Online_DPI: a web server to calculate the diffraction precision index for a protein structure

2015 ◽  
Vol 48 (3) ◽  
pp. 939-942 ◽  
Author(s):  
K. S. Dinesh Kumar ◽  
M. Gurusaran ◽  
S. N. Satheesh ◽  
P. Radha ◽  
S. Pavithra ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Three Dimensional ◽  
Web Server ◽  
Data Bank ◽  
Atomic Displacement ◽  
Precision Index ◽  
Client Machine ◽  
Atomic Displacement Parameters ◽  
Temperature Factors ◽  
Coordinate Error

An online computing server,Online_DPI(where DPI denotes the diffraction precision index), has been created to calculate the `Cruickshank DPI' value for a given three-dimensional protein or macromolecular structure. It also estimates the atomic coordinate error for all the atoms available in the structure. It is an easy-to-use web server that enables users to visualize the computed values dynamically on the client machine. Users can provide the Protein Data Bank (PDB) identification code or upload the three-dimensional atomic coordinates from the client machine. The computed DPI value for the structure and the atomic coordinate errors for all the atoms are included in the revised PDB file. Further, users can graphically view the atomic coordinate error along with `temperature factors' (i.e.atomic displacement parameters). In addition, the computing engine is interfaced with an up-to-date local copy of the Protein Data Bank. New entries are updated every week, and thus users can access all the structures available in the Protein Data Bank. The computing engine is freely accessible online at http://cluster.physics.iisc.ernet.in/dpi/.

PAP: a protein analysis package

1990 ◽  
Vol 23 (5) ◽  
pp. 434-436 ◽  
Author(s):  
T. Callahan ◽  
W. B. Gleason ◽  
T. P. Lybrand
Keyword(s):  
Protein Data Bank ◽  
Digital Equipment Corporation ◽  
Protein Structures ◽  
Three Dimensional ◽  
Data Bank ◽  
Scatter Plot ◽  
Linear Sequence ◽  
Analysis Package ◽  
Temperature Factors ◽  
Digital Equipment

A program package has been assembled for the analysis of protein coordinates which are in the Brookhaven Protein Data Bank (PDB) format. These programs can be used to make two types of φ–ψ plots: a Ramachandran-style scatter plot, and a plot of φ and ψ values as a function of the linear sequence. Programs are also available for the display of distance diagonal plots for proteins. Two protein structures can be compared and the resulting r.m.s. differences in the structures plotted as a function of sequence. Temperature factors can be analyzed and plotted as a function of the linear sequence. In addition, various utilities are supplied for splitting PDB files which contain multiple subunits into individual files and also for renumbering PDB files. A utility is also provided for converting Amber-style PDB files into standard PDB files. Priestle's program RIBBON [J. Appl. Cryst. (1988), 21, 572–576] has been converted to run in a stand-alone mode with interactive rotation of the three-dimensional ribbon picture. Programs are Silicon Graphics four-dimensional level and have been tested on 4D70/GT and personal Iris workstations, although programs which give Postscript output have been converted to run on Digital Equipment Corporation VAX computers and Sun workstations.

[29] Protein data bank archives of three-dimensional macromolecular structures

1997 ◽  
pp. 556-571 ◽  
Author(s):  
Enrique E. Abola ◽  
Joel L. Sussman ◽  
Jaime Prilusky ◽  
Nancy O. Manning
Keyword(s):  
Protein Data Bank ◽  
Three Dimensional ◽  
Data Bank

scholarly journals BLASTing away preconceptions in crystallization trials

2019 ◽  
Vol 75 (3) ◽  
pp. 184-192 ◽  
Author(s):  
Gabriel Jan Abrahams ◽  
Janet Newman
Keyword(s):  
Protein Data Bank ◽  
Sequence Similarity ◽  
Three Dimensional ◽  
Protein Sequences ◽  
Protein Molecule ◽  
Data Bank ◽  
Dimensional Structure ◽  
Critical Step ◽  
Quantitative Verification ◽  
Better Than

Crystallization is in many cases a critical step for solving the three-dimensional structure of a protein molecule. Determining which set of chemicals to use in the initial screen is typically agnostic of the protein under investigation; however, crystallization efficiency could potentially be improved if this were not the case. Previous work has assumed that sequence similarity may provide useful information about appropriate crystallization cocktails; however, the authors are not aware of any quantitative verification of this assumption. This research investigates whether, given current information, one can detect any correlation between sequence similarity and crystallization cocktails. BLAST was used to quantitate the similarity between protein sequences in the Protein Data Bank, and this was compared with three estimations of the chemical similarities of the respective crystallization cocktails. No correlation was detected between proteins of similar (but not identical) sequence and their crystallization cocktails, suggesting that methods of determining screens based on this assumption are unlikely to result in screens that are better than those currently in use.

scholarly journals Super: a web server to rapidly screen superposable oligopeptide fragments from the protein data bank

2012 ◽  
Vol 40 (W1) ◽  
pp. W334-W339 ◽  
Author(s):  
James H. Collier ◽  
Arthur M. Lesk ◽  
Maria Garcia de la Banda ◽  
Arun S. Konagurthu
Keyword(s):  
Protein Data Bank ◽  
Web Server ◽  
Data Bank

scholarly journals Protein Data Bank (PDB): Database of Three-Dimensional Structural Information of Biological Macromolecules

1998 ◽  
Vol 54 (6) ◽  
pp. 1078-1084 ◽  
Author(s):  
Joel L. Sussman ◽  
Dawei Lin ◽  
Jiansheng Jiang ◽  
Nancy O. Manning ◽  
Jaime Prilusky ◽  
...  
Keyword(s):  
Nucleic Acids ◽  
Protein Data Bank ◽  
Structural Information ◽  
National Laboratory ◽  
Three Dimensional ◽  
Data Bank ◽  
Brookhaven National Laboratory ◽  
Biological Macromolecules

The Protein Data Bank (PDB) at Brookhaven National Laboratory, is a database containing experimentally determined three-dimensional structures of proteins, nucleic acids and other biological macromolecules, with approximately 8000 entries. Data are easily submittedviaPDB's WWW-based toolAutoDep, in either mmCIF or PDB format, and are most conveniently examinedviaPDB's WWW-based tool3DB Browser.

MLDB: macromolecule ligand database

2009 ◽  
Vol 43 (1) ◽  
pp. 200-202 ◽  
Author(s):  
S. E. Saravanan ◽  
R. Karthi ◽  
K. Sathish ◽  
K. Kokila ◽  
R. Sabarinathan ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Structural Biology ◽  
Scientific Community ◽  
Three Dimensional ◽  
Data Bank

MLDB (macromolecule ligand database) is a knowledgebase containing ligands co-crystallized with the three-dimensional structures available in the Protein Data Bank. The proposed knowledgebase serves as an open resource for the analysis and visualization of all ligands and their interactions with macromolecular structures. MLDB can be used to search ligands, and their interactions can be visualized both in text and graphical formats. MLDB will be updated at regular intervals (weekly) with automated Perl scripts. The knowledgebase is intended to serve the scientific community working in the areas of molecular and structural biology. It is available free to users around the clock and can be accessed at http://dicsoft2.physics.iisc.ernet.in/mldb/.

scholarly journals Worldwide Protein Data Bank validation information: usage and trends

2018 ◽  
Vol 74 (3) ◽  
pp. 237-244 ◽  
Author(s):  
Oliver S. Smart ◽  
Vladimír Horský ◽  
Swanand Gore ◽  
Radka Svobodová Vařeková ◽  
Veronika Bendová ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Three Dimensional ◽  
Data Bank ◽  
Resonance Spectroscopy ◽  
X Ray ◽  
Validation Metrics ◽  
Task Forces ◽  
X Ray Crystallography ◽  
Structure Properties

Realising the importance of assessing the quality of the biomolecular structures deposited in the Protein Data Bank (PDB), the Worldwide Protein Data Bank (wwPDB) partners established Validation Task Forces to obtain advice on the methods and standards to be used to validate structures determined by X-ray crystallography, nuclear magnetic resonance spectroscopy and three-dimensional electron cryo-microscopy. The resulting wwPDB validation pipeline is an integral part of the wwPDB OneDep deposition, biocuration and validation system. The wwPDB Validation Service webserver (https://validate.wwpdb.org) can be used to perform checks prior to deposition. Here, it is shown how validation metrics can be combined to produce an overall score that allows the ranking of macromolecular structures and domains in search results. The ValTrendsDBdatabase provides users with a convenient way to access and analyse validation information and other properties of X-ray crystal structures in the PDB, including investigating trends in and correlations between different structure properties and validation metrics.

Is the growth rate of Protein Data Bank sufficient to solve the protein structure prediction problem using template-based modeling?

2015 ◽  
Vol 11 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Michal Brylinski
Keyword(s):  
Protein Structure ◽  
Protein Data Bank ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Structural Information ◽  
Three Dimensional ◽  
Data Bank ◽  
Prediction Problem ◽  
Three Dimensional Models ◽  
Protein Structure Prediction Problem

AbstractThe Protein Data Bank (PDB) undergoes an exponential expansion in terms of the number of macromolecular structures deposited every year. A pivotal question is how this rapid growth of structural information improves the quality of three-dimensional models constructed by contemporary bioinformatics approaches. To address this problem, we performed a retrospective analysis of the structural coverage of a representative set of proteins using remote homology detected by COMPASS and HHpred. We show that the number of proteins whose structures can be confidently predicted increased during a 9-year period between 2005 and 2014 on account of the PDB growth alone. Nevertheless, this encouraging trend slowed down noticeably around the year 2008 and has yielded insignificant improvements ever since. At the current pace, it is unlikely that the protein structure prediction problem will be solved in the near future using existing template-based modeling techniques. Therefore, further advances in experimental structure determination, qualitatively better approaches in fold recognition, and more accurate template-free structure prediction methods are desperately needed.

Temperature-dependent analysis of thermal motion, disorder and structures of tris(ethylenediamine)zinc(II) sulfate and tris(ethylenediamine)copper(II) sulfate

2011 ◽  
Vol 67 (1) ◽  
pp. 53-62 ◽  
Author(s):  
Stef Smeets ◽  
Pascal Parois ◽  
Hans-Beat Bürgi ◽  
Martin Lutz
Keyword(s):  
Three Dimensional ◽  
Atomic Displacement ◽  
Thermal Motion ◽  
Temperature Phase ◽  
Acta Cryst ◽  
Bond Behaviour ◽  
Different Temperatures ◽  
Jahn Teller ◽  
Atomic Displacement Parameters ◽  
A Site

The crystal structures of the title compounds have been determined in the temperature range 140–290 K for the zinc complex, and 190–270 K for the copper complex. The two structures are isostructural in the trigonal space group P{\bar{3}1c} with the sulfate anion severely disordered on a site with 32 (D 3) symmetry. This sulfate disorder leads to a disordered three-dimensional hydrogen-bond network, with the N—H atoms acting as donors and the sulfate O atoms as acceptors. The displacement parameters of the N and C atoms in both compounds contain disorder contributions in the out-of-ligand plane direction owing to ring puckering and/or disorder in hydrogen bonding. In the Zn compound the vibrational amplitudes in the bond directions are closely similar. Their differences show no significant deviations from rigid-bond behaviour. In the Cu compound, a (presumably) dynamic Jahn–Teller effect is identified from a temperature-independent contribution to the displacement ellipsoids of the N atom along the N—Cu bond. These conclusions derive from analyses of the atomic displacement parameters with the Hirshfeld test, with rigid-body models at different temperatures, and with a normal coordinate analysis. This analysis considers the atomic displacement parameters (ADPs) from all different temperatures simultaneously and provides a detailed description of both the thermal motion and the disorder in the cation. The Jahn–Teller radii of the Cu compound derived on the basis of the ADP analysis and from the bond distances in the statically distorted low-temperature phase [Lutz (2010). Acta Cryst. C66, m330–m335] are found to be the same.

scholarly journals Redetermination of the crystal structure of R 5Si4 (R = Pr, Nd) from single-crystal X-ray diffraction data

2020 ◽  
Vol 76 (4) ◽  
pp. 510-513
Author(s):  
Kaori Yokota ◽  
Ryuta Watanuki ◽  
Miki Nakashima ◽  
Masatomo Uehara ◽  
Jun Gouchi ◽  
...  
Keyword(s):  
Single Crystal ◽  
Diffraction Data ◽  
Three Dimensional ◽  
Atomic Displacement ◽  
Crystal Data ◽  
X Ray Diffraction ◽  
Acta Cryst ◽  
X Ray ◽  
Atomic Displacement Parameters ◽  
First Time

The crystal structures of praseodymium silicide (5/4), Pr5Si4, and neodymium silicide (5/4), Nd5Si4, were redetermined using high-quality single-crystal X-ray diffraction data. The previous structure reports of Pr5Si4 were only based on powder X-ray diffraction data [Smith et al. (1967). Acta Cryst. 22 940–943; Yang et al. (2002b). J. Alloys Compd. 339, 189–194; Yang et al., (2003). J. Alloys Compd. 263, 146–153]. On the other hand, the structure of Nd5Si4 has been determined from powder data [neutron; Cadogan et al., (2002). J. Phys. Condens. Matter, 14, 7191–7200] and X-ray [Smith et al. (1967). Acta Cryst. 22 940–943; Yang et al. (2002b). J. Alloys Compd. 339, 189–194; Yang et al., (2003). J. Alloys Compd. 263, 146–153] and single-crystal data with isotropic atomic displacement parameters [Roger et al., (2006). J. Alloys Compd. 415, 73–84]. In addition, the anisotropic atomic displacement parameters for all atomic sites have been determined for the first time. These compounds are confirmed to have the tetragonal Zr5Si4-type structure (space group: P41212), as reported previously (Smith et al., 1967). The structure is built up by distorted body-centered cubes consisting of Pr(Nd) atoms, which are linked to each other by edge-sharing to form a three-dimensional framework. This framework delimits zigzag channels in which the silicon dimers are situated.

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