![]() ![]() 2001), the integral membrane protein complex DsbB-DsbA (Tang et al. 1992), bovine pancreatic trypsin inhibitor (Schiffer et al. The calculations indicated that the two sets of data are consistent for a number of studied proteins (interleukin-1 β (Shaanan et al. Joint refinements against X-ray and NMR data were previously performed using distance restraints and backbone dihedral angles as NMR restraints, through the programs CNS and X-PLOR (Brunger et al. On the other hand, the violating restraints in the joint refinement may provide an indication of the regions where real differences occur. The fact that X-ray and NMR data can be combined to produce models that are compatible with both sets of data, in the sense that (i) the crystallographic R-factor and the free R-factor are the same to those calculated with X-ray data alone, and that (ii) the NMR restraint violations are minimal, indicates that the discrepancies between solution and crystal structures may be apparent rather than real, and that a joint refinement against all data may provide a more reliable model than those obtained using one of the techniques alone. It was noticed that crystal models frequently present a large number of NOE distance violations, as well as solution models obtained by NMR poorly fit the X-ray data: these discrepancies may either be due to differences in the molecular structure between solution and solid state, or to the different but complementary information contained in these two types of data. X-ray data, NMR-derived distance restraints and backbone dihedral angles were previously used for a joint refinement of protein structure (Shaanan et al. However, before following this path, one should consider first if the X-ray data has sufficient information to position atoms and bonds that are observed by NMR, because, if placed with a low accuracy, inconsistencies may lose significance (structural noise) (Zweckstetter and Bax 2002). Quite often, these inconsistencies are interpreted as significant and subsequently reconciled by considering structural rearrangements on passing from solid state to solution and/or invoking mobility of different extents and on different timescales (Chou et al. It is often the case that the X-ray structures and the NMR data are not in perfect agreement with each other. The combination of these techniques thus yields valuable information throughout the whole range of distances, even in the presence of suboptimal X-ray and/or NMR data. X-ray crystallographic diffraction (and cryo-EM) data give information that progress from the overall shape of the molecule up to individual atom positions as the resolution increases on the contrary, NMR data mostly progress from short-range inter-atom distances and bond orientations to the overall shape of the molecule with increasing number and quality of restraints. 8.5%), and single particle cryo electron microscopy (no. 89.6%) and solution NMR spectroscopy (no. By and large, the two most common experimental techniques for biomolecular structure determination are X-ray diffraction (no. 2013 van den Bedem and Fraser 2015 Carlon et al. Integrated Structural Biology tries to merge the results from different experimental techniques, making the most of the information encoded in each (Ward et al. We show three different examples where NMR and X-ray data can be reconciled to a unique structural model without invoking mobility. The new feature may either help in improving the refinement, or assist in spotting differences between the crystal and the solution data. ![]() We thus introduce a set of new features of REFMAC-NMR that allow for improved handling of RDC data for multidomain proteins and multisubunit biomolecular complexes, and encompasses the use of pseudo-contact shifts as an additional source of NMR-based information. Here, we discuss the effect of including a-priori knowledge on the properties of the system to reduce the number of experimental data needed to obtain a more complete picture. Once crystals are obtained, it is often rather easy to obtain a complete X-ray dataset, however it is time-consuming to obtain an exhaustive NMR dataset. The first are exquisitely sensitive to the local details but does not give any information about overall shape, whereas the latter encodes more the information about the overall shape but at the same time tends to miss the local details even at the highest resolutions. In this frame, one of the combinations, which we have implemented in REFMAC-NMR, is residual dipolar couplings from NMR together with experimental data from X-ray diffraction. Data integration in structural biology has become a paradigm for the characterization of biomolecular systems, and it is now accepted that combining different techniques can fill the gaps in each other’s blind spots. ![]()
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