Antimicrobial resistance is an increasingly worrying healthcare challenge that calls for the development of novel classes of antibiotics. In this post we showcase the tool MEZE and recent published work  from a team a researchers at the Universities of Edinburgh and Bristol that is advancing biomolecular simulation protocols for metalloenzymes-drug interactions.

Metallo beta-lactamases and antimicrobial resistance

Metallo-β-lactamases (MBLs) are enzymes produced by certain bacteria that confer resistance to a broad spectrum of β-lactam antibiotics, including carbapenems, which are often used as a last resort for severe infections. These enzymes hydrolyze the β-lactam ring, rendering the antibiotics ineffective. MBLs require zinc ions for their catalytic activity and are not inhibited by traditional β-lactamase inhibitors, making infections caused by MBL-producing pathogens particularly challenging to treat. The spread of MBL genes among bacteria via horizontal gene transfer exacerbates the global antimicrobial resistance crisis, necessitating urgent development of new inhibitors and therapeutic strategies.

Alchemical Free Energy calculation workflow for Metallo beta-lactamases

Relative Binding Free Energy (RBFE) calculations using alchemical methods are well-established in computer-aided drug discovery. However, reliably modeling the binding of metallo-beta-lactamase (MBL) inhibitors is challenging due to the frequent involvement of interactions with zinc ions in the enzyme’s active site.

In this study, Guven et al. compared RBFE protocols for two beta-lactamases. The first enzyme, KPC-2, is a serine beta-lactamase that can be modeled using established RBFE workflows. The second enzyme, VIM-2, is a metallo-beta-lactamase featuring two divalent zinc ions in its active site. The team tested two different setup protocols. In the first approach, zinc coordination bonds were replaced with harmonic restraints. In the second approach, the upgraded Amber Force Field (UAFF) was used to parameterize zinc-binding residues.

To implement these simulation protocols into RBFE workflows, the team developed an open-source software package called Meze. Meze builds on OpenBioSim’s BioSimSpace to facilitate the assembly of parameterized, solvated protein-ligand systems. This process involved converting between Gromacs and AMBER file formats, planning RBFE networks via BioSimSpace‘s interface to the tool LOMAP, and analyzing RBFE trajectories through BioSimSpace‘s interface to alchemlyb. RBFE trajectories were generated using OpenBioSim’s Sire SOMD1 engine. Finally, the edge RBFEs were analyzed with the tool cinnabar to produce binding free energy estimates.

 

 

The overall pipeline produced accurate results when applied to the less challenging serine beta-lactamase KPC-2 (R = 0.93), validating the scientific workflow before addressing the more complex case of VIM-2. For VIM-2, QM/MM modeling was employed to validate the choice of coordination environment for AFE calculations.

Surprisingly, the simple harmonic restraints approach used to enforce a zinc coordination pattern showed some degree of predictiveness for affinity predictions (R = 0.55). Encouragingly, the use of the more sophisticated UAFF parameters to describe zinc-binding residues further improved correlations with experimental data (R = 0.78).

 

While further protocol refinement—particularly to better model polarization effects—could enhance accuracy, the results suggest that a method like UAFF, which does not significantly increase computational costs, could be a valuable tool for deploying RBFE calculations on metallo-beta-lactamases. This research also demonstrates the practical utility of alchemical free energy calculation workflows assembled with open-source software components.

References

Metallo-beta-lactamases paper) ” Protocols for Metallo- and Serine-b-Lactamase Free Energy Predictions: Insights from Cross-Class Inhibiors” Jasmine Guven, Marko Hanzevacki, Papa Kalita, Adrian J. Mulholland, Antonia S. J. S. May J. Phys. Chem. B, 128, 50,  12416-12424, 2024 doi:10.1021/acs.jpcb.4c06379

BioSimSpace paper) ”BioSimSpace: An interoperable Python framework for biomolecular simulation” Hedges, L. O. ; Mey, A. S. J. S. ; Laughton, C. A. ; Gervasio, F. L. ; Mulholland, A. J. ; Woods, C. J. ; Michel, j.  Journal of Open Source Software, 4(43), 1831, 2019  doi:10.21105/joss.01831

Sire paper) ”Sire: An Interoperability Engine for Prototyping Algorithms and Exchanging Information Between Molecular Simulation Programs” Christopher J. Woods, Lester Hedges, Adrian Mulholland, Maturos Malaisree, Paolo Tosco, Hannes H. Loeffler, Miroslav Suruzhon, Matthew Burman, Sofia Bariami, Stefano Bosisio, Gaetano Calabro, Finlay Clark, Antonia S. J. S. Mey, Julien Michel J. Chem. Phys. , 160, 202503, 2024 doi:10.1063/5.0200458

MEZE repository) https://github.com/meyresearch/metalloenzymes

Written by Julien Michel.