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1.  Structure of the protein core of translation initiation factor 2 in apo, GTP-bound and GDP-bound forms 
The crystal structures of the eubacterial translation initiation factor 2 in apo form and with bound GDP and GTP reveal conformational changes upon nucleotide binding and hydrolysis, notably of the catalytically important histidine in the switch II region.
Translation initiation factor 2 (IF2) is involved in the early steps of bacterial protein synthesis. It promotes the stabilization of the initiator tRNA on the 30S initiation complex (IC) and triggers GTP hydrolysis upon ribosomal subunit joining. While the structure of an archaeal homologue (a/eIF5B) is known, there are significant sequence and functional differences in eubacterial IF2, while the trimeric eukaryotic IF2 is completely unrelated. Here, the crystal structure of the apo IF2 protein core from Thermus thermophilus has been determined by MAD phasing and the structures of GTP and GDP complexes were also obtained. The IF2–GTP complex was trapped by soaking with GTP in the cryoprotectant. The structures revealed conformational changes of the protein upon nucleotide binding, in particular in the P-loop region, which extend to the functionally relevant switch II region. The latter carries a catalytically important and conserved histidine residue which is observed in different conformations in the GTP and GDP complexes. Overall, this work provides the first crystal structure of a eubacterial IF2 and suggests that activation of GTP hydrolysis may occur by a conformational repositioning of the histidine residue.
doi:10.1107/S0907444913006422
PMCID: PMC3663118  PMID: 23695237
translation initiation factor 2; Thermus thermophilus; GTP; GDP
2.  Towards automated crystallographic structure refinement with phenix.refine  
phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods.
phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. It has several automation features and is also highly flexible. Several hundred parameters enable extensive customizations for complex use cases. Multiple user-defined refinement strategies can be applied to specific parts of the model in a single refinement run. An intuitive graphical user interface is available to guide novice users and to assist advanced users in managing refinement projects. X-ray or neutron diffraction data can be used separately or jointly in refinement. phenix.refine is tightly integrated into the PHENIX suite, where it serves as a critical component in automated model building, final structure refinement, structure validation and deposition to the wwPDB. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods.
doi:10.1107/S0907444912001308
PMCID: PMC3322595  PMID: 22505256
structure refinement; PHENIX; joint X-ray/neutron refinement; maximum likelihood; TLS; simulated annealing; subatomic resolution; real-space refinement; twinning; NCS
3.  On the use of logarithmic scales for analysis of diffraction data 
Conventional and free R factors and their difference, as well as the ratio of the number of measured reflections to the number of atoms in the crystal, were studied as functions of the resolution at which the structures were reported. When the resolution was taken uniformly on a logarithmic scale, the most frequent values of these functions were quasi-linear over a large resolution range.
Predictions of the possible model parameterization and of the values of model characteristics such as R factors are important for macromolecular refinement and validation protocols. One of the key parameters defining these and other values is the resolution of the experimentally measured diffraction data. The higher the resolution, the larger the number of diffraction data N ref, the larger its ratio to the number N at of non-H atoms, the more parameters per atom can be used for modelling and the more precise and detailed a model can be obtained. The ratio N ref/N at was calculated for models deposited in the Protein Data Bank as a function of the resolution at which the structures were reported. The most frequent values for this distribution depend essentially linearly on resolution when the latter is expressed on a uniform logarithmic scale. This defines simple analytic formulae for the typical Matthews coefficient and for the typically allowed number of parameters per atom for crystals diffracting to a given resolution. This simple dependence makes it possible in many cases to estimate the expected resolution of the experimental data for a crystal with a given Matthews coefficient. When expressed using the same logarithmic scale, the most frequent values for R and R free factors and for their difference are also essentially linear across a large resolution range. The minimal R-factor values are practically constant at resolutions better than 3 Å, below which they begin to grow sharply. This simple dependence on the resolution allows the prediction of expected R-factor values for unknown structures and may be used to guide model refinement and validation.
doi:10.1107/S0907444909039638
PMCID: PMC2789003  PMID: 19966414
resolution; logarithmic scale; R factor; data-to-parameter ratio
4.  Cluster analysis for phasing with molecular replacement: a feasibility study 
Molecular replacement with the simultaneous use of several search functions may solve the phase problem when the conventional molecular-replacement procedure fails to identify the solution.
Molecular replacement can fail to find a solution, namely a unique orientation and position of a search model, even when many search models are tested under various conditions. Simultaneous use of the results of these searches may help in the solution of such difficult structures. A closeness between the peaks of several calculated rotation functions may identify the model orientation. The largest and most compact cluster of such peaks usually corresponds to models which are oriented similarly to the molecule under study. A search for the optimal translation may be more problematic and both individual translation functions and straightforward cluster analysis in the space of geometric parameters such as rotation angles and translation vectors may give no result. An improvement may be obtained by performing cluster analysis of the peaks of several translation functions in phase-set space. In this case, the Fourier maps computed using the observed structure-factor magnitudes and the phases calculated from differently positioned models are compared. Again, as a rule, the largest and the most compact cluster corresponds to the correct solution. The result of the updated procedure is no longer a single search model but an averaged Fourier map.
doi:10.1107/S090744490900969X
PMCID: PMC2703570  PMID: 19564684
molecular replacement; persistent solution; cluster analysis; phasing
5.  Crystallographic model quality at a glance 
The representation of crystallographic model characteristics in the form of a polygon allows the quick comparison of a model with a set of previously solved structures.
A crystallographic macromolecular model is typically characterized by a list of quality criteria, such as R factors, deviations from ideal stereochemistry and average B factors, which are usually provided as tables in publications or in structural databases. In order to facilitate a quick model-quality evaluation, a graphical representation is proposed. Each key parameter such as R factor or bond-length deviation from ‘ideal values’ is shown graphically as a point on a ‘ruler’. These rulers are plotted as a set of lines with the same origin, forming a hub and spokes. Different parts of the rulers are coloured differently to reflect the frequency (red for a low frequency, blue for a high frequency) with which the corresponding values are observed in a reference set of structures determined previously. The points for a given model marked on these lines are connected to form a polygon. A polygon that is strongly compressed or dilated along some axes reveals unusually low or high values of the corresponding characteristics. Polygon vertices in ‘red zones’ indicate parameters which lie outside typical values.
doi:10.1107/S0907444908044296
PMCID: PMC2651759  PMID: 19237753
model quality; PDB; validation; refinement; PHENIX
6.  On macromolecular refinement at subatomic resolution with interatomic scatterers 
Modelling deformation electron density using interatomic scatters is simpler than multipolar methods, produces comparable results at subatomic resolution and can easily be applied to macromolecules.
A study of the accurate electron-density distribution in molecular crystals at subatomic resolution (better than ∼1.0 Å) requires more detailed models than those based on independent spherical atoms. A tool that is conventionally used in small-molecule crystallography is the multipolar model. Even at upper resolution limits of 0.8–1.0 Å, the number of experimental data is insufficient for full multipolar model refinement. As an alternative, a simpler model composed of conventional independent spherical atoms augmented by additional scatterers to model bonding effects has been proposed. Refinement of these mixed models for several benchmark data sets gave results that were comparable in quality with the results of multipolar refinement and superior to those for conventional models. Applications to several data sets of both small molecules and macromolecules are shown. These refinements were performed using the general-purpose macromolecular refinement module phenix.refine of the PHENIX package.
doi:10.1107/S0907444907046148
PMCID: PMC2808317  PMID: 18007035
structure refinement; subatomic resolution; deformation density; interatomic scatterers; PHENIX

Results 1-6 (6)