Evidence map›Paper›PMID 27177310›Full record

ArticleNature communications2016

A human genome-wide loss-of-function screen identifies effective chikungunya antiviral drugs.

Alexander Karlas, Stefano Berre, Thérèse Couderc, Margus Varjak, Peter Braun, Michael Meyer, Nicolas Gangneux, Liis Karo-Astover, Friderike Weege, Martin Raftery and 7 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2016. 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
10.6field-weighted citation impact, top 1% 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

54 citing papers in PubMed, 85 citations in OpenAlex.

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  17. Small Molecule Inhibitors Targeting Chikungunya Virus.Current topics in microbiology and immunology · 2022
    Review
  18. Understanding Molecular Pathogenesis with Chikungunya Virus Research Tools.Current topics in microbiology and immunology · 2022
    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

17 authors at 8 institutions in 3 countries.

Alexander KarlasMax Planck Institute for Infection Biology, Department of Molecular Biology, Charitéplatz 1, 10117 Berlin, Germany.
Stefano BerreInstitut Pasteur, Biology of Infection Unit, 28 rue du Dr. Roux, 75015 Paris, France.
Thérèse CoudercInstitut Pasteur, Biology of Infection Unit, 28 rue du Dr. Roux, 75015 Paris, France.
Margus VarjakInstitute of Technology, University of Tartu, Nooruse 1, 50411 Tartu, Estonia.
Peter BraunMax Planck Institute for Infection Biology, Department of Molecular Biology, Charitéplatz 1, 10117 Berlin, Germany.
Michael MeyerSteinbeis Innovation gGmbH, Center for Systems Biomedicine, Haydnallee 21, 14612 Falkensee, Germany.
Nicolas GangneuxInstitut Pasteur, Biology of Infection Unit, 28 rue du Dr. Roux, 75015 Paris, France.
Liis Karo-AstoverInstitute of Technology, University of Tartu, Nooruse 1, 50411 Tartu, Estonia.
Friderike WeegeMax Planck Institute for Infection Biology, Department of Molecular Biology, Charitéplatz 1, 10117 Berlin, Germany.
Martin RafteryInstitute of Virology, Charité University Medicine, Charitéplatz 1, 10117 Berlin, Germany.
Günther SchönrichInstitute of Virology, Charité University Medicine, Charitéplatz 1, 10117 Berlin, Germany.
Uwe KlemmMax Planck Institute for Infection Biology, Core Facility Experimental Animals, Charitéplatz 1, 10117 Berlin, Germany.
Anne WurzlbauerLudwig-Maximilians-University, Department of Pharmacy-Center for Drug Research, Butenandtstraße 5-13, 81377 Munich, Germany.
Franz BracherLudwig-Maximilians-University, Department of Pharmacy-Center for Drug Research, Butenandtstraße 5-13, 81377 Munich, Germany.
Andres MeritsInstitute of Technology, University of Tartu, Nooruse 1, 50411 Tartu, Estonia.
Thomas F MeyerMax Planck Institute for Infection Biology, Department of Molecular Biology, Charitéplatz 1, 10117 Berlin, Germany.
Marc LecuitInstitut Pasteur, Biology of Infection Unit, 28 rue du Dr. Roux, 75015 Paris, France.
Charité - Universitätsmedizin Berlin · DEMax Planck Institute for Infection Biology · DEUniversity of Tartu · EEBiology of Infection · FRLudwig-Maximilians-Universität München · DEInserm · FRInstitut Pasteur · FRSteinbeis Foundation · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents.

Indexed as

AnimalsAntiviral AgentsChikungunya FeverChikungunya virusFuransGene Expression ProfilingGenome, HumanHEK293 CellsHost-Pathogen InteractionsHumansMicePimozideRNA, Small InterferingSmall Molecule LibrariesVirus Replication5-(tetradecyloxy)-2-furancarboxylic acidAntiviral AgentsFuransPimozideRNA, Small InterferingSmall Molecule Libraries

Identifiers

PMID27177310
PMCPMC4865845
OpenAlexW2389103695

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.