Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

B-factor accuracy in protein crystal structures.

ABSTRACT: The accuracy of B factors in protein crystal structures has been determined by comparing the same atoms in numerous, independent crystal structures of Gallus gallus lysozyme. Both B-factor absolute differences and normal probability plots indicate that the estimated B-factor errors are quite large, close to 9 Å² in ambient-temperature structures and to 6 Å² in low-temperature structures, and surprisingly are comparable to values estimated two decades ago. It is well known that B factors are not due to local movements only but reflect several, additional factors from crystal defects, large-scale disorder, diffraction data quality etc. It therefore remains essential to normalize B factors when comparing different crystal structures, although it has clearly been shown that they provide useful information about protein dynamics. Improved, quantitative analyses of raw B factors require novel experimental and computational tools that are able to disaggregate local movements from other features and properties that affect B factors.

SUBMITTER: Carugo O

PROVIDER: S-EPMC8725162 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

B-factor accuracy in protein crystal structures.

Carugo Oliviero O

Acta crystallographica. Section D, Structural biology 20220101 Pt 1

The accuracy of B factors in protein crystal structures has been determined by comparing the same atoms in numerous, independent crystal structures of Gallus gallus lysozyme. Both B-factor absolute differences and normal probability plots indicate that the estimated B-factor errors are quite large, close to 9 Å<sup>2</sup> in ambient-temperature structures and to 6 Å<sup>2</sup> in low-temperature structures, and surprisingly are comparable to values estimated two decades ago. It is well known t ...[more]

PMID: 34981763

Similar Datasets

AI-based protein models enhance the accuracy of experimentally determined protein crystal structures.

Project description: Not available

| S-EPMC10324573 | biostudies-literature

Protein NMR structures refined with Rosetta have higher accuracy relative to corresponding X-ray crystal structures.

Project description:We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5-22 kDa, restrained Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 37 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10-25 kDa the less CPU intensive restrained Rosetta refinement protocols provided equally or more accurate structures. The restrained Rosetta protocols described here can improve the accuracy of protein NMR structures and should find broad and general for studies of protein structure and function.

| S-EPMC4129517 | biostudies-literature

Unsupervised determination of protein crystal structures.

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

Internal motion in protein crystal structures.

Project description:The binding states of the substrates and the environment have significant influence on protein motion. We present the analysis of such motion derived from anisotropic atomic displacement parameters (ADPs) in a set of atomic resolution protein structures. Local structural motion caused by ligand binding as well as functional loops showing cooperative patterns of motion could be inferred. The results are in line with proposed protonation states, hydrogen bonding patterns and the location of distinctly flexible regions: we could locate the mobile active site loop in a virus integrase, distinguish the subdomains in RNAse A and hydroxynitrile lyase, and reconstruct the molecular architecture in a xylanase. We demonstrate that the ADP-based motion analysis provides information at high level of detail and that the structural changes needed for substrate attachment or release may be derived from single X-ray structures.

| S-EPMC2868237 | biostudies-literature

Decoding Corticotropin-Releasing Factor Receptor Type 1 Crystal Structures.

Project description:The structural analysis of class B G protein-coupled receptors (GPCR), cell surface proteins responding to peptide hormones, has until recently been restricted to the extracellular domain (ECD). Corticotropin-releasing factor receptor type 1 (CRF1R) is a class B receptor mediating stress response and also considered a drug target for depression and anxiety. Here we report the crystal structure of the transmembrane domain of human CRF1R in complex with the small-molecule antagonist CP-376395 in a hexagonal setting with translational non-crystallographic symmetry. Molecular dynamics and metadynamics simulations on this novel structure and the existing TMD structure for CRF1R provides insight as to how the small molecule ligand gains access to the induced-fit allosteric binding site with implications for the observed selectivity against CRF2R. Furthermore, molecular dynamics simulations performed using a full-length receptor model point to key interactions between the ECD and extracellular loop 3 of the TMD providing insight into the full inactive state of multidomain class B GPCRs.

| S-EPMC5684783 | biostudies-literature

Crystal structures of transcription factor NusG in light of its nucleic acid- and protein-binding activities.

Project description:Microbial transcription modulator NusG interacts with RNA polymerase and termination factor rho, displaying striking functional homology to eukaryotic Spt5. The protein is also a translational regulator. We have determined crystal structures of Aquifex aeolicus NusG showing a modular design: an N-terminal RNP-like domain, a C-terminal element with a KOW sequence motif and a species-specific immunoglobulin-like fold. The structures reveal bona fide nucleic acid binding sites, and nucleic acid binding activities can be detected for NusG from three organisms and for the KOW element alone. A conserved KOW domain is defined as a new class of nucleic acid binding folds. This module is a close structural homolog of tudor protein-protein interaction motifs. Putative protein binding sites for the RNP and KOW domains can be deduced, which differ from the areas implicated in nucleic acid interactions. The results strongly argue that both protein and nucleic acid contacts are important for NusG's functions and that the factor can act as an adaptor mediating indirect protein-nucleic acid associations.

| S-EPMC126194 | biostudies-literature

Mining protein dynamics from sets of crystal structures using "consensus structures".

Project description:In this work, we describe two novel approaches to utilize the dynamic structure information implicitly contained in large crystal structure data sets. The first approach visualizes both consistent as well as variable ligand-induced changes in ligand-bound compared with apo protein crystal structures. For this purpose, information was mined from B-factors and ligand-induced residue displacements in multiple crystal structures, minimizing experimental error and noise. With this approach, the mechanism of action of non-nucleoside reverse transcriptase inhibitors (NNRTIs) as an inseparable combination of distortion of protein dynamics and conformational changes of HIV-1 reverse transcriptase was corroborated (a combination of the previously proposed "molecular arthritis" and "distorted site" mechanisms). The second approach presented here uses "consensus structures" to map common binding features that are present in a set of structures of NNRTI-bound HIV-1 reverse transcriptase. Consensus structures are based on different levels of structural overlap of multiple crystal structures and are used to analyze protein-ligand interactions. The structures are shown to yield information about conserved hydrogen bonding interactions as well as binding-pocket flexibility, shape, and volume. From the consensus structures, a common wild type NNRTI binding pocket emerges. Furthermore, we were able to identify a conserved backbone hydrogen bond acceptor at P236 and a novel hydrophobic subpocket, which are not yet utilized by current drugs. Our methods introduced here reinterpret the atom information and make use of the data variability by using multiple structures, complementing classical 3D structural information of single structures.

| S-EPMC2867014 | biostudies-literature

Accuracy of functional surfaces on comparatively modeled protein structures.

Project description:Identification and characterization of protein functional surfaces are important for predicting protein function, understanding enzyme mechanism, and docking small compounds to proteins. As the rapid speed of accumulation of protein sequence information far exceeds that of structures, constructing accurate models of protein functional surfaces and identify their key elements become increasingly important. A promising approach is to build comparative models from sequences using known structural templates such as those obtained from structural genome projects. Here we assess how well this approach works in modeling binding surfaces. By systematically building three-dimensional comparative models of proteins using MODELLER: , we determine how well functional surfaces can be accurately reproduced. We use an alpha shape based pocket algorithm to compute all pockets on the modeled structures, and conduct a large-scale computation of similarity measurements (pocket RMSD and fraction of functional atoms captured) for 26,590 modeled enzyme protein structures. Overall, we find that when the sequence fragment of the binding surfaces has more than 45% identity to that of the template protein, the modeled surfaces have on average an RMSD of 0.5 Å, and contain 48% or more of the binding surface atoms, with nearly all of the important atoms in the signatures of binding pockets captured.

| S-EPMC3415962 | biostudies-literature

Water polygons in high-resolution protein crystal structures.

Project description:We have analyzed the interstitial water (ISW) structures in 1500 protein crystal structures deposited in the Protein Data Bank that have greater than 1.5 A resolution with less than 90% sequence similarity with each other. We observed varieties of polygonal water structures composed of three to eight water molecules. These polygons may represent the time- and space-averaged structures of "stable" water oligomers present in liquid water, and their presence as well as relative population may be relevant in understanding physical properties of liquid water at a given temperature. On an average, 13% of ISWs are localized enough to be visible by X-ray diffraction. Of those, averages of 78% are water molecules in the first water layer on the protein surface. Of the localized ISWs beyond the first layer, almost half of them form water polygons such as trigons, tetragons, as well as expected pentagons, hexagons, higher polygons, partial dodecahedrons, and disordered networks. Most of the octagons and nanogons are formed by fusion of smaller polygons. The trigons are most commonly observed. We suggest that our observation provides an experimental basis for including these water polygon structures in correlating and predicting various water properties in liquid state.

| S-EPMC2775207 | biostudies-literature

A method for validating the accuracy of NMR protein structures.

Project description:We present a method that measures the accuracy of NMR protein structures. It compares random coil index [RCI] against local rigidity predicted by mathematical rigidity theory, calculated from NMR structures [FIRST], using a correlation score (which assesses secondary structure), and an RMSD score (which measures overall rigidity). We test its performance using: structures refined in explicit solvent, which are much better than unrefined structures; decoy structures generated for 89 NMR structures; and conventional predictors of accuracy such as number of restraints per residue, restraint violations, energy of structure, ensemble RMSD, Ramachandran distribution, and clashscore. Restraint violations and RMSD are poor measures of accuracy. Comparisons of NMR to crystal structures show that secondary structure is equally accurate, but crystal structures are typically too rigid in loops, whereas NMR structures are typically too floppy overall. We show that the method is a useful addition to existing measures of accuracy.

| S-EPMC7749147 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data