Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Experimental charge density from electron microscopic maps.

ABSTRACT: The charge density (CD) distribution of an atom is the difference per unit volume between the positive charge of its nucleus and the distribution of the negative charges carried by the electrons that are associated with it. The CDs of the atoms in macromolecules are responsible for their electrostatic potential (ESP) distributions, which can now be visualized using cryo-electron microscopy at high resolution. CD maps can be recovered from experimental ESP density maps using the negative Laplacian operation. CD maps are easier to interpret than ESP maps because they are less sensitive to long-range electrostatic effects. An ESP-to-CD conversion involves multiplication of amplitudes of structure factors as Fourier transforms of these maps in reciprocal space by 1/d2 , where d is the resolution of reflections. In principle, it should be possible to determine the charges carried by the individual atoms in macromolecules by comparing experimental CD maps with experimental ESP maps.

SUBMITTER: Wang J

PROVIDER: S-EPMC5521614 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Experimental charge density from electron microscopic maps.

Wang Jimin J

Protein science : a publication of the Protein Society 20170531 8

The charge density (CD) distribution of an atom is the difference per unit volume between the positive charge of its nucleus and the distribution of the negative charges carried by the electrons that are associated with it. The CDs of the atoms in macromolecules are responsible for their electrostatic potential (ESP) distributions, which can now be visualized using cryo-electron microscopy at high resolution. CD maps can be recovered from experimental ESP density maps using the negative Laplacia ...[more]

PMID: 28543856

Similar Datasets

On the interpretation of electron microscopic maps of biological macromolecules.

Project description:The images of flash-frozen biological macromolecules produced by cryo-electron microscopy (EM) can be used to generate accurate, three-dimensional, electric potential maps for these molecules that resemble X-ray-derived electron density maps. However, unlike electron density maps, electric potential maps can include negative features that might for example represent the negatively charged, backbone phosphate groups of nucleic acids or protein carboxylate side chains, which can complicate their interpretation. This study examines the images of groups that include charged atoms that appear in recently-published, high-resolution EM potential maps of the ribosome and ?-galactosidase. Comparisons of simulated maps of these same groups with their experimental counterparts highlight the impact that charge has on the appearance of electric potential maps.

| S-EPMC5192980 | biostudies-literature

Targeted conformational search with map-restrained self-guided Langevin dynamics: application to flexible fitting into electron microscopic density maps.

Project description:We present a map-restrained self-guided Langevin dynamics (MapSGLD) simulation method for efficient targeted conformational search. The targeted conformational search represents simulations under restraints defined by experimental observations and/or by user specified structural requirements. Through map-restraints, this method provides an efficient way to maintain substructures and to set structure targets during conformational searching. With an enhanced conformational searching ability of self-guided Langevin dynamics, this approach is suitable for simulating large-scale conformational changes, such as the formation of macromolecular assemblies and transitions between different conformational states. Using several examples, we illustrate the application of this method in flexible fitting of atomic structures into density maps derived from cryo-electron microscopy.

| S-EPMC3785014 | biostudies-literature

Statistical quality indicators for electron-density maps.

Project description:The commonly used validation metrics for the local agreement of a structure model with the observed electron density, namely the real-space R (RSR) and the real-space correlation coefficient (RSCC), are reviewed. It is argued that the primary goal of all validation techniques is to verify the accuracy of the model, since precision is an inherent property of the crystal and the data. It is demonstrated that the principal weakness of both of the above metrics is their inability to distinguish the accuracy of the model from its precision. Furthermore, neither of these metrics in their usual implementation indicate the statistical significance of the result. The statistical properties of electron-density maps are reviewed and an improved alternative likelihood-based metric is suggested. This leads naturally to a χ(2) significance test of the difference density using the real-space difference density Z score (RSZD). This is a metric purely of the local model accuracy, as required for effective model validation and structure optimization by practising crystallographers prior to submission of a structure model to the PDB. A new real-space observed density Z score (RSZO) is also proposed; this is a metric purely of the model precision, as a substitute for other precision metrics such as the B factor.

| S-EPMC3322605 | biostudies-literature

Charge Density Waves in Electron-Doped Molybdenum Disulfide.

Project description:We present the discovery of a charge density wave (CDW) ground state in heavily electron-doped molybdenum disulfide (MoS2). This is the first observation of a CDW in any d2 (column 6) transition metal dichalcogenide (TMD). The band structure of MoS2 is distinct from the d0 and d1 TMDs in which CDWs have been previously observed, facilitating new insight into CDW formation. We demonstrate a metal-insulator transition at 85 K, a 25 meV gap at the Fermi level, and two distinct CDW modulations, (2√3 × 2√3) R30° and 2 × 2, attributable to Fermi surface nesting (FSN) and electron-phonon coupling (EPC), respectively. This simultaneous exhibition of FSN and EPC CDW modulations is unique among observations of CDW ground states, and we discuss this in the context of band folding. Our observations provide a route toward the resolution of controversies surrounding the origin of CDW modulations in TMDs.

| S-EPMC8397392 | biostudies-literature

YUP.SCX: coaxing atomic models into medium resolution electron density maps.

Project description:The structures of large macromolecular complexes in different functional states can be determined by cryo-electron microscopy, which yields electron density maps of low to intermediate resolutions. The maps can be combined with high-resolution atomic structures of components of the complex, to produce a model for the complex that is more accurate than the formal resolution of the map. To this end, methods have been developed to dock atomic models into density maps rigidly or flexibly, and to refine a docked model so as to optimize the fit of the atomic model into the map. We have developed a new refinement method called YUP.SCX. The electron density map is converted into a component of the potential energy function to which terms for stereochemical restraints and volume exclusion are added. The potential energy function is then minimized (using simulated annealing) to yield a stereochemically-restrained atomic structure that fits into the electron density map optimally. We used this procedure to construct an atomic model of the 70S ribosome in the pre-accommodation state. Although some atoms are displaced by as much as 33A, they divide themselves into nearly rigid fragments along natural boundaries with smooth transitions between the fragments.

| S-EPMC2702770 | biostudies-literature

Rapid chain tracing of polypeptide backbones in electron-density maps.

Project description:A method for the rapid tracing of polypeptide backbones has been developed. The method creates an approximate chain tracing that is useful for visual evaluation of whether a structure has been solved and for use in scoring the quality of electron-density maps. The essence of the method is to (i) sample candidate C(alpha) positions at spacings of approximately 0.6 A along ridgelines of high electron density, (ii) list all possible nonapeptides that satisfy simple geometric and density criteria using these candidate C(alpha) positions, (iii) score the nonapeptides and choose the highest scoring ones, and (iv) find the longest chains that can be made by connecting nonamers. An indexing and storage scheme that allows a single calculation of most distances and density values is used to speed up the process. The method was applied to 42 density-modified electron-density maps at resolutions from 1.5 to 3.8 A. A total of 21 428 residues in these maps were traced in 24 CPU min with an overall r.m.s.d. of 1.61 A for C(alpha) atoms compared with the known refined structures. The method appears to be suitable for rapid evaluation of electron-density map quality.

| S-EPMC2827349 | biostudies-literature

Rapid model building of beta-sheets in electron-density maps.

Project description:A method for rapidly building beta-sheets into electron-density maps is presented. beta-Strands are identified as tubes of high density adjacent to and nearly parallel to other tubes of density. The alignment and direction of each strand are identified from the pattern of high density corresponding to carbonyl and C(beta) atoms along the strand averaged over all repeats present in the strand. The beta-strands obtained are then assembled into a single atomic model of the beta-sheet regions. The method was tested on a set of 42 experimental electron-density maps at resolutions ranging from 1.5 to 3.8 A. The beta-sheet regions were nearly completely built in all but two cases, the exceptions being one structure at 2.5 A resolution in which a third of the residues in beta-sheets were built and a structure at 3.8 A in which under 10% were built. The overall average r.m.s.d. of main-chain atoms in the residues built using this method compared with refined models of the structures was 1.5 A.

| S-EPMC2827348 | biostudies-literature

Rapid model building of alpha-helices in electron-density maps.

Project description:A method for the identification of alpha-helices in electron-density maps at low resolution followed by interpretation at moderate to high resolution is presented. Rapid identification is achieved at low resolution, where alpha-helices appear as tubes of density. The positioning and direction of the alpha-helices is obtained at moderate to high resolution, where the positions of side chains can be seen. The method was tested on a set of 42 experimental electron-density maps at resolutions ranging from 1.5 to 3.8 A. An average of 63% of the alpha-helical residues in these proteins were built and an average of 76% of the residues built matched helical residues in the refined models of the proteins. The overall average r.m.s.d. between main-chain atoms in the modeled alpha-helices and the nearest atom with the same name in the refined models of the proteins was 1.3 A.

| S-EPMC2827347 | biostudies-literature

Creating protein models from electron-density maps using particle-filtering methods.

Project description:One bottleneck in high-throughput protein crystallography is interpreting an electron-density map, that is, fitting a molecular model to the 3D picture crystallography produces. Previously, we developed ACMI (Automatic Crystallographic Map Interpreter), an algorithm that uses a probabilistic model to infer an accurate protein backbone layout. Here, we use a sampling method known as particle filtering to produce a set of all-atom protein models. We use the output of ACMI to guide the particle filter's sampling, producing an accurate, physically feasible set of structures.We test our algorithm on 10 poor-quality experimental density maps. We show that particle filtering produces accurate all-atom models, resulting in fewer chains, lower sidechain RMS error and reduced R factor, compared to simply placing the best-matching sidechains on ACMI's trace. We show that our approach produces a more accurate model than three leading methods--Textal, Resolve and ARP/WARP--in terms of main chain completeness, sidechain identification and crystallographic R factor.Source code and experimental density maps available at http://ftp.cs.wisc.edu/machine-learning/shavlik-group/programs/acmi/

| S-EPMC2567142 | biostudies-literature

Nhs: network-based hierarchical segmentation for cryo-electron microscopy density maps.

Project description:Cryo-electron microscopy (cryo-EM) experiments yield low-resolution (3-30 Å) 3D-density maps of macromolecules. These density maps are segmented to identify structurally distinct proteins, protein domains, and subunits. Such partitioning aids the inference of protein motions and guides fitting of high-resolution atomistic structures. Cryo-EM density map segmentation has traditionally required tedious and subjective manual partitioning or semisupervised computational methods, whereas validation of resulting segmentations has remained an open problem in this field. We introduce a network-based hierarchical segmentation (Nhs) method, that provides a multi-scale partitioning, reflecting local and global clustering, while requiring no user input. This approach models each map as a graph, where map voxels constitute nodes and weighted edges connect neighboring voxels. Nhs initiates Markov diffusion (or random walk) on the weighted graph. As Markov probabilities homogenize through diffusion, an intrinsic segmentation emerges. We validate the segmentations with ground-truth maps based on atomistic models. When implemented on density maps in the 2010 Cryo-EM Modeling Challenge, Nhs efficiently and objectively partitions macromolecules into structurally and functionally relevant subregions at multiple scales.

| S-EPMC3483038 | 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