Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Solvent dramatically affects protein structure refinement.

ABSTRACT: One of the most challenging problems in protein structure prediction is improvement of homology models (structures within 1-3 A C(alpha) rmsd of the native structure), also known as the protein structure refinement problem. It has been shown that improvement could be achieved using in vacuo energy minimization with molecular mechanics and statistically derived continuously differentiable hybrid knowledge-based (KB) potential functions. Globular proteins, however, fold and function in aqueous solution in vivo and in vitro. In this work, we study the role of solvent in protein structure refinement. Molecular dynamics in explicit solvent and energy minimization in both explicit and implicit solvent were performed on a set of 75 native proteins to test the various energy potentials. A more stringent test for refinement was performed on 729 near-native decoys for each native protein. We use a powerfully convergent energy minimization method to show that implicit solvent (GBSA) provides greater improvement for some proteins than the KB potential: 24 of 75 proteins showing an average improvement of >20% in C(alpha) rmsd from the native structure with GBSA, compared to just 7 proteins with KB. Molecular dynamics in explicit solvent moved the structures further away from their native conformation than the initial, unrefined decoys. Implicit solvent gives rise to a deep, smooth potential energy attractor basin that pulls toward the native structure.

SUBMITTER: Chopra G

PROVIDER: S-EPMC2600579 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

RNA structure refinement using NMR solvent accessibility data.

Project description:NMR spectroscopy is a powerful technique to study ribonucleic acids (RNAs) which are key players in a plethora of cellular processes. Although the NMR toolbox for structural studies of RNAs expanded during the last decades, they often remain challenging. Here, we show that solvent paramagnetic relaxation enhancements (sPRE) induced by the soluble, paramagnetic compound Gd(DTPA-BMA) provide a quantitative measure for RNA solvent accessibility and encode distance-to-surface information that correlates well with RNA structure and improves accuracy and convergence of RNA structure determination. Moreover, we show that sPRE data can be easily obtained for RNAs with any isotope labeling scheme and is advantageous regarding sample preparation, stability and recovery. sPRE data show a large dynamic range and reflect the global fold of the RNA suggesting that they are well suited to identify interaction surfaces, to score structural models and as restraints in RNA structure determination.

| S-EPMC5511288 | biostudies-literature

Assessment of protein structure refinement in CASP9.

Project description:We assess performance in the structure refinement category in CASP9. Two years after CASP8, the performance of the best groups has not improved. There are few groups that improve any of our assessment scores with statistical significance. Some predictors, however, are able to consistently improve the physicality of the models. Although we cannot identify any clear bottleneck in improving refinement, several points arise: (1) The refinement portion of CASP has too few targets to make many statistically meaningful conclusions. (2) Predictors are usually very conservative, limiting the possibility of large improvements in models. (3) No group is actually able to correctly rank their five submissions-indicating that potentially better models may be discarded. (4) Different sampling strategies work better for different refinement problems; there is no single strategy that works on all targets. In general, conservative strategies do better, while the greatest improvements come from more adventurous sampling-at the cost of consistency. Comparison with experimental data reveals aspects not captured by comparison to a single structure. In particular, we show that improvement in backbone geometry does not always mean better agreement with experimental data. Finally, we demonstrate that even given the current challenges facing refinement, the refined models are useful for solving the crystallographic phase problem through molecular replacement. Proteins 2011;. © 2011 Wiley-Liss, Inc.

| S-EPMC3238793 | biostudies-literature

Manure refinement affects apple rhizosphere bacterial community structure: a study in sandy soil.

Project description:We used DNA-based pyrosequencing to characterize the bacterial community structure of the sandy soil of an apple orchard with different manure ratios. Five manure percentages (5%, 10%, 15%, 20% and 25%) were examined. More than 10,000 valid reads were obtained for each replicate. The communities were composed of five dominant groups (Proteobacteria, Actinobacteria, Chloroflexi, Acidobacteria and Bacteroidetes), of which Proteobacteria content gradually decreased from 41.38% to 37.29% as manure ratio increased from 0% to 25%, respectively. Redundancy analysis showed that 37 classes were highly correlated with manure ratio, 18 of which were positively correlated. Clustering revealed that the rhizosphere samples were grouped into three components: low manure (control, 5%) treatment, medium manure (10%, 15%) treatment and high manure (20%, 25%) treatment. Venn analysis of species types of these three groups revealed that the bacteria community difference was primarily reflected by quantity ratio rather than species variety. Although greater manure content led to higher soil organic matter content, the medium manure improved soil showed the highest urease activity and saccharase activity, while 5% to 20% manure ratio improvement also resulted in higher bacteria diversity than control and 25% manure ratio treatment. Our experimental results suggest that the use of a proper manure ratio results in significantly higher soil enzyme activity and different bacteria community patterns, whereas the use of excessive manure amounts has negative effect on soil quality.

| S-EPMC3796563 | biostudies-literature

Assessment of the protein-structure refinement category in CASP8.

Project description:Here, we summarize the assessment of protein structure refinement in CASP8. Twenty-four groups refined a total of 12 target proteins. Averaging over all groups and all proteins, there was no net improvement over the original starting models. However, there are now some individual research groups who consistently do improve protein structures relative to a starting starting model. We compare various measures of quality assessment, including (i) standard backbone-based methods, (ii) new methods from the Richardson group, and (iii) ensemble-based methods for comparing experimental structures, such as NMR NOE violations and the suitability of the predicted models to serve as templates for molecular replacement. On the whole, there is a general correlation among various measures. However, there are interesting differences. Sometimes a structure that is in better agreement with the experimental data is judged to be slightly worse by GDT-TS. This suggests that for comparing protein structures that are already quite close to the native, it may be preferable to use ensemble-based experimentally derived measures of quality, in addition to single-structure-based methods such as GDT-TS.

| S-EPMC2801025 | biostudies-literature

Benchmarking of structure refinement methods for protein complex models.

Project description:Protein structure docking is the process in which the quaternary structure of a protein complex is predicted from individual tertiary structures of the protein subunits. Protein docking is typically performed in two main steps. The subunits are first docked while keeping them rigid to form the complex, which is then followed by structure refinement. Structure refinement is crucial for a practical use of computational protein docking models, as it is aimed for correcting conformations of interacting residues and atoms at the interface. Here, we benchmarked the performance of eight existing protein structure refinement methods in refinement of protein complex models. We show that the fraction of native contacts between subunits is by far the most straightforward metric to improve. However, backbone dependent metrics, based on the Root Mean Square Deviation proved more difficult to improve via refinement.

| S-EPMC8671191 | biostudies-literature

Protein structure prediction by all-atom free-energy refinement.

Project description:BackgroundThe reliable prediction of protein tertiary structure from the amino acid sequence remains challenging even for small proteins. We have developed an all-atom free-energy protein forcefield (PFF01) that we could use to fold several small proteins from completely extended conformations. Because the computational cost of de-novo folding studies rises steeply with system size, this approach is unsuitable for structure prediction purposes. We therefore investigate here a low-cost free-energy relaxation protocol for protein structure prediction that combines heuristic methods for model generation with all-atom free-energy relaxation in PFF01.ResultsWe use PFF01 to rank and cluster the conformations for 32 proteins generated by ROSETTA. For 22/10 high-quality/low quality decoy sets we select near-native conformations with an average Calpha root mean square deviation of 3.03 A/6.04 A. The protocol incorporates an inherent reliability indicator that succeeds for 78% of the decoy sets. In over 90% of these cases near-native conformations are selected from the decoy set. This success rate is rationalized by the quality of the decoys and the selectivity of the PFF01 forcefield, which ranks near-native conformations an average 3.06 standard deviations below that of the relaxed decoys (Z-score).ConclusionAll-atom free-energy relaxation with PFF01 emerges as a powerful low-cost approach toward generic de-novo protein structure prediction. The approach can be applied to large all-atom decoy sets of any origin and requires no preexisting structural information to identify the native conformation. The study provides evidence that a large class of proteins may be foldable by PFF01.

| S-EPMC1832197 | biostudies-literature

Protein structure refinement using 13C alpha chemical shift tensors.

Project description:We have obtained the (13)C alpha chemical shift tensors for each amino acid in the protein GB1. We then developed a CST force field and incorporated this into the Xplor-NIH structure determination program. GB1 structures obtained by using CST restraints had improved precision over those obtained in the absence of CST restraints and were also more accurate. When combined with isotropic chemical shifts, distance, and vector angle restraints, the root-mean squared error with respect to existing X-ray structures was better than approximately 1.0 A. These results are of broad general interest since they show that chemical shift tensors can be used in protein structure refinement, improving both structural accuracy and precision, opening up the way to accurate de novo structure determination.

| S-EPMC2751586 | biostudies-literature

Protein Structure Refinement through Structure Selection and Averaging from Molecular Dynamics Ensembles.

Project description:A molecular dynamics (MD) simulation based protocol for structure refinement of template-based model predictions is described. The protocol involves the application of restraints, ensemble averaging of selected subsets, interpolation between initial and refined structures, and assessment of refinement success. It is found that sub-microsecond MD-based sampling when combined with ensemble averaging can produce moderate but consistent refinement for most systems in the CASP targets considered here.

| S-EPMC3603382 | biostudies-literature

Local Protein Structure Refinement via Molecular Dynamics Simulations with locPREFMD.

Project description:A method for the local refinement of protein structures that targets improvements in local stereochemistry while preserving the overall fold is presented. The method uses force field-based minimization and sampling via molecular dynamics simulations with a modified force field to bring bonds, angles, and torsion angles into an acceptable range for high-resolution protein structures. The method is implemented in the locPREFMD web server and was tested on computational models submitted to CASP11. Using MolProbity scores as the main assessment criterion, the locPREFMD method significantly improves the stereochemical quality of given input models close to the quality expected for experimental structures while maintaining the C? coordinates of the initial model.

| S-EPMC4962792 | biostudies-literature

Protein structure fitting and refinement guided by cryo-EM density.

Project description:For many macromolecular assemblies, both a cryo-electron microscopy map and atomic structures of its component proteins are available. Here we describe a method for fitting and refining a component structure within its map at intermediate resolution (<15 A). The atomic positions are optimized with respect to a scoring function that includes the crosscorrelation coefficient between the structure and the map as well as stereochemical and nonbonded interaction terms. A heuristic optimization that relies on a Monte Carlo search, a conjugate-gradients minimization, and simulated annealing molecular dynamics is applied to a series of subdivisions of the structure into progressively smaller rigid bodies. The method was tested on 15 proteins of known structure with 13 simulated maps and 3 experimentally determined maps. At approximately 10 A resolution, Calpha rmsd between the initial and final structures was reduced on average by approximately 53%. The method is automated and can refine both experimental and predicted atomic structures.

| S-EPMC2409374 | 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