Evidence map›Paper›PMID 34012080›Full record

ReviewNature2021

Unconventional viral gene expression mechanisms as therapeutic targets.

Jessica Sook Yuin Ho, Zeyu Zhu, Ivan Marazzi

Open access · bronzeAbstract readReview
PubMed Publisher
In one paragraph

Review in Nature, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
6.8field-weighted citation impact, top 3% 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

39 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
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  4. Review
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  10. Global cis-regulatory landscape of double-stranded DNA viruses.bioRxiv : the preprint server for biology · 2025
    Article
  11. Article
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  13. Review
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  17. Review
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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

3 authors at 1 institution in 1 country.

Jessica Sook Yuin Ho *Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Zeyu Zhu *Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Ivan MarazziDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ivan.marazzi@mssm.edu.ORCID http://orcid.org/0000-0003-3376-0922
Icahn School of Medicine at Mount Sinai · US

Funding

Dynamic regulatory network models of human response to influenza virusU01AI150748 · NIAID · UNIVERSITY OF CALIFORNIA-IRVINE · PI MARAZZI, IVAN, MIRALDI, EMILY · 2020 to 2024
$5.8M
NIAID NIH HHS U01 AI150748Wellcome Trust 1017892
6 · The paper itself

Abstract

Unlike the human genome that comprises mostly noncoding and regulatory sequences, viruses have evolved under the constraints of maintaining a small genome size while expanding the efficiency of their coding and regulatory sequences. As a result, viruses use strategies of transcription and translation in which one or more of the steps in the conventional gene-protein production line are altered. These alternative strategies of viral gene expression (also known as gene recoding) can be uniquely brought about by dedicated viral enzymes or by co-opting host factors (known as host dependencies). Targeting these unique enzymatic activities and host factors exposes vulnerabilities of a virus and provides a paradigm for the design of novel antiviral therapies. In this Review, we describe the types and mechanisms of unconventional gene and protein expression in viruses, and provide a perspective on how future basic mechanistic work could inform translational efforts that are aimed at viral eradication.

Indexed as

AnimalsAntiviral AgentsFrameshifting, RibosomalGene Expression Regulation, ViralGenome, ViralHost Microbial InteractionsHumansRNA SplicingVirus DiseasesAntiviral Agents

Identifiers

PMID34012080
OpenAlexW3160493544

What OpenQuestion holds

Textmetadata
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.