Evidence map›Paper›PMID 35037717›Full record

ArticleJournal of cellular biochemistry2022

Integrative multiomics and in silico analysis revealed the role of ARHGEF1 and its screened antagonist in mild and severe COVID-19 patients.

Prakash Jha, Prithvi Singh, Shweta Arora, Armiya Sultan, Arnab Nayek, Kalaiarasan Ponnusamy, Mansoor Ali Syed, Ravins Dohare, Madhu Chopra

Open access · greenAbstract read
In one paragraph

Article in Journal of cellular biochemistry, 2022. 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
3.1field-weighted citation impact, top 7% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

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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 at 4 institutions in 1 country.

Prakash JhaLaboratory of Molecular Modeling and Anticancer Drug Development, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, New Delhi, India.
Prithvi SinghCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.
Shweta AroraDepartment of Biotechnology, Translational Research Lab, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India.
Armiya SultanDepartment of Biosciences, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India.ORCID 0000-0001-5373-8824
Arnab NayekDepartment of Biochemistry, All India Institute of Medical Sciences, New Delhi, India.
Kalaiarasan PonnusamySynthetic Biology Lab, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India.
Mansoor Ali SyedDepartment of Biotechnology, Translational Research Lab, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India.
Ravins DohareCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.ORCID 0000-0002-0602-3719
Madhu ChopraLaboratory of Molecular Modeling and Anticancer Drug Development, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, New Delhi, India.
Jamia Millia Islamia · INAmbedkar University Delhi · INAll India Institute of Medical Sciences · INJawaharlal Nehru University · IN

Funding

Indian Council of Medical Research 5/3/8/13/ITR-F/2018-ITRIndian Council of Medical Research BMI/11(89)/2020Science and Engineering Research Board DST/INSPIRE/03/2016/000026
6 · The paper itself

Abstract

COVID-19 is a sneaking deadly disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The rapid increase in the number of infected patients worldwide enhances the exigency for medicines. However, precise therapeutic drugs are not available for COVID-19; thus, exhaustive research is critically required to unscramble the pathogenic tools and probable therapeutic targets for the development of effective therapy. This study utilizes a chemogenomics strategy, including computational tools for the identification of viral-associated differentially expressed genes (DEGs), and molecular docking of potential chemical compounds available in antiviral, anticancer, and natural product-based libraries against these DEGs. We scrutinized the messenger RNA expression profile of SARS-CoV-2 patients, publicly available on the National Center for Biotechnology Information-Gene Expression Omnibus database, stratified them into different groups based on the severity of infection, superseded by identification of overlapping mild and severe infectious (MSI)-DEGs. The profoundly expressed MSI-DEGs were then subjected to trait-linked weighted co-expression network construction and hub module detection. The hub module MSI-DEGs were then exposed to enrichment (gene ontology + pathway) and protein-protein interaction network analyses where Rho guanine nucleotide exchange factor 1 (ARHGEF1) gene conjectured in all groups and could be a probable target of therapy. Finally, we used the molecular docking and molecular dynamics method to identify inherent hits against the ARHGEF1 gene from antiviral, anticancer, and natural product-based libraries. Although the study has an identified significant association of the ARHGEF1 gene in COVID19; and probable compounds targeting it, using in silico methods, these targets need to be validated by both in vitro and in vivo methods to effectively determine their therapeutic efficacy against the devastating virus.

Indexed as

COVID-19COVID-19 Drug TreatmentGene OntologyHumansMolecular Docking SimulationRho Guanine Nucleotide Exchange FactorsSARS-CoV-2ARHGEF1 protein, humanRho Guanine Nucleotide Exchange FactorsARHGEF1gene co-expression networkmolecular dockingmolecular dynamicsMSI-DEGsSARS-CoV-2

Identifiers

PMID35037717
PMCPMC9015317
OpenAlexW4205552009

What OpenQuestion holds

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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.