MDockPeP: A Web Server for Blind Prediction of Protein–Peptide Complex Structures

2020 ◽  
pp. 259-272
Author(s):  
Xianjin Xu ◽  
Xiaoqin Zou
Keyword(s):  
Web Server ◽  
Complex Structures ◽  
Peptide Complex ◽  
Blind Prediction

scholarly journals Blind Prediction of Protein-Peptide Complex Structures: A Novel Method and a Web Server

2018 ◽  
Vol 114 (3) ◽  
pp. 55a
Author(s):  
Xianjin Xu ◽  
Chengfei Yan ◽  
Xiaoqin Zou
Keyword(s):  
Web Server ◽  
Complex Structures ◽  
Peptide Complex ◽  
Blind Prediction ◽  
Novel Method

scholarly journals HNADOCK: a nucleic acid docking server for modeling RNA/DNA–RNA/DNA 3D complex structures

2019 ◽  
Vol 47 (W1) ◽  
pp. W35-W42 ◽  
Author(s):  
Jiahua He ◽  
Jun Wang ◽  
Huanyu Tao ◽  
Yi Xiao ◽  
Sheng-You Huang
Keyword(s):  
Nucleic Acid ◽  
Success Rate ◽  
Rna Processing ◽  
Web Server ◽  
Complex Structures ◽  
Interaction Prediction ◽  
Rna Interaction ◽  
User Friendly ◽  
Rna Complexes ◽  
Docking Accuracy

AbstractInteractions between nuclide acids (RNA/DNA) play important roles in many basic cellular activities like transcription regulation, RNA processing, and protein synthesis. Therefore, determining the complex structures between RNAs/DNAs is crucial to understand the molecular mechanism of related RNA/DNA–RNA/DNA interactions. Here, we have presented HNADOCK, a user-friendly web server for nucleic acid (NA)–nucleic acid docking to model the 3D complex structures between two RNAs/DNAs, where both sequence and structure inputs are accepted for RNAs, while only structure inputs are supported for DNAs. HNADOCK server was tested through both unbound structure and sequence inputs on the benchmark of 60 RNA–RNA complexes and compared with the state-of-the-art algorithm SimRNA. For structure input, HNADOCK server achieved a high success rate of 71.7% for top 10 predictions, compared to 58.3% for SimRNA. For sequence input, HNADOCK server also obtained a satisfactory performance and gave a success rate of 83.3% when the bound RNA templates are included or 53.3% when excluding those bound RNA templates. It was also found that inclusion of the inter-RNA base-pairing information from RNA–RNA interaction prediction can significantly improve the docking accuracy, especially for the top prediction. HNADOCK is fast and can normally finish a job in about 10 minutes. The HNADOCK web server is available at http://huanglab.phys.hust.edu.cn/hnadock/.

scholarly journals Substrate binding and specificity of rhomboid intramembrane protease revealed by substrate–peptide complex structures

2014 ◽  
Vol 33 (20) ◽  
pp. 2408-2421 ◽  
Author(s):  
Sebastian Zoll ◽  
Stancho Stanchev ◽  
Jakub Began ◽  
Jan Škerle ◽  
Martin Lepšík ◽  
...  
Keyword(s):  
Substrate Binding ◽  
Complex Structures ◽  
Peptide Complex ◽  
Substrate Peptide

scholarly journals Can AlphaFold2 predict protein-peptide complex structures accurately?

2021 ◽  
Author(s):  
Junsu Ko ◽  
Juyong Lee
Keyword(s):  
Structure Prediction ◽  
Good Accuracy ◽  
Higher Order ◽  
Order Structure ◽  
Sequence Information ◽  
Test Cases ◽  
Complex Structures ◽  
Peptide Complex ◽  
Peptide Complexes

In this preprint, we investigated whether AlphaFold2, AF2, can predict protein-peptide complex structures only with sequence information. We modeled the structures of 203 protein-peptide complexes from the PepBDB DB and 183 from the PepSet. The structures were modeling with concatenated sequences of receptors and peptides via poly-glycine linker. We found that for more than half of the test cases, AF2 predicted the bound structures of peptides with good accuracy, C_alpha-RMSD of a peptide < 3.0 angstrom. For about 40% of cases, the peptide structures were modeled with an accuracy of C_alpha-RMSD < 2.0 angstrom. Our benchmark results clearly show that AF2 has a great potential to be applied to various higher-order structure prediction tasks.

scholarly journals Protocols for All-Atom Reconstruction and High-Resolution Refinement of Protein–Peptide Complex Structures

2020 ◽  
pp. 273-287 ◽  
Author(s):  
Aleksandra E. Badaczewska-Dawid ◽  
Alisa Khramushin ◽  
Andrzej Kolinski ◽  
Ora Schueler-Furman ◽  
Sebastian Kmiecik
Keyword(s):  
High Resolution ◽  
Complex Structures ◽  
Peptide Complex

scholarly journals Building and rebuilding N-glycans in protein structure models

2019 ◽  
Vol 75 (4) ◽  
pp. 416-425 ◽  
Author(s):  
Bart van Beusekom ◽  
Natasja Wezel ◽  
Maarten L. Hekkelman ◽  
Anastassis Perrakis ◽  
Paul Emsley ◽  
...  
Keyword(s):  
Protein Folding ◽  
Protein Structure ◽  
Biological Function ◽  
Protein Structures ◽  
Web Server ◽  
Complex Structures ◽  
Post Translational Modifications

N-Glycosylation is one of the most common post-translational modifications and is implicated in, for example, protein folding and interaction with ligands and receptors. N-Glycosylation trees are complex structures of linked carbohydrate residues attached to asparagine residues. While carbohydrates are typically modeled in protein structures, they are often incomplete or have the wrong chemistry. Here, new tools are presented to automatically rebuild existing glycosylation trees, to extend them where possible, and to add new glycosylation trees if they are missing from the model. The method has been incorporated in the PDB-REDO pipeline and has been applied to build or rebuild 16 452 carbohydrate residues in 11 651 glycosylation trees in 4498 structure models, and is also available from the PDB-REDO web server. With better modeling of N-glycosylation, the biological function of this important modification can be better and more easily understood.

Cell morphology, volume, and surface area determinations from multilevel contouring within HVEM micrographs of serial sections and whole-cell mounts

1987 ◽  
Vol 45 ◽  
pp. 588-589
Author(s):  
M. Marko ◽  
A. Leith ◽  
D. Parsons
Keyword(s):  
Surface Area ◽  
Electron Micrographs ◽  
Cell Morphology ◽  
Individual Variation ◽  
Serial Section ◽  
Stereo Pair ◽  
Complex Structures ◽  
Serial Sections ◽  
Surface Areas ◽  
Computer Based

The use of serial sections and computer-based 3-D reconstruction techniques affords an opportunity not only to visualize the shape and distribution of the structures being studied, but also to determine their volumes and surface areas. Up until now, this has been done using serial ultrathin sections.The serial-section approach differs from the stereo logical methods of Weibel in that it is based on the Information from a set of single, complete cells (or organelles) rather than on a random 2-dimensional sampling of a population of cells. Because of this, it can more easily provide absolute values of volume and surface area, especially for highly-complex structures. It also allows study of individual variation among the cells, and study of structures which occur only infrequently.We have developed a system for 3-D reconstruction of objects from stereo-pair electron micrographs of thick specimens.

Stereo modeling of HVEM specimens by serial tilting and computer graphics

1986 ◽  
Vol 44 ◽  
pp. 34-35
Author(s):  
J.R. McIntosh ◽  
D.L. Stemple ◽  
William Bishop ◽  
G.W. Hannaway
Keyword(s):  
Computer Graphics ◽  
Analytical Methods ◽  
Photographic Film ◽  
Complex Structures ◽  
Multiple Objects ◽  
Multiple Images ◽  
3 Dimensional

EM specimens often contain 3-dimensional information that is lost during micrography on a single photographic film. Two images of one specimen at appropriate orientations give a stereo view, but complex structures composed of multiple objects of graded density that superimpose in each projection are often difficult to decipher in stereo. Several analytical methods for 3-D reconstruction from multiple images of a serially tilted specimen are available, but they are all time-consuming and computationally intense.

EXELFS Studies of Carbon Fibers

1990 ◽  
Vol 48 (2) ◽  
pp. 72-73
Author(s):  
V. Serin ◽  
K. Hssein ◽  
G. Zanchi ◽  
J. Sévely
Keyword(s):  
Carbon Fibers ◽  
Energy Analysis ◽  
Electron Excitation ◽  
Complex Structures ◽  
High Modulus ◽  
Promising Technique ◽  
X Ray ◽  
Fine Structures ◽  
X Ray Absorption

The present developments of electron energy analysis in the microscopes by E.E.L.S. allow an accurate recording of the spectra and of their different complex structures associated with the inner shell electron excitation by the incident electrons (1). Among these structures, the Extended Energy Loss Fine Structures (EXELFS) are of particular interest. They are equivalent to the well known EXAFS oscillations in X-ray absorption spectroscopy. Due to the EELS characteristic, the Fourier analysis of EXELFS oscillations appears as a promising technique for the characterization of composite materials, the major constituents of which are low Z elements. Using EXELFS, we have developed a microstructural study of carbon fibers. This analysis concerns the carbon K edge, which appears in the spectra at 285 eV. The purpose of the paper is to compare the local short range order, determined by this way in the case of Courtauld HTS and P100 ex-polyacrylonitrile carbon fibers, which are high tensile strength (HTS) and high modulus (HM) fibers respectively.

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