Multi-scale Simulation of Enzyme Activity and Inhibition

  • Hira Jabeen

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)


Antimicrobial resistance is a growing crisis on a global scale endangering human lives and various facets of modern medicine. The rise in antibiotic resistance has created significant concern by putting the efficacy of crucial drugs at risk across the world. In Gram-negative bacteria, the predominant cause of resistance against the most prescribed class of drugs, βlactam antibiotics, is due to the production and evolution of β-Lactamase enzymes. These enzymes render the antibiotics ineffective by hydrolyzing the β-lactam core. In this thesis, a
multiscale simulation approach is used to understand the hydrolysis and inhibition of β-lactam antibiotics, such as carbapenems, by class A serine β-lactamases.
The hydrolysis of a carbapenem antibiotic is inspected using quantum mechanics/molecular mechanics QM/MM molecular dynamics simulations and the active-site electrostatic interactions are quantified by measuring electric fields with a custom-made script. We discovered that the fields correlate well with activity and identified seven positions, some distal, that distinguish efficient carbapenemases. Combining electric field calculations with principal component analysis enabled a detailed per-residue study of the electrostatic determinants of β-lactamase activity. Our analysis revealed that a cluster of seven residues
dominates electrostatic oxyanion stabilization and, together with the two established catalytic residues, differentiates carbapenemases from non carbapenemases. Electric-field analysis may help predict the activity of β lactamases and guide new-generation antibiotics.
The temperature dependence of biochemical reactions is a crucial parameter for equilibrium and homeostasis. The rate of these enzyme catalysed reaction declines at a higher temperature even in the absence of denaturation. Macromolecular rate theory (MMRT) introduced an activation heat capacity, ∆Cǂ, a parameter that elucidates the curvature of the rate of the reaction without denaturation. Here, molecular dynamics simulations are used to calculate ∆Cǂ of three TEM-type enzymes to understand the dynamical behaviour associated with thermodynamics properties. The result showed a negative ∆Cǂ of two TEM variants which differ only by two mutations. Dynamic cross-correlation and shortest pathway maps were used to further investigate the effects of mutations on the overall enzyme scaffold dynamics and contribution to negative heat capacity change, ∆Cǂ. This work provided deeper insight into the enzyme
dynamics and activation heat capacity that can pinpoint the optimum temperature for enzyme catalysed reactions.
Lastly, we focused on extended-spectrum TEM variants to understand the impact of proximal and distal mutations on β-lactam hydrolysis. TEM-1 type enzymes are penicillinases but have reduced activity against carbapenems and cephalosporins. Extended spectrum βlactamases, particularly TEM-52, are simulated to understand enhanced cephalosporinase activity. QM/MM simulations were used to understand differences in penicillin (Ampicillin), carbapenems (Meropenem and Imipenem), and Cephalosporin (Ceftazidime) breakdown by
three TEM variants. An increase in the active site volume was observed in TEM52, due to G238S mutation, which correlates to activity against newer generation cephalosporins. This study reveals implications of subtle changes in the active side hydrogen bonds and enzyme conformational changes on the substrate activity.
Overall, this thesis advances our understanding the mechanistic details of class A serine βlactamases. We show how active-site electrostatics distinguish β lactamase activity, how activation heat capacity may contribute to catalysis, and how subtle changes at the active site can affect the breakdown of β-lactam antibiotics. The insights gained through this work may help for developing new strategies to combat antibiotic resistance. This works paves the way to reliably predicting the phenotypes of novel resistance genes through MD simulations. Such insights extend beyond information treatments and might also assist the development of novel drugs by determining the activity of existent β-lactamases against next-generation β-lactams antibiotics.
Date of Award23 Jan 2024
Original languageEnglish
Awarding Institution
  • The University of Bristol
SponsorsHigher Education Department
SupervisorAdrian J Mulholland (Supervisor) & Jim Spencer (Supervisor)

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