scholarly journals Three-Dimensional Protein Structural Data Mining Based on the Glycine Filter Reduced Representation

2005 ◽  
Vol 4 (2) ◽  
pp. 33-42
Author(s):  
Hiroaki KATO ◽  
Shin-ichi CHIKAMATSU ◽  
Yoshimasa TAKAHASHI ◽  
Hidetsugu ABE
Keyword(s):  
Data Mining ◽  
Three Dimensional ◽  
Structural Data ◽  
Reduced Representation

scholarly journals Diaminoimidazopyrimidines: Access via the Groebke-Blackburn-Bienaymé Reaction and Structural Data Mining

2020 ◽  
Author(s):  
Markella Konstantinidou ◽  
Zlata Boiarska ◽  
Roberto Butera ◽  
Constantinos G. Neochoritis ◽  
Katarzyna Kurpiewska ◽  
...  
Keyword(s):  
Data Mining ◽  
Structural Data

scholarly journals Three-Dimensional Structures of Carbohydrates and Where to Find Them

2020 ◽  
Vol 21 (20) ◽  
pp. 7702 ◽  
Author(s):  
Sofya I. Scherbinina ◽  
Philip V. Toukach
Keyword(s):  
Experimental Data ◽  
Molecular Modeling ◽  
Computational Methods ◽  
Three Dimensional ◽  
Structural Diversity ◽  
Structural Data ◽  
Structural Features ◽  
Data Validation ◽  
Data Generation ◽  
Efficient Treatment

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

scholarly journals WONKAandOOMMPPAA: analysis of protein–ligand interaction data to direct structure-based drug design

2017 ◽  
Vol 73 (3) ◽  
pp. 279-285
Author(s):  
Charlotte M. Deane ◽  
Ian D. Wall ◽  
Darren V. S. Green ◽  
Brian D. Marsden ◽  
Anthony R. Bradley
Keyword(s):  
Three Dimensional ◽  
Structural Data ◽  
Data Sets ◽  
Interaction Data ◽  
Activity Data ◽  
Ligand Interaction ◽  
Structure Based Drug Design ◽  
Web Based ◽  
Protein Ligand Interaction ◽  
Ligand Activity

In this work, two freely available web-based interactive computational tools that facilitate the analysis and interpretation of protein–ligand interaction data are described. Firstly,WONKA, which assists in uncovering interesting and unusual features (for example residue motions) within ensembles of protein–ligand structures and enables the facile sharing of observations between scientists. Secondly,OOMMPPAA, which incorporates protein–ligand activity data with protein–ligand structural data using three-dimensional matched molecular pairs.OOMMPPAAhighlights nuanced structure–activity relationships (SAR) and summarizes available protein–ligand activity data in the protein context. In this paper, the background that led to the development of both tools is described. Their implementation is outlined and their utility using in-house Structural Genomics Consortium (SGC) data sets and openly available data from the PDB and ChEMBL is described. Both tools are freely available to use and download at http://wonka.sgc.ox.ac.uk/WONKA/ and http://oommppaa.sgc.ox.ac.uk/OOMMPPAA/.

A current assessment of photosystem II structure

1996 ◽  
Vol 16 (2) ◽  
pp. 159-187 ◽  
Author(s):  
William V. Nicholson ◽  
Robert C. Ford ◽  
Andreas Holzenburg
Keyword(s):  
Photosystem Ii ◽  
Structural Information ◽  
Three Dimensional ◽  
Structural Data ◽  
X Ray Diffraction ◽  
Membrane Protein Complex ◽  
Fast Absorption ◽  
Current Assessment ◽  
Electron Microscopical ◽  
A Current

This review covers the recent progress in the elucidation of the structure of photosystem II (PSII). Because much of the structural information for this membrane protein complex has been revealed by electron microscopy (EM), the review will also consider the specific technical and interpretation problems that arise with EM where they are of particular relevance to the structural data. Most recent reviews of photosystem II structure have concentrated on molecular studies of the PSII genes and on the likely roles of the subunits that they encode or they were mainly concerned with the biophysical data and fast absorption spectroscopy largely relating to electron transfer in various purified PSII preparations. In this review, we will focus on the approaches to the three-dimensional architecture of the complex and the lipid bilayer in which it is located (the thylakoid membrane) with special emphasis placed upon electron microscopical studies of PSII-containing thylakoid membranes. There are a few reports of 3D crystals of PSII and of associated X-ray diffraction measurements and although little structural information has so far been obtained from such studies (because of the lack of 3D crystals of sufficient quality), the prospects for such studies are also assessed.

A framework for big data driven process analysis and optimization for additive manufacturing

2019 ◽  
Vol 25 (2) ◽  
pp. 308-321 ◽  
Author(s):  
Arfan Majeed ◽  
Jingxiang Lv ◽  
Tao Peng
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Additive Manufacturing ◽  
Production Efficiency ◽  
Process Analysis ◽  
Three Dimensional ◽  
Big Data Analytics ◽  
Production Performance ◽  
Content Type ◽  
Processing And Storage

Purpose This paper aims to present an overall framework of big data-based analytics to optimize the production performance of additive manufacturing (AM) process. Design/methodology/approach Four components, namely, big data application, big data sensing and acquisition, big data processing and storage, model establishing, data mining and process optimization were presented to comprise the framework. Key technologies including the big data acquisition and integration, big data mining and knowledge sharing mechanism were developed for the big data analytics for AM. Findings The presented framework was demonstrated by an application scenario from a company of three-dimensional printing solutions. The results show that the proposed framework benefited customers, manufacturers, environment and even all aspects of manufacturing phase. Research limitations/implications This study only proposed a framework, and did not include the realization of the algorithm for data analysis, such as association, classification and clustering. Practical implications The proposed framework can be used to optimize the quality, energy consumption and production efficiency of the AM process. Originality/value This paper introduces the concept of big data in the field of AM. The proposed framework can be used to make better decisions based on the big data during manufacturing process.

scholarly journals The World of Cyclic Dinucleotides in Bacterial Behavior

Molecules ◽  
2020 ◽  
Vol 25 (10) ◽  
pp. 2462 ◽  
Author(s):  
Aline Dias da Purificação ◽  
Nathalia Marins de Azevedo ◽  
Gabriel Guarany de Araujo ◽  
Robson Francisco de Souza ◽  
Cristiane Rodrigues Guzzo
Keyword(s):  
Intracellular Signaling ◽  
Three Dimensional ◽  
Structural Data ◽  
Research Topic ◽  
Signaling Networks ◽  
Bacterial Cells ◽  
Signaling Systems ◽  
The World ◽  
Second Messenger Systems ◽  
Cyclic Dinucleotides

The regulation of multiple bacterial phenotypes was found to depend on different cyclic dinucleotides (CDNs) that constitute intracellular signaling second messenger systems. Most notably, c-di-GMP, along with proteins related to its synthesis, sensing, and degradation, was identified as playing a central role in the switching from biofilm to planktonic modes of growth. Recently, this research topic has been under expansion, with the discoveries of new CDNs, novel classes of CDN receptors, and the numerous functions regulated by these molecules. In this review, we comprehensively describe the three main bacterial enzymes involved in the synthesis of c-di-GMP, c-di-AMP, and cGAMP focusing on description of their three-dimensional structures and their structural similarities with other protein families, as well as the essential residues for catalysis. The diversity of CDN receptors is described in detail along with the residues important for the interaction with the ligand. Interestingly, genomic data strongly suggest that there is a tendency for bacterial cells to use both c-di-AMP and c-di-GMP signaling networks simultaneously, raising the question of whether there is crosstalk between different signaling systems. In summary, the large amount of sequence and structural data available allows a broad view of the complexity and the importance of these CDNs in the regulation of different bacterial behaviors. Nevertheless, how cells coordinate the different CDN signaling networks to ensure adaptation to changing environmental conditions is still open for much further exploration.

scholarly journals Protein Structure Determination in Living Cells

2019 ◽  
Vol 20 (10) ◽  
pp. 2442 ◽  
Author(s):  
Teppei Ikeya ◽  
Peter Güntert ◽  
Yutaka Ito
Keyword(s):  
Protein Structure ◽  
Structure Determination ◽  
Structure Prediction ◽  
Structural Information ◽  
Nuclear Overhauser Effect ◽  
Protein Structures ◽  
Three Dimensional ◽  
Structural Data ◽  
Sample Tube ◽  
In Cells

To date, in-cell NMR has elucidated various aspects of protein behaviour by associating structures in physiological conditions. Meanwhile, current studies of this method mostly have deduced protein states in cells exclusively based on ‘indirect’ structural information from peak patterns and chemical shift changes but not ‘direct’ data explicitly including interatomic distances and angles. To fully understand the functions and physical properties of proteins inside cells, it is indispensable to obtain explicit structural data or determine three-dimensional (3D) structures of proteins in cells. Whilst the short lifetime of cells in a sample tube, low sample concentrations, and massive background signals make it difficult to observe NMR signals from proteins inside cells, several methodological advances help to overcome the problems. Paramagnetic effects have an outstanding potential for in-cell structural analysis. The combination of a limited amount of experimental in-cell data with software for ab initio protein structure prediction opens an avenue to visualise 3D protein structures inside cells. Conventional nuclear Overhauser effect spectroscopy (NOESY)-based structure determination is advantageous to elucidate the conformations of side-chain atoms of proteins as well as global structures. In this article, we review current progress for the structure analysis of proteins in living systems and discuss the feasibility of its future works.

scholarly journals Trehalulose Synthase Native and Carbohydrate Complexed Structures Provide Insights into Sucrose Isomerization

2007 ◽  
Vol 282 (38) ◽  
pp. 28126-28136 ◽  
Author(s):  
Stéphanie Ravaud ◽  
Xavier Robert ◽  
Hildegard Watzlawick ◽  
Richard Haser ◽  
Ralf Mattes ◽  
...  
Keyword(s):  
Substrate Recognition ◽  
Three Dimensional ◽  
Enzyme Reaction ◽  
Structural Data ◽  
Side Reactions ◽  
Binding Modes ◽  
Product Specificity ◽  
Reaction Specificity ◽  
First Time ◽  
Enzyme Targeting

Various diseases related to the overconsumption of sugar make a growing need for sugar substitutes. Because sucrose is an inexpensive and readily available d-glucose donor, the industrial potential for enzymatic synthesis of the sucrose isomers trehalulose and/or isomaltulose from sucrose is large. The product specificity of sucrose isomerases that catalyze this reaction depends essentially on the possibility for tautomerization of sucrose, which is required for trehalulose formation. For optimal use of the enzyme, targeting controlled synthesis of these functional isomers, it is necessary to minimize the side reactions. This requires an extensive analysis of substrate binding modes and of the specificity-determining sites in the structure. The 1.6-2.2-Å resolution three-dimensional structures of native and mutant complexes of a trehalulose synthase from Pseudomonas mesoacidophila MX-45 mimic successive states of the enzyme reaction. Combined with mutagenesis studies they give for the first time thorough insights into substrate recognition and processing and reaction specificities of these enzymes. Among the important outcomes of this study is the revelation of an aromatic clamp defined by Phe256 and Phe280 playing an essential role in substrate recognition and in controlling the reaction specificity, which is further supported by mutagenesis studies. Furthermore, this study highlights essential residues for binding the glucosyl and fructosyl moieties. The introduction of subtle changes informed by comparative three-dimensional structural data observed within our study can lead to fundamental modifications in the mode of action of sucrose isomerases and hence provide a template for industrial catalysts.

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