The Significance of Tetramerization in Promoter Recruitment by Stat5

ABSTRACT Stat5a and Stat5b are rapidly activated by a wide range of cytokines and growth factors, including interleukin-2 (IL-2). We have previously shown that these signal transducers and activators of transcription (STAT proteins) are key regulatory proteins that bind to two tandem gamma interferon-activated site (GAS) motifs within an IL-2 response element (positive regulatory region III [PRRIII]) in the human IL-2Rα promoter. In this study, we demonstrate cooperative binding of Stat5 to PRRIII and explore the molecular basis underlying this cooperativity. We demonstrate that formation of a tetrameric Stat5 complex is essential for the IL-2-inducible activation of PRRIII. Stable tetramer formation of Stat5 is mediated through protein-protein interactions involving a tryptophan residue conserved in all STATs and a lysine residue in the Stat5 N-terminal domain (N domain). The functional importance of tetramer formation is shown by the decreased levels of transcriptional activation associated with mutations in these residues. Moreover, the requirement for STAT protein-protein interactions for gene activation from a promoter with tandemly linked GAS motifs can be relieved by strengthening the avidity of protein-DNA interactions for the individual binding sites. Taken together, these studies demonstrate that a dimeric but tetramerization-deficient Stat5 protein can activate only a subset of target sites. For functional activity on a wider range of potential recognition sites, N-domain-mediated oligomerization is essential.

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A Specificity and Targeting Subunit of a Human SWI/SNF Family-Related Chromatin-Remodeling Complex

Molecular and Cellular Biology ◽

10.1128/mcb.20.23.8879-8888.2000 ◽

2000 ◽

Vol 20 (23) ◽

pp. 8879-8888 ◽

Cited By ~ 193

Author(s):

Zuqin Nie ◽

Yutong Xue ◽

Dafeng Yang ◽

Sharleen Zhou ◽

Bonnie J. Deroo ◽

...

Keyword(s):

Glucocorticoid Receptor ◽

Chromatin Remodeling ◽

Protein Interactions ◽

Transcriptional Activation ◽

Gene Activation ◽

Dna Interaction ◽

Protein Protein Interactions ◽

Baf Complex ◽

Chromatin Remodeling Complexes

ABSTRACT The SWI/SNF family of chromatin-remodeling complexes facilitates gene activation by assisting transcription machinery to gain access to targets in chromatin. This family includes BAF (also called hSWI/SNF-A) and PBAF (hSWI/SNF-B) from humans and SWI/SNF and Rsc fromSaccharomyces cerevisiae. However, the relationship between the human and yeast complexes is unclear because all human subunits published to date are similar to those of both yeast SWI/SNF and Rsc. Also, the two human complexes have many identical subunits, making it difficult to distinguish their structures or functions. Here we describe the cloning and characterization of BAF250, a subunit present in human BAF but not PBAF. BAF250 contains structural motifs conserved in yeast SWI1 but not in any Rsc components, suggesting that BAF is related to SWI/SNF. BAF250 is also a homolog of the Drosophila melanogaster Osa protein, which has been shown to interact with a SWI/SNF-like complex in flies. BAF250 possesses at least two conserved domains that could be important for its function. First, it has an AT-rich DNA interaction-type DNA-binding domain, which can specifically bind a DNA sequence known to be recognized by a SWI/SNF family-related complex at the β-globin locus. Second, BAF250 stimulates glucocorticoid receptor-dependent transcriptional activation, and the stimulation is sharply reduced when the C-terminal region of BAF250 is deleted. This region of BAF250 is capable of interacting directly with the glucocorticoid receptor in vitro. Our data suggest that BAF250 confers specificity to the human BAF complex and may recruit the complex to its targets through either protein-DNA or protein-protein interactions.

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Sequence representations and their utility for predicting protein-protein interactions

10.1101/2019.12.31.890699 ◽

2019 ◽

Author(s):

Dhananjay Kimothi ◽

Pravesh Biyani ◽

James M Hogan

Keyword(s):

Protein Interactions ◽

Chemical Properties ◽

Protein Classification ◽

Protein Protein Interactions ◽

Sequence Search ◽

Physico Chemical ◽

Wide Range ◽

Individual Sequences ◽

The Individual ◽

Low Dimensional

AbstractProtein-Protein Interactions (PPIs) are a crucial mechanism underpinning the function of the cell. Predicting the likely relationship between a pair of proteins is thus an important problem in bioinformatics, and a wide range of machine-learning based methods have been proposed for this task. Their success is heavily dependent on the construction of the feature vectors, with most using a set of physico-chemical properties derived from the sequence. Few work directly with the sequence itself.Recent works on embedding sequences in a low dimensional vector space has shown the utility of this approach for tasks such as protein classification and sequence search. In this paper, we extend these ideas to the PPI task, making inferences from the pair instead of for the individual sequences. We evaluate the method on human and yeast PPI datasets, benchmarking against the established methods. These results demonstrate that we can obtain sequence encodings for the PPI task which achieve similar levels of performance to existing methods without reliance on complex physico-chemical feature sets.

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Cooperative Binding of Transcription Factors is a Hallmark of Active Enhancers

10.1101/2020.08.17.253146 ◽

2020 ◽

Author(s):

Satyanarayan Rao ◽

Kami Ahmad ◽

Srinivas Ramachandran

Keyword(s):

Transcription Factors ◽

Single Molecule ◽

Protein Interactions ◽

Transcriptional Activation ◽

Binding Sites ◽

Gene Activation ◽

Cooperative Binding ◽

Protein Protein Interactions ◽

Chromatin Profiling

AbstractEnhancers harbor binding motifs that recruit transcription factors (TFs) for gene activation. While cooperative binding of TFs at enhancers is known to be critical for transcriptional activation of a handful of developmental enhancers, the extent TF cooperativity genome-wide is unknown. Here, we couple high-resolution nuclease footprinting with single-molecule methylation profiling to characterize TF cooperativity at active enhancers in the Drosophila genome. Enrichment of short MNase-protected DNA segments indicates that the majority of enhancers harbor two or more TF binding sites, and we uncover protected fragments that correspond to co-bound sites in thousands of enhancers. We integrate MNase-seq, methylation accessibility profiling, and CUT&RUN chromatin profiling as a comprehensive strategy to characterize co-binding of the Trithorax-like (TRL) DNA binding protein and multiple other TFs and identify states where an enhancer is bound by no TF, by either single factor, by multiple factors, or where binding sites are occluded by nucleosomes. From the analysis of co-binding, we find that cooperativity dominates TF binding in vivo at a majority of active enhancers. TF cooperativity can occur without apparent protein-protein interactions and provides a mechanism to effectively clear nucleosomes and promote enhancer function.

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The OsERF115/AP2EREBP110 Transcription Factor Is Involved in the Multiple Stress Tolerance to Heat and Drought in Rice Plants

International Journal of Molecular Sciences ◽

10.3390/ijms22137181 ◽

2021 ◽

Vol 22 (13) ◽

pp. 7181

Author(s):

Seong-Im Park ◽

Hyeok Jin Kwon ◽

Mi Hyeon Cho ◽

Ji Sun Song ◽

Beom-Gi Kim ◽

...

Keyword(s):

Stress Tolerance ◽

Transcriptional Activation ◽

Individual Plant ◽

Hormone Signaling ◽

Combined Stress ◽

Drought Treatment ◽

Wide Range ◽

The Individual ◽

Potential Use ◽

Multiple Stress Tolerance

The AP2/EREBP family transcription factors play important roles in a wide range of stress tolerance and hormone signaling. In this study, a heat-inducible rice ERF gene was isolated and functionally characterized. The OsERF115/AP2EREBP110 was categorized to Group-IIIc of the rice AP2/EREBP family and strongly induced by heat and drought treatment. The OsERF115/AP2EREBP110 protein targeted to nuclei and suppressed the ABA-induced transcriptional activation of Rab16A promoter in rice protoplasts. Overexpression of OsERF115/AP2EREBP110 enhanced thermotolerance of seeds and vegetative growth stage plants. The OsERF115/AP2EREBP110 overexpressing (OE) plants exhibited higher proline level and increased expression of a proline biosynthesis P5CS1 gene. Phenotyping of water use dynamics of the individual plant indicates that the OsERF115/AP2EREBP110-OE plant exhibited better water saving traits under heat and drought combined stress. Our combined results suggest the potential use of OsERF115/AP2EREBP110 as a candidate gene for genetic engineering approaches to develop heat and drought stress-tolerant crops.

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Ways into Understanding HIF Inhibition

Cancers ◽

10.3390/cancers13010159 ◽

2021 ◽

Vol 13 (1) ◽

pp. 159

Author(s):

Tina Schönberger ◽

Joachim Fandrey ◽

Katrin Prost-Fingerle

Keyword(s):

Protein Interactions ◽

Target Genes ◽

Protein Protein Interactions ◽

Low Oxygen ◽

Drug Candidates ◽

Open Questions ◽

Wide Range ◽

Hif Pathway

Hypoxia is a key characteristic of tumor tissue. Cancer cells adapt to low oxygen by activating hypoxia-inducible factors (HIFs), ensuring their survival and continued growth despite this hostile environment. Therefore, the inhibition of HIFs and their target genes is a promising and emerging field of cancer research. Several drug candidates target protein–protein interactions or transcription mechanisms of the HIF pathway in order to interfere with activation of this pathway, which is deregulated in a wide range of solid and liquid cancers. Although some inhibitors are already in clinical trials, open questions remain with respect to their modes of action. New imaging technologies using luminescent and fluorescent methods or nanobodies to complement widely used approaches such as chromatin immunoprecipitation may help to answer some of these questions. In this review, we aim to summarize current inhibitor classes targeting the HIF pathway and to provide an overview of in vitro and in vivo techniques that could improve the understanding of inhibitor mechanisms. Unravelling the distinct principles regarding how inhibitors work is an indispensable step for efficient clinical applications and safety of anticancer compounds.

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

Molecular and Cellular Biology ◽

10.1128/mcb.14.9.6021-6029.1994 ◽

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.

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Elucidating Protein-protein Interactions Through Computational Approaches and Designing Small Molecule Inhibitors Against them for Various Diseases

Current Topics in Medicinal Chemistry ◽

10.2174/1568026618666181025114903 ◽

2018 ◽

Vol 18 (20) ◽

pp. 1719-1736 ◽

Cited By ~ 3

Author(s):

Sharanya Sarkar ◽

Khushboo Gulati ◽

Manikyaprabhu Kairamkonda ◽

Amit Mishra ◽

Krishna Mohan Poluri

Keyword(s):

Small Molecule ◽

Protein Interactions ◽

Small Molecule Inhibitors ◽

Computational Techniques ◽

Protein Protein Interactions ◽

Computational Tools ◽

Computational Approaches ◽

Protein Protein Interaction ◽

Wide Range ◽

Therapeutic Measures

Background: To carry out wide range of cellular functionalities, proteins often associate with one or more proteins in a phenomenon known as Protein-Protein Interaction (PPI). Experimental and computational approaches were applied on PPIs in order to determine the interacting partners, and also to understand how an abnormality in such interactions can become the principle cause of a disease. Objective: This review aims to elucidate the case studies where PPIs involved in various human diseases have been proven or validated with computational techniques, and also to elucidate how small molecule inhibitors of PPIs have been designed computationally to act as effective therapeutic measures against certain diseases. Results: Computational techniques to predict PPIs are emerging rapidly in the modern day. They not only help in predicting new PPIs, but also generate outputs that substantiate the experimentally determined results. Moreover, computation has aided in the designing of novel inhibitor molecules disrupting the PPIs. Some of them are already being tested in the clinical trials. Conclusion: This review delineated the classification of computational tools that are essential to investigate PPIs. Furthermore, the review shed light on how indispensable computational tools have become in the field of medicine to analyze the interaction networks and to design novel inhibitors efficiently against dreadful diseases in a shorter time span.

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Metallocluster transactions: dynamic protein interactions guide the biosynthesis of Fe–S clusters in bacteria

Biochemical Society Transactions ◽

10.1042/bst20180365 ◽

2018 ◽

Vol 46 (6) ◽

pp. 1593-1603 ◽

Cited By ~ 9

Author(s):

Chenkang Zheng ◽

Patricia C. Dos Santos

Keyword(s):

Protein Interactions ◽

Protein Complexes ◽

Specific Protein ◽

Biological Synthesis ◽

Cluster Assembly ◽

Sequence Motifs ◽

Protein Protein Interactions ◽

Cysteine Desulfurase ◽

Wide Range ◽

Domains Of Life

Iron–sulfur (Fe–S) clusters are ubiquitous cofactors present in all domains of life. The chemistries catalyzed by these inorganic cofactors are diverse and their associated enzymes are involved in many cellular processes. Despite the wide range of structures reported for Fe–S clusters inserted into proteins, the biological synthesis of all Fe–S clusters starts with the assembly of simple units of 2Fe–2S and 4Fe–4S clusters. Several systems have been associated with the formation of Fe–S clusters in bacteria with varying phylogenetic origins and number of biosynthetic and regulatory components. All systems, however, construct Fe–S clusters through a similar biosynthetic scheme involving three main steps: (1) sulfur activation by a cysteine desulfurase, (2) cluster assembly by a scaffold protein, and (3) guided delivery of Fe–S units to either final acceptors or biosynthetic enzymes involved in the formation of complex metalloclusters. Another unifying feature on the biological formation of Fe–S clusters in bacteria is that these systems are tightly regulated by a network of protein interactions. Thus, the formation of transient protein complexes among biosynthetic components allows for the direct transfer of reactive sulfur and Fe–S intermediates preventing oxygen damage and reactions with non-physiological targets. Recent studies revealed the importance of reciprocal signature sequence motifs that enable specific protein–protein interactions and consequently guide the transactions between physiological donors and acceptors. Such findings provide insights into strategies used by bacteria to regulate the flow of reactive intermediates and provide protein barcodes to uncover yet-unidentified cellular components involved in Fe–S metabolism.

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Cytosolic localization and in vitro assembly of human de novo thymidylate synthesis complex

10.1101/2020.12.23.423904 ◽

2020 ◽

Author(s):

Sharon Spizzichino ◽

Dalila Boi ◽

Giovanna Boumis ◽

Roberta Lucchi ◽

Francesca R. Liberati ◽

...

Keyword(s):

Cancer Cells ◽

Protein Interactions ◽

De Novo ◽

Proximity Ligation Assay ◽

Protein Protein Interactions ◽

Aggregation State ◽

Entire Complex ◽

The Individual ◽

Thymidylate Synthesis

ABSTRACTDe novo thymidylate synthesis is a crucial pathway for normal and cancer cells. Deoxythymidine monophosphate (dTMP) is synthesized by the combined action of three enzymes: thymidylate synthase (TYMS), serine hydroxymethyltransferase (SHMT) and dihydrofolate reductase (DHFR), targets of widely used chemotherapeutics such as antifolates and 5-fluorouracil. These proteins translocate to the nucleus after SUMOylation and are suggested to assemble in this compartment into the thymidylate synthesis complex (dTMP-SC). We report the intracellular dynamics of the complex in lung cancer cells by in situ proximity ligation assay, showing that it is also detected in the cytoplasm. We have successfully assembled the dTMP synthesis complex in vitro, employing tetrameric SHMT1 and a bifunctional chimeric enzyme comprising human TYMS and DHFR. We show that the SHMT1 tetrameric state is required for efficient complex assembly, indicating that this aggregation state is evolutionary selected in eukaryotes to optimize protein-protein interactions. Lastly, our results on the activity of the complete thymidylate cycle in vitro, provide a useful tool to develop drugs targeting the entire complex instead of the individual components.

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Practical Model Selection for Prospective Virtual Screening

10.1101/337956 ◽

2018 ◽

Cited By ~ 1

Author(s):

Shengchao Liu ◽

Moayad Alnammi ◽

Spencer S. Ericksen ◽

Andrew F. Voter ◽

Gene E. Ananiev ◽

...

Keyword(s):

Random Forest ◽

Virtual Screening ◽

Protein Interactions ◽

High Throughput Screening ◽

Screening Methods ◽

Protein Protein Interactions ◽

Screening Algorithm ◽

Screening Performance ◽

Wide Range ◽

Public Datasets

AbstractVirtual (computational) high-throughput screening provides a strategy for prioritizing compounds for experimental screens, but the choice of virtual screening algorithm depends on the dataset and evaluation strategy. We consider a wide range of ligand-based machine learning and docking-based approaches for virtual screening on two protein-protein interactions, PriA-SSB and RMI-FANCM, and present a strategy for choosing which algorithm is best for prospective compound prioritization. Our workflow identifies a random forest as the best algorithm for these targets over more sophisticated neural network-based models. The top 250 predictions from our selected random forest recover 37 of the 54 active compounds from a library of 22,434 new molecules assayed on PriA-SSB. We show that virtual screening methods that perform well in public datasets and synthetic benchmarks, like multi-task neural networks, may not always translate to prospective screening performance on a specific assay of interest.

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