms to "know what to do" in a previously unseen atomic configuration. In other words, quantum mechanically accurate energies and forces between atoms in an enzyme's active site are readily available. Hence, the potential energy surface of the active site can be quickly and accurately explored, both statically and dynamically.
A most suitable prototype case for using FFLUX in enzyme engineering is that of terpenoids. They are the most abundant and largest class (>75,000) of natural products[3]. Most are commonly found in plants, with biological roles ranging from interspecies communication to intracellular signalling and defence against predatory species. Their commercial use is wide ranging as pharmaceuticals, herbicides, flavourings, fragrances and biofuels. Molecular dynamics simulations suggest that the monoterpene synthase class of enzymes do not undergo large-scale conformational changes during the reaction cycle (after initial substrate binding), making them attractive targets for structured-based protein engineering to expand their catalytic scope toward alternative monoterpene scaffolds. This very important class of compounds has been thoroughly studied in the MIB, which enriches the scope for interaction with experimentalists.
The aim of the project is to create a step change in the realism of modelling an enzyme's active site. A rigorous yet accessible quantum mechanical description of a reaction is vital for ultimate progress. Only with detailed atomic insight into the mechanism of an enzymatic reaction, using FFLUX-for-enzymes, can one correctly rationalise the design of future enzymes.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/T008725/1 01/10/2020 30/09/2028
2449420 Studentship BB/T008725/1 01/10/2020 30/09/2024 Yulian Manchev