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Ab Initio Raman Spectra of β-Lactamase Inhibitor Intermediates Bound to E166A SHV β-Lactamase
Andrea Miani1, Marion Skalweit Helfand1, Simone Raugei1
1SISSA and INFM-DEMOCRITOS center via Beirut 2, I-34014, Trieste, Italy, and Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, Ohio 44106.
Computational Raman spectroscopy of enzyme-bound beta-lactamase inhibitors like clavulanic acid and tazobactam reveals key vibrational properties. This enhances understanding of bacterial drug resistance mechanisms.
Area of Science:
- Biochemistry
- Computational Chemistry
- Spectroscopy
Background:
- Bacterial drug resistance is a major global health concern.
- Beta-lactamase enzymes confer resistance to beta-lactam antibiotics.
- Understanding enzyme-inhibitor interactions is crucial for developing new therapeutics.
Purpose of the Study:
- To computationally investigate the structural and vibrational properties of beta-lactamase inhibitors bound to a mutated enzyme.
- To analyze and assign experimental vibrational Raman spectra for enzyme-bound clavulanic acid and tazobactam.
- To assess the accuracy of different computational methods for predicting Raman spectra.
Main Methods:
- Hybrid molecular mechanics/quantum mechanics (QM/MM) simulations were employed.
- Simulations were performed on clavulanic acid and tazobactam intermediates bound to E166A SHV beta-lactamase.
- Raman spectra were analyzed using time autocorrelation function of polarizability and instantaneous normal modes.
Main Results:
- The trans-enamine moiety's stretchings strongly couple with N-H rocking, forming bands between 1600-1640 cm⁻¹.
- Accurate description of Raman scattering requires including mechanical and electrical anharmonicity.
- Environmental electrostatic fields dynamically modulate Raman activity.
Conclusions:
- The study provides insights into the vibrational spectra of enzyme-bound beta-lactamase inhibitors.
- Computational methods, particularly QM/MM, are valuable for analyzing drug resistance mechanisms.
- Understanding anharmonicity and environmental effects is key for accurate spectral prediction.
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