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Determination of Crystal Structures

Determination of Crystal Structures

In the late 1800s, the revelation that light extended beyond visible wavelengths led to the discovery of X-rays by Wilhelm Roentgen. Recognized as high-energy electromagnetic radiation with short wavelengths, X-rays prompted exploration into their interaction with crystals. Max von Laue proposed in 1912 that the periodic arrangement of atoms, ions, or molecules in crystals would cause them to diffract X-rays, a hypothesis confirmed through experiments with copper sulfate and zinc sulfide...

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Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

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AlphaFold-guided molecular replacement for solving challenging crystal structures.

Wei Wang¹, Zhen Gong¹, Wayne A Hendrickson¹

¹Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA.

Acta Crystallographica. Section D, Structural Biology

|December 23, 2024

Summary

This summary is machine-generated.

AlphaFold-guided molecular replacement (MR) now enables automated protein structure determination for challenging cases. This method successfully solves many previously intractable crystal structure analyses, reducing the need for experimental phase evaluation.

Keywords:

Hsp70 DnaK adenylate kinase glycoprotein hormones machine learning molecular replacement phase evaluation

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Last Updated: Apr 30, 2026

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Published on: June 28, 2013

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Published on: May 13, 2020

Area of Science:

Structural Biology
Biophysics
Computational Biology

Background:

Molecular replacement (MR) is a key technique for determining biomolecular crystal structures.
Traditional MR relies on known homologous structures, limiting its application to novel proteins.
Experimental de novo phase evaluation is often required for structures lacking recognizable similarity.

Purpose of the Study:

To automate an AlphaFold-guided molecular replacement (MR) procedure tailored for crystal structure determination.
To expand the applicability of MR to proteins with no recognizable similarity to existing structures.
To develop a computational approach that reduces reliance on experimental phasing.

Main Methods:

Optimized reliability cutoff parameters for residue inclusion in AlphaFold predictions.
Developed strategies for MR solution using domain-specific or subcluster-based AlphaFold predictions for alternative conformations.
Implemented an automated Phenix procedure to survey trials of increasing computational complexity.
Tested subclustering on enzyme systems with multiple challenging conformations.

Main Results:

Achieved a 92% success rate on a set of 158 challenging PDB problems.
Achieved a 93% success rate on a second set of 215 challenging problems.
Successfully solved previously MR-intractable crystal structure analyses.

Conclusions:

AlphaFold-guided MR significantly expands the reach of molecular replacement for protein structure determination.
This automated approach can replace experimental de novo phasing for many challenging cases.
The developed method effectively functions as a de novo phasing method for structural biology.