Dynamical responses predict a distal site that modulates activity in an antibiotic resistance enzyme

β-Lactamases, which hydrolyse β-lactam antibiotics, are key determinants of antibiotic resistance. Predicting the sites and effects of distal mutations in enzymes is challenging. For β-lactamases, the ability to make such predictions would contribute to understanding activity against, and developmen...

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Veröffentlicht in:Chemical science (Cambridge) 2024-09, Vol.15 (41), p.17232-17244
Hauptverfasser: Beer, Michael, Oliveira, Ana Sofia F, Tooke, Catherine L, Hinchliffe, Philip, Tsz Yan Li, Angie, Balega, Balazs, Spencer, James, Mulholland, Adrian J
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Sprache:eng
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Zusammenfassung:β-Lactamases, which hydrolyse β-lactam antibiotics, are key determinants of antibiotic resistance. Predicting the sites and effects of distal mutations in enzymes is challenging. For β-lactamases, the ability to make such predictions would contribute to understanding activity against, and development of, antibiotics and inhibitors to combat resistance. Here, using dynamical non-equilibrium molecular dynamics (D-NEMD) simulations combined with experiments, we demonstrate that intramolecular communication networks differ in three class A SulpHydryl Variant (SHV)-type β-lactamases. Differences in network architecture and correlated motions link to catalytic efficiency and β-lactam substrate spectrum. Further, the simulations identify a distal residue at position 89 in the clinically important carbapenemase 2 (KPC-2), as a participant in similar networks, suggesting that mutation at this position would modulate enzyme activity. Experimental kinetic, biophysical and structural characterisation of the naturally occurring, but previously biochemically uncharacterised, KPC-2 mutant with several antibiotics and inhibitors reveals significant changes in hydrolytic spectrum, specifically reducing activity towards carbapenems without effecting major structural or stability changes. These results show that D-NEMD simulations can predict distal sites where mutation affects enzyme activity. This approach could have broad application in understanding enzyme evolution, and in engineering of natural and enzymes.
ISSN:2041-6520
2041-6539
DOI:10.1039/d4sc03295k