Back

Hydrogen-bonding changes cause differences in imipenem breakdown activity in OXA-48 variants

Wang, D.; Mulholland, A. J.; Spencer, J. J.; van der Kamp, M. W.

2026-01-22 biochemistry
10.64898/2026.01.20.700306 bioRxiv
Show abstract

The {beta}-lactamase OXA-48 efficiently hydrolyses carbapenem antibiotics, especially imipenem. Carbapenem resistance is a rising clinical concern, and is frequently associated with OXA-48 and its variants. OXA-48 variants carrying different mutations in the {beta}5-{beta}6 loop differ in hydrolytic activity towards imipenem. OXA-517 has a higher KM, but similar kcat for imipenem hydrolysis, compared to OXA-48, whereas OXA-163 and -405, which have similar mutations in the {beta}5-{beta}6 loop, are less active. Multiscale simulations (using quantum mechanics/molecular mechanics, QM/MM) of deacylation of the respective imipenem acylenzymes show this to be most efficient when the deacylating water (DW) acts as a hydrogen bond (H-bond) donor to imipenem, and the carboxylated Lys73 base is less hydrated. Calculated barriers for deacylation correlate very well with experimental data, but for OXA-163 and -405 only when DW acts as a H-bond acceptor. Dynamics simulations of imipenem acylenzyme complexes show that mutations in the {beta}5-{beta}6 loop change the active site H-bond network. In OXA-48, the DW H-bonding pattern linked to high activity is more frequently sampled, and in OXA-517 it is stabilised through H-bonding to Thr213; explaining the higher kcat values compared to OXA-163 and -405, where this is not the case. Furthermore, simulations of non-covalent imipenem complexes indicate that increased KM for OXA-517 is linked to lower binding affinity, caused by repositioning of bound imipenem. Our work identifies the molecular basis for differences in imipenem hydrolytic activity between OXA-48 variants, offering detailed insights into how active site interactions alter the dynamics and reaction efficiencies related to antibiotic resistance.

Published in Journal of Chemical Information and Modeling (predicted rank #1) · training set

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

Journal of Chemical Information and Modeling · published here
238 papers in training set
Top 0.4%
14.9%
2
Chemical Science
73 papers in training set
Top 0.1%
14.9%
3
Nature Communications
5641 papers in training set
Top 21%
7.8%
4
ACS Catalysis
18 papers in training set
Top 0.1%
6.2%
5
Communications Biology
993 papers in training set
Top 2%
5.4%
6
JACS Au
43 papers in training set
Top 0.1%
4.8%
50% of probability mass above
7
Journal of Chemical Theory and Computation
140 papers in training set
Top 0.4%
4.3%
8
eLife
5828 papers in training set
Top 27%
4.3%
9
Biochemistry
148 papers in training set
Top 0.7%
3.2%
10
PLOS Computational Biology
1863 papers in training set
Top 11%
2.6%
11
Scientific Reports
3612 papers in training set
Top 43%
2.4%
12
Proteins: Structure, Function, and Bioinformatics
88 papers in training set
Top 0.6%
2.1%
13
The Journal of Physical Chemistry B
167 papers in training set
Top 1.0%
1.9%
14
ACS Central Science
71 papers in training set
Top 0.6%
1.9%
15
Structure
193 papers in training set
Top 2%
1.4%
16
Computational and Structural Biotechnology Journal
242 papers in training set
Top 5%
1.1%
17
Communications Chemistry
48 papers in training set
Top 1%
1.1%
18
Biophysical Journal
631 papers in training set
Top 4%
1.1%
19
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 35%
1.1%
20
Angewandte Chemie International Edition
93 papers in training set
Top 2%
1.1%
21
Journal of Biological Chemistry
690 papers in training set
Top 8%
1.0%
22
Protein Science
246 papers in training set
Top 3%
1.0%
23
ACS Chemical Biology
167 papers in training set
Top 3%
0.8%
24
Journal of Medicinal Chemistry
77 papers in training set
Top 1%
0.6%
25
International Journal of Molecular Sciences
494 papers in training set
Top 18%
0.6%
26
The Journal of Chemical Physics
56 papers in training set
Top 0.6%
0.6%
27
Biomolecules
100 papers in training set
Top 4%
0.6%