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Neutron Crystallography Data Collection and Processing for Modelling Hydrogen Atoms in Protein Structures

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Published on: December 1, 2020

Toward Real Real-Space Refinement of Atomic Models.

Alexandre G Urzhumtsev^1,2, Vladimir Y Lunin³

¹Centre for Integrative Biology, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS-INSERM-UdS, 1 rue Laurent Fries, BP 10142, 67404 Illkirch, France.

International Journal of Molecular Sciences

|October 27, 2022

Summary

This study explores calculating atomic images for real-space refinement of macromolecular models. Analytical functions enable practical feasibility assessments for improving structural accuracy.

Keywords:

CPU time atomic images inhomogeneous resolution map calculation real-space refinement refinement programs shell decomposition

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Area of Science:

Structural Biology
Computational Chemistry
Crystallography

Background:

High-quality atomic models are crucial for understanding molecular structures.
Model refinement against diffraction data (reciprocal-space) or experimental maps (real-space) yields structural information.
Real-space refinement requires comparing experimental maps with maps calculated from atomic models.

Purpose of the Study:

To discuss the practical feasibility of calculating atomic images for real-space refinement.
To enable accurate comparison between experimental maps and model-derived maps.
To enhance the refinement of macromolecular atomic models.

Main Methods:

Maps are calculated as sums of 'atomic images'—3D peaky functions with Fourier ripples.
Atomic images and model maps are expressed analytically as functions of coordinates, atomic displacement parameters, and local resolution.
The feasibility of these calculations for macromolecular models is assessed.

Main Results:

Analytical expressions for atomic images and model maps are derived.
The methodology allows for the incorporation of local resolution variations.
The study evaluates the practical applicability of this computational approach.

Conclusions:

The analytical calculation of atomic images is feasible for real-space refinement.
This approach offers a robust method for improving macromolecular atomic models.
Accurate structural information can be obtained through advanced real-space refinement techniques.