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Updated: May 16, 2026

Synthesizing Amino Acids Modified with Reactive Carbonyls in Silico to Assess Structural Effects Using Molecular Dynamics Simulations
Published on: April 26, 2024
Carbonic anhydrase binding site parameterization in OPLS-AA force field.
Guillaume Bernadat1, Claudiu T Supuran, Bogdan I Iorga
1Institut de Chimie des Substances Naturelles, CNRS UPR 2301, Labex LERMIT, Centre de Recherche de Gif, 1 Avenue de la Terrasse, F-91198 Gif-sur-Yvette, France.
This study optimized carbonic anhydrase binding site parameters in the OPLS-AA force field using quantum chemistry. Accurate force field parameters were developed, improving molecular dynamics simulations for metallo-enzymes.
Area of Science:
- Biochemistry
- Computational Chemistry
- Structural Biology
Background:
- Carbonic anhydrase is crucial for biological CO2 regulation.
- Accurate molecular dynamics simulations require precise force field parameters.
- Existing force fields may not fully capture the nuances of enzyme active sites.
Purpose of the Study:
- To parameterize the carbonic anhydrase binding site within the OPLS-AA force field.
- To investigate the impact of different protonation states (OH2 and OH-) on atomic partial charges.
- To validate the developed force field parameters using molecular dynamics simulations.
Main Methods:
- Quantum chemistry calculations were employed for parameterization.
- Three distinct parameterization protocols were tested.
- Atomic partial charges were calculated considering both neutral and anionic forms of the binding site.
- Molecular dynamics simulations were used for validation.
Main Results:
- Significant differences in atomic partial charges were observed between the OH2 and OH(-) forms.
- Including an extended binding site in charge calculations proved essential for accuracy.
- The validated force field parameters demonstrated good performance in simulations.
Conclusions:
- The developed OPLS-AA force field parameters enhance the accuracy of molecular dynamics simulations for carbonic anhydrase.
- This work provides a foundation for more reliable computational studies of metallo-enzymes.
- Facilitates in-silico investigations of enzyme mechanisms and inhibitor design.
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