scholarly journals A chemical interpretation of protein electron density maps in the worldwide protein data bank

2019 ◽  
Author(s):  
Sen Yao ◽  
Hunter N.B. Moseley
Keyword(s):  
Protein Data Bank ◽  
Electron Density ◽  
Structural Model ◽  
Data Bank ◽  
X Ray ◽  
New Methods ◽  
Link Type ◽  
Density Maps ◽  
Structure Factors ◽  
Python Package

AbstractHigh-quality three-dimensional structural data is of great value for the functional interpretation of biomacromolecules, especially proteins; however, structural quality varies greatly across the entries in the worldwide Protein Data Bank (wwPDB). Since 2008, the wwPDB has required the inclusion of structure factors with the deposition of x-ray crystallographic structures to support the independent evaluation of structures with respect to the underlying experimental data used to derive those structures. However, interpreting the discrepancies between the structural model and its underlying electron density data is difficult, since derived electron density maps use arbitrary electron density units which are inconsistent between maps from different wwPDB entries. Therefore, we have developed a method that converts electron density values into units of electrons. With this conversion, we have developed new methods that can evaluate specific regions of an x-ray crystallographic structure with respect to a physicochemical interpretation of its corresponding electron density map. We have systematically compared all deposited x-ray crystallographic protein models in the wwPDB with their underlying electron density maps, if available, and characterized the electron density in terms of expected numbers of electrons based on the structural model. The methods generated coherent evaluation metrics throughout all PDB entries with associated electron density data, which are consistent with visualization software that would normally be used for manual quality assessment. To our knowledge, this is the first attempt to derive units of electrons directly from electron density maps without the aid of the underlying structure factors. These new metrics are biochemically-informative and can be extremely useful for filtering out low-quality structural regions from inclusion into systematic analyses that span large numbers of PDB entries. Furthermore, these new metrics will improve the ability of non-crystallographers to evaluate regions of interest within PDB entries, since only the PDB structure and the associated electron density maps are needed. These new methods are available as a well-documented Python package on GitHub and the Python Package Index under a modified Clear BSD open source license.Author summaryElectron density maps are very useful for validating the x-ray structure models in the Protein Data Bank (PDB). However, it is often daunting for non-crystallographers to use electron density maps, as it requires a lot of prior knowledge. This study provides methods that can infer chemical information solely from the electron density maps available from the PDB to interpret the electron density and electron density discrepancy values in terms of units of electrons. It also provides methods to evaluate regions of interest in terms of the number of missing or excessing electrons, so that a broader audience, such as biologists or bioinformaticians, can also make better use of the electron density information available in the PDB, especially for quality control purposes.Software and full results available athttps://github.com/MoseleyBioinformaticsLab/pdb_eda (software on GitHub)https://pypi.org/project/pdb-eda/ (software on PyPI)https://pdb-eda.readthedocs.io/en/latest/ (documentation on ReadTheDocs)https://doi.org/10.6084/m9.figshare.7994294 (code and results on FigShare)

scholarly journals PDBrenum: a webserver and program providing Protein Data Bank files renumbered according to their UniProt sequences

2021 ◽  
Author(s):  
Bulat Faezov ◽  
Roland L. Dunbrack
Keyword(s):  
Protein Data Bank ◽  
Data Bank ◽  
Post Translational Modifications ◽  
X Ray ◽  
X Ray Crystallography ◽  
Link Type ◽  
Binding Partners ◽  
Cryo Electron Microscopy ◽  
Comparative Structure ◽  
In The Beginning

AbstractThe Protein Data Bank (PDB) was established at Brookhaven National Laboratories in 1971 as an archive for biological macromolecular crystal structures. In the beginning the archive held only seven structures but in early 2021, the database has more than 170,000 structures solved by X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and other methods. Many proteins have been studied under different conditions (e.g., binding partners such as ligands, nucleic acids, or other proteins; mutations and post-translational modifications), thus enabling comparative structure-function studies. However, these studies are made more difficult because authors are allowed by the PDB to number the amino acids in each protein sequence in any manner they wish. This results in the same protein being numbered differently in the available PDB entries. In addition to the coordinates, there are many fields that contain information regarding specific residues in the sequence of each protein in the entry. Here we provide a webserver and Python3 application that fixes the PDB sequence numbering problem by replacing the author numbering with numbering derived from the corresponding UniProt sequences. We obtain this correspondence from the SIFTS database from PDBe. The server and program can take a list of PDB entries and provide renumbered files in mmCIF format and the legacy PDB format for both asymmetric unit files and biological assembly files provided by PDBe. The server can also take a list of UniProt identifiers (“P04637” or “P53_HUMAN”) and return the desired files.AvailabilitySource code is freely available at https://github.com/Faezov/PDBrenum. The webserver is located at: http://dunbrack3.fccc.edu/[email protected] or [email protected].

Validation of carbohydrate structures: not just nomenclature

2014 ◽  
Vol 70 (a1) ◽  
pp. C1481-C1481
Author(s):  
Jon Agirre ◽  
Kevin Cowtan
Keyword(s):  
Protein Data Bank ◽  
Correlation Coefficient ◽  
Electron Density ◽  
Systematic Study ◽  
Data Bank ◽  
Real Space ◽  
Space Correlation ◽  
Structure Factors ◽  
Ring Distortion ◽  
Experimental Electron Density

Despite the key implications carbohydrates have in a multitude of pathological processes, a large number of the sugar-containing structures deposited into the Protein Data Bank (PDB) show nomenclature errors [1] that persist even after the remediation of the PDB archive [2]. Here we present the results from a systematic study of the conformation and ring distortion of cyclic carbohydrate models for which structure factors have been deposited into the PDB. These models have also been scored using a real-space correlation coefficient calculated between model and experimental electron density. The results have enabled us to produce a database of well-refined carbohydrate structures for use in the framework of an automated sugar-detecting software, to be announced shortly.

Transient electron density maps from femtosecond x-ray powder diffraction

2014 ◽  
Vol 70 (a1) ◽  
pp. C100-C100
Author(s):  
Vincent Juvé ◽  
Flavio Zamponi ◽  
Marcel Holtz ◽  
Michael Woerner ◽  
Thomas Elsaesser
Keyword(s):  
Charge Transfer ◽  
Electron Density ◽  
Powder Diffraction ◽  
Maximum Entropy Method ◽  
Entropy Method ◽  
X Rays ◽  
X Ray ◽  
Density Maps ◽  
Structure Factors ◽  
Diffraction Angle

Ultrashort hard x-ray pulses are sensitive probes of structural dynamics on the picometer length and femtosecond time scales of electronic and atomic motions. Using short hard x-ray pulses as probe in a pump-probe scheme allow to do femtosecond x-ray diffraction experiments [1], which provide transient electron density maps at a femtosecond timescale with a sub-angstrom spatial resolution. In a typical femtosecond x-ray powder diffraction experiment many Debye-Scherrer rings, up to a maximum diffraction angle 2θmax, are recorded for each time delay between the optical pump and the hard x-ray probe. From the diffraction pattern, the change of the diffracted intensity of each rings are monitored. The interference of diffracted x-rays from the many unexcited cells, with known structure factors coming from steady-state measurement, and diffracted x-rays from the few excited cells allows for the detection of the transients structure factors. Problems could arise if the 3D-Fourier transform is directly used because of the abrupt end of the collected information in the reciprocal space (maximum diffraction angle 2θmax). In order to overcome this problem, the Maximum Entropy Method is apply to the data and the transient electron density maps are derived. We apply the femtosecond x-ray powder diffraction technique and the Maximum Entropy Method to study the induced transient polarization by high optical fields on ionic crystals. Such polarizations are connected to a spatial redistribution of electronic charge, which corresponds to a charge transfer between the two ionic compounds [2]. While the charge transfer originates from the anion to the cation in the LiBH and the NaBH4, the LiH exhibits a peculiar behavior: the charge transfer occurs from the cation to the anion. As result from comparison with calculations in the COHSEX framework, this behavior is due to the strong electronic correlations in the LiH [3].

Synchrotron X-ray study of Er3Al5O12 and Yb3Al5O12 garnets

2001 ◽  
Vol 57 (2) ◽  
pp. 136-141 ◽  
Author(s):  
Barbara Etschmann ◽  
Victor Streltsov ◽  
Nobuo Ishizawa ◽  
E. N. Maslen
Keyword(s):  
Rare Earth ◽  
Electron Density ◽  
Relative Position ◽  
Nearest Neighbor ◽  
Difference Electron Density ◽  
X Ray ◽  
Density Maps ◽  
Structure Factors ◽  
The Difference ◽  
The Rare Earth

Structure factors for Er3Al5O12 and Yb3Al5O12 garnets were measured using focused synchrotron X-radiation, with λ = 0.7500 (2) and 0.7000 (2) Å, respectively. The difference electron density maps for Er3Al5O12 and Yb3Al5O12 were similar, as expected. This was attributed to the 4f electrons being shielded, which reduces their effectiveness in chemical bonding and the relative position of the rare-earth atoms in the periodic table. The symmetry of the difference electron density around the rare-earth atoms was found to reflect that of the cation geometry, emphasizing the importance of second nearest-neighbor interactions. This is consistent with the view that oxide-type structures may be regarded as a packed array of cations with anions in the interstices.

scholarly journals Of crystals, structure factors and diffraction images

2008 ◽  
Vol 41 (3) ◽  
pp. 659-659 ◽  
Author(s):  
Luca Jovine ◽  
Ekaterina Morgunova ◽  
Rudolf Ladenstein
Keyword(s):  
Protein Data Bank ◽  
Data Bank ◽  
X Ray Diffraction ◽  
X Ray ◽  
Structure Factors

It is suggested that it would be useful if raw X-ray diffraction images could be included in data depositions with the Protein Data Bank.

scholarly journals Finding high-quality metal ion-centric regions across the worldwide Protein Data Bank

2019 ◽  
Author(s):  
Sen Yao ◽  
Hunter N.B. Moseley
Keyword(s):  
Protein Data Bank ◽  
Electron Density ◽  
Metal Binding ◽  
Metal Ion ◽  
Data Bank ◽  
Structural Quality ◽  
Global Evaluation ◽  
Density Maps ◽  
Quality Control Criteria ◽  
Control Criteria

AbstractAs the number of macromolecular structures in the worldwide Protein Data Bank (wwPDB) continues to grow rapidly, more attention is being paid to the quality of its data, especially for use in aggregated structural and dynamics analyses. In this study, we systematically analyzed 3.5 Å regions around all metal ions across all PDB entries with supporting electron density maps available from the PDB in Europe. All resulting metal ion-centric regions were evaluated with respect to four quality-control criteria involving electron density resolution, atom occupancy, symmetry atom exclusion, and regional electron density discrepancy. The resulting list of metal binding sites passing all four criteria possess high regional structural quality and should be beneficial to a wide variety of downstream analyses. This study demonstrates an approach for the pan-PDB evaluation of metal binding site structural quality with respect to underlying x-ray crystallographic experimental data represented in available electron density maps of proteins. For non-crystallographers in particular, we hope to change the focus and discussion of structural quality from a global evaluation to a regional evaluation, since all structural entries in the wwPDB appear to have both regions of high and low structural quality.

scholarly journals Homology-based loop modelling yields more complete crystallographic protein structures

2018 ◽  
Author(s):  
Bart van Beusekom ◽  
Krista Joosten ◽  
Maarten L. Hekkelman ◽  
Robbie P. Joosten ◽  
Anastassis Perrakis
Keyword(s):  
Protein Structure ◽  
Protein Function ◽  
Model Building ◽  
Protein Structures ◽  
Data Bank ◽  
X Ray ◽  
New Methods ◽  
Density Maps ◽  
Complete Protein ◽  
Automated Procedures

AbstractInherent protein flexibility, poor or low-resolution diffraction data, or poor electron density maps, often inhibit building complete structural models during X-ray structure determination. However, advances in crystallographic refinement and model building nowadays often allow to complete previously missing parts. Here, we present algorithms that identify regions missing in a certain model but present in homologous structures in the Protein Data Bank (PDB), and “graft” these regions of interest. These new regions are refined and validated in a fully automated procedure. Including these developments in our PDB-REDO pipeline, allowed to build 24,962 missing loops in the PDB. The models and the automated procedures are publically available through the PDB-REDO databank and web server (https://pdb-redo.eu). More complete protein structure models enable a higher quality public archive, but also a better understanding of protein function, better comparison between homologous structures, and more complete data mining in structural bioinformatics projects.SynopsisThousands of missing regions in existing protein structure models are completed using new methods based on homology.

scholarly journals Finding High-Quality Metal Ion-Centric Regions Across the Worldwide Protein Data Bank

Molecules ◽  
2019 ◽  
Vol 24 (17) ◽  
pp. 3179
Author(s):  
Sen Yao ◽  
Hunter N.B. Moseley
Keyword(s):  
Protein Data Bank ◽  
Electron Density ◽  
Metal Binding ◽  
Metal Ion ◽  
Data Bank ◽  
Structural Quality ◽  
Global Evaluation ◽  
Density Maps ◽  
Quality Control Criteria ◽  
Control Criteria

As the number of macromolecular structures in the worldwide Protein Data Bank (wwPDB) continues to grow rapidly, more attention is being paid to the quality of its data, especially for use in aggregated structural and dynamics analyses. In this study, we systematically analyzed 3.5 Å regions around all metal ions across all PDB entries with supporting electron density maps available from the PDB in Europe. All resulting metal ion-centric regions were evaluated with respect to four quality-control criteria involving electron density resolution, atom occupancy, symmetry atom exclusion, and regional electron density discrepancy. The resulting list of metal binding sites passing all four criteria possess high regional structural quality and should be beneficial to a wide variety of downstream analyses. This study demonstrates an approach for the pan-PDB evaluation of metal binding site structural quality with respect to underlying X-ray crystallographic experimental data represented in the available electron density maps of proteins. For non-crystallographers in particular, we hope to change the focus and discussion of structural quality from a global evaluation to a regional evaluation, since all structural entries in the wwPDB appear to have both regions of high and low structural quality.

A synchrotron X-ray study of the electron density in C-type rare earth oxides

1996 ◽  
Vol 52 (3) ◽  
pp. 414-422 ◽  
Author(s):  
E. N. Maslen ◽  
V. A. Streltsov ◽  
N. Ishizawa
Keyword(s):  
Heavy Metal ◽  
Rare Earth ◽  
Electron Density ◽  
Approximate Symmetry ◽  
Data Set ◽  
X Ray ◽  
Metal Atoms ◽  
Structure Factors ◽  
Deformation Electron Density ◽  
Synthetic Crystals

Structure factors for small synthetic crystals of the C-type rare earth (RE) sesquioxides Y2O3, Dy2O3 and Ho2O3 were measured with focused λ = 0.7000 (2) Å, synchrotron X-radiation, and for Ho2O3 were re-measured with an MoKα (λ = 0.71073 Å) source. Approximate symmetry in the deformation electron density (Δρ) around a RE atom with pseudo-octahedral O coordination matches the cation geometry. Interactions between heavy metal atoms have a pronounced effect on the Δρ map. The electron-density symmetry around a second RE atom is also perturbed significantly by cation–anion interactions. The compounds magnetic properties reflect this complexity. Space group Ia{\bar 3}, cubic, Z = 16, T = 293 K: Y2O3, Mr = 225.82, a = 10.5981 (7) Å, V = 1190.4 (2) Å3, Dx = 5.040 Mg m−3, μ 0.7 = 37.01 mm−1, F(000) = 1632, R = 0.067, wR = 0.067, S = 9.0 (2) for 1098 unique reflections; Dy2O3, Mr = 373.00, a = 10.6706 (7) Å, V = 1215.0 (2) Å3, Dx = 8.156 Mg m−3, μ 0.7 = 44.84 mm−1, F(000) = 2496, R = 0.056, wR = 0.051, S = 7.5 (2) for 1113 unique reflections; Ho2O3, Mr = 377.86, a = 10.606 (2) Å, V = 1193.0 (7) Å3, Dx = 8.415 Mg m−3, μ 0.7 = 48.51 mm−1 F(000) = 2528, R = 0.072, wR = 0.045, S = 9.2 (2) for 1098 unique reflections of the synchrotron data set.

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