Evidence map›Paper›PMID 21297107›Full record

ArticleJournal of biomolecular screening2011

Optimized high-throughput screen for hepatitis C virus translation inhibitors.

Katherine E Berry, Betty Peng, David Koditek, Douglas Beeman, Nikos Pagratis, Jason K Perry, Jay Parrish, Weidong Zhong, Jennifer A Doudna, I-hung Shih

Open access · hybridAbstract read
In one paragraph

Article in Journal of biomolecular screening, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Katherine E BerryDepartment of Chemistry, University of California, Berkeley, CA, USA.
Betty Peng
David Koditek
Douglas Beeman
Nikos Pagratis
Jason K Perry
Jay Parrish
Weidong Zhong
Jennifer A Doudna
I-hung Shih
Gilead Sciences (United States) · USUniversity of California, Berkeley · US

Funding

STRUCTURE AND FUNCTION OF HUMAN TRANSLATION COMPLEXESP01GM073732 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI DOUDNA, JENNIFER A · 2006 to 2010
$6.5M
NIGMS NIH HHS P01 GM073732
6 · The paper itself

Abstract

Hepatitis C virus (HCV) is a considerable global health problem for which new classes of therapeutics are needed. The authors developed a high-throughput assay to identify compounds that selectively block translation initiation from the HCV internal ribosome entry site (HCV IRES). Rabbit reticulocyte lysate conditions were optimized to faithfully report on authentic HCV IRES-dependent translation relative to a 5' capped mRNA control. The authors screened a library of ~430,000 small molecules for IRES inhibition, leading to ~1700 initial hits. After secondary counterscreening, the vast majority of hits proved to be luciferase and general translation inhibitors. Despite well-optimized in vitro translation conditions, in the end, the authors found no selective HCV IRES inhibitors but did discover a new scaffold of general translation inhibitor. The analysis of these molecules, as well we the finding that a large fraction of false positives resulted from off-target effects, highlights the challenges inherent in screens for RNA-specific inhibitors.

Indexed as

High-Throughput Screening AssaysProtein Synthesis InhibitorsAnimalsDrug Evaluation, PreclinicalGenes, ReporterHepacivirusHumansProtein BiosynthesisPuromycinRabbitsReproducibility of ResultsResearch DesignRNA, MessengerRNA, ViralSmall Molecule LibrariesProtein Synthesis InhibitorsPuromycinRNA, MessengerRNA, ViralSmall Molecule Libraries

Identifiers

PMID21297107
PMCPMC3260011
OpenAlexW2116762284

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.