RT Journal Article
SR Electronic
T1 A Multi-Crystal Method for Extracting Obscured Signal from Crystallographic Electron Density
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 073411
DO 10.1101/073411
A1 Nicholas M Pearce
A1 Anthony R Bradley
A1 Patrick Collins
A1 Tobias Krojer
A1 Radoslaw P Nowak
A1 Romain Talon
A1 Brian D Marsden
A1 Sebastian Kelm
A1 Jiye Shi
A1 Charlotte M Deane
A1 Frank von Delft
YR 2016
UL http://biorxiv.org/content/early/2016/09/05/073411.abstract
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.