Abstract
Biomolecular modelling has become an invaluable tool in enzyme-catalysed mechanism elucidation, understanding enzyme selectivity, and in the design of new drug compounds. In this thesis, molecular modelling techniques including quantum mechanics/molecular mechanics (QM/MM) methods, in combination with energy minimisations, molecular dynamics (MD), and umbrella sampling, are used to investigate the reactivity of three enzymes: the L1 metallo--lactamase, insulin-regulated aminopeptidase (IRAP) and, in response to the 2020 pandemic, the SARS-CoV-2 main protease (Mpro).A reactivity study was carried out on the L1-catalysed hydrolysis of the -lactam antibiotics faropenem and ertapenem. In combination with crystallography, QM/MM MD simulations and energy minimisations identified the imine state as the most likely hydrolysed product tautomer. QM/MM free energy surfaces also showed the hydrolysis of faropenem and ertapenem to proceed via a tetrahedral intermediate, which may be useful in designing analogue inhibitors for L1 to restore antibiotic efficacy.
A further reactivity study focussed on investigating how IRAP can hydrolyse the cyclic neuropeptide oxytocin but not the linear neuropeptide Ang IV. In QM/MM MD simulations, the catalytic glutamate, Glu465, adopted different conformations in the enzyme-substrate complexes, due to Ang IV forming more active site hydrogen bonds than oxytocin. QM/MM MD simulations also identified stable tetrahedral intermediates in both the hydrolysis of Ang IV and oxytocin, however, Ang IV adopted a poor conformation for facilitating the next step of the reaction, explaining why IRAP cannot hydrolyse Ang IV.
Finally, an investigation was carried out into the resting protonation state of the SARS-CoV-2 Mpro cysteine-histidine catalytic dyad when a natural substrate is bound. MM MD simulations and QM/MM free energy profiles determined a neutral dyad as the most likely protonation state, as well as identifying the nearby histidine residue His163 as N-protonated. These results have direct implications for future Mpro modelling, and the further development of Mpro antiviral drugs.
| Date of Award | 2 Dec 2021 |
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| Original language | English |
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| Supervisor | Craig P Butts (Supervisor) & Adrian J Mulholland (Supervisor) |