Buy article online - an online subscription or single-article purchase is required to access this article.
research papers
The toolbox for computational protein crystallography is full of easy-to-use applications for the routine solution and refinement of periodic diffraction data sets and protein structures. There is a gap in the available software when it comes to aperiodic crystallographic data. Current protein crystallography software cannot handle modulated data, and small-molecule software for aperiodic crystallography cannot work with protein structures. To adapt software for modulated protein data requires training data to test and debug the changed software. Thus, a comprehensive training data set consisting of atomic positions with associated modulation functions and the modulated structure factors packaged as both a three-dimensional supercell and as a modulated structure in (3+1)D superspace has been created. The (3+1)D data were imported into Jana2006; this is the first time that this has been performed for protein data.