Evidence map›Paper›PMID 34452405›Full record

ArticleViruses2021

Multi-Tissue Transcriptomic-Informed In Silico Investigation of Drugs for the Treatment of Dengue Fever Disease.

Beatriz Sierra, Ana Cristina Magalhães, Daniel Soares, Bruno Cavadas, Ana B Perez, Mayling Alvarez, Eglis Aguirre, Claudia Bracho, Luisa Pereira, Maria G Guzman

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

10 authors at 2 institutions in 2 countries.

Beatriz SierraVirology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), Havana 11400, Cuba.
Ana Cristina Magalhãesi3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal.
Daniel Soaresi3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal.
Bruno Cavadasi3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal.
Ana B PerezVirology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), Havana 11400, Cuba.
Mayling AlvarezVirology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), Havana 11400, Cuba.
Eglis AguirreVirology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), Havana 11400, Cuba.
Claudia BrachoVirology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), Havana 11400, Cuba.
Luisa Pereirai3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal.ORCID 0000-0002-4271-1527
Maria G GuzmanVirology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), Havana 11400, Cuba.
Instituto de Medicina Tropical “Pedro Kourí” · CUUniversidade do Porto · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptomics, proteomics and pathogen-host interactomics data are being explored for the in silico-informed selection of drugs, prior to their functional evaluation. The effectiveness of this kind of strategy has been put to the test in the current COVID-19 pandemic, and it has been paying off, leading to a few drugs being rapidly repurposed as treatment against SARS-CoV-2 infection. Several neglected tropical diseases, for which treatment remains unavailable, would benefit from informed in silico investigations of drugs, as performed in this work for Dengue fever disease. We analyzed transcriptomic data in the key tissues of liver, spleen and blood profiles and verified that despite transcriptomic differences due to tissue specialization, the common mechanisms of action, "Adrenergic receptor antagonist", "ATPase inhibitor", "NF-kB pathway inhibitor" and "Serotonin receptor antagonist", were identified as druggable (e.g., oxprenolol, digoxin, auranofin and palonosetron, respectively) to oppose the effects of severe Dengue infection in these tissues. These are good candidates for future functional evaluation and clinical trials.

Indexed as

TranscriptomeAdenosine TriphosphatasesAdrenergic AntagonistsAntiviral AgentsBrainComputer SimulationDengueDrug DiscoveryDrug Evaluation, PreclinicalDrug RepositioningHumansLiverMetabolic Networks and PathwaysNF-kappa BSerotonin AntagonistsSevere DengueAdenosine TriphosphatasesAdrenergic AntagonistsAntiviral AgentsNF-kappa BSerotonin Antagonistscommon mechanisms of actionDengue fever diseasein silico evaluation of drugsmulti-tissue transcriptomicstissue specialization

Identifiers

PMID34452405
PMCPMC8402662
OpenAlexW3190323594

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.