Evidence map›Paper›PMID 34556735›Full record

ArticleScientific reports2021

Network neighbors of viral targets and differentially expressed genes in COVID-19 are drug target candidates.

Carme Zambrana, Alexandros Xenos, René Böttcher, Noël Malod-Dognin, Nataša Pržulj

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Simplicity within biological complexity.Bioinformatics advances · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Journal of biosciences · 2022
    Review
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

5 authors.

Carme ZambranaBarcelona Supercomputing Center, Barcelona, Spain.
Alexandros XenosBarcelona Supercomputing Center, Barcelona, Spain.
René BöttcherBarcelona Supercomputing Center, Barcelona, Spain.
Noël Malod-DogninBarcelona Supercomputing Center, Barcelona, Spain.
Nataša PržuljBarcelona Supercomputing Center, Barcelona, Spain. natasha@bsc.es.

Funding

Agencia Estatal de Investigación PID2019-105500GB-I00European Research Council 770827
6 · The paper itself

Abstract

The COVID-19 pandemic is raging. It revealed the importance of rapid scientific advancement towards understanding and treating new diseases. To address this challenge, we adapt an explainable artificial intelligence algorithm for data fusion and utilize it on new omics data on viral-host interactions, human protein interactions, and drugs to better understand SARS-CoV-2 infection mechanisms and predict new drug-target interactions for COVID-19. We discover that in the human interactome, the human proteins targeted by SARS-CoV-2 proteins and the genes that are differentially expressed after the infection have common neighbors central in the interactome that may be key to the disease mechanisms. We uncover 185 new drug-target interactions targeting 49 of these key genes and suggest re-purposing of 149 FDA-approved drugs, including drugs targeting VEGF and nitric oxide signaling, whose pathways coincide with the observed COVID-19 symptoms. Our integrative methodology is universal and can enable insight into this and other serious diseases.

Indexed as

COVID-19 Drug TreatmentAntiviral AgentsArtificial IntelligenceCOVID-19Drug Evaluation, PreclinicalDrug RepositioningGene Regulatory NetworksHumansModels, TheoreticalPandemicsPharmaceutical PreparationsSARS-CoV-2Signal TransductionAntiviral AgentsPharmaceutical Preparations

Identifiers

PMID34556735
PMCPMC8460804

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.