scholarly journals TRI_tool: a web-tool for prediction of protein–protein interactions in human transcriptional regulation

2016 ◽  
Vol 33 (2) ◽  
pp. 289-291 ◽  
Author(s):  
Vladimir Perovic ◽  
Neven Sumonja ◽  
Branislava Gemovic ◽  
Eneda Toska ◽  
Stefan G. Roberts ◽  
...  
Keyword(s):  
Transcriptional Regulation ◽  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Web Tool

scholarly journals FLAME: A Web Tool for Functional and Literature Enrichment Analysis of Multiple Gene Lists

Biology ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 665
Author(s):  
Foteini Thanati ◽  
Evangelos Karatzas ◽  
Fotis A. Baltoumas ◽  
Dimitrios J. Stravopodis ◽  
Aristides G. Eliopoulos ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Enrichment Analysis ◽  
Experimental Colitis ◽  
Functional Enrichment ◽  
Protein Protein Interactions ◽  
Web Tool ◽  
Single List ◽  
Gene Ontologies ◽  
User Friendly ◽  
The Given

Functional enrichment is a widely used method for interpreting experimental results by identifying classes of proteins/genes associated with certain biological functions, pathways, diseases, or phenotypes. Despite the variety of existing tools, most of them can process a single list per time, thus making a more combinatorial analysis more complicated and prone to errors. In this article, we present FLAME, a web tool for combining multiple lists prior to enrichment analysis. Users can upload several lists and use interactive UpSet plots, as an alternative to Venn diagrams, to handle unions or intersections among the given input files. Functional and literature enrichment, along with gene conversions, are offered by g:Profiler and aGOtool applications for 197 organisms. FLAME can analyze genes/proteins for related articles, Gene Ontologies, pathways, annotations, regulatory motifs, domains, diseases, and phenotypes, and can also generate protein–protein interactions derived from STRING. We have validated FLAME by interrogating gene expression data associated with the sensitivity of the distal part of the large intestine to experimental colitis-propelled colon cancer. FLAME comes with an interactive user-friendly interface for easy list manipulation and exploration, while results can be visualized as interactive and parameterizable heatmaps, barcharts, Manhattan plots, networks, and tables.

scholarly journals FLAME: a web tool for functional and literature enrichment analysis of multiple gene lists

2021 ◽  
Author(s):  
Foteini Thanati ◽  
Evangelos Karatzas ◽  
Fotis Baltoumas ◽  
Dimitrios J Stravopodis ◽  
Aristides G Eliopoulos ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Enrichment Analysis ◽  
Experimental Colitis ◽  
Functional Enrichment ◽  
Protein Protein Interactions ◽  
Web Tool ◽  
Single List ◽  
Gene Ontologies ◽  
User Friendly ◽  
The Given

Functional enrichment is a widely used method for interpreting experimental results by identifying classes of proteins/genes associated with certain biological functions, pathways, diseases or phenotypes. Despite the variety of existing tools, most of them can process a single list per time, thus making a more combinatorial analysis more complicated and prone to errors. In this article, we present FLAME, a web tool for combining multiple lists prior to enrichment analysis. Users can upload several lists of preference and use interactive UpSet plots, as an alternative to Venn diagrams, to handle unions or intersections among the given input files. Functional and literature enrichment along with gene conversions are offered by g:Profiler and aGOtool applications for 197 organisms. In its current version, FLAME can analyze genes/proteins for related articles, Gene Ontologies, pathways, annotations, regulatory motifs, domains, diseases, phenotypes while it can also generate protein-protein interactions derived from STRING. We have herein validated FLAME by interrogating gene expression data associated with the sensitivity of the distal part of the large intestine to experimental colitis-propelled colon cancer. The FLAME application comes with an interactive user-friendly interface which allows easy list manipulation and exploration, while results can be visualized as interactive and parameterizable heatmaps, barcharts, Manhattan plots, networks and tables. Availability: FLAME application: http://flame.pavlopouloslab.info Code: https://github.com/PavlopoulosLab/FLAME

scholarly journals Impact of the N-Terminal Domain of STAT3 in STAT3-Dependent Transcriptional Activity

2015 ◽  
Vol 35 (19) ◽  
pp. 3284-3300 ◽  
Author(s):  
Tiancen Hu ◽  
Jennifer E. Yeh ◽  
Luca Pinello ◽  
Jaison Jacob ◽  
Srinivas Chakravarthy ◽  
...  
Keyword(s):  
Transcriptional Regulation ◽  
Dna Binding ◽  
Protein Interactions ◽  
Target Genes ◽  
Nuclear Translocation ◽  
Biological Effects ◽  
Null Mouse ◽  
Protein Protein Interactions ◽  
Terminal Domain

The transcription factor STAT3 is constitutively active in many cancers, where it mediates important biological effects, including cell proliferation, differentiation, survival, and angiogenesis. The N-terminal domain (NTD) of STAT3 performs multiple functions, such as cooperative DNA binding, nuclear translocation, and protein-protein interactions. However, it is unclear which subsets of STAT3 target genes depend on the NTD for transcriptional regulation. To identify such genes, we compared gene expression inSTAT3-null mouse embryonic fibroblasts (MEFs) stably expressing wild-type STAT3 or STAT3 from which NTD was deleted. NTD deletion reduced the cytokine-induced expression of specific STAT3 target genes by decreasing STAT3 binding to their regulatory regions. To better understand the potential mechanisms of this effect, we determined the crystal structure of the STAT3 NTD and identified a dimer interface responsible for cooperative DNA bindingin vitro. We also observed an Ni2+-mediated oligomer with an as yet unknown biological function. Mutations on both dimer and Ni2+-mediated interfaces affected the cytokine induction of STAT3 target genes. These studies shed light on the role of the NTD in transcriptional regulation by STAT3 and provide a structural template with which to design STAT3 NTD inhibitors with potential therapeutic value.

LUCIFERASES FOR THE STUDY OF PROTEIN–PROTEIN INTERACTIONS IN LIVE CELLS AND ANIMALS

Nano LIFE ◽  
2010 ◽  
Vol 01 (01n02) ◽  
pp. 79-87 ◽  
Author(s):  
A. K. M. KAFI ◽  
MITSURU HATTORI ◽  
TAKEAKI OZAWA
Keyword(s):  
Transcriptional Regulation ◽  
Protein Interactions ◽  
Protein Modification ◽  
Specific Protein ◽  
Live Cells ◽  
Protein Protein Interactions ◽  
Recent Developments ◽  
Split Luciferase Complementation ◽  
Spatio Temporal ◽  
Split Luciferase

Many imaging technologies based on luminescent proteins have proven useful for detecting protein–protein interactions, tracking cells in mice, and monitoring transcriptional regulation of specific genes. Especially, novel bioluminescent proteins have advanced the study of induced protein interactions and protein modification in live cells and animals. This review focuses on recent developments of bioluminescent probes for quantitative evaluation of specific protein–protein interactions and their spatio-temporal imaging by means of split luciferase complementation techniques. From the comparison between fluorescent and bioluminescent proteins, advantages and drawbacks of the bioluminescence techniques are described.

Chemical biology approaches to study histone interactors

2021 ◽  
Author(s):  
Antony J. Burton ◽  
Ghaith M. Hamza ◽  
Andrew X. Zhang ◽  
Tom W. Muir
Keyword(s):  
Mass Spectrometry ◽  
Transcriptional Regulation ◽  
Protein Interactions ◽  
Chemical Biology ◽  
Genomic Stability ◽  
Protein Protein Interactions ◽  
Post Translational Modification ◽  
Ppi Networks ◽  
Histone Ptms ◽  
Approaches To Study

Protein–protein interactions (PPIs) in the nucleus play key roles in transcriptional regulation and ensure genomic stability. Critical to this are histone-mediated PPI networks, which are further fine-tuned through dynamic post-translational modification. Perturbation to these networks leads to genomic instability and disease, presenting epigenetic proteins as key therapeutic targets. This mini-review will describe progress in mapping the combinatorial histone PTM landscape, and recent chemical biology approaches to map histone interactors. Recent advances in mapping direct interactors of histone PTMs as well as local chromatin interactomes will be highlighted, with a focus on mass-spectrometry based workflows that continue to illuminate histone-mediated PPIs in unprecedented detail.

scholarly journals Inositol polyphosphate multikinase (IPMK) in transcriptional regulation and nuclear inositide metabolism

2016 ◽  
Vol 44 (1) ◽  
pp. 279-285 ◽  
Author(s):  
M. Merced Malabanan ◽  
Raymond D. Blind
Keyword(s):  
Transcriptional Regulation ◽  
Protein Interactions ◽  
Flexible Substrate ◽  
Short Review ◽  
Inositol Polyphosphate ◽  
Protein Protein Interactions ◽  
Functional Protein ◽  
History Of ◽  
Inositol Polyphosphate Multikinase ◽  
Regulatory Functions

Inositol polyphosphate multikinase (IPMK, ipk2, Arg82, ArgRIII) is an inositide kinase with unusually flexible substrate specificity and the capacity to partake in many functional protein–protein interactions (PPIs). By merging these two activities, IPMK is able to execute gene regulatory functions that are very unique and only now beginning to be recognized. In this short review, we present a brief history of IPMK, describe the structural biology of the enzyme and highlight a few recent discoveries that have shed more light on the role IPMK plays in inositide metabolism, nuclear signalling and transcriptional regulation.

scholarly journals microProtein Prediction Program (miP3): A Software for Predicting microProteins and Their Target Transcription Factors

2015 ◽  
Vol 2015 ◽  
pp. 1-4 ◽  
Author(s):  
Niek de Klein ◽  
Enrico Magnani ◽  
Michael Banf ◽  
Seung Yon Rhee
Keyword(s):  
Transcriptional Regulation ◽  
Transcription Factors ◽  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Feedback Controls ◽  
Prediction Program ◽  
Functional Classes ◽  
Shed Light

An emerging concept in transcriptional regulation is that a class of truncated transcription factors (TFs), called microProteins (miPs), engages in protein-protein interactions with TF complexes and provides feedback controls. A handful of miP examples have been described in the literature but the extent of their prevalence is unclear. Here we present an algorithm that predicts miPs and their target TFs from a sequenced genome. The algorithm is called miP prediction program (miP3), which is implemented in Python. The software will help shed light on the prevalence, biological roles, and evolution of miPs. Moreover, miP3 can be used to predict other types of miP-like proteins that may have evolved from other functional classes such as kinases and receptors. The program is freely available and can be applied to any sequenced genome.

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