Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “interactomics”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10Linked to original sources
PubMed2024

MX2 forms nucleoporin-comprising cytoplasmic biomolecular condensates that lure viral capsids.

Human myxovirus resistance 2 (MX2) can restrict HIV-1 and herpesviruses at a post-entry step through a process requiring an interaction between MX2 and the viral capsids. The involvement of other host cell factors, however, remains poorly understood. Here, we mapped the proximity interactome of MX2, revealing strong enrichment of phenylalanine-glycine (FG)-rich proteins related to the nuclear pore complex as well as proteins that are part of cytoplasmic ribonucleoprotein granules. MX2 interacted with these proteins to form multiprotein cytoplasmic biomolecular condensates that were essential for its anti-HIV-1 and anti-herpes simplex virus 1 (HSV-1) activity. MX2 condensate formation required the disordered N-terminal region and MX2 dimerization. Incoming HIV-1 and HSV-1 capsids associated with MX2 at these dynamic cytoplasmic biomolecular condensates, preventing nuclear entry of their viral genomes. Thus, MX2 forms cytoplasmic condensates that likely act as nuclear pore decoys, trapping capsids and inducing premature viral genome release to interfere with nuclear targeting of HIV-1 and HSV-1.

Humans↗
PubMed2026

Characterization of a Ku-binding motif in the C-terminal region of RAG2.

We applied an unsupervised interactome analysis with the RAG2 C-terminal region (R2CT) in v-abl pro-B cells undergoing V(D)J recombination. Mass-spectrometry analyses showed that Ku70 and Ku80 were among the top 10 hits. To further strengthen these observations, we performed Proximity Ligation Assay (PLA) and characterize the existence of a GFP-R2CT-Ku complex formation in cellulo. The interaction of several partners with Ku70/80 (Ku) through Ku-binding motifs (KBMs) in their sequences governs their enrolment in NHEJ repair complexes. Through sequence analysis, we identified a KBM within R2CT (R-KBM, amino acids 589-527). We confirmed by calorimetry a specific micromolar interaction between this RAG2 region and Ku70/80/DNA complex. The RAG2 motif KBM can be subdivided in two conserved parts that have no interaction individually. AlphaFold2 prediction coupled with molecular dynamic simulations indicate that the C-terminal part of the RAG2 motif interacts with Ku80 on the same site than the NHEJ factor XLF. These in silico analyses indicated that the N-terminal part of the RAG2 motif interacts with DNA adjacent to Ku with a major role of the K503 residue in agreement with disruption of the interaction observed with the K503E mutant. This study further extends the large ensemble of proteins recruited at DSBs by KBM motifs and substantiates the model of a tight coupling between DNA breakage and repair during V(D)J recombination, mediated by the Ku-RAG2 C-terminus interaction.

Ku Autoantigen↗
PubMed2006

Molecular basis of human Usher syndrome: deciphering the meshes of the Usher protein network provides insights into the pathomechanisms of the Usher disease.

Usher syndrome (USH) is the most frequent cause of combined deaf-blindness in man. It is clinically and genetically heterogeneous and at least 12 chromosomal loci are assigned to three clinical USH types, namely USH1A-G, USH2A-C, USH3A (Davenport, S.L.H., Omenn, G.S., 1977. The heterogeneity of Usher syndrome. Vth Int. Conf. Birth Defects, Montreal; Petit, C., 2001. Usher syndrome: from genetics to pathogenesis. Annu. Rev. Genomics Hum. Genet. 2, 271-297). Mutations in USH type 1 genes cause the most severe form of USH. In USH1 patients, congenital deafness is combined with a pre-pubertal onset of retinitis pigmentosa (RP) and severe vestibular dysfunctions. Those with USH2 have moderate to severe congenital hearing loss, non-vestibular dysfunction and a later onset of RP. USH3 is characterized by variable RP and vestibular dysfunction combined with progressive hearing loss. The gene products of eight identified USH genes belong to different protein classes and families. There are five known USH1 molecules: the molecular motor myosin VIIa (USH1B); the two cell-cell adhesion cadherin proteins, cadherin 23 (USH1D) and protocadherin 15, (USH1F) and the scaffold proteins, harmonin (USH1C) and SANS (USH1G). In addition, two USH2 genes and one USH3A gene have been identified. The two USH2 genes code for the transmembrane protein USH2A, also termed USH2A ("usherin") and the G-protein-coupled 7-transmembrane receptor VLGR1b (USH2C), respectively, whereas the USH3A gene encodes clarin-1, a member of the clarin family which exhibits 4-transmembrane domains. Molecular analysis of USH1 protein function revealed that all five USH1 proteins are integrated into a protein network via binding to PDZ domains in the USH1C protein harmonin. Furthermore, this scaffold function of harmonin is supported by the USH1G protein SANS. Recently, we have shown that the USH2 proteins USH2A and VLGR1b as well as the candidate for USH2B, the sodium bicarbonate co-transporter NBC3, are also integrated into this USH protein network. In the inner ear, these interactions are essential for the differentiation of hair cell stereocilia but may also participate in the mechano-electrical signal transduction and the synaptic function of maturated hair cells. In the retina, the co-expression of all USH1 and USH2 proteins at the synapse of photoreceptor cells indicates that they are organized in an USH protein network there. The identification of the USH protein network indicates a common pathophysiological pathway in USH. Dysfunction or absence of any of the molecules in the mutual "interactome" related to the USH disease may lead to disruption of the network causing senso-neuronal degeneration in the inner ear and the retina, the clinical symptoms of USH.

Adaptor Proteins, Signal Transducing↗
PubMed2005

Non-coding RNAs: new players in eukaryotic biology.

The completion of the human, mouse and other eukaryotic genomes were important scientific milestones, but they were just small steps towards the understanding of eukaryotic biology. Recent transcriptome analysis and different experimental approaches have identified a surprisingly large number of non-coding RNAs (ncRNAs) in eukaryotic cells. ncRNAs comprise microRNAs, anti-sense transcripts and other Transcriptional Units containing a high density of stop codons and lacking any extensive "Open Reading Frame". They have been shown to regulate gene expression by novel mechanisms such as RNA interference, gene co-suppression, gene silencing, imprinting and DNA demethylation. It is becoming clear that these novel RNAs perform critical functions during development and cell differentiation. There is also mounting evidence of their involvement in cancer and neurological diseases. Together, all this information indicates that ncRNAs are emerging as a new class of functional transcripts in eukaryotes. Therefore, great challenges lie in the years ahead: understanding the molecular biology of higher organisms will require revealing all proteins (Proteome), all ncRNAs (RNome) and their interactions (Interactome) in the complex molecular scenario within eukaryotic cells.

Animals↗
PubMed2004

Proteomics techniques for cystic fibrosis research.

Numerous factors, other than mutations in the CFTR gene, affect the phenotypic variability of cystic fibrosis (CF). With a two-dimensional electrophoresis (2-DE) analysis of total protein expression profiles (proteomics) of CF versus non-CF cells it is possible to obtain an integrative picture of CF cellular alterations. Through this approach, proteins that interact differently with wild type- and mutant-CFTR can also be identified (interactomics). This can provide insight into CF pathophysiology as well as clues for novel therapeutic targets. Additionally, protein profiling can ultimately identify novel disease markers with the potential for a CF diagnosis not based on the analysis of CFTR gene.

Clinical Laboratory Techniques↗
PubMed2006

Co-evolutionary analysis of domains in interacting proteins reveals insights into domain-domain interactions mediating protein-protein interactions.

Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein-protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the non-interacting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain-domain interactions. Given a protein-protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain-domain interactions, and used known domain-domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain-domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites.

Amino Acid Sequence↗
PubMed2024

An Intrinsically Disordered RNA Binding Protein Modulates mRNA Translation and Storage.

Proteins with intrinsically disordered regions (IDR) play diverse functions in regulating gene expression in the cell. Many of these proteins interact with cytoplasmic ribosomes. However, the molecular functions related to the interactions are largely unclear. In this study, using an abundant RNA-binding protein, Sbp1, with a structurally well-defined RNA recognition motif and an intrinsically disordered RGG domain as a model system, we investigated how an RNA binding protein with IDR modulates mRNA storage and translation. Using genomic and molecular approaches, we show that Sbp1 slows ribosome movement on cellular mRNAs and promotes polysome stacking or aggregation. Sbp1-associated polysomes display a ring-shaped structure in addition to a beads-on-string morphology visualized under the electron microscope, likely to be an intermediate slow translation state between actively translating polysomes and the translation-sequestered RNA granule. Moreover, the binding of Sbp1 to the 5'UTRs of mRNAs represses both cap-dependent and cap-independent translation initiation of proteins, many are functionally important for general protein synthesis in the cell. Finally, post-translational modifications at the arginine in the RGG motif change the Sbp1 protein interactome and play important roles in directing cellular mRNAs to either translation or storage. Taken together, our study demonstrates that under physiological conditions, intrinsically disordered RNA binding proteins promote polysome aggregation and regulate mRNA translation and storage using multiple distinctive mechanisms. This research also establishes a framework with which functions of other IDR-containing proteins can be investigated and defined.

RNA-Binding Proteins↗
PubMed2026

Proteome-wide Ubiquitinome Profiling Reveals Substrate-specific Dynamics Within the USP7 Network.

USP7 is a pleiotropic deubiquitylating enzyme that is involved in tumor suppression, (neuro) development, chromatin regulation and the DNA damage response. How USP7 regulates these diverse pathways is still unclear. Here, we report data-independent acquisition and label free quantitation mass spectrometry to profile the proteome-wide impact of USP7 on substrate de-ubiquitylation and overall protein abundance. First, we identified proteins associated with endogenous USP7 by immunopurification followed by data-independent acquisition and label free quantitation mass spectrometry. Integration of our new results with earlier interactomes of epitope-tagged USP7 yielded a consensus set of high-confidence protein targets. Domain mapping analysis revealed that, in addition to the TRAF domain, the ubiquitin-like domains of USP7 play a key role in substrate selection. Using specific enrichment of tryptic K-ε-GG peptides, we mapped proteome-wide changes in ubiquitinome dynamics following inhibition of USP7. Combining unbiased proteome-wide and targeted quantitative mass spectrometry revealed that deubiquitylation by USP7 can have different effects on the stability of distinct substrates, and suggests that USP7's activity profile is substrate-dependent rather than an intrinsic enzymatic property. Thus, in addition to providing a proteome-wide map of USP7 target sites, our multi-angle proteomics approach reveals that the effects of USP7-mediated deubiquitylation on its targets are remarkably variable and substrate-specific. Finally, based on these detailed molecular insights we show how USP7 connects various neurodevelopmental syndromes and tumor suppression pathways.

Ubiquitin-Specific Peptidase 7↗
PubMed2006

Efficient inefficiency: biochemical "junk" may represent molecular bridesmaids awaiting emergent function as a buffer against environmental fluctuation.

The biochemical function of many parts of the genome, transcriptome, proteome, and interactome remain largely unknown. We propose that portions of these fundamental building blocks of life have no current biochemical function per se. Rather, sections of these "omes" may contribute to an inventory of biochemical parts and circuits that participate in the development of emergent functions. Low fidelity deoxyribonucleic acid replication, transcription, translation, and post-translational modification all represent potential mechanisms to produce an inventory of parts. Stochastic processes that influence the conformations of ribonucleic acid molecules and proteins may also contribute to potential biochemical inventory. Some components of the biochemical inventory may enable future adaptations, some may produce disease, and some may remain useless. The function of many of these components await discovery, not by science, but by evolution. While carrying such purposeless biochemical units may appear to dilute fitness by exacting a thermodynamic cost, we argue that net fitness becomes enhanced when considering the value for potential future innovations. One can envision components that intermingle, interact, and act out mock pathways, but in most cases remain molecular bridesmaids. Given sufficiently low thermodynamic cost, such stochastic cycling may persist until a markedly advantageous or cataclysmically disadvantageous trait emerges. Maladaptive screening and utilization of inventory content can lead to disease phenotypes, a process buffered and regulated in part by the heat shock protein and stress response network. Whereas failure of the ubiquitin pathway to recycle misfolded proteins has become increasingly recognized as a source of disease, protein misfolding may itself represent one step in a process that maximizes functional innovation through increasing proteomic diversity. Fractal correlates of these processes occur at the organizational level of cells and organisms. That the abnormal accumulation of units induces local collapse may serve to limit the extension of damage to the greater system at large. The immune and cognitive systems that selectively sample and prune environmental content may serve as additional portals for innovation.

Adaptation, Physiological↗
PubMed2004

Hot spots for modulating toxicity identified by genomic phenotyping and localization mapping.

DNA repair and checkpoint pathways protect against carcinogen-induced toxicity. Here, we describe additional, equally protective pathways discovered by interrogating 4,733 yeast proteins for their ability to diminish toxicity induced by four known carcinogens. A computational mapping strategy for global phenotypic data was developed to build a systems toxicology model detailing recovery from carcinogen exposure and identifying protein complexes that modulate toxicity. Global phenotypic data were merged with global subcellular localization and protein interactome data to generate an integrated picture of cellular recovery after carcinogen exposure. Statistically validated results from this systems-wide integration demonstrate that, in addition to the nucleus, subnetworks of toxicity-modulating proteins were overrepresented in the vacuolar membrane, endosome, endoplasmic reticulum, and mitochondrion. In addition, we show that many proteins associated with RNA polymerase II, macromolecular trafficking, and vacuole function can now be counted among the many proteins that modulate carcinogen-induced toxicity.

Cell Nucleus↗
PubMed2026

From pan-life phase insights to PhaseHub: Analyzing protein condensate complexity.

Intracellular biomolecular condensation forms multicomponent signaling hubs that regulate development, stress responses, and environmental adaptation. While the molecular grammar encoded within scaffold proteins defines the basal associative features driving condensation, heterotypic condensates are intrinsically dynamic, multicomponent, and far-from-equilibrium systems. Consequently, how condensates organize component composition, stoichiometry, and functional specificity in space and time under physiological conditions remains poorly understood. Addressing this challenge requires integrative frameworks that combine predictive biophysical features with experimental information on protein abundance, interaction networks, subcellular localization, and evolutionary conservation. In this study, we first analyzed phase separation (PS) proteins across the tree of life in 1106 species, revealing a stark contrast in computationally predicted PS propensity between eukaryotes and prokaryotes, with genome size as a key determinant. Through a broad analysis of amino acid homorepeat-containing proteins (HRPs) across all species, we uncovered how PS evolves via a balance between functional condensation and avoidance of harmful, aggregation-prone sequences. We further identified potential signaling hubs and components across kingdoms by integrating PS-positive proteins with experimentally derived abundance and interactome data from four model eukaryotic species. Using Arabidopsis as a model, we dissected the relationships among PS propensity, condensation hub prediction, HRPs, subcellular localization, and structural conservation. Finally, we developed PhaseHub, a user-friendly interface for exploring scaffold-client dynamics, PS components, sequence signatures within each PS protein, and hubs. Collectively, our work provides an evolutionary framework for understanding multicomponent PS hubs by integrating molecular grammar with physiological context, thereby facilitating hypothesis generation and rational design.

Phase Separation↗
PubMed2026

Selenoprotein S associates with complexes governing membrane protein biogenesis and translation-associated processes.

Human selenoprotein S (selenos) is part of the integrated cellular stress response and linked to protein quality control and signaling pathways. Consequently, genetic polymorphisms of selenos are associated with increased risks for diabetes, dyslipidemia, and cardiovascular diseases. Determining the specific roles of selenos in these cellular pathways and diseases has been challenging, as selenos associates with a wide range of protein complexes. Thus, to map the cellular functions of selenos and uncover their interconnections, we used affinity purification and in vivo crosslinking to stabilize transient protein interactions, followed by proteomics to record the resulting selenos interactome. Through mapping of selenos protein partners, we found evidence that selenos associates with complexes responsible for the insertion of membrane proteins into the endoplasmic reticulum (ER) bilayer and their connected quality control components. Furthermore, selenos is also part of metabolic, trafficking, and mitochondrial pathways. Notably, proteins involved in translation preferentially associate with selenos when its C-terminal intrinsically disordered segment containing the redox-active motif is accessible. Together, these results identify the C-terminal redox loop of selenos as a central interaction hub connecting translation with ER membrane protein biogenesis and quality control.

Selenoproteins↗
PubMed2005

A systems biology perspective on protein structural dynamics and signal transduction.

The functional dynamics of signal transduction through protein interaction networks are determined both by network topology and by the signal processing properties of component proteins. In order to understand the emergent properties of signal transduction networks in terms of information processing, storage and decision making, we not only need to map the so-called 'interactome' but, perhaps more importantly, we also have to understand how the structural dynamics of constituent proteins shape non-linear responses through cooperativity and allostery. Several in silico methods have been developed to identify networks of cooperative residues in proteins and help infer their mode of action. Applying this type of analysis to important classes of modular signal transduction domains should, in principle, allow the function of these proteins to be abstracted in terms of their information processing characteristics, permitting better comprehension of the systemic properties of biological networks.

Binding Sites↗
PubMed2006

Target selection for complex structural genomics.

Most cellular processes are carried out by macromolecular assemblies and regulated through a complex network of transient protein-protein interactions. Genome-wide interaction discovery experiments are already delivering the first drafts of whole organism interactomes and, thus, depicting the limits of the interaction space. However, a complete understanding of molecular interactions can only come from high-resolution three-dimensional structures, as they provide key atomic details about the binding interfaces. The launch of structural genomics initiatives focused on protein interactions and complexes could quickly fill up the interaction space with structural details, offering a new perspective on how cell networks operate at atomic level. Clear target selection strategies that rationally identify the key interactions and complexes that should be first tackled are fundamental to maximize the return, minimize the costs and prevent experimental difficulties.

Genomics↗
PubMed2003

How reliable are experimental protein-protein interaction data?

Data of protein-protein interactions provide valuable insight into the molecular networks underlying a living cell. However, their accuracy is often questioned, calling for a rigorous assessment of their reliability. The computation offered here provides an intelligible mean to assess directly the rate of true positives in a data set of experimentally determined interacting protein pairs. We show that the reliability of high-throughput yeast two-hybrid assays is about 50%, and that the size of the yeast interactome is estimated to be 10,000-16,600 interactions.

Protein Binding↗
PubMed2002

Computational methods for the prediction of protein interactions.

Establishing protein interaction networks is crucial for understanding cellular operations. Detailed knowledge of the 'interactome', the full network of protein-protein interactions, in model cellular systems should provide new insights into the structure and properties of these systems. Parallel to the first massive application of experimental techniques to the determination of protein interaction networks and protein complexes, the first computational methods, based on sequence and genomic information, have emerged.

Artificial Gene Fusion↗
PubMed2005

Biological networks and analysis of experimental data in drug discovery.

Cellular life can be represented and studied as the 'interactome'--a dynamic network of biochemical reactions and signaling interactions between active proteins. Systemic networks analysis can be used for the integration and functional interpretation of high-throughput experimental data, which are abundant in drug discovery but currently poorly utilized. The composition and topology of complex networks are closely associated with vital cellular functions, which have important implications for life science research. Here we outline recent advances in the field, available tools and applications of network analysis in drug discovery.

Computer Simulation↗
PubMed2005

Methods to reveal domain networks.

The development and application of high-throughput technology to study protein interactions has led to the construction of complex interaction maps, the correct interpretation of which is crucial to the identification of targets for drug development. Here we propose that a more informative description of protein interaction networks can be achieved by considering explicitly the modular nature of proteins. In this representation, proteins are drawn as covalently linked modular domains binding to their target sites in partner proteins. Families of conserved modules that bind to relatively short peptides mediate a large fraction of the non-covalent interactions linking different proteins in the network. As these interactions are often involved in the propagation of signal transduction, determining the recognition specificity of each domain family member is an essential step toward a functional description of the global interactome.

Peptide Library↗