The PanDDA (Pan-Dataset Density Analysis) method identifies "changed-state" signal (e.g. binding ligands) in crystallographic datasets by contrasting putative changed-state datasets against a series of "ground-state" (e.g. unbound) datasets; this identifies regions that are significantly different to the ground-state. Since changed states are invariably present at sub-unitary occupancy in the crystal, the PanDDA method includes further steps to deconvolute the superposition of crystal states, revealing generally clear density for the changed state of the crystal and simplifying modelling.
The analysis of the crystallographic data is performed with pandda.analyse. The changed-state of the crystal can then be modelled with pandda.inspect (using coot). pandda.export merges the models of the bound and unbound states of the crystal to create multi-state ensembles, and prepares the structures for refinement. Occupancy parameter files are automatically generated to allow the occupancies of the superposed states to be grouped in refinement.
data_dirs - Wild-carded path to the input directories
pdb_style - The naming style of the refined pdb file in the input directory (any wild-carded sections must match the wild-carded secions in data_dirs)
mtz_style - The naming style of the refined mtz file in the input directory if different to pdb_style (any wild-carded sections must match the wild-carded sections in data_dirs)
lig_style - The naming style of the cif files for any ligands that are present in the crystal (leaving as the default will pick up all cif files in the input directories)
cpus - The number of cpus to use for processing
Nicholas Pearce, Sebastian Kelm, Jiye Shi, Charlotte Deane & Frank von Delft