Polarizable embedding for simulating redox potentials of biomolecules.

Area of Science:

• Biochemistry and Biophysics
• Computational Chemistry
• Molecular Modeling

Background:

• Redox reactions are fundamental to vital biological processes like photosynthesis and respiration.
• Accurate computational methods are needed to understand redox-active macromolecules.
• Predicting redox potentials is key to mechanistic biological insights.

Purpose of the Study:

• To develop and validate a computational protocol for accurate redox potential estimation in biological macromolecules.
• To investigate the impact of environmental polarization and long-range electrostatics on redox potential calculations.
• To apply the method to a specific biological system, cryptochrome 1.

Main Methods:

• Utilized a polarizable embedding hybrid quantum-classical approach.
• Focused on theoretical descriptions including environment polarization and long-range electrostatic interactions.
• Tested the protocol on the cryptochrome 1 protein from Arabidopsis thaliana.

Main Results:

• Environmental polarization significantly impacts redox potential estimates, causing differences up to 1.4 V.
• Long-range electrostatic interactions contribute substantially to computed redox potentials.
• The simulated reduction potential for cryptochrome 1 (0.07 V) closely matched experimental data (-0.15 V).

Conclusions:

• The hybrid quantum-classical approach with polarizable embedding provides accurate redox potential predictions for biological macromolecules.
• Accounting for environmental polarization and long-range electrostatics is essential for reliable computational characterization of redox events.
• This method enhances understanding of mechanistic features in biological redox systems.