Evidence map›Paper›PMID 31239057›Full record

ArticleMethods in enzymology2019

Identifying and validating small molecules interacting with RNA (SMIRNAs).

Matthew D Disney, Sai Pradeep Velagapudi, Yue Li, Matthew G Costales, Jessica L Childs-Disney

Abstract read
In one paragraph

Article in Methods in enzymology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Targeting RNA structures with small molecules.Nature reviews. Drug discovery · 2022
    Review
  5. Review
  6. Small molecule-RNA targeting: starting with the fundamentals.Chemical communications (Cambridge, England) · 2020
    Article
  7. How We Think about Targeting RNA with Small Molecules.Journal of medicinal chemistry · 2020
    Article
  8. RNA-ligand molecular docking: advances and challenges.Wiley interdisciplinary reviews. Computational molecular science
    Article
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

5 authors.

Matthew D DisneyDepartment of Chemistry, The Scripps Research Institute, Jupiter, FL, United States. Electronic address: disney@scripps.edu.
Sai Pradeep VelagapudiDepartment of Chemistry, The Scripps Research Institute, Jupiter, FL, United States.
Yue LiDepartment of Chemistry, The Scripps Research Institute, Jupiter, FL, United States.
Matthew G CostalesDepartment of Chemistry, The Scripps Research Institute, Jupiter, FL, United States.
Jessica L Childs-DisneyDepartment of Chemistry, The Scripps Research Institute, Jupiter, FL, United States.

Funding

Validation of r(G4C2)exp-binding small molecules in vivo and c9FTD/ALS biomarker developmentP01NS099114 · NINDS · UNIVERSITY OF FLORIDA · PI DISNEY, MATTHEW D, PETRUCELLI, LEONARD · 2017 to 2021
$6.5M
Using a disease-affected cell to synthesize its own drugDP1NS096898 · NINDS · SCRIPPS FLORIDA · PI DISNEY, MATTHEW D · 2015 to 2019
$5.0M
Sequence-based Design of Small Molecules Targeting RNAR01GM097455 · NIGMS · SCRIPPS FLORIDA · PI DISNEY, MATTHEW D · 2012 to 2019
$4.6M
NIGMS NIH HHS R01 GM097455NINDS NIH HHS DP1 NS096898NINDS NIH HHS P01 NS099114
6 · The paper itself

Abstract

High throughput sequencing has revolutionized our ability to identify aberrant RNA expression and mutations that cause or contribute to disease. These data can be used directly to design oligonucleotide-based modalities using Watson-Crick pairing to target unstructured regions in an RNA. A complementary, although more difficult, strategy to deactivate a malfunctioning RNA is to target highly structured regions with small molecules. Indeed, RNA structures are directly causative of disease. Herein, we discuss emerging strategies to design high affinity, selective, bioactive ligands targeting RNA, or small molecules interacting with RNA (SMIRNAs), and target validation and profiling methods. An experimental foundation is required for a lead identification strategy for RNA structures, constructed from a library-vs.-library screen that probes vast libraries of small molecules for binding RNA three dimensional folds. Dubbed 2-dimensional combinatorial screening (2DCS), the resulting data can be mined against transcriptomes or the composite of RNAs that are produced in an organism to define folded RNA structures that can be targeted. By applying SMIRNAs to cells and using target validation tools such as Chemical Cross-Linking and Isolation by Pull-down (Chem-CLIP) and Small Molecule Nucleic Acid Profiling by Cleavage Applied to RNA (RiboSNAP), all targets engaged in cells can be defined, along with rules for molecular recognition to affect RNA biology. This chapter will describe lessons learned in applying these approaches in vitro, in cells, and in pre-clinical animal models of disease, enabling SMIRNAs to capture opportunities in chemical biology.

Indexed as

AnimalsCell LineDrug DesignGene LibraryHumansModels, MolecularNucleic Acid ConformationOligonucleotides, AntisensePolymerase Chain ReactionRNASmall Molecule LibrariesOligonucleotides, AntisenseRNASmall Molecule LibrariesAntisenseLead identificationLibrary-vs.-library screeningMicroRNAsRepeat expansionRNARNA-small molecule affinity landscapesSmall moleculesTargetingTarget profilingTarget validation

Identifiers

PMID31239057
PMCPMC6628145

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.