scholarly journals GlyMDB: Glycan Microarray Database and analysis toolset

2019 ◽  
Vol 36 (8) ◽  
pp. 2438-2442 ◽  
Author(s):  
Yiwei Cao ◽  
Sang-Jun Park ◽  
Akul Y Mehta ◽  
Richard D Cummings ◽  
Wonpil Im
Keyword(s):  
Fluorescence Intensity ◽  
Microarray Data ◽  
Motif Discovery ◽  
Binding Proteins ◽  
Biological Activities ◽  
Supplementary Information ◽  
Binding Motif ◽  
Structural Determinants ◽  
Glycan Microarray ◽  
Microarray Database

Abstract Motivation Glycan microarrays are capable of illuminating the interactions of glycan-binding proteins (GBPs) against hundreds of defined glycan structures, and have revolutionized the investigations of protein–carbohydrate interactions underlying numerous critical biological activities. However, it is difficult to interpret microarray data and identify structural determinants promoting glycan binding to glycan-binding proteins due to the ambiguity in microarray fluorescence intensity and complexity in branched glycan structures. To facilitate analysis of glycan microarray data alongside protein structure, we have built the Glycan Microarray Database (GlyMDB), a web-based resource including a searchable database of glycan microarray samples and a toolset for data/structure analysis. Results The current GlyMDB provides data visualization and glycan-binding motif discovery for 5203 glycan microarray samples collected from the Consortium for Functional Glycomics. The unique feature of GlyMDB is to link microarray data to PDB structures. The GlyMDB provides different options for database query, and allows users to upload their microarray data for analysis. After search or upload is complete, users can choose the criterion for binder versus non-binder classification. They can view the signal intensity graph including the binder/non-binder threshold followed by a list of glycan-binding motifs. One can also compare the fluorescence intensity data from two different microarray samples. A protein sequence-based search is performed using BLAST to match microarray data with all available PDB structures containing glycans. The glycan ligand information is displayed, and links are provided for structural visualization and redirection to other modules in GlycanStructure.ORG for further investigation of glycan-binding sites and glycan structures. Availability and implementation http://www.glycanstructure.org/glymdb. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals GLAD: GLycan Array Dashboard, a visual analytics tool for glycan microarrays

2019 ◽  
Vol 35 (18) ◽  
pp. 3536-3537 ◽  
Author(s):  
Akul Y Mehta ◽  
Richard D Cummings
Keyword(s):  
Data Mining ◽  
Microarray Data ◽  
Visual Analytics ◽  
Supplementary Information ◽  
Glycan Array ◽  
Visual Data Mining ◽  
Array Data ◽  
Glycan Microarray ◽  
Multiple Data ◽  
Data Files

Abstract Motivation Traditional glycan microarray data is typically presented as excel files with limited visualization and interactivity. Thus, comparisons and analysis of glycan array data have been difficult, and there is need for a tool to facilitate data mining of glycan array data. Results GLAD (GLycan Array Dashboard) is a web-based tool to visualize, analyze, present and mine glycan microarray data. GLAD allows users to input multiple data files to create comparisons. GLAD extends the capability of the microarray data to produce more comparative visualizations in the form of grouped bar charts, heatmaps, calendar heatmaps, force graphs and correlation maps in order to analyze broad sets of samples. Additionally, it allows users to filter, sort and normalize the data and view glycan structures in an interactive manner, to facilitate faster visual data mining. Availability and implementation GLAD is freely available for use on the Web at https://glycotoolkit.com/Tools/GLAD/ with all major modern browsers (Edge, Firefox, Chrome, Safari). Supplementary information Full documentation and video tutorials for GLAD can be found on https://glycotoolkit.com/GLAD.

scholarly journals Subcellular Targeting of p33ING1b by Phosphorylation-Dependent 14-3-3 Binding Regulates p21WAF1 Expression

2006 ◽  
Vol 26 (8) ◽  
pp. 2947-2954 ◽  
Author(s):  
Wei Gong ◽  
Michael Russell ◽  
Keiko Suzuki ◽  
Karl Riabowol
Keyword(s):  
Kinase Inhibitor ◽  
Biological Activities ◽  
Ectopic Expression ◽  
Growth Stress ◽  
Nuclear Localization Sequence ◽  
Binding Motif ◽  
Subcellular Targeting ◽  
Cyclin Dependent Kinase Inhibitor ◽  
Cargo Proteins ◽  
Localization Sequence

ABSTRACT ING1 is a type II tumor suppressor that affects cell growth, stress signaling, apoptosis, and DNA repair by altering chromatin structure and regulating transcription. Decreased ING1 expression is seen in several human cancers, and mislocalization has been noted in diverse types of cancer cells. Aberrant targeting may, therefore, functionally inactivate ING1. Bioinformatics analysis identified a sequence between the nuclear localization sequence and plant homeodomain domains of ING1 that closely matched the binding motif of 14-3-3 proteins that target cargo proteins to specific subcellular locales. We find that the widely expressed p33ING1b splicing isoform of ING1 interacts with members of the 14-3-3 family of proteins and that this interaction is regulated by the phosphorylation status of ING1. 14-3-3 binding resulted in significant amounts of p33ING1b protein being tethered in the cytoplasm. As shown previously, ectopic expression of p33ING1b increased levels of the p21Waf1 cyclin-dependent kinase inhibitor upon UV-induced DNA damage. Overexpression of 14-3-3 inhibited the up-regulation of p21Waf1 by p33ING1b, consistent with the idea that mislocalization blocks at least one of ING1's biological activities. These data support the idea that the 14-3-3 proteins play a crucial role in regulating the activity of p33ING1b by directing its subcellular localization.

scholarly journals Insulin-like growth factor (IGF)-II binding to IGF-binding proteins and IGF receptors is modified by deletion of the N-terminal hexapeptide or substitution of arginine for glutamate-6 in IGF-II

1993 ◽  
Vol 293 (3) ◽  
pp. 713-719 ◽  
Author(s):  
G L Francis ◽  
S E Aplin ◽  
S J Milner ◽  
K A McNeil ◽  
F J Ballard ◽  
...  
Keyword(s):  
Growth Factor ◽  
Binding Proteins ◽  
Biological Activities ◽  
Biological Properties ◽  
Hepatoma Cells ◽  
Insulin Like Growth Factor ◽  
Igf Binding Proteins ◽  
Anabolic Response ◽  
Igf I ◽  
Igf Binding

Recombinant insulin-like growth factor-II (IGF-II) and two structural analogues, des(1-6)IGF-II and [Arg6]-IGF-II, were produced to investigate the role of N-terminal residues in binding to IGF-binding proteins (IGFBPs) and hence the biological properties of the modified peptides. The growth factors were modelled on two previously characterized variants of IGF-I, des(1-3)IGF-I and [Arg3]-IGF-I, which both show substantially decreased binding to IGFBPs and were expressed as fusion proteins in Escherichia coli. The biological activities of the corresponding analogues of IGF-I and IGF-II were compared in rat L6 myoblasts and H35B hepatoma cells. In the L6-myoblast protein-synthesis assay, the IGF-II analogues, des(1-6)IGF-II and [Arg6]-IGF-II, were slightly more potent than IGF-II but about 10-fold less potent than IGF-I and 100-fold less potent than the respective IGF-I analogues, des(1-3)IGF-I and [Arg3]IGF-I. In H35 hepatoma cells the anabolic response measured was the inhibition of protein breakdown, and the potency order was insulin >>> [Arg3]-IGF-I > des(1-3)IGF-I > [Arg6]-IGF-II > des(1-6)IGF-II > IGF-I > IGF-II. Binding of the IGFs and their analogues to the type 1 IGF receptor in L6 myoblasts and to the insulin receptor in H35 hepatoma cells did not fully explain the observed anabolic potency differences. Moreover, binding of all four analogues to the IGFBPs secreted by L6 myoblasts and H35B hepatoma cells was greatly decreased compared with the parent IGF. We conclude that the observed anabolic response to each IGF was determined by their relative binding to the competing cell receptor and IGFBP binding sites present.

DBP-GAPred: An intelligent method for prediction of DNA-binding proteins types by enhanced evolutionary profile features with ensemble learning

2021 ◽  
pp. 2150018
Author(s):  
Omar Barukab ◽  
Farman Ali ◽  
Sher Afzal Khan
Keyword(s):  
Dna Binding ◽  
Binding Proteins ◽  
Biological Activities ◽  
Dna Binding Proteins ◽  
Support Vector ◽  
The Novel ◽  
Double Stranded Dna ◽  
Difference Formula ◽  
Ensemble Strategy ◽  
Inflammatory Drugs

DNA-binding proteins (DBPs) perform an influential role in diverse biological activities like DNA replication, slicing, repair, and transcription. Some DBPs are indispensable for understanding many types of human cancers (i.e. lung, breast, and liver cancer) and chronic diseases (i.e. AIDS/HIV, asthma), while other kinds are involved in antibiotics, steroids, and anti-inflammatory drugs designing. These crucial processes are closely related to DBPs types. DBPs are categorized into single-stranded DNA-binding proteins (ssDBPs) and double-stranded DNA-binding proteins (dsDBPs). Few computational predictors have been reported for discriminating ssDBPs and dsDBPs. However, due to the limitations of the existing methods, an intelligent computational system is still highly desirable. In this work, features from protein sequences are discovered by extending the notion of dipeptide composition (DPC), evolutionary difference formula (EDF), and K-separated bigram (KSB) into the position-specific scoring matrix (PSSM). The highly intrinsic information was encoded by a compression approach named discrete cosine transform (DCT) and the model was trained with support vector machine (SVM). The prediction performance was further boosted by the genetic algorithm (GA) ensemble strategy. The novel predictor (DBP-GAPred) acquired 1.89%, 0.28%, and 6.63% higher accuracies on jackknife, 10-fold, and independent dataset tests, respectively than the best predictor. These outcomes confirm the superiority of our method over the existing predictors.

Ca2+-binding proteins of cilia and infraciliary lattice ofParamecium tetraurelia: their phosphorylation by purified endogenous Ca2+-dependent protein kinases

2002 ◽  
Vol 115 (9) ◽  
pp. 1973-1984
Author(s):  
Kwanghee Kim ◽  
Min Son ◽  
Joan B. Peterson ◽  
David L. Nelson
Keyword(s):  
Protein Kinases ◽  
Calcium Binding ◽  
Binding Proteins ◽  
Soluble Fraction ◽  
Biological Activities ◽  
Anion Exchange Chromatography ◽  
Exchange Chromatography ◽  
Paramecium Tetraurelia ◽  
Dependent Protein

We purified two small, acidic calcium-binding proteins(ParameciumCa2+-binding proteins, PCBP-25α and PCBP-25β) from Paramecium tetraurelia by Ca2+-dependent chromatography on phenyl-Sepharose and by anion-exchange chromatography. The proteins were immunologically distinct. Monoclonal antibodies against PCBP-25β did not react with PCBP-25α, and antibodies against centrin from Chlamydomonas reacted with PCBP-25α but not with PCBP-25β. Like the centrins described previously, both PCBPs were associated with the infraciliary lattice (ICL), a fibrillar cytoskeletal element in Paramecium. Both were also present in isolated cilia, from which they could be released (with dynein) by a high-salt wash, and both PCBPs cosedimented with dynein in a sucrose gradient. PCBP-25β was especially prominent in cilia and in the deciliation supernatant, a soluble fraction released during the process of deciliation. The results of immunoreactivity and localization experiments suggest that PCBP-25α is a Paramecium centrin and that PCBP-25β is a distinct Ca2+-binding protein that confers Ca2+ sensitivity on some component of the cilium, ciliary basal body or ICL.We characterized these proteins and Paramecium calmodulin as substrates for two Ca2+-dependent protein kinases purified from Paramecium. PCBP-25α and calmodulin were in vitro substrates for one of the two Ca2+-dependent protein kinases (CaPK-2), but only PCBP-25α was phosphorylated by CaPK-1. These results raise the possibility that the biological activities of PCBP-25α and calmodulin are regulated by phosphorylation.

scholarly journals Tools for generating and analyzing glycan microarray data

2020 ◽  
Vol 16 ◽  
pp. 2260-2271
Author(s):  
Akul Y Mehta ◽  
Jamie Heimburg-Molinaro ◽  
Richard D Cummings
Keyword(s):  
Microarray Data ◽  
Automated Analysis ◽  
Experimental Methods ◽  
Vital Role ◽  
Data Repositories ◽  
Glycan Microarray ◽  
Manual Analysis ◽  
Analysis Tools ◽  
Biological Polymers ◽  
Informatics Tools

Glycans are one of the major biological polymers found in the mammalian body. They play a vital role in a number of physiologic and pathologic conditions. Glycan microarrays allow a plethora of information to be obtained on protein–glycan binding interactions. In this review, we describe the intricacies of the generation of glycan microarray data and the experimental methods for studying binding. We highlight the importance of this knowledge before moving on to the data analysis. We then highlight a number of tools for the analysis of glycan microarray data such as data repositories, data visualization and manual analysis tools, automated analysis tools and structural informatics tools.

PmliPred: a method based on hybrid model and fuzzy decision for plant miRNA–lncRNA interaction prediction

2020 ◽  
Vol 36 (10) ◽  
pp. 2986-2992 ◽  
Author(s):  
Qiang Kang ◽  
Jun Meng ◽  
Jun Cui ◽  
Yushi Luan ◽  
Ming Chen
Keyword(s):  
Biological Activities ◽  
Learning Model ◽  
Supplementary Information ◽  
Fuzzy Decision ◽  
Interaction Prediction ◽  
Machine Learning Model ◽  
Plant Mirna ◽  
Mechanism Of Interaction ◽  
Polymerase Chain ◽  
Deep Learning Model

Abstract Motivation The studies have indicated that not only microRNAs (miRNAs) or long non-coding RNAs (lncRNAs) play important roles in biological activities, but also their interactions affect the biological process. A growing number of studies focus on the miRNA–lncRNA interactions, while few of them are proposed for plant. The prediction of interactions is significant for understanding the mechanism of interaction between miRNA and lncRNA in plant. Results This article proposes a new method for fulfilling plant miRNA–lncRNA interaction prediction (PmliPred). The deep learning model and shallow machine learning model are trained using raw sequence and manually extracted features, respectively. Then they are hybridized based on fuzzy decision for prediction. PmliPred shows better performance and generalization ability compared with the existing methods. Several new miRNA–lncRNA interactions in Solanum lycopersicum are successfully identified using quantitative real time–polymerase chain reaction from the candidates predicted by PmliPred, which further verifies its effectiveness. Availability and implementation The source code of PmliPred is freely available at http://bis.zju.edu.cn/PmliPred/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Microbe-focused glycan array screening platform

2019 ◽  
Vol 116 (6) ◽  
pp. 1958-1967 ◽  
Author(s):  
Andreas Geissner ◽  
Anika Reinhardt ◽  
Christoph Rademacher ◽  
Timo Johannssen ◽  
João Monteiro ◽  
...  
Keyword(s):  
Binding Proteins ◽  
Microarray Platform ◽  
Innate Immune ◽  
Glycan Array ◽  
Phase Synthesis ◽  
Glycan Microarray ◽  
Solution Phase Synthesis ◽  
Screening Platform ◽  
Excellent Tool

Interactions between glycans and glycan binding proteins are essential for numerous processes in all kingdoms of life. Glycan microarrays are an excellent tool to examine protein–glycan interactions. Here, we present a microbe-focused glycan microarray platform based on oligosaccharides obtained by chemical synthesis. Glycans were generated by combining different carbohydrate synthesis approaches including automated glycan assembly, solution-phase synthesis, and chemoenzymatic methods. The current library of more than 300 glycans is as diverse as the mammalian glycan array from the Consortium for Functional Glycomics and, due to its microbial focus, highly complementary. This glycan platform is essential for the characterization of various classes of glycan binding proteins. Applications of this glycan array platform are highlighted by the characterization of innate immune receptors and bacterial virulence factors as well as the analysis of human humoral immunity to pathogenic glycans.

Insights into adaptor binding to the AAA protein p97

2008 ◽  
Vol 36 (1) ◽  
pp. 62-67 ◽  
Author(s):  
Heidi O. Yeung ◽  
Patrik Kloppsteck ◽  
Hajime Niwa ◽  
Rivka L. Isaacson ◽  
Steve Matthews ◽  
...  
Keyword(s):  
Current Knowledge ◽  
Biological Activities ◽  
Binding Motif ◽  
Binding Modes ◽  
Aaa Atpase ◽  
Essential Component ◽  
Cellular Pathways ◽  
Aaa Protein ◽  
Structural Homologues ◽  
Binding Mechanisms

The AAA (ATPase associated with various cellular activities) p97 [also known as VCP (valosin-containing protein)] participates in numerous biological activities and is an essential component of the ubiquitin signalling pathway. A plethora of adaptors have been reported for p97, and increasing evidence is suggesting that it is through adaptor binding that p97 is diverted into different cellular pathways. Studying the interaction between p97 and its adaptors is therefore crucial to our understanding of the physiological roles of the protein. The interactions between p97 and the PUB [PNGase (peptide N-glycosidase)/ubiquitin-associated] domain of PNGase, the UBX (ubiquitin regulatory X) domain of p47, and the UBD (ubiquitin D) domain of Npl4 have been structurally characterized. UBX and UBD are structural homologues that share similar p97-binding modes; it is plausible that other proteins that contain a UBX/UBX-like domain also interact with p97 via similar mechanisms. In addition, several short p97-interacting motifs, such as VBM (VCP-binding motif), VIM (VCP-interacting motif) and SHP, have been identified recently and are also shared between p97 adaptors, hinting that proteins possessing the same p97-binding motif might also share common p97-binding mechanisms. In this review, we aim to summarize our current knowledge on adaptor binding to p97.

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