Quantum refinement in real and reciprocal space using the Phenix and ORCA software

Area of Science:

• Biophysics
• Structural Biology
• Computational Chemistry

Background:

• X-ray crystallography, neutron crystallography, and cryo-electron microscopy (cryo-EM) are key techniques for determining atomic structures of biological macromolecules.
• Current methods rely on empirical restraints to ensure chemically reasonable structures, but these are less accurate for ligands and metal sites due to scarce data and formulation challenges.
• Quantum mechanical calculations can address these limitations by refining specific parts of the structure.

Purpose of the Study:

• To present a new implementation of quantum refinement that interfaces Phenix and ORCA software.
• To demonstrate the effectiveness of this quantum refinement approach for X-ray and neutron crystallography data.
• To explore the application of quantum refinement to cryo-EM data, particularly for metal sites.

Main Methods:

• Integration of quantum mechanical calculations with established structure refinement software (Phenix and ORCA).
• Application to biological macromolecules including manganese superoxide dismutase, V- and Fe-nitrogenase, and particulate methane monooxygenase.
• Analysis of experimental data, empirical restraints, and quantum mechanical quality measures like strain energy.

Main Results:

• The new quantum refinement implementation effectively improves X-ray and neutron crystal structures.
• The method successfully reproduces previous findings and allows for structural discrimination.
• Application to cryo-EM data for particulate methane monooxygenase shows promise for refining metal sites, where accurate empirical restraints are currently unavailable.

Conclusions:

• Quantum refinement offers a powerful approach to enhance the accuracy of macromolecular structures determined by various experimental methods.
• This technique is particularly valuable for refining the structures of ligands and metal sites, overcoming limitations of traditional empirical restraints.
• The presented implementation provides a robust tool for structural biologists and computational chemists, with significant potential for cryo-EM applications.