New perceptions of transcription factor properties from NMR

1998 ◽  
Vol 76 (2-3) ◽  
pp. 368-378 ◽  
Author(s):  
Stefan Bagby ◽  
Cheryl H Arrowsmith ◽  
Mitsuhiko Ikura
Keyword(s):  
Transcription Factor ◽  
Protein Interactions ◽  
Dna Interaction ◽  
Protein Protein Interactions ◽  
Nmr Studies ◽  
X Ray ◽  
X Ray Crystallography ◽  
Protein Protein Interaction ◽  
Structural Problems ◽  
Induced Folding

The complementarity of NMR and X-ray crystallography for biomacromolecular studies has been particularly evident in analysis of transcription factor structures and interactions. While X-ray crystallography can be used to tackle relatively complicated structural problems including multicomponent (three and higher) complexes, NMR studies have provided new insights into the nature of protein-DNA and protein-protein interactions that would be difficult to obtain by other biophysical methods. We describe herein some of the novel and important information recently derived from NMR studies of transcription factors.Key words: protein-DNA interaction, protein-protein interaction, induced folding, conformational fluctuations, transcriptional regulation.

Decoding Protein-protein Interactions: An Overview

2020 ◽  
Vol 20 (10) ◽  
pp. 855-882
Author(s):  
Olivia Slater ◽  
Bethany Miller ◽  
Maria Kontoyianni
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Drug Repurposing ◽  
Protein Docking ◽  
Target Space ◽  
Protein Protein Interactions ◽  
X Ray Crystallography ◽  
Protein Protein Interaction ◽  
Interaction Sites ◽  
Long Time

Drug discovery has focused on the paradigm “one drug, one target” for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

Regulative interactions of the osmosensing C-terminal domain in the trimeric glycine betaine transporter BetP from Corynebacterium glutamicum

2009 ◽  
Vol 390 (8) ◽  
Author(s):  
Reinhard Krämer ◽  
Christine Ziegler
Keyword(s):  
Amino Acid ◽  
Corynebacterium Glutamicum ◽  
Protein Interactions ◽  
Regulation Mechanism ◽  
Protein Protein Interactions ◽  
Molecular Switching ◽  
X Ray ◽  
X Ray Crystallography ◽  
Terminal Domain ◽  
Domain Reorientation

Abstract Activation of the osmoregulated trimeric betaine transporter BetP from Corynebacterium glutamicum was shown to depend mainly on the correct folding and integrity of its 55 amino acid long, partly α-helical C-terminal domain. Reorientation of the three C-terminal domains in the BetP trimer indicates different lipid-protein and protein-protein interactions of the C-terminal domain during osmoregulation. A regulation mechanism is suggested where this domain switches the transporter from the inactive to the active state. Interpretation of recently obtained electron and X-ray crystallography data of BetP led to a structure-function based model of C-terminal molecular switching involved in osmoregulation.

scholarly journals The TCP transcription factor HvTB2 heterodimerizes with VRS5(HvTB1) and controls spike architecture in barley

2021 ◽  
Author(s):  
Tatiana de Souza Moraes ◽  
Sam W. van Es ◽  
Inmaculada Hernández-Pinzón ◽  
Gwendolyn K. Kirschner ◽  
Froukje van der Wal ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Plant Architecture ◽  
Transcriptional Regulators ◽  
Class Ii ◽  
Barley Plant ◽  
Cereal Crop ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction

AbstractBarley is the fourth largest cereal crop grown worldwide, and essential for food and feed production. Phenotypically, the barley spike, which is unbranched, occurs in two main architectural shapes: two-rowed or six-rowed. In the 6-rowed cultivars, all three florets of the triple floret meristem develop into seeds while in 2-rowed lines only the central floret forms a seed. VRS5(HvTB1), act as inhibitor of lateral seed outgrowth and vrs5(hvtb1) mutants display a six-rowed spike architecture. VRS5(HvTB1) is a member of the TCP transcription factor (TF) family, which often form protein-protein interactions with other transcriptional regulators to modulate the expression of their target genes.Despite the key role of VRS5(HvTB1) in regulating barley plant architecture, there is hardly any knowledge on its molecular mode-of-action. We performed an extensive phylogenetic analysis of the TCP transcription factor family, followed by an in-vitro protein-protein interaction study using yeast-two-hybrid. Our analysis shows that VRS5(HvTB1) has a diverse interaction capacity, interacting with class II TCP’s, NF-Y TF, but also chromatin modellers. Further analysis of the interaction capacity of VRS5(HvTB1) with other TCP TFs shows that VRS5(HvTB1) preferably interacts with other class II TCP TFs within the TB1 clade. One of these interactors, encoded by HvTB2, shows a similar expression pattern when compared to VRS5(HvTB1). Haplotype analysis of HvTB2 suggest that this gene is highly conserved and shows hardly any variation in cultivars or wild barley. Induced mutations in HvTB2 trough CRISPR-CAS9 mutagenesis in cv. Golden Promise resulted in barley plants that lost their characteristic unbranched spike architecture. hvtb2 mutants exhibited branches arising at the main spike, suggesting that, similar to VRS5(HvTB1), HvTB2 act as inhibitor of branching. Taken together, our protein-protein interaction studies of VRS5(HvTB1) resulted in the identification of HvTB2, another key regulator of spike architecture in barley. Understanding the molecular network, including protein-protein interactions, of key regulators of plant architecture such as VRS5(HvTB1) provide new routes towards the identification of other key regulators of plant architecture in barley.Author summaryTranscriptional regulation is one of the basic molecular processes that drives plant growth and development. The key TCP transcriptional regulator TEOSINTE BRANCHED 1 (TB1) is one of these key regulators that has been targeted during domestication of several crops for its role as modulator of branching. Also in barley, a key cereal crop, HvTB1 (also referred to as VRS5), inhibits the outgrowth or side shoots, or tillers, and seeds. Despite its key role in barley development, there is hardly any knowledge on the molecular network that is utilized by VRS5(HvTB1). Transcriptional regulators form homo- and heterodimers to regulate the expression of their downstream targets. Here, we performed an extensive phylogenetic analysis of TCP transcription factors (TFs) in barley, followed by protein-protein interaction studies of VRS5(HvTB1). Our analysis indicates, that VRS5(HvTB1) has a diverse capacity of interacting with class II TCPs, NF-Y TF, but also chromatin modellers. Induced mutagenesis trough CRISPR-CAS mutagenesis of one of the putative VRS5(HvTB1) interactors, HvTB2, resulted in barley plants with branched spikes. This shows that insight into the VRS5(HvTB1) interactome, followed by detailed functional analysis of potential interactors is essential to truly understand how TCPs modulate plant architecture. The study presented here provides a first step to underpin the protein-protein interactome of VRS5(HvTB1) and identify other, yet unknown, key regulators of barley plant architecture.

The human androgen receptor AF1 transactivation domain: interactions with transcription factor IIF and molten-globule-like structural characteristics

2006 ◽  
Vol 34 (6) ◽  
pp. 1054-1057 ◽  
Author(s):  
D.N. Lavery ◽  
I.J. McEwan
Keyword(s):  
Transcription Factor ◽  
Androgen Receptor ◽  
Protein Interactions ◽  
Structural Characteristics ◽  
Molten Globule ◽  
Transactivation Domain ◽  
Protein Protein Interactions ◽  
Induced Folding ◽  
Transcription Factor Iif ◽  
Structural Aspects

The AR (androgen receptor) is a ligand-activated transcription factor and member of the steroid receptor superfamily. The AR responds to the ligands testosterone and dihydrotestosterone and activates multiple downstream genes required in development and reproduction. During the events of transactivation, the AR makes specific protein–protein interactions with several basal transcription factors such as TBP (TATA-box-binding protein) and TFIIF (transcription factor IIF). These interactions occur predominantly within a defined region termed AF1 (activation function-1) located within the highly disordered N-terminal domain of the receptor. Our focus is on the structural aspects of AF1 and how this flexible and disordered domain generates functional interactions with regulators of transcription. Our working hypothesis is that AR-AF1 domain exhibits induced folding when contacted by transcription regulators (such as TFIIF) into a more compact and ‘active’ conformation, enabling further co-regulator recruitment and ultimately transcription. Structural flexibility and intrinsic disorder of AR-AF1 were studied using predictive algorithms and fluorescence spectroscopy under different experimental conditions and the results revealed this domain retains characteristics indicative of molten-globule or pre-molten-globule-like structures. We hypothesize that this partially folded intermediate state is important for, and enables the AF1 domain to make, multiple protein–protein interactions. The structural aspects of AR-AF1 and interactions with TFIIF are discussed.

scholarly journals Identification of β-Strand Mediated Protein-Protein Interaction Inhibitors Using Ligand-Directed Fragment Ligation

2020 ◽  
Author(s):  
Zsófia Hegedüs Zsófia Hegedüs ◽  
Fruzsina Hobor ◽  
Deborah K. Shoemark ◽  
sergio Celis ◽  
Lu-Yun Lian ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Electrostatic Interactions ◽  
Significant Proportion ◽  
Selective Inhibition ◽  
Peptide Sequence ◽  
Protein Protein Interactions ◽  
X Ray Crystallography ◽  
Protein Protein Interaction ◽  
Ligand Discovery ◽  
Dynamics Simulations

β-Strand mediated protein-protein interactions (PPIs) represent underexploited targets for chemical probe development despite representing a significant proportion of known and therapeutically relevant PPI targets. β-strand mimicry is challenging given that both amino acid side-chains and backbone hydrogen-bonds are typically required for molecular recognition, yet these are oriented along perpendicular vectors. This paper describes an alternative approach using GKAP/SHANK1 PDZ as a model and dynamic ligation screening to identify small-molecule replacements for tranches of peptide sequence. A peptide truncation of GKAP functionalized at the N- and C-termini with acylhydrazone groups was used as an anchor. Reversible acylhydrazone bond exchange with a library of aldehyde fragments in the presence of the protein as template and <i>in situ</i> screening using a fluorescence anisotropy (FA) assay identified peptide hybrid hits with comparable affinity to the GKAP peptide binding sequence. Identified hits were validated using FA, ITC, NMR and X-ray crystallography to confirm selective inhibition of the target PDZ-mediated PPI and mode of binding. These analyses together with molecular dynamics simulations demonstrated the ligands make transient interactions with an unoccupied basic patch through electrostatic interactions, establishing proof-of-concept that this unbiased approach to ligand discovery represents a powerful addition to the armory of tools that can be used to identify PPI modulators.

scholarly journals Copper(I)-mediated protein–protein interactions result from suboptimal interaction surfaces

2009 ◽  
Vol 422 (1) ◽  
pp. 37-42 ◽  
Author(s):  
Lucia Banci ◽  
Ivano Bertini ◽  
Vito Calderone ◽  
Nunzia Della-Malva ◽  
Isabella C. Felli ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Metal Binding ◽  
Site Directed Mutagenesis ◽  
Protein Protein Interactions ◽  
X Ray ◽  
X Ray Crystallography ◽  
Metal Binding Domain ◽  
Modelling Techniques ◽  
Cellular Pathways ◽  
P Type

The homoeostasis of metal ions in cells is the result of the contribution of several cellular pathways that involve transient, often weak, protein–protein interactions. Metal transfer typically implies the formation of adducts where the metal itself acts as a bridge between proteins, by co-ordinating residues of both interacting partners. In the present study we address the interaction between the human copper(I)-chaperone HAH1 (human ATX1 homologue) and a metal-binding domain in one of its partners, namely the P-type copper-transporting ATPase, ATP7A (ATPase, Cu+ transporting, α polypeptide). The adduct was structurally characterized in solution, in the presence of copper(I), and through X-ray crystallography, upon replacing copper(I) with cadmium(II). Further insight was obtained through molecular modelling techniques and site-directed mutagenesis. It was found that the interaction involves a relatively small interface (less than 1000 Å2, 1 Å=0.1 nm) with a low fraction of non-polar atoms. These observations provide a possible explanation for the low affinity of the two apoproteins. It appears that electrostatics is important in selecting which domain of the ATPase is able to form detectable amounts of the metal-mediated adduct with HAH1.

scholarly journals Characterization of known protein complexes using k-connectivity and other topological measures

F1000Research ◽  
2015 ◽  
Vol 2 ◽  
pp. 172
Author(s):  
Suzanne R Gallagher ◽  
Debra S Goldberg
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Clustering Coefficient ◽  
Edge Density ◽  
Protein Protein Interactions ◽  
X Ray Crystallography ◽  
Protein Protein Interaction ◽  
Unknown Protein ◽  
Topological Measures

Many protein complexes are densely packed, so proteins within complexes often interact with several other proteins in the complex. Steric constraints prevent most proteins from simultaneously binding more than a handful of other proteins, regardless of the number of proteins in the complex. Because of this, as complex size increases, several measures of the complex decrease within protein-protein interaction networks. However, k-connectivity, the number of vertices or edges that need to be removed in order to disconnect a graph, may be consistently high for protein complexes. The property of k-connectivity has been little used previously in the investigation of protein-protein interactions. To understand the discriminative power of k-connectivity and other topological measures for identifying unknown protein complexes, we characterized these properties in known Saccharomyces cerevisiae protein complexes in networks generated both from highly accurate X-ray crystallography experiments which give an accurate model of each complex, and also as the complexes appear in high-throughput yeast 2-hybrid studies in which new complexes may be discovered. We also computed these properties for appropriate random subgraphs.We found that clustering coefficient, mutual clustering coefficient, and k-connectivity are better indicators of known protein complexes than edge density, degree, or betweenness. This suggests new directions for future protein complex-finding algorithms.

scholarly journals Characterization of known protein complexes using k-connectivity and other topological measures

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 172 ◽  
Author(s):  
Suzanne R Gallagher ◽  
Debra S Goldberg
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Clustering Coefficient ◽  
Edge Density ◽  
Protein Protein Interactions ◽  
X Ray Crystallography ◽  
Protein Protein Interaction ◽  
Unknown Protein ◽  
Topological Measures

Many protein complexes are densely packed, so proteins within complexes often interact with several other proteins in the complex. Steric constraints prevent most proteins from simultaneously binding more than a handful of other proteins, regardless of the number of proteins in the complex. Because of this, as complex size increases, several measures of the complex decrease within protein-protein interaction networks. However, k-connectivity, the number of vertices or edges that need to be removed in order to disconnect a graph, may be consistently high for protein complexes. The property of k-connectivity has been little used previously in the investigation of protein-protein interactions. To understand the discriminative power of k-connectivity and other topological measures for identifying unknown protein complexes, we characterized these properties in known Saccharomyces cerevisiae protein complexes in networks generated both from highly accurate X-ray crystallography experiments which give an accurate model of each complex, and also as the complexes appear in high-throughput yeast 2-hybrid studies in which new complexes may be discovered. We also computed these properties for appropriate random subgraphs. We found that clustering coefficient, mutual clustering coefficient, and k-connectivity are better indicators of known protein complexes than edge density, degree, or betweenness. This suggests new directions for future protein complex-finding algorithms.

scholarly journals Identification of β-Strand Mediated Protein-Protein Interaction Inhibitors Using Ligand-Directed Fragment Ligation

2020 ◽  
Author(s):  
Zsófia Hegedüs Zsófia Hegedüs ◽  
Fruzsina Hobor ◽  
Deborah K. Shoemark ◽  
sergio Celis ◽  
Lu-Yun Lian ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Electrostatic Interactions ◽  
Significant Proportion ◽  
Selective Inhibition ◽  
Peptide Sequence ◽  
Protein Protein Interactions ◽  
X Ray Crystallography ◽  
Protein Protein Interaction ◽  
Ligand Discovery ◽  
Dynamics Simulations

β-Strand mediated protein-protein interactions (PPIs) represent underexploited targets for chemical probe development despite representing a significant proportion of known and therapeutically relevant PPI targets. β-strand mimicry is challenging given that both amino acid side-chains and backbone hydrogen-bonds are typically required for molecular recognition, yet these are oriented along perpendicular vectors. This paper describes an alternative approach using GKAP/SHANK1 PDZ as a model and dynamic ligation screening to identify small-molecule replacements for tranches of peptide sequence. A peptide truncation of GKAP functionalized at the N- and C-termini with acylhydrazone groups was used as an anchor. Reversible acylhydrazone bond exchange with a library of aldehyde fragments in the presence of the protein as template and <i>in situ</i> screening using a fluorescence anisotropy (FA) assay identified peptide hybrid hits with comparable affinity to the GKAP peptide binding sequence. Identified hits were validated using FA, ITC, NMR and X-ray crystallography to confirm selective inhibition of the target PDZ-mediated PPI and mode of binding. These analyses together with molecular dynamics simulations demonstrated the ligands make transient interactions with an unoccupied basic patch through electrostatic interactions, establishing proof-of-concept that this unbiased approach to ligand discovery represents a powerful addition to the armory of tools that can be used to identify PPI modulators.

An efficient transient assays system using Agrobacterium-mediated transformation of onion (Allium cepa) epidermal cells

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Yu-Miao Zhang ◽  
Jun Wang ◽  
Tao Wu
Keyword(s):  
Subcellular Localization ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Epidermal Cells ◽  
Cyclin Dependent Kinase ◽  
Protein Subcellular Localization ◽  
Protein Protein Interactions ◽  
Efficient System ◽  
Protein Protein Interaction ◽  
Onion Epidermal Cells

In this study, the Agrobacterium infection medium, infection duration, detergent, and cell density were optimized. The sorghum-based infection medium (SbIM), 10-20 min infection time, addition of 0.01% Silwet L-77, and Agrobacterium optical density at 600 nm (OD600), improved the competence of onion epidermal cells to support Agrobacterium infection at >90% efficiency. Cyclin-dependent kinase D-2 (CDKD-2) and cytochrome c-type biogenesis protein (CYCH), protein-protein interactions were localized. The optimized procedure is a quick and efficient system for examining protein subcellular localization and protein-protein interaction.

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