Evidence map›Paper›PMID 35560453›Full record

ArticleMolecular carcinogenesis2022

Delineating functional mechanisms of the p53/p63/p73 family of transcription factors through identification of protein-protein interactions using interface mimicry.

Emine Guven-Maiorov, Nozomi Sakakibara, Roshini M Ponnamperuma, Kun Dong, Hector Matar, Kathryn E King, Wendy C Weinberg

Open access · greenAbstract read
In one paragraph

Article in Molecular carcinogenesis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 56% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Emine Guven-MaiorovLaboratory of Molecular Oncology, Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.ORCID 0000-0002-7388-9811
Nozomi SakakibaraLaboratory of Molecular Oncology, Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.ORCID 0000-0003-3581-8067
Roshini M PonnamperumaLaboratory of Molecular Oncology, Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
Kun DongLaboratory of Molecular Oncology, Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
Hector MatarLaboratory of Molecular Oncology, Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.ORCID 0000-0002-1804-5333
Kathryn E KingLaboratory of Molecular Oncology, Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.ORCID 0000-0001-6357-0930
Wendy C WeinbergLaboratory of Molecular Oncology, Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.ORCID 0000-0002-8299-7339
United States Food and Drug Administration · US

Funding

Intramural FDA HHS FD999999Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

Members of the p53 family of transcription factors-p53, p63, and p73-share a high degree of homology; however, members can be activated in response to different stimuli, perform distinct (sometimes opposing) roles and are expressed in different tissues. The level of complexity is increased further by the transcription of multiple isoforms of each homolog, which may interact or interfere with each other and can impact cellular outcome. Proteins perform their functions through interacting with other proteins (and/or with nucleic acids). Therefore, identification of the interactors of a protein and how they interact in 3D is essential to fully comprehend their roles. By utilizing an in silico protein-protein interaction prediction method-HMI-PRED-we predicted interaction partners of p53 family members and modeled 3D structures of these protein interaction complexes. This method recovered experimentally known interactions while identifying many novel candidate partners. We analyzed the similarities and differences observed among the interaction partners to elucidate distinct functions of p53 family members and provide examples of how this information may yield mechanistic insight to explain their overlapping versus distinct/opposing outcomes in certain contexts. While some interaction partners are common to p53, p63, and p73, the majority are unique to each member. Nevertheless, most of the enriched pathways associated with these partners are common to all members, indicating that the members target the same biological pathways but through unique mediators. p63 and p73 have more common enriched pathways compared to p53, supporting their similar developmental roles in different tissues.

Indexed as

Transcription FactorsTumor Suppressor Protein p53DNA-Binding ProteinsHumansNuclear ProteinsTumor Protein p73Tumor Suppressor ProteinsDNA-Binding ProteinsNuclear ProteinsTranscription FactorsTumor Protein p73Tumor Suppressor Protein p53Tumor Suppressor Proteinscomputational predictionmodelingp53 homologsp53/p63/p73protein-protein interaction

Identifiers

PMID35560453
PMCPMC9949960
OpenAlexW4280496894

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.