Evidence map›Paper›PMID 39024368›Full record

ArticlePloS one2024

In-silico discovery of common molecular signatures for which SARS-CoV-2 infections and lung diseases stimulate each other, and drug repurposing.

Muhammad Habibulla Alamin, Md Matiur Rahaman, Farzana Ferdousi, Arnob Sarker, Md Ahad Ali, Md Bayazid Hossen, Bandhan Sarker, Nishith Kumar, Md Nurul Haque Mollah

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Discovery of novel repurposed anthelminthics againstCurrent research in parasitology & vector-borne diseases · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. 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

9 authors.

Muhammad Habibulla AlaminFaculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh.
Md Matiur RahamanFaculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh.ORCID 0000-0001-9799-9364
Farzana FerdousiFaculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh.
Arnob SarkerFaculty of Science, Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi, Bangladesh.
Md Ahad AliFaculty of Science, Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh.
Md Bayazid HossenFaculty of Science, Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh.
Bandhan SarkerFaculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh.
Nishith KumarFaculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh.
Md Nurul Haque MollahFaculty of Science, Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh.ORCID 0000-0002-3883-3396

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 caused by SARS-CoV-2 is a global health issue. It is yet a severe risk factor to the patients, who are also suffering from one or more chronic diseases including different lung diseases. In this study, we explored common molecular signatures for which SARS-CoV-2 infections and different lung diseases stimulate each other, and associated candidate drug molecules. We identified both SARS-CoV-2 infections and different lung diseases (Asthma, Tuberculosis, Cystic Fibrosis, Pneumonia, Emphysema, Bronchitis, IPF, ILD, and COPD) causing top-ranked 11 shared genes (STAT1, TLR4, CXCL10, CCL2, JUN, DDX58, IRF7, ICAM1, MX2, IRF9 and ISG15) as the hub of the shared differentially expressed genes (hub-sDEGs). The gene ontology (GO) and pathway enrichment analyses of hub-sDEGs revealed some crucial common pathogenetic processes of SARS-CoV-2 infections and different lung diseases. The regulatory network analysis of hub-sDEGs detected top-ranked 6 TFs proteins and 6 micro RNAs as the key transcriptional and post-transcriptional regulatory factors of hub-sDEGs, respectively. Then we proposed hub-sDEGs guided top-ranked three repurposable drug molecules (Entrectinib, Imatinib, and Nilotinib), for the treatment against COVID-19 with different lung diseases. This recommendation is based on the results obtained from molecular docking analysis using the AutoDock Vina and GLIDE module of Schrödinger. The selected drug molecules were optimized through density functional theory (DFT) and observing their good chemical stability. Finally, we explored the binding stability of the highest-ranked receptor protein RELA with top-ordered three drugs (Entrectinib, Imatinib, and Nilotinib) through 100 ns molecular dynamic (MD) simulations with YASARA and Desmond module of Schrödinger and observed their consistent performance. Therefore, the findings of this study might be useful resources for the diagnosis and therapies of COVID-19 patients who are also suffering from one or more lung diseases.

Indexed as

COVID-19COVID-19 Drug TreatmentDrug RepositioningLung DiseasesSARS-CoV-2Antiviral AgentsComputer SimulationGene Regulatory NetworksHumansMolecular Docking SimulationAntiviral Agents

Identifiers

PMID39024368
PMCPMC11257407

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Registered trials

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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.