PT  - JOURNAL ARTICLE
AU  - Nicholas M Pearce
AU  - Anthony R Bradley
AU  - Patrick Collins
AU  - Tobias Krojer
AU  - Radoslaw P Nowak
AU  - Romain Talon
AU  - Brian D Marsden
AU  - Sebastian Kelm
AU  - Jiye Shi
AU  - Charlotte M Deane
AU  - Frank von Delft
TI  - A Multi-Crystal Method for Extracting Obscured Signal from Crystallographic Electron Density
AID  - 10.1101/073411
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 073411
4099  - http://biorxiv.org/content/early/2016/09/05/073411.short
4100  - http://biorxiv.org/content/early/2016/09/05/073411.full
AB  - Macromolecular crystallography is relied on to reveal subtle atomic difference between samples (e.g. ligand binding); yet their detection and modelling is subjective and ambiguous density is experimentally common, since molecular states of interest are generally only fractionally present. The existing approach relies on careful modelling for maximally accurate maps to make contributions of the minor fractions visible (1); in practice, this is time-consuming and non-objective (2–4). Instead, our PanDDA method automatically reveals clear electron density for only the changed state, even from poor models and inaccurate maps, by subtracting a proportion of the confounding ground state, accurately estimated by averaging many ground state crystals. Changed states are objectively identifiable from statistical distributions of density values; arbitrarily large searches are thus automatable. The method is completely general, implying new best practice for all changed-state studies. Finally, we demonstrate the incompleteness of current atomic models, and the need for new multi-crystal deconvolution paradigms.One Sentence Summary Normally uninterpretable map regions are reliably modelled by deconvoluting superposed crystal states, even with poor starting models.