Evidence map›Paper›PMID 33131530›Full record

ArticleComputers in biology and medicine2020

Multi-omics-based identification of SARS-CoV-2 infection biology and candidate drugs against COVID-19.

Debmalya Barh, Sandeep Tiwari, Marianna E Weener, Vasco Azevedo, Aristóteles Góes-Neto, M Michael Gromiha, Preetam Ghosh

Open access · greenAbstract read
In one paragraph

Article in Computers in biology and medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
2.0field-weighted citation impact, top 8% 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

45 citing papers in PubMed, 94 citations in OpenAlex.

  1. Multi-omics to study chronic respiratory diseases and viral infections.European respiratory review : an official journal of the European Respiratory Society · 2026
    Review
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  6. Exploring the underlying molecular mechanisms of acute myocardial infarction after SARS-CoV-2 infection.American heart journal plus : cardiology research and practice · 2024
    Article
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  9. Review
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  15. Glutamine-Driven Metabolic Adaptation to COVID-19 Infection.Indian journal of clinical biochemistry : IJCB · 2023
    Article
  16. Article
  17. Review
  18. Article
  19. 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

7 authors at 4 institutions in 3 countries.

Debmalya BarhInstitute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur, WB, India. Electronic address: dr.barh@gmail.com.
Sandeep TiwariLaboratório de Genética Celular e Molecular, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Marianna E WeenerClinical Research Center, Oftalmic, CRO, 119334, Bardina Str.22/4, Moscow, Russia.
Vasco AzevedoLaboratório de Genética Celular e Molecular, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Aristóteles Góes-NetoLaboratório de Biologia Molecular e Computacional de Fungos, Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil.
M Michael GromihaDepartment of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras (IIT-M), Chennai, 600036, India.
Preetam GhoshDepartment of Computer Science, Virginia Commonwealth University, Richmond, VA, 23284, USA.
Universidade Federal de Minas Gerais · BRIndian Institute of Technology Madras · INInstitute of Bioinformatics and Applied Biotechnology · INVirginia Commonwealth University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SARS-CoV-2 has ushered a global pandemic with no effective drug being available at present. Although several FDA-approved drugs are currently under clinical trials for drug repositioning, there is an on-going global effort for new drug identification. In this paper, using multi-omics (interactome, proteome, transcriptome, and bibliome) data and subsequent integrated analysis, we present the biological events associated with SARS-CoV-2 infection and identify several candidate drugs against this viral disease. We found that: (i) Interactome-based infection pathways differ from the other three omics-based profiles. (ii) Viral process, mRNA splicing, cytokine and interferon signaling, and ubiquitin mediated proteolysis are important pathways in SARS-CoV-2 infection. (iii) SARS-CoV-2 infection also shares pathways with Influenza A, Epstein-Barr virus, HTLV-I, Measles, and Hepatitis virus. (iv) Further, bacterial, parasitic, and protozoan infection pathways such as Tuberculosis, Malaria, and Leishmaniasis are also shared by this virus. (v) A total of 50 candidate drugs, including the prophylaxis agents and pathway specific inhibitors are identified against COVID-19. (vi) Betamethasone, Estrogen, Simvastatin, Hydrocortisone, Tositumomab, Cyclosporin A etc. are among the important drugs. (vii) Ozone, Nitric oxide, plasma components, and photosensitizer drugs are also identified as possible therapeutic candidates. (viii) Curcumin, Retinoic acids, Vitamin D, Arsenic, Copper, and Zinc may be the candidate prophylaxis agents. Nearly 70% of our identified agents are previously suggested to have anti-COVID-19 effects or under clinical trials. Among our identified drugs, the ones that are not yet tested, need validation with caution while an appropriate drug combination from these candidate drugs along with a SARS-CoV-2 specific antiviral agent is needed for effective COVID-19 management.

Indexed as

Antiviral AgentsBetacoronavirusCoronavirus InfectionsDatabases, GeneticDrug DiscoveryModels, BiologicalPandemicsPneumonia, ViralCOVID-19HumansProteomicsSARS-CoV-2Antiviral AgentsCandidate drugsCOVID-19Infection pathwaysInteractomeProphylaxis agentsProteomeSARS-CoV-2Transcriptome

Identifiers

PMID33131530
PMCPMC7547373
OpenAlexW3091948906

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.