Abstract
The growth of diffraction-quality crystals and experimental phasing remain two of the main bottlenecks in protein crystallography. Here, the high-affinity copper(II)-binding tripeptide GHK was fused to the N-terminus of a GFP variant and an MBP-FG peptide fusion. The GHK tag promoted crystallization, with various residues (His, Asp, His/Pro) from symmetry molecules completing the copper(II) square-pyramidal coordination sphere. Rapid structure determination by copper SAD phasing could be achieved, even at a very low Bijvoet ratio or after significant radiation damage. When collecting highly redundant data at a wavelength close to the copper absorption edge, residual S-atom positions could also be located in log-likelihood-gradient maps and used to improve the phases. The GHK copper SAD method provides a convenient way of both crystallizing and phasing macromolecular structures, and will complement the current trend towards native sulfur SAD and MR-SAD phasing.
Highlights
In an X-ray diffraction experiment, information relating to the phase of each reflection is lost, which poses the so-called ‘phase problem’ in protein crystallography
These phase estimations can be obtained by molecular replacement (MR), where a known homologous structure is positioned in the new unit cell and phases are calculated from this model
Tremendous advances have been made in protein crystallography in hardware, software, methodology and data-collection methods
Summary
In an X-ray diffraction experiment, information relating to the phase of each reflection is lost, which poses the so-called ‘phase problem’ in protein crystallography. These phase estimations can be obtained by molecular replacement (MR), where a known homologous structure is positioned in the new unit cell and phases are calculated from this model. Tremendous advances have been made in protein crystallography in hardware, software, methodology and data-collection methods. High-throughput robotics, mixed matrix seeding and automatic crystal detection are only some of the methods being used or developed to reduce the crystallization bottleneck (D’Arcy et al, 2014; Dierks et al, 2010). Structural genomics has provided the Protein Data Bank (PDB) with a large number of deposited structures that can be used in MR searches via automated pipelines
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