Evidence map›Paper›PMID 35277538›Full record

ArticleScientific reports2022

Computational identification of host genomic biomarkers highlighting their functions, pathways and regulators that influence SARS-CoV-2 infections and drug repurposing.

Md Parvez Mosharaf, Md Selim Reza, Md Kaderi Kibria, Fee Faysal Ahmed, Md Hadiul Kabir, Sohel Hasan, Md Nurul Haque Mollah

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 3 pooled it
8.7field-weighted citation impact, top 2% 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

28 citing papers in PubMed, 3 syntheses or guidelines pooled it, 45 citations in OpenAlex.

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  18. Informatics in medicine unlocked · 2023
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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 1 institution in 2 countries.

Md Parvez Mosharaf *Bioinformatics Laboratory, Department of Statistics, Rajshahi University, Rajshahi, 6205, Bangladesh.
Md Selim Reza *Bioinformatics Laboratory, Department of Statistics, Rajshahi University, Rajshahi, 6205, Bangladesh.
Md Kaderi Kibria *Bioinformatics Laboratory, Department of Statistics, Rajshahi University, Rajshahi, 6205, Bangladesh.
Fee Faysal AhmedBioinformatics Laboratory, Department of Statistics, Rajshahi University, Rajshahi, 6205, Bangladesh.
Md Hadiul KabirBioinformatics Laboratory, Department of Statistics, Rajshahi University, Rajshahi, 6205, Bangladesh.
Sohel HasanDepartment of Biochemistry and Molecular Biology, Rajshahi University, Rajshahi, 6205, Bangladesh.
Md Nurul Haque MollahBioinformatics Laboratory, Department of Statistics, Rajshahi University, Rajshahi, 6205, Bangladesh. mollah.stat.bio@ru.ac.bd.
University of Rajshahi · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pandemic threat of COVID-19 has severely destroyed human life as well as the economy around the world. Although, the vaccination has reduced the outspread, but people are still suffering due to the unstable RNA sequence patterns of SARS-CoV-2 which demands supplementary drugs. To explore novel drug target proteins, in this study, a transcriptomics RNA-Seq data generated from SARS-CoV-2 infection and control samples were analyzed. We identified 109 differentially expressed genes (DEGs) that were utilized to identify 10 hub-genes/proteins (TLR2, USP53, GUCY1A2, SNRPD2, NEDD9, IGF2, CXCL2, KLF6, PAG1 and ZFP36) by the protein-protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of hub-DEGs revealed some important functions and signaling pathways that are significantly associated with SARS-CoV-2 infections. The interaction network analysis identified 5 TFs proteins and 6 miRNAs as the key regulators of hub-DEGs. Considering 10 hub-proteins and 5 key TFs-proteins as drug target receptors, we performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 FDA approved drugs. We found Torin-2, Rapamycin, Radotinib, Ivermectin, Thiostrepton, Tacrolimus and Daclatasvir as the top ranked seven candidate drugs. We investigated their resistance performance against the already published COVID-19 causing top-ranked 11 independent and 8 protonated receptor proteins by molecular docking analysis and found their strong binding affinities, which indicates that the proposed drugs are effective against the state-of-the-arts alternatives independent receptor proteins also. Finally, we investigated the stability of top three drugs (Torin-2, Rapamycin and Radotinib) by using 100 ns MD-based MM-PBSA simulations with the two top-ranked proposed receptors (TLR2, USP53) and independent receptors (IRF7, STAT1), and observed their stable performance. Therefore, the proposed drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections.

Indexed as

COVID-19 Drug TreatmentDrug RepositioningCase-Control StudiesCOVID-19Gene Regulatory NetworksGenetic MarkersHumansMolecular Docking SimulationProtein Interaction MapsSARS-CoV-2Genetic Markers

Identifiers

PMID35277538
PMCPMC8915158
OpenAlexW4220858019

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.