Date Published: November 01, 2018
Publisher: International Union of Crystallography
Author(s): Brendan Sullivan, Rick Archibald, Patricia S. Langan, Holger Dobbek, Martin Bommer, Robert L. McFeeters, Leighton Coates, Xiaoping Wang, Franz Gallmeier, John M. Carpenter, Vickie Lynch, Paul Langan.
It is demonstrated that using three-dimensional profile fitting of Bragg peaks increases the accuracy and resolution of neutron crystallographic data collected from proteins and reveals new features in nuclear density maps calculated from these data.
Neutron crystallography can provide structural, chemical and functional information on biological macromolecules that is difficult or impossible to obtain using other techniques (Blakeley et al., 2008 ▸). One of its main advantages is the ability to directly visualize hydrogen (H) or deuterium (D) atoms at modest resolutions of around 2.0–2.5 Å (Bacik et al., 2017 ▸; Kwon et al., 2016 ▸; Casadei et al., 2014 ▸; Coates et al., 2008 ▸; Wan et al., 2015 ▸; Chen & Unkefer, 2017 ▸). Despite its potential to elucidate the molecular mechanisms behind a wealth of phenomena (Langan et al., 2018 ▸; Schaffner et al., 2017 ▸), the application of neutron crystallography remains limited by the relatively weak intensity of available neutron beams and the high neutron scattering background arising from incoherent scattering by hydrogen within the sample (O’Dell et al., 2016 ▸). While more powerful beamlines and advances in sample preparation have helped to address these challenges, there are also opportunities to develop more advanced computational tools to improve the accuracies of the measured neutron crystallographic data and of the resulting refined structures. Previously, we have developed new computational tools for joint X-ray and neutron refinement that result in more accurate structures (Afonine et al., 2010 ▸). In this work, we focus on a new computational tool to increase the accuracy of the neutron crystallographic data.
We have presented full three-dimensional profile fitting of entire neutron crystallographic data sets for the first time. In contrast to other recent profile fitting performed in detector space (Tomoyori & Tamada, 2016 ▸; Yano et al., 2016 ▸; Gutmann, 2017 ▸), this integration is performed in reciprocal space. As has been argued previously (Schultz et al., 2014 ▸), there are several convenient features of integrating in reciprocal space. Most notably, the peak shapes are straightforward to model. In particular, it is straightforward to isolate peaks at high resolutions. In reciprocal space these peaks maintain separation, and even with a unit cell as large as that of PsbO (∼200 Å) there are no obvious effects of peak overlap. The background can be straightforwardly assessed over a large volume of reciprocal space by considering (h − η, k − η, l − η) to (h + η, k + η, l + η), which aids the quantitation of high-resolution peaks over integration in detector space.