201 research outputs found
The Kanarra fold-thrust structure - the leading edge of the Sevier fold-thrust belt, southwestern Utah: Geology of the Intermountain West
The multiple origins proposed for the Kanarra anticline in southwestern Utah as a drag-fold along the Hurricane fault, a Laramide monocline, a Sevier fault-propagation fold, or a combination of these processes, serve to muddy its tectonic significance. This in part reflects the structural complexity of the exposed eastern half of the fold. The fold evolved from open and up-right to overturned and tight, is cross-cut by multiple faults, and was subsequently dismembered by the Hurricane fault. The western half of the fold is obscured because of burial, along with the hanging wall of the Hurricane fault, beneath Neogene and younger sediments and volcanics. We present the results of detailed bedrock geologic mapping, and geologic cross sections restored to Late Cretaceous time (prior to Basin and Range extension), to demonstrate the Kanarra anticline is a compound anticline-syncline pair inextricably linked with concomitant thrust faulting that formed during the Sevier orogeny. We propose the name Kanarra fold-thrust structure to unambiguously identify the close spatial and temporal association of folding and thrusting in formation of this prominent geologic feature. We identify a previously unrecognized thrust, the Red Rock Trail thrust, as a forelimb shear thrust that was in a favorable orientation and position to have been soft-linked, and locally hard-linked, with the thrust ramp of the basal detachment to form a break thrust. The east verging Red Rock Trail thrust is recognized by a distinctive cataclasite in the Lower Jurassic Navajo Sandstone. The hanging wall of the Red Rock Trail thrust is displaced eastward over the Middle Jurassic Carmel Formation and Upper Cretaceous Formations and can be traced for at least 27 km and possibly farther. We contend the Kanarra fold-thrust structure unambiguously defines the leading edge of the Sevier fold-thrust belt in southwestern Utah. Stratigraphic relationships in the southern and northern part of the Kanarra fold-thrust structure constrain its development between the early and late Campanian (about 84 to 71 Ma) but possibly younger. In southwest Utah, initial movement along the Iron Springs thrust at about 100 Ma (Quick and others, 2020) and subsequent eastward advancement of the Sevier deformation front to the Red Rock Trail thrust at about 84 to 71 Ma coincided with well-documented magmatic flare ups in the Cordilleran arc in the hinterland of the Sevier fold-thrust belt. This temporal relationship between magmatic flare ups and thrusting is consistent with a close correspondence between arc-related processes and episodic foreland deformation
Data growth and its impact on the SCOP database: new developments
The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. The SCOP hierarchy comprises the following levels: Species, Protein, Family, Superfamily, Fold and Class. While keeping the original classification scheme intact, we have changed the production of SCOP in order to cope with a rapid growth of new structural data and to facilitate the discovery of new protein relationships. We describe ongoing developments and new features implemented in SCOP. A new update protocol supports batch classification of new protein structures by their detected relationships at Family and Superfamily levels in contrast to our previous sequential handling of new structural data by release date. We introduce pre-SCOP, a preview of the SCOP developmental version that enables earlier access to the information on new relationships. We also discuss the impact of worldwide Structural Genomics initiatives, which are producing new protein structures at an increasing rate, on the rates of discovery and growth of protein families and superfamilies. SCOP can be accessed at http://scop.mrc-lmb.cam.ac.uk/scop
AutoPSI: a database for automatic structural classification of protein sequences and structures
In protein research, structural classifications of protein domains provided by databases such as SCOP play an important role. However, as such databases have to be curated and prepared carefully, they update only up to a few times per year, and in between newly entered PDB structures cannot be used in cases where a structural classification is required. The Automated Protein Structure Identification (AutoPSI) database delivers predicted SCOP classifications for several thousand yet unclassified PDB entries as well as millions of UniProt sequences in an automated fashion. In order to obtain predictions, we make use of two recently published methods, namely AutoSCOP (sequence-based) and Vorolign (structure-based) and the consensus of both. With our predictions, we bridge the gap between SCOP versions for proteins with known structures in the PDB and additionally make structure predictions for a very large number of UniProt proteins. AutoPSI is freely accessible at http://www.bio.ifi.lmu.de/AutoPSIDB
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High-throughput isolation and characterization of untagged membrane protein complexes: outer membrane complexes of Desulfovibrio vulgaris.
Cell membranes represent the "front line" of cellular defense and the interface between a cell and its environment. To determine the range of proteins and protein complexes that are present in the cell membranes of a target organism, we have utilized a "tagless" process for the system-wide isolation and identification of native membrane protein complexes. As an initial subject for study, we have chosen the Gram-negative sulfate-reducing bacterium Desulfovibrio vulgaris. With this tagless methodology, we have identified about two-thirds of the outer membrane- associated proteins anticipated. Approximately three-fourths of these appear to form homomeric complexes. Statistical and machine-learning methods used to analyze data compiled over multiple experiments revealed networks of additional protein-protein interactions providing insight into heteromeric contacts made between proteins across this region of the cell. Taken together, these results establish a D. vulgaris outer membrane protein data set that will be essential for the detection and characterization of environment-driven changes in the outer membrane proteome and in the modeling of stress response pathways. The workflow utilized here should be effective for the global characterization of membrane protein complexes in a wide range of organisms
SimShiftDB; local conformational restraints derived from chemical shift similarity searches on a large synthetic database
We present SimShiftDB, a new program to extract conformational data from protein chemical shifts using structural alignments. The alignments are obtained in searches of a large database containing 13,000 structures and corresponding back-calculated chemical shifts. SimShiftDB makes use of chemical shift data to provide accurate results even in the case of low sequence similarity, and with even coverage of the conformational search space. We compare SimShiftDB to HHSearch, a state-of-the-art sequence-based search tool, and to TALOS, the current standard tool for the task. We show that for a significant fraction of the predicted similarities, SimShiftDB outperforms the other two methods. Particularly, the high coverage afforded by the larger database often allows predictions to be made for residues not involved in canonical secondary structure, where TALOS predictions are both less frequent and more error prone. Thus SimShiftDB can be seen as a complement to currently available methods
Predicting Secondary Structures, Contact Numbers, and Residue-wise Contact Orders of Native Protein Structure from Amino Acid Sequence by Critical Random Networks
Prediction of one-dimensional protein structures such as secondary structures
and contact numbers is useful for the three-dimensional structure prediction
and important for the understanding of sequence-structure relationship. Here we
present a new machine-learning method, critical random networks (CRNs), for
predicting one-dimensional structures, and apply it, with position-specific
scoring matrices, to the prediction of secondary structures (SS), contact
numbers (CN), and residue-wise contact orders (RWCO). The present method
achieves, on average, accuracy of 77.8% for SS, correlation coefficients
of 0.726 and 0.601 for CN and RWCO, respectively. The accuracy of the SS
prediction is comparable to other state-of-the-art methods, and that of the CN
prediction is a significant improvement over previous methods. We give a
detailed formulation of critical random networks-based prediction scheme, and
examine the context-dependence of prediction accuracies. In order to study the
nonlinear and multi-body effects, we compare the CRNs-based method with a
purely linear method based on position-specific scoring matrices. Although not
superior to the CRNs-based method, the surprisingly good accuracy achieved by
the linear method highlights the difficulty in extracting structural features
of higher order from amino acid sequence beyond that provided by the
position-specific scoring matrices.Comment: 20 pages, 1 figure, 5 tables; minor revision; accepted for
publication in BIOPHYSIC
PROMALS3D web server for accurate multiple protein sequence and structure alignments
Multiple sequence alignments are essential in computational sequence and structural analysis, with applications in homology detection, structure modeling, function prediction and phylogenetic analysis. We report PROMALS3D web server for constructing alignments for multiple protein sequences and/or structures using information from available 3D structures, database homologs and predicted secondary structures. PROMALS3D shows higher alignment accuracy than a number of other advanced methods. Input of PROMALS3D web server can be FASTA format protein sequences, PDB format protein structures and/or user-defined alignment constraints. The output page provides alignments with several formats, including a colored alignment augmented with useful information about sequence grouping, predicted secondary structures and consensus sequences. Intermediate results of sequence and structural database searches are also available. The PROMALS3D web server is available at: http://prodata.swmed.edu/promals3d/
Towards a comprehensive structural coverage of completed genomes: a structural genomics viewpoint
BACKGROUND: Structural genomics initiatives were established with the aim of solving protein structures on a large-scale. For many initiatives, such as the Protein Structure Initiative (PSI), the primary aim of target selection is focussed towards structurally characterising protein families which, so far, lack a structural representative. It is therefore of considerable interest to gain insights into the number and distribution of these families, and what efforts may be required to achieve a comprehensive structural coverage across all protein families. RESULTS: In this analysis we have derived a comprehensive domain annotation of the genomes using CATH, Pfam-A and Newfam domain families. We consider what proportions of structurally uncharacterised families are accessible to high-throughput structural genomics pipelines, specifically those targeting families containing multiple prokaryotic orthologues. In measuring the domain coverage of the genomes, we show the benefits of selecting targets from both structurally uncharacterised domain families, whilst in addition, pursuing additional targets from large structurally characterised protein superfamilies. CONCLUSION: This work suggests that such a combined approach to target selection is essential if structural genomics is to achieve a comprehensive structural coverage of the genomes, leading to greater insights into structure and the mechanisms that underlie protein evolution
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NMR structure of the N-terminal domain of the replication initiator protein DnaA
DnaA is an essential component in the initiation of bacterial chromosomal replication. DnaA binds to a series of 9 base pair repeats leading to oligomerization, recruitment of the DnaBC helicase, and the assembly of the replication fork machinery. The structure of the N-terminal domain (residues 1-100) of DnaA from Mycoplasma genitalium was determined by NMR spectroscopy. The backbone r.m.s.d. for the first 86 residues was 0.6 +/- 0.2 Angstrom based on 742 NOE, 50 hydrogen bond, 46 backbone angle, and 88 residual dipolar coupling restraints. Ultracentrifugation studies revealed that the domain is monomeric in solution. Features on the protein surface include a hydrophobic cleft flanked by several negative residues on one side, and positive residues on the other. A negatively charged ridge is present on the opposite face of the protein. These surfaces may be important sites of interaction with other proteins involved in the replication process. Together, the structure and NMR assignments should facilitate the design of new experiments to probe the protein-protein interactions essential for the initiation of DNA replication
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