ArticleAssay and drug development technologies2010
Characterization and optimization of a novel protein-protein interaction biosensor high-content screening assay to identify disruptors of the interactions between p53 and hDM2.
Article in Assay and drug development technologies, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 29 citations in OpenAlex.
- Miniaturization and characterization of patient derived hepatocellular carcinoma tumor organoid cultures for cancer drug discovery applications.SLAS discovery : advancing life sciences R & D · 2025Article
- Functional display of bioactive peptides on the vGFP scaffold.Scientific reports · 2021Article
- High Content Positional Biosensor Assay to Screen for Compounds that Prevent or Disrupt Androgen Receptor and Transcription Intermediary Factor 2 Protein-Protein Interactions.Methods in molecular biology (Clifton, N.J.) · 2018Article
- High Content Imaging Assays for IL-6-Induced STAT3 Pathway Activation in Head and Neck Cancer Cell Lines.Methods in molecular biology (Clifton, N.J.) · 2018Article
- High-Content Screening Comparison of Cancer Drug Accumulation and Distribution in Two-Dimensional and Three-Dimensional Culture Models of Head and Neck Cancer.Assay and drug development technologies · 2018Article
- Reconfiguring the AR-TIF2 Protein-Protein Interaction HCS Assay in Prostate Cancer Cells and Characterizing the Hits from a LOPAC Screen.Assay and drug development technologies · 2016Article
- HCS campaign to identify selective inhibitors of IL-6-induced STAT3 pathway activation in head and neck cancer cell lines.Assay and drug development technologies · 2015Article
- High-content positional biosensor screening assay for compounds to prevent or disrupt androgen receptor and transcriptional intermediary factor 2 protein-protein interactions.Assay and drug development technologies · 2014Article
- Targeting p53-MDM2-MDMX loop for cancer therapy.Sub-cellular biochemistry · 2014Review
- Targeting protein-protein interactions as an anticancer strategy.Trends in pharmacological sciences · 2013Review
- The p53-MDM2/MDMX axis - A chemotype perspective.MedChemComm · 2011Article
- High-content pSTAT3/1 imaging assays to screen for selective inhibitors of STAT3 pathway activation in head and neck cancer cell lines.Assay and drug development technologiesArticle
- High-Content Screening Campaign to Identify Compounds That Inhibit or Disrupt Androgen Receptor-Transcriptional Intermediary Factor 2 Protein-Protein Interactions for the Treatment of Prostate Cancer.Assay and drug development technologiesArticle
- Assays to Interrogate the Ability of Compounds to Inhibit the AF-2 or AF-1 Transactivation Domains of the Androgen Receptor.Assay and drug development technologiesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
We present here the characterization and optimization of a novel imaging-based positional biosensor high-content screening (HCS) assay to identify disruptors of p53-hDM2 protein-protein interactions (PPIs). The chimeric proteins of the biosensor incorporated the N-terminal PPI domains of p53 and hDM2, protein targeting sequences (nuclear localization and nuclear export sequence), and fluorescent reporters, which when expressed in cells could be used to monitor p53-hDM2 PPIs through changes in the subcellular localization of the hDM2 component of the biosensor. Coinfection with the recombinant adenovirus biosensors was used to express the NH-terminal domains of p53 and hDM2, fused to green fluorescent protein and red fluorescent protein, respectively, in U-2 OS cells. We validated the p53-hDM2 PPI biosensor (PPIB) HCS assay with Nutlin-3, a compound that occupies the hydrophobic pocket on the surface of the N-terminus of hDM2 and blocks the binding interactions with the N-terminus of p53. Nutlin-3 disrupted the p53-hDM2 PPIB in a concentration-dependent manner and provided a robust, reproducible, and stable assay signal window that was compatible with HCS. The p53-hDM2 PPIB assay was readily implemented in HCS and we identified four (4) compounds in the 1,280-compound Library of Pharmacologically Active Compounds that activated the p53 signaling pathway and elicited biosensor signals that were clearly distinct from the responses of inactive compounds. Anthracycline (topoisomerase II inhibitors such as mitoxantrone and ellipticine) and camptothecin (topoisomerase I inhibitor) derivatives including topotecan induce DNA double strand breaks, which activate the p53 pathway through the ataxia telangiectasia mutated-checkpoint kinase 2 (ATM-CHK2) DNA damage response pathway. Although mitoxantrone, ellipticine, camptothecin, and topotecan all exhibited concentration-dependent disruption of the p53-hDM2 PPIB, they were much less potent than Nutlin-3. Further, their corresponding cellular images and quantitative HCS data did not completely match the Nutlin-3 phenotypic profile.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.