Protein crystals are used in X-ray diffraction experiments to determine the 3D structure of the macromolecule which forms the building blocks of the crystal. During a diffraction experiments such a crystal is rotated in an X-ray beam and the diffracted waves create a distinct pattern which is recorded as intensities on a detector. The neatness of packing the building blocks inside the crystal, the stability and brightness of the X-ray source and beam along with the recording capabilities of the detector all have an influence on the quality of the data that can be achieved in a given experiment. The process for turning the intensity spots on a diffraction image into a list of reflections is called data reduction. Several metrics have been developed, to assess the quality of data at different steps during the data reduction process. The resulting list of reflections and the quality of the data encoded therein is crucial for the next step, phase determination, which allows a crystallographer to elucidate the internal 3D structure of the building blocks. For data of low quality, a researcher will often encounter many difficulties when attempting phase determination and most likely will not be able to identify the locations of atoms within the crystal.
In this seminar we will look at the general term “data quality”, which factors affect the data, how this applies to the case of macromolecular crystallography, what procedures have been put in place to assess data quality and how to improve it.