Unveiling the structural features that regulate carbapenem deacylation in KPC-2 through QM/MM and interpretable...

Area of Science:

• Biochemistry
• Computational Chemistry
• Drug Resistance

Background:

• Carbapenem resistance in bacteria poses significant clinical and economic challenges.
• Carbapenemase-producing bacteria deactivate carbapenem antibiotics via rapid hydrolysis.

Purpose of the Study:

• To elucidate the structural determinants of carbapenemase deacylation activity.
• To understand the mechanism of imipenem hydrolysis by KPC-2 carbapenemases.

Main Methods:

• Combined quantum mechanical/molecular mechanical (QM/MM) simulations to model reaction pathways.
• Machine learning (ML) models to predict activation barriers from conformational features.
• Shapley additive explanation (SHAP) for mechanistic insights and QM/MM wavefunction analysis for verification.

Main Results:

• Identified key structural features regulating the KPC-2/imipenem deacylation activation barrier.
• Demonstrated the concert effect of hydrogen bonding and carbapenem tautomerization states.
• Validated the efficacy of interpretable ML in analyzing complex simulation data.

Conclusions:

• Hydrogen bonding and carbapenem ring tautomerization are critical for KPC-2 deacylation activity.
• Interpretable ML effectively extracts mechanistic insights from QM/MM simulations.
• Findings contribute to understanding carbapenem resistance mechanisms.