ArticleBioorganic & medicinal chemistry2010
Functional profiling of p53-binding sites in Hdm2 and Hdmx using a genetic selection system.
Article in Bioorganic & medicinal chemistry, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- Optimized Construction of a Yeast SICLOPPS Library for UnbiasedBiochemistry · 2024Article
- Identification of selective protein-protein interaction inhibitors using efficientChemical science · 2019Article
- Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system.Microbiology and molecular biology reviews : MMBR · 2012Review
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Upregulation of structurally homologous oncoproteins Hdm2 and Hdmx has been linked to the depletion or inactivation of their common regulation target the tumor suppressor p53 protein leading to the progression of cancer. The restoration of the p53 function, rendered suppressed or dormant by these negative regulators, establishes, therefore, a unique opportunity for a targeted induction of apoptosis in cancers that retain wild-type p53. While several small molecules have been reported to rescue the tumor suppressor by antagonizing the Hdm2-p53 interaction, these agents displayed limited application scope by being ineffective in tumors enriched with active Hdmx. Here, we describe the use of a genetic selection system and encoded library of conformationally pre-organized peptides to perform functional profiling of each regulator revealing specific recognition features that guide the antagonism of Hdm2-p53 and Hdmx-p53 interactions. Structure-activity relationship analysis of the most effective leads identified functional and structural elements mediating selective recognition of the two structurally related regulators, while providing convenient starting points for further activity optimization.
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