Automated Crystal Structure Determination Has its Pitfalls: Correction to the Crystal Structures of Iodine Azide.
Ontology highlight
ABSTRACT:
SUBMITTER: Muller U
PROVIDER: S-EPMC8361933 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Efficient determination of protein crystal structures requires automated x-ray data analysis. Here, we describe the expert system ELVES and its use to determine automatically the structure of a 12-kDa protein. Multiwavelength anomalous diffraction analysis of a selenomethionyl derivative was used to image the Asn-16-Ala variant of the GCN4 leucine zipper. In contrast to the parallel, dimeric coiled coil formed by the WT sequence, the mutant unexpectedly formed an antiparallel trimer. This structural switch reveals how avoidance of core cavities at a single site can select the native fold of a protein. All structure calculations, including indexing, data processing, locating heavy atoms, phasing by multiwavelength anomalous diffraction, model building, and refinement, were completed without human intervention. The results demonstrate the feasibility of automated methods for determining high-resolution, x-ray crystal structures of proteins.
| S-EPMC341770 | biostudies-literature
Project description:We present a method for automatic solution of protein crystal structures. The method proceeds with a single initial model obtained, for instance, by molecular replacement (MR). If a good-quality search model is not available, as often is the case with MR of distant homologs, our method first can automatically screen a large pool of poorly placed models and single out promising candidates for further processing if there are any. We demonstrate its utility by solving a set of synthetic cases in the 2.9- to 3.45-Å resolution.
| S-EPMC6561213 | biostudies-literature
Project description:PpcA is a small protein with 71 residues that contains three covalently bound hemes. The structures of single mutants at residue 58 have shown larger deviations in another part of the protein molecule than at the site of the mutation. Closer examination of the crystal packing has revealed the origin of this unexpected structural change. The site of mutation is within Van der Waals distance from another protein molecule related by a crystallographic twofold axis within the crystal. The structural changes occurred at or near the mutation site have led to a slight adjustment of the surface residues in contact. The observed deviations between the native and the mutant molecular structures are derived from the new crystal packing even though the two crystals are essentially isomorphous. Without careful consideration of the crystal lattice a non-expert looking at only the coordinates deposited in the Protein Data Bank could draw erroneous conclusion that mutation in one part of the molecule affected the structure of the protein in a distant part of the molecule.
| S-EPMC4109977 | biostudies-literature
Project description:Serial rotation electron diffraction (SerialRED) has been developed as a fully automated technique for three-dimensional electron diffraction data collection that can run autonomously without human intervention. It builds on the previously established serial electron diffraction technique, in which submicrometre-sized crystals are detected using image processing algorithms. Continuous rotation electron diffraction (cRED) data are collected on each crystal while dynamically tracking the movement of the crystal during rotation using defocused diffraction patterns and applying a set of deflector changes. A typical data collection screens up to 500 crystals per hour, and cRED data are collected from suitable crystals. A data processing pipeline is developed to process the SerialRED data sets. Hierarchical cluster analysis is implemented to group and identify the different phases present in the sample and to find the best matching data sets to be merged for subsequent structure analysis. This method has been successfully applied to a series of zeolites and a beam-sensitive metal-organic framework sample to study its capability for structure determination and refinement. Two multi-phase samples were tested to show that the individual crystal phases can be identified and their structures determined. The results show that refined structures obtained using automatically collected SerialRED data are indistinguishable from those collected manually using the cRED technique. At the same time, SerialRED has lower requirements of expertise in transmission electron microscopy and is less labor intensive, making it a promising high-throughput crystal screening and structure analysis tool.
| S-EPMC6760450 | biostudies-literature
Project description:Many macromolecular model-building and refinement programs can automatically place solvent atoms in electron density at moderate-to-high resolution. This process frequently builds water molecules in place of elemental ions, the identification of which must be performed manually. The solvent-picking algorithms in phenix.refine have been extended to build common ions based on an analysis of the chemical environment as well as physical properties such as occupancy, B factor and anomalous scattering. The method is most effective for heavier elements such as calcium and zinc, for which a majority of sites can be placed with few false positives in a diverse test set of structures. At atomic resolution, it is observed that it can also be possible to identify tightly bound sodium and magnesium ions. A number of challenges that contribute to the difficulty of completely automating the process of structure completion are discussed.
| S-EPMC3975891 | biostudies-literature
Project description: Not available
| S-EPMC10413960 | biostudies-literature
Project description:SummaryPONDEROSA (Peak-picking Of Noe Data Enabled by Restriction of Shift Assignments) accepts input information consisting of a protein sequence, backbone and sidechain NMR resonance assignments, and 3D-NOESY ((13)C-edited and/or (15)N-edited) spectra, and returns assignments of NOESY crosspeaks, distance and angle constraints, and a reliable NMR structure represented by a family of conformers. PONDEROSA incorporates and integrates external software packages (TALOS+, STRIDE and CYANA) to carry out different steps in the structure determination. PONDEROSA implements internal functions that identify and validate NOESY peak assignments and assess the quality of the calculated three-dimensional structure of the protein. The robustness of the analysis results from PONDEROSA's hierarchical processing steps that involve iterative interaction among the internal and external modules. PONDEROSA supports a variety of input formats: SPARKY assignment table (.shifts) and spectrum file formats (.ucsf), XEASY proton file format (.prot), and NMR-STAR format (.star). To demonstrate the utility of PONDEROSA, we used the package to determine 3D structures of two proteins: human ubiquitin and Escherichia coli iron-sulfur scaffold protein variant IscU(D39A). The automatically generated structural constraints and ensembles of conformers were as good as or better than those determined previously by much less automated means.AvailabilityThe program, in the form of binary code along with tutorials and reference manuals, is available at http://ponderosa.nmrfam.wisc.edu/.
| S-EPMC3106192 | biostudies-literature
Project description:The reduction of uridine to dihydrouridine at specific positions in tRNA is catalysed by dihydrouridine synthase (Dus) enzymes. Increased expression of human dihydrouridine synthase 2 (hDus2) has been linked to pulmonary carcinogenesis, while its knockdown decreased cancer cell line viability, suggesting that it may serve as a valuable target for therapeutic intervention. Here, the X-ray crystal structure of a construct of hDus2 encompassing the catalytic and tRNA-recognition domains (residues 1-340) determined at 1.9 Å resolution is presented. It is shown that the structure can be determined automatically by phenix.mr_rosetta starting from a bacterial Dus enzyme with only 18% sequence identity and a significantly divergent structure. The overall fold of the human Dus2 is similar to that of bacterial enzymes, but has a larger recognition domain and a unique three-stranded antiparallel β-sheet insertion into the catalytic domain that packs next to the recognition domain, contributing to domain-domain interactions. The structure may inform the development of novel therapeutic approaches in the fight against lung cancer.
| S-EPMC4498606 | biostudies-literature
Project description:Conventional NMR structure determination requires nearly complete assignment of the cross peaks of a refined NOESY peak list. Depending on the size of the protein and quality of the spectral data, this can be a time-consuming manual process requiring several rounds of peak list refinement and structure determination. Programs such as Aria, CYANA, and AutoStructure can generate models using unassigned NOESY data but are very sensitive to the quality of the input peak lists and can converge to inaccurate structures if the signal-to-noise of the peak lists is low. Here, we show that models with high accuracy and reliability can be produced by combining the strengths of the high-resolution structure prediction program Rosetta with global measures of the agreement between structure models and experimental data. A first round of models generated using CS-Rosetta (Rosetta supplemented with backbone chemical shift information) are filtered on the basis of their goodness-of-fit with unassigned NOESY peak lists using the DP-score, and the best fitting models are subjected to high resolution refinement with the Rosetta rebuild-and-refine protocol. This hybrid approach uses both local backbone chemical shift and the unassigned NOESY data to direct Rosetta trajectories toward the native structure and produces more accurate models than AutoStructure/CYANA or CS-Rosetta alone, particularly when using raw unedited NOESY peak lists. We also show that when accurate manually refined NOESY peak lists are available, Rosetta refinement can consistently increase the accuracy of models generated using CYANA and AutoStructure.
| S-EPMC2841443 | biostudies-literature
Project description:The protocols currently used for protein structure determination by nuclear magnetic resonance (NMR) depend on the determination of a large number of upper distance limits for proton-proton pairs. Typically, this task is performed manually by an experienced researcher rather than automatically by using a specific computer program. To assess whether it is indeed possible to generate in a fully automated manner NMR structures adequate for deposition in the Protein Data Bank, we gathered 10 experimental data sets with unassigned nuclear Overhauser effect spectroscopy (NOESY) peak lists for various proteins of unknown structure, computed structures for each of them using different, fully automatic programs, and compared the results to each other and to the manually solved reference structures that were not available at the time the data were provided. This constitutes a stringent "blind" assessment similar to the CASP and CAPRI initiatives. This study demonstrates the feasibility of routine, fully automated protein structure determination by NMR.
| S-EPMC3609704 | biostudies-literature