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NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

678
When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
678

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Neutron Crystallography Data Collection and Processing for Modelling Hydrogen Atoms in Protein Structures
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Quantum refinement in real and reciprocal space using the Phenix and ORCA software.

Kristoffer J M Lundgren1, Octav Caldararu1, Esko Oksanen1

  • 1Department of Computational Chemistry, Lund University, Chemical Centre, PO Box 124, SE-221 00 Lund, Sweden.

Iucrj
|September 30, 2024
PubMed
Summary

Quantum refinement enhances macromolecular structures by integrating quantum mechanics with experimental data. This method improves accuracy for ligands and metal sites, especially in cryo-electron microscopy (cryo-EM) data where empirical restraints are lacking.

Keywords:
Fe-nitrogenaseMn superoxide dismutaseQM/MMV-nitrogenaseX-ray crystallographycryo-EMneutron crystallographyparticulate methane monooxygenasequantum refinement

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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.