How far are we from automatic crystal structure solution via molecular-replacement techniques?
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ABSTRACT:
SUBMITTER: Burla MC
PROVIDER: S-EPMC6939436 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A description of REMO22, a new molecular replacement program for proteins and nucleic acids, is provided. This program, as with REMO09, can use various types of prior information through appropriate conditional distribution functions. Its efficacy in model searching has been validated through several test cases involving proteins and nucleic acids. Although REMO22 can be configured with different protocols according to user directives, it has been developed primarily as an automated tool for determining the crystal structures of macromolecules. To evaluate REMO22's utility in the current crystallographic environment, its experimental results must be compared favorably with those of the most widely used Molecular Replacement (MR) programs. To accomplish this, we chose two leading tools in the field, PHASER and MOLREP. REMO22, along with MOLREP and PHASER, were included in pipelines that contain two additional steps: phase refinement (SYNERGY) and automated model building (CAB). To evaluate the effectiveness of REMO22, SYNERGY and CAB, we conducted experimental tests on numerous macromolecular structures. The results indicate that REMO22, along with its pipeline REMO22 + SYNERGY + CAB, presents a viable alternative to currently used phasing tools.
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Project description:The solution structure of murine gammaS-crystallin (gammaS) has been determined by multidimensional triple resonance NMR spectroscopy, using restraints derived from two sets of dipolar couplings, recorded in different alignment media, and supplemented by a small number of NOE distance restraints. gammaS consists of two topologically similar domains, arranged with an approximate twofold symmetry, and each domain shows close structural homology to closely related (approximately 50% sequence identity) domains found in other members of the gamma-crystallin family. Each domain consists of two four-strand "Greek key" beta-sheets. Although the domains are tightly anchored to one another by the hydrophobic surfaces of the two inner Greek key motifs, the N-arm, the interdomain linker and several turn regions show unexpected flexibility and disorder in solution. This may contribute entropic stabilization to the protein in solution, but may also indicate nucleation sites for unfolding or other structural transitions. The method used for solving the gammaS structure relies on the recently introduced molecular fragment replacement method, which capitalizes on the large database of protein structures previously solved by X-ray crystallography and NMR.
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Project description:The function of proteins is influenced not only by the atomic structure but also by the detailed structure of the solvent surrounding it. Computational studies of protein structure also critically depend on the water structure around the protein. Herein we compare the water structure obtained from molecular dynamics (MD) simulations of galectin-3 in complex with two ligands to crystallographic water molecules observed in the corresponding crystal structures. We computed MD trajectories both in a water box, which mimics a protein in solution, and in a crystallographic unit cell, which mimics a protein in a crystal. The calculations were compared to crystal structures obtained at both cryogenic and room temperature. Two types of analyses of the MD simulations were performed. First, the positions of the crystallographic water molecules were compared to peaks in the MD density after alignment of the protein in each snapshot. The results of this analysis indicate that all simulations reproduce the crystallographic water structure rather poorly. However, if we define the crystallographic water sites based on their distances to nearby protein atoms and follow these sites throughout the simulations, the MD simulations reproduce the crystallographic water sites much better. This shows that the failure of MD simulations to reproduce the water structure around proteins in crystal structures observed both in this and previous studies is caused by the problem of identifying water sites for a flexible and dynamic protein (traditionally done by overlaying the structures). Our local clustering approach solves the problem and shows that the MD simulations reasonably reproduce the water structure observed in crystals. Furthermore, analysis of the crystal MD simulations indicates a few water molecules that are close to unmodeled electron density peaks in the crystal structures, suggesting that crystal MD could be used as a complementary tool for identifying and modelling water in protein crystallography.
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Project description:Determining new protein structures from X-ray diffraction data at low resolution or with a weak anomalous signal is a difficult and often an impossible task. Here we propose a multivariate algorithm that simultaneously combines the structure determination steps. In tests on over 140 real data sets from the protein data bank, we show that this combined approach can automatically build models where current algorithms fail, including an anisotropically diffracting 3.88 Å RNA polymerase II data set. The method seamlessly automates the process, is ideal for non-specialists and provides a mathematical framework for successfully combining various sources of information in image processing.
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Project description:The title compound, di(strontium/lead) hexa-aluminate, is a member of the solid solution series (Sr2-x Pb x )Al6O11. It contains two statistically occupied M (2+) (M = Sr, Pb) sites [both with site symmetries ..m; Sr:Pb occupancy ratios = 0.756 (2):0.244 (2) and 0.8968 (19):0.1032 (19)] that are located in the voids of an aluminate framework. The M (2+) sites are surrounded by six and seven O atoms, respectively, if a cut-off M-O distance of 3 Å is chosen, resulting in considerably distorted MO x polyhedra. The aluminate framework consists of three AlO6 octa-hedra (two with point-group symmetries ..2/m and one with ..2) sharing edges to form partially filled layers extending parallel to (100) and located at x = 0, 0.5. Adjacent AlO6 layers are linked by a network made up from two crystallographically different AlO4 tetra-hedra by sharing corners.
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Project description:BackgroundComputational models of protein structures were proved to be useful as search models in Molecular Replacement (MR), a common method to solve the phase problem faced by macromolecular crystallography. The success of MR depends on the accuracy of a search model. Unfortunately, this parameter remains unknown until the final structure of the target protein is determined. During the last few years, several Model Quality Assessment Programs (MQAPs) that predict the local accuracy of theoretical models have been developed. In this article, we analyze whether the application of MQAPs improves the utility of theoretical models in MR.ResultsFor our dataset of 615 search models, the real local accuracy of a model increases the MR success ratio by 101% compared to corresponding polyalanine templates. On the contrary, when local model quality is not utilized in MR, the computational models solved only 4.5% more MR searches than polyalanine templates. For the same dataset of the 615 models, a workflow combining MR with predicted local accuracy of a model found 45% more correct solution than polyalanine templates. To predict such accuracy MetaMQAPclust, a "clustering MQAP" was used.ConclusionsUsing comparative models only marginally increases the MR success ratio in comparison to polyalanine structures of templates. However, the situation changes dramatically once comparative models are used together with their predicted local accuracy. A new functionality was added to the GeneSilico Fold Prediction Metaserver in order to build models that are more useful for MR searches. Additionally, we have developed a simple method, AmIgoMR (Am I good for MR?), to predict if an MR search with a template-based model for a given template is likely to find the correct solution.
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Project description:Iron-containing porphyrins are essential for all life as electron carriers. Since iron is poorly available in an oxidizing environment, bacterial growth may be restricted by iron limitation, and this has led to the evolution of a huge variety of iron-uptake systems. Among pathogens, iron scavenging from the haemoglobin of an animal host is a common means of acquiring sufficient iron for growth. The Isd system of Staphylococcus aureus is a well studied example; the bacterium devotes considerable resources to the construction of surface proteins that deftly remove haem from haemoglobin and pass it along a chain of related proteins, eventually delivering the haem to the cytoplasm, where it can be utilized or degraded. All organisms, however, must deal with haem and related molecules, which are by their nature hydrophobic and prone to precipitate, and which tend to promote the formation of reactive oxygen species. Chaperones are an obvious solution to the problem of maintaining a pool of haem for insertion into cytochromes without allowing naked haem to cause damage. YdiE is a very small protein from Escherichia coli of only 63 residues which may play a role in haem trafficking. Here, NMR analysis and the crystal structure of the protein to high resolution are reported.
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Project description:Molecular replacement (MR) is the predominant route to solution of the phase problem in macromolecular crystallography. Where the lack of a suitable homologue precludes conventional MR, one option is to predict the target structure using bioinformatics. Such modelling, in the absence of homologous templates, is called ab initio or de novo modelling. Recently, the accuracy of such models has improved significantly as a result of the availability, in many cases, of residue-contact predictions derived from evolutionary covariance analysis. Covariance-assisted ab initio models representing structurally uncharacterized Pfam families are now available on a large scale in databases, potentially representing a valuable and easily accessible supplement to the PDB as a source of search models. Here, the unconventional MR pipeline AMPLE is employed to explore the value of structure predictions in the GREMLIN and PconsFam databases. It was tested whether these deposited predictions, processed in various ways, could solve the structures of PDB entries that were subsequently deposited. The results were encouraging: nine of 27 GREMLIN cases were solved, covering target lengths of 109-355 residues and a resolution range of 1.4-2.9 Å, and with target-model shared sequence identity as low as 20%. The cluster-and-truncate approach in AMPLE proved to be essential for most successes. For the overall lower quality structure predictions in the PconsFam database, remodelling with Rosetta within the AMPLE pipeline proved to be the best approach, generating ensemble search models from single-structure deposits. Finally, it is shown that the AMPLE-obtained search models deriving from GREMLIN deposits are of sufficiently high quality to be selected by the sequence-independent MR pipeline SIMBAD. Overall, the results help to point the way towards the optimal use of the expanding databases of ab initio structure predictions.
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