scholarly journals ChIPSummitDB: a ChIP-seq-based database of human transcription factor binding sites and the topological arrangements of the proteins bound to them

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Erik Czipa ◽  
Mátyás Schiller ◽  
Tibor Nagy ◽  
Levente Kontra ◽  
László Steiner ◽  
...  
Keyword(s):  
Binding Site ◽  
Protein Interactions ◽  
Average Distance ◽  
Regulatory Elements ◽  
Binding Motif ◽  
Data Sets ◽  
Protein Protein Interactions ◽  
Distance Distributions ◽  
Co Precipitation ◽  
Genomic Regions

Abstract ChIP-seq reveals genomic regions where proteins, e.g. transcription factors (TFs) interact with DNA. A substantial fraction of these regions, however, do not contain the cognate binding site for the TF of interest. This phenomenon might be explained by protein–protein interactions and co-precipitation of interacting gene regulatory elements. We uniformly processed 3727 human ChIP-seq data sets and determined the cistrome of 292 TFs, as well as the distances between the TF binding motif centers and the ChIP-seq peak summits. ChIPSummitDB enables the analysis of ChIP-seq data using multiple approaches. The 292 cistromes and corresponding ChIP-seq peak sets can be browsed in GenomeView. Overlapping SNPs can be inspected in dbSNPView. Most importantly, the MotifView and PairShiftView pages show the average distance between motif centers and overlapping ChIP-seq peak summits and distance distributions thereof, respectively. In addition to providing a comprehensive human TF binding site collection, the ChIPSummitDB database and web interface allows for the examination of the topological arrangement of TF complexes genome-wide. ChIPSummitDB is freely accessible at http://summit.med.unideb.hu/summitdb/. The database will be regularly updated and extended with the newly available human and mouse ChIP-seq data sets.

scholarly journals ChIPSummitDB: A ChIP-seq-based database of human transcription factor binding sites and the topological arrangements of the proteins bound to them

2019 ◽  
Author(s):  
Erik Czipa ◽  
Mátyás Schiller ◽  
Tibor Nagy ◽  
Levente Kontra ◽  
László Steiner ◽  
...  
Keyword(s):  
Binding Site ◽  
Protein Interactions ◽  
Average Distance ◽  
Regulatory Elements ◽  
Binding Motif ◽  
Data Sets ◽  
Protein Protein Interactions ◽  
Distance Distributions ◽  
Co Precipitation ◽  
Genomic Regions

ABSTRACTChIP-Seq reveals genomic regions where proteins, e.g. transcription factors (TFs) interact with DNA. A substantial fraction of these regions, however, do not contain the cognate binding site for the TF of interest. This phenomenon might be explained by protein-protein interactions and co-precipitation of interacting gene regulatory elements. We uniformly processed 3,727 human ChIP-Seq data sets and determined the cistrome of 292 TFs, as well as the distances between the TF binding motif centers and the ChIP-Seq peak summits.ChIPSummitDB enables the analysis of ChIP-Seq data using multiple approaches. The 292 cistromes and corresponding ChIP-Seq peak sets can be browsed in GenomeView. Overlapping SNPs can be inspected in dbSNPView. Most importantly, the MotifView and PairShiftView pages show the average distance between motif centers and overlapping ChIP-Seq peak summits and distance distributions thereof, respectively.In addition to providing a comprehensive human TF binding site collection, the ChIPSummitDB database and web interface allows for the examination of the topological arrangement of TF complexes genome-wide. ChIPSummitDB is freely accessible at http://summit.med.unideb.hu/summitdb/. The database will be regularly updated and extended with the newly available human and mouse ChIP-Seq data sets.

scholarly journals Mapping cell type-specific transcriptional enhancers using high affinity, lineage-specific Ep300 bioChIP-seq

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Pingzhu Zhou ◽  
Fei Gu ◽  
Lina Zhang ◽  
Brynn N Akerberg ◽  
Qing Ma ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Regulatory Elements ◽  
Specific Protein ◽  
Cell Type ◽  
Protein Protein Interactions ◽  
Selective Method ◽  
Tissue Specific ◽  
Transcriptional Enhancers ◽  
Cell Type Specific ◽  
Genomic Regions

Understanding the mechanisms that regulate cell type-specific transcriptional programs requires developing a lexicon of their genomic regulatory elements. We developed a lineage-selective method to map transcriptional enhancers, regulatory genomic regions that activate transcription, in mice. Since most tissue-specific enhancers are bound by the transcriptional co-activator Ep300, we used Cre-directed, lineage-specific Ep300 biotinylation and pulldown on immobilized streptavidin followed by next generation sequencing of co-precipitated DNA to identify lineage-specific enhancers. By driving this system with lineage-specific Cre transgenes, we mapped enhancers active in embryonic endothelial cells/blood or skeletal muscle. Analysis of these enhancers identified new transcription factor heterodimer motifs that likely regulate transcription in these lineages. Furthermore, we identified candidate enhancers that regulate adult heart- or lung- specific endothelial cell specialization. Our strategy for tissue-specific protein biotinylation opens new avenues for studying lineage-specific protein-DNA and protein-protein interactions.

c-Fos-induced activation of a TATA-box-containing promoter involves direct contact with TATA-box-binding protein

1994 ◽  
Vol 14 (9) ◽  
pp. 6021-6029
Author(s):  
R Metz ◽  
A J Bannister ◽  
J A Sutherland ◽  
C Hagemeier ◽  
E C O'Rourke ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Transcriptional Activation ◽  
Binding Protein ◽  
Tata Box ◽  
Binding Motif ◽  
Protein Protein Interactions ◽  
High Concentrations ◽  
Tata Box Binding Protein

Transcriptional activation in eukaryotes involves protein-protein interactions between regulatory transcription factors and components of the basal transcription machinery. Here we show that c-Fos, but not a related protein, Fra-1, can bind the TATA-box-binding protein (TBP) both in vitro and in vivo and that c-Fos can also interact with the transcription factor IID complex. High-affinity binding to TBP requires c-Fos activation modules which cooperate to activate transcription. One of these activation modules contains a TBP-binding motif (TBM) which was identified through its homology to TBP-binding viral activators. This motif is required for transcriptional activation, as well as TBP binding. Domain swap experiments indicate that a domain containing the TBM can confer TBP binding on Fra-1 both in vitro and in vivo. In vivo activation experiments indicate that a GAL4-Fos fusion can activate a promoter bearing a GAL4 site linked to a TATA box but that this activity does not occur at high concentrations of GAL4-Fos. This inhibition (squelching) of c-Fos activity is relieved by the presence of excess TBP, indicating that TBP is a direct functional target of c-Fos. Removing the TBM from c-Fos severely abrogates activation of a promoter containing a TATA box but does not affect activation of a promoter driven only by an initiator element. Collectively, these results suggest that c-Fos is able to activate via two distinct mechanisms, only one of which requires contact with TBP. Since TBP binding is not exhibited by Fra-1, TBP-mediated activation may be one characteristic that discriminates the function of Fos-related proteins.

A crosslinked and ribosylated actin trimer does not interact productively with myosin

2019 ◽  
Vol 97 (2) ◽  
pp. 140-147 ◽  
Author(s):  
Navneet Sidhu ◽  
John F. Dawson
Keyword(s):  
Binding Site ◽  
Protein Interactions ◽  
Binding Proteins ◽  
Binding Protein ◽  
Dnase I ◽  
Protein Protein Interactions ◽  
Adp Ribosylation ◽  
Myosin Binding ◽  
Pointed End

A purified F-actin-derived actin trimer that interacts with end-binding proteins did not activate or bind the side-binding protein myosin under rigor conditions. Remodeling of the actin trimer by the binding of gelsolin did not rescue myosin binding, nor did the use of different means of inhibiting the polymerization of the trimer. Our results demonstrate that ADP-ribosylation on all actin subunits of an F-actin-derived trimer inhibits myosin binding and that the binding of DNase-I to the pointed end subunits of a crosslinked trimer also remodels the myosin binding site. Taken together, this work highlights the need for a careful balance between modification of actin subunits and maintaining protein–protein interactions to produce a physiologically relevant short F-actin complex.

Deep learning based prediction of reversible HAT/HDAC-specific lysine acetylation

2019 ◽  
Vol 21 (5) ◽  
pp. 1798-1805 ◽  
Author(s):  
Kai Yu ◽  
Qingfeng Zhang ◽  
Zekun Liu ◽  
Yimeng Du ◽  
Xinjiao Gao ◽  
...  
Keyword(s):  
Deep Learning ◽  
Protein Interactions ◽  
Web Server ◽  
Data Sets ◽  
Lysine Acetylation ◽  
Protein Acetylation ◽  
Protein Protein Interactions ◽  
Cellular Processes ◽  
Protein Lysine Acetylation ◽  
Specific Regulation

Abstract Protein lysine acetylation regulation is an important molecular mechanism for regulating cellular processes and plays critical physiological and pathological roles in cancers and diseases. Although massive acetylation sites have been identified through experimental identification and high-throughput proteomics techniques, their enzyme-specific regulation remains largely unknown. Here, we developed the deep learning-based protein lysine acetylation modification prediction (Deep-PLA) software for histone acetyltransferase (HAT)/histone deacetylase (HDAC)-specific acetylation prediction based on deep learning. Experimentally identified substrates and sites of several HATs and HDACs were curated from the literature to generate enzyme-specific data sets. We integrated various protein sequence features with deep neural network and optimized the hyperparameters with particle swarm optimization, which achieved satisfactory performance. Through comparisons based on cross-validations and testing data sets, the model outperformed previous studies. Meanwhile, we found that protein–protein interactions could enrich enzyme-specific acetylation regulatory relations and visualized this information in the Deep-PLA web server. Furthermore, a cross-cancer analysis of acetylation-associated mutations revealed that acetylation regulation was intensively disrupted by mutations in cancers and heavily implicated in the regulation of cancer signaling. These prediction and analysis results might provide helpful information to reveal the regulatory mechanism of protein acetylation in various biological processes to promote the research on prognosis and treatment of cancers. Therefore, the Deep-PLA predictor and protein acetylation interaction networks could provide helpful information for studying the regulation of protein acetylation. The web server of Deep-PLA could be accessed at http://deeppla.cancerbio.info.

scholarly journals Computational Prediction of Protein-Protein Interactions of Human Tyrosinase

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Su-Fang Wang ◽  
Sangho Oh ◽  
Yue-Xiu Si ◽  
Zhi-Jiang Wang ◽  
Hong-Yan Han ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Rna Binding ◽  
3D Structure ◽  
Computational Prediction ◽  
Binding Motif ◽  
Protein Protein Interactions ◽  
Lim Domains ◽  
Binding Partners ◽  
Computational Predictions ◽  
Human Tyrosinase

The various studies on tyrosinase have recently gained the attention of researchers due to their potential application values and the biological functions. In this study, we predicted the 3D structure of human tyrosinase and simulated the protein-protein interactions between tyrosinase and three binding partners, four and half LIM domains 2 (FHL2), cytochrome b-245 alpha polypeptide (CYBA), and RNA-binding motif protein 9 (RBM9). Our interaction simulations showed significant binding energy scores of −595.3 kcal/mol for FHL2, −859.1 kcal/mol for CYBA, and −821.3 kcal/mol for RBM9. We also investigated the residues of each protein facing toward the predicted site of interaction with tyrosinase. Our computational predictions will be useful for elucidating the protein-protein interactions of tyrosinase and studying its binding mechanisms.

scholarly journals Getting into position: the catalytic mechanisms of protein ubiquitylation

2004 ◽  
Vol 379 (3) ◽  
pp. 513-525 ◽  
Author(s):  
Lori A. PASSMORE ◽  
David BARFORD
Keyword(s):  
Protein Interactions ◽  
Regulatory Elements ◽  
Substrate Selection ◽  
Protein Protein Interactions ◽  
Different Types ◽  
Catalytic Mechanisms ◽  
Cellular Pathways ◽  
Ubiquitin Conjugating Enzymes ◽  
Insight Into

The role of protein ubiquitylation in the control of diverse cellular pathways has recently gained widespread attention. Ubiquitylation not only directs the targeted destruction of tagged proteins by the 26 S proteasome, but it also modulates protein activities, protein–protein interactions and subcellular localization. An understanding of the components involved in protein ubiquitylation (E1s, E2s and E3s) is essential to understand how specificity and regulation are conferred upon these pathways. Much of what we know about the catalytic mechanisms of protein ubiquitylation comes from structural studies of the proteins involved in this process. Indeed, structures of ubiquitin-activating enzymes (E1s) and ubiquitin-conjugating enzymes (E2s) have provided insight into their mechanistic details. E3s (ubiquitin ligases) contain most of the substrate specificity and regulatory elements required for protein ubiquitylation. Although several E3 structures are available, the specific mechanistic role of E3s is still unclear. This review will discuss the different types of ubiquitin signals and how they are generated. Recent advances in the field of protein ubiquitylation will be examined, including the mechanisms of E1, E2 and E3. In particular, we discuss the complexity of molecular recognition required to impose selectivity on substrate selection and topology of poly-ubiquitin chains.

scholarly journals Binding Site Prediction for Protein-Protein Interactions and Novel Motif Discovery using Re-occurring Polypeptide Sequences

2011 ◽  
Vol 12 (1) ◽  
pp. 225 ◽  
Author(s):  
Adam Amos-Binks ◽  
Catalin Patulea ◽  
Sylvain Pitre ◽  
Andrew Schoenrock ◽  
Yuan Gui ◽  
...  
Keyword(s):  
Binding Site ◽  
Protein Interactions ◽  
Motif Discovery ◽  
Protein Protein Interactions ◽  
Site Prediction ◽  
Binding Site Prediction ◽  
Polypeptide Sequences

scholarly journals Zyxin Interacts with the SH3 Domains of the Cytoskeletal Proteins LIM-nebulette and Lasp-1

2004 ◽  
Vol 279 (19) ◽  
pp. 20401-20410 ◽  
Author(s):  
Bo Li ◽  
Lei Zhuang ◽  
Beat Trueb
Keyword(s):  
Binding Site ◽  
Focal Adhesions ◽  
Sh3 Domain ◽  
Cytoskeletal Proteins ◽  
Site Directed Mutagenesis ◽  
Binding Motif ◽  
Sh3 Domains ◽  
Sorting Nexin ◽  
Sarcomeric Protein ◽  
Co Precipitation

Zyxin is a versatile component of focal adhesions in eukaryotic cells. Here we describe a novel binding partner of zyxin, which we have named LIM-nebulette. LIM-nebulette is an alternative splice variant of the sarcomeric protein nebulette, which, in contrast to nebulette, is expressed in non-muscle cells. It displays a modular structure with an N-terminal LIM domain, three nebulin-like repeats, and a C-terminal SH3 domain and shows high similarity to another cytoskeletal protein, Lasp-1 (LIM and SH3 protein-1). Co-precipitation studies and results obtained with the two-hybrid system demonstrate that LIM-nebulette and Lasp-1 interact specifically with zyxin. Moreover, the SH3 domain from LIM-nebulette is both necessary and sufficient for zyxin binding. The SH3 domains from Lasp-1 and nebulin can also interact with zyxin, but the SH3 domains from more distantly related proteins such as vinexin and sorting nexin 9 do not. On the other hand, the binding site in zyxin is situated at the extreme N terminus as shown by site-directed mutagenesis. LIM-nebulette and Lasp-1 use the same linear binding motif. This motif shows some similarity to a class II binding site but does not contain the classical PXXP sequence. LIM-nebulette reveals a subcellular distribution at focal adhesions similar to Lasp-1. Thus, LIM-nebulette, Lasp-1, and zyxin may play an important role in the organization of focal adhesions.

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