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DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor

Nature evolves molecular interaction networks through persistent perturbation and selection, in stark contrast to drug discovery, which evaluates candidates one at a time by screening. Here, nature’s highly parallel ligand-target search paradigm is recapitulated in a screen of a DNA-encoded library...

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Autores principales: Benhamou, Raphael I., Suresh, Blessy M., Tong, Yuquan, Cochrane, Wesley G., Cavett, Valerie, Vezina-Dawod, Simon, Abegg, Daniel, Childs-Disney, Jessica L., Adibekian, Alexander, Paegel, Brian M., Disney, Matthew D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8833215/
https://www.ncbi.nlm.nih.gov/pubmed/35110406
http://dx.doi.org/10.1073/pnas.2114971119
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author Benhamou, Raphael I.
Suresh, Blessy M.
Tong, Yuquan
Cochrane, Wesley G.
Cavett, Valerie
Vezina-Dawod, Simon
Abegg, Daniel
Childs-Disney, Jessica L.
Adibekian, Alexander
Paegel, Brian M.
Disney, Matthew D.
author_facet Benhamou, Raphael I.
Suresh, Blessy M.
Tong, Yuquan
Cochrane, Wesley G.
Cavett, Valerie
Vezina-Dawod, Simon
Abegg, Daniel
Childs-Disney, Jessica L.
Adibekian, Alexander
Paegel, Brian M.
Disney, Matthew D.
author_sort Benhamou, Raphael I.
collection PubMed
description Nature evolves molecular interaction networks through persistent perturbation and selection, in stark contrast to drug discovery, which evaluates candidates one at a time by screening. Here, nature’s highly parallel ligand-target search paradigm is recapitulated in a screen of a DNA-encoded library (DEL; 73,728 ligands) against a library of RNA structures (4,096 targets). In total, the screen evaluated ∼300 million interactions and identified numerous bona fide ligand–RNA three-dimensional fold target pairs. One of the discovered ligands bound a 5′GAG/3′CCC internal loop that is present in primary microRNA-27a (pri-miR-27a), the oncogenic precursor of microRNA-27a. The DEL-derived pri-miR-27a ligand was cell active, potently and selectively inhibiting pri-miR-27a processing to reprogram gene expression and halt an otherwise invasive phenotype in triple-negative breast cancer cells. By exploiting evolutionary principles at the earliest stages of drug discovery, it is possible to identify high-affinity and selective target–ligand interactions and predict engagements in cells that short circuit disease pathways in preclinical disease models.
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spelling pubmed-88332152022-02-18 DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor Benhamou, Raphael I. Suresh, Blessy M. Tong, Yuquan Cochrane, Wesley G. Cavett, Valerie Vezina-Dawod, Simon Abegg, Daniel Childs-Disney, Jessica L. Adibekian, Alexander Paegel, Brian M. Disney, Matthew D. Proc Natl Acad Sci U S A Biological Sciences Nature evolves molecular interaction networks through persistent perturbation and selection, in stark contrast to drug discovery, which evaluates candidates one at a time by screening. Here, nature’s highly parallel ligand-target search paradigm is recapitulated in a screen of a DNA-encoded library (DEL; 73,728 ligands) against a library of RNA structures (4,096 targets). In total, the screen evaluated ∼300 million interactions and identified numerous bona fide ligand–RNA three-dimensional fold target pairs. One of the discovered ligands bound a 5′GAG/3′CCC internal loop that is present in primary microRNA-27a (pri-miR-27a), the oncogenic precursor of microRNA-27a. The DEL-derived pri-miR-27a ligand was cell active, potently and selectively inhibiting pri-miR-27a processing to reprogram gene expression and halt an otherwise invasive phenotype in triple-negative breast cancer cells. By exploiting evolutionary principles at the earliest stages of drug discovery, it is possible to identify high-affinity and selective target–ligand interactions and predict engagements in cells that short circuit disease pathways in preclinical disease models. National Academy of Sciences 2022-02-02 2022-02-08 /pmc/articles/PMC8833215/ /pubmed/35110406 http://dx.doi.org/10.1073/pnas.2114971119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Biological Sciences
Benhamou, Raphael I.
Suresh, Blessy M.
Tong, Yuquan
Cochrane, Wesley G.
Cavett, Valerie
Vezina-Dawod, Simon
Abegg, Daniel
Childs-Disney, Jessica L.
Adibekian, Alexander
Paegel, Brian M.
Disney, Matthew D.
DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor
title DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor
title_full DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor
title_fullStr DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor
title_full_unstemmed DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor
title_short DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor
title_sort dna-encoded library versus rna-encoded library selection enables design of an oncogenic noncoding rna inhibitor
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8833215/
https://www.ncbi.nlm.nih.gov/pubmed/35110406
http://dx.doi.org/10.1073/pnas.2114971119
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