Evidence map›Paper›PMID 32811513›Full record

ReviewJournal of translational medicine2020

The current landscape of coronavirus-host protein-protein interactions.

Laure Perrin-Cocon, Olivier Diaz, Clémence Jacquemin, Valentine Barthel, Eva Ogire, Christophe Ramière, Patrice André, Vincent Lotteau, Pierre-Olivier Vidalain

Abstract readReview
In one paragraph

Review in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing 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

54 citing papers in PubMed.

  1. Article
  2. AI-Guided Binding Mechanisms and Molecular Dynamics for MERS-CoV.International journal of molecular sciences · 2026
    Article
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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

9 authors.

Laure Perrin-CoconCIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 69007, Lyon, France.
Olivier DiazCIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 69007, Lyon, France.
Clémence JacqueminCIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 69007, Lyon, France.
Valentine BarthelCIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 69007, Lyon, France.
Eva OgireCIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 69007, Lyon, France.
Christophe RamièreCIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 69007, Lyon, France.
Patrice AndréCIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 69007, Lyon, France.
Vincent LotteauCIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 69007, Lyon, France. vincent.lotteau@inserm.fr.
Pierre-Olivier VidalainCIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 69007, Lyon, France. pierre-olivier.vidalain@inserm.fr.ORCID 0000-0003-3082-7407

Funding

Conseil Régional de l'île de La Réunion DIRED 20181189
6 · The paper itself

Abstract

In less than 20 years, three deadly coronaviruses, SARS-CoV, MERS-CoV and SARS-CoV-2, have emerged in human population causing hundreds to hundreds of thousands of deaths. Other coronaviruses are causing epizootic representing a significant threat for both domestic and wild animals. Members of this viral family have the longest genome of all RNA viruses, and express up to 29 proteins establishing complex interactions with the host proteome. Deciphering these interactions is essential to identify cellular pathways hijacked by these viruses to replicate and escape innate immunity. Virus-host interactions also provide key information to select targets for antiviral drug development. Here, we have manually curated the literature to assemble a unique dataset of 1311 coronavirus-host protein-protein interactions. Functional enrichment and network-based analyses showed coronavirus connections to RNA processing and translation, DNA damage and pathogen sensing, interferon production, and metabolic pathways. In particular, this global analysis pinpointed overlooked interactions with translation modulators (GIGYF2-EIF4E2), components of the nuclear pore, proteins involved in mitochondria homeostasis (PHB, PHB2, STOML2), and methylation pathways (MAT2A/B). Finally, interactome data provided a rational for the antiviral activity of some drugs inhibiting coronaviruses replication. Altogether, this work describing the current landscape of coronavirus-host interactions provides valuable hints for understanding the pathophysiology of coronavirus infections and developing effective antiviral therapies.

Indexed as

Protein Interaction MapsAnimalsBetacoronavirusCoronavirusCoronavirus InfectionsCOVID-19Databases, ProteinHost-Pathogen InteractionsHumansMitochondrial ProteinsPandemicsPneumonia, ViralProhibitinsSARS-CoV-2Transcription FactorsViral ProteinsMitochondrial ProteinsPHB2 protein, humanPHB protein, humanProhibitinsTranscription FactorsViral ProteinsCoronavirusInteractomeProtein–protein interactionsSARS-CoV-2Virus-host interactions

Identifiers

PMID32811513
PMCPMC7432461

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.