A scored human protein–protein interaction network to catalyze genomic interpretation

Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus Borup; Horn, Heiko; Mercer, Johnathan; Slodkowicz, Greg; Workman, Christopher T.; Rigina, Olga; Rapacki, Kristoffer; Stærfeldt, Hans Henrik; Brunak, Søren; Jensen, Thomas Skøt; Lage, Kasper

doi:10.1038/nmeth.4083

Cited by 555 publications

(433 citation statements)

References 46 publications

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“…The interaction between nNOS and PSD-95 ensures that nNOS and NMDAR are in close proximity, where Ca 2+ influx under normal conditions leads to NO generation, which is required for further signaling. Screening of a 150 000 compound library identified IC87201 (2-((1H-benzo[d] [1,2,3]triazol-5-ylamino)methyl)-4,6-dichlorophenol) as an inhibitor of the PSD-95/nNOS interaction with an IC 50 of 31 µm. [115][116][117] There has therefore been a keen interest in disrupting the ternary PSD-95/nNOS/NMDAR complex, representing a potential novel mode of action for the treatment of ischemic stroke.…”

Section: Targeting Pdz Domains Of Postsynaptic Density Protein 95/synmentioning

confidence: 99%

PDZ Domains as Drug Targets

Christensen

Čalyševa

Fernandes

et al. 2019

Advanced Therapeutics

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Protein-protein interactions within protein networks shape the human interactome, which often is promoted by specialized protein interaction modules, such as the postsynaptic density-95 (PSD-95), discs-large, zona occludens 1 (ZO-1) (PDZ) domains. PDZ domains play a role in several cellular functions, from cell-cell communication and polarization, to regulation of protein transport and protein metabolism. PDZ domain proteins are also crucial in the formation and stability of protein complexes, establishing an important bridge between extracellular stimuli detected by transmembrane receptors and intracellular responses. PDZ domains have been suggested as promising drug targets in several diseases, ranging from neurological and oncological disorders to viral infections. In this review, the authors describe structural and genetic aspects of PDZ-containing proteins and discuss the current status of the development of small-molecule and peptide modulators of PDZ domains. An overview of potential new therapeutic interventions in PDZ-mediated protein networks is also provided.

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Section: Targeting Pdz Domains Of Postsynaptic Density Protein 95/synmentioning

confidence: 99%

PDZ Domains as Drug Targets

Christensen

Čalyševa

Fernandes

et al. 2019

Advanced Therapeutics

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“…Enriched Gene Ontology terms were identified for proteins with significant differential expression between conditions at 5% FDR using the conditional hypergeometric test [78] implemented in the GOstats R package [79] , with terms from each branch of the ontology analyzed separately. Enrichment for protein-protein interactions between differentially expressed proteins was assessed using the InBioMap database [22] . The likelihood of the observed number of interactions between differentially expressed proteins was evaluated by randomly rewiring the InBioMap interactome 100 times using a degree-preserving algorithm [23] in order to maintain network topology, with the number of iterations for the edge rewiring algorithm set to 6.9 × the number of edges in each network [80] .…”

Section: Data Analysis For Shotgun Proteomics Of the Ifn Responsementioning

confidence: 99%

“…We therefore sought to determine whether proteins that were differentially expressed at 24 h, relative to 4 h or to unstimulated cells, displayed a statistically significant tendency to physically interact. Comparing the observed number of protein-protein interactions in the InBio Map database [22] to randomly rewired networks [23] revealed a substantial excess of physical protein-protein interactions, relative to random expectation ( Figure 1F-G). We therefore hypothesized that, in addition to its effects on ISG transcription, IFN stimulation induces widespread rewiring of protein-protein interaction networks.…”

Section: Introductionmentioning

confidence: 97%

Dynamic rewiring of the human interactome by interferon signalling

Kerr

Skinnider

Madero

et al. 2019

Preprint

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Background:The type I interferon (IFN) response is an ancient pathway that protects cells against viral pathogens by inducing the transcription of hundreds of IFN-stimulated genes (ISGs). Transcriptomic and biochemical approaches have established comprehensive catalogues of ISGs across species and cell types, but their antiviral mechanisms remain incompletely characterized. Here, we apply a combination of quantitative proteomic approaches to delineate the effects of IFN signalling on the human proteome, culminating in the use of protein correlation profiling to map IFN-induced rearrangements in the human protein-protein interaction network. Results:We identified >27,000 protein interactions in IFN-stimulated and unstimulated cells, many of which involve proteins associated with human disease and are observed exclusively within the IFN-stimulated network. Differential network analysis reveals interaction rewiring across a surprisingly broad spectrum of cellular pathways in the antiviral response. We identify IFN-dependent protein-protein interactions mediating novel regulatory mechanisms at the transcriptional and translational levels, with one such interaction modulating the transcriptional activity of STAT1. Moreover, we reveal IFN-dependent changes in ribosomal composition that act to buffer ISG protein synthesis.Conclusions : Our map of the IFN interactome provides a global view of the complex cellular networks activated during the antiviral response, placing ISGs in a functional context, and serves as a framework to understand how these networks are dysregulated in autoimmune or inflammatory disease. interaction network in differential and physiologically relevant contexts at the proteome scale represents a longstanding challenge [16] .Here, we apply a combination of quantitative proteomic approaches to chart the molecular landscape of type I IFN signalling, culminating in the use of protein correlation profiling (PCP)[17] to map interferon-induced rearrangements in the human interactome. The resulting protein-protein interaction network, encompassing over 27,000 interactions, reveals widespread rewiring of physical interactions and places known ISGs in an IFN-dependent functional context.We find evidence that the most evolutionarily conserved subset of ISGs are induced to physically interact in response to IFN stimulation, and experimentally validate the role of one such interaction in modulating STAT1 transcription. We develop statistical methods for differential network analysis to characterize interactome rewiring at the functional level, leading us to identify alterations in ribosome composition induced by interferon signalling that selectively downregulate ISG synthesis in order to fine-tune the IFN response. Collectively, this differential network map of the IFN-induced interactome provides a resource to mechanistically dissect the IFN response in the context of viral infection and autoimmune disease. RESULTS Proteome-wide analysis of the type I IFN responseWhereas the transcriptional response to IFN s...

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“…Protein-protein interaction (PPI) data were downloaded from STRING v10.0 19 and InBioMap. 20 Finally, a non-redundant PPI network containing 7638 proteins and 160 420 interactions was obtained for further analysis. The topological features of the network were analyzed by igraph package in R software.…”

Section: Identificationmentioning

confidence: 99%

Identification of genes with universally upregulated or downregulated expressions in colorectal cancer

Song

Liu

et al. 2018

J of Gastro and Hepatol

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Background and Aim Differentially expressed (DE) genes detected at the population‐level through case–control comparison provide no information on the dysregulation frequencies of DE genes in a cancer. In this work, we aimed to identify the genes with universally upregulated or downregulated expressions in colorectal cancer (CRC). Methods We firstly clarified that DE genes in an individual cancer tissue should be the disease‐relevant genes, which are dysregulated in the cancer tissue in comparison with its own previously normal state. Then, we identified DE genes at the individual level for 2233 CRC samples collected from multiple data sources using the RankComp algorithm. Results We found 26 genes that were upregulated or downregulated in almost all the 2233 CRC samples and validated the results using 124 CRC tissues with paired adjacent normal tissues. Especially, we found that two genes (AJUBA and EGFL6), upregulated universally in CRC tissues, were extremely lowly expressed in normal colorectal tissues, which were considered to be oncogenes in CRC oncogenesis and development. Oppositely, we found that one gene (LPAR1), downregulated universally in CRC tissues, was silenced in CRC tissues but highly expressed in normal colorectal tissues, which were considered to be tumor suppressor genes in CRC. Functional evidences revealed that these three genes may induce CRC through deregulating pathways for ribosome biogenesis, cell proliferation, and cell cycle. Conclusions In conclusion, the individual‐level DE genes analysis can help us find genes dysregulated universally in CRC tissues, which may be important diagnostic biomarkers and therapy targets.

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A scored human protein–protein interaction network to catalyze genomic interpretation

Cited by 555 publications

References 46 publications

PDZ Domains as Drug Targets

PDZ Domains as Drug Targets

Dynamic rewiring of the human interactome by interferon signalling

Identification of genes with universally upregulated or downregulated expressions in colorectal cancer

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