Evidence map›Paper›PMID 41219276›Full record

ArticleScientific reports2025

In-silico discovery of druggable molecular signatures that drive dengue fever to severe dengue fever highlighting common pathogenesis through single-cell RNA-Seq analysis.

Md Al Noman, Md Abdul Latif, Md Foysal Ahmed, Md Shariful Islam, Md Al Amin Pappu, Md Sanoar Hossain, Md Bayazid Hossen, Tasfia Noor, Md Manir Hossain Mollah, Md Hadiul Kabir and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Md Al NomanBioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
Md Abdul LatifBioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
Md Foysal AhmedBioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
Md Shariful IslamBioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
Md Al Amin PappuBioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
Md Sanoar HossainBioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
Md Bayazid HossenDepartment of Agricultural and Applied Statistics, Bangladesh Agricultural University, Mymensingh, 2202, Bangladesh.
Tasfia NoorDepartment of Computer Science and Engineering (CSE), Rajshahi University of Engineering and Technology (RUET), Rajshahi, 6203, Bangladesh.
Md Manir Hossain MollahDepartment of Physical Sciences, Independent University, Bangladesh (IUB), Dhaka, Bangladesh.
Md Hadiul KabirBioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
Md Nurul Haque MollahBioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh. mollah.stat.bio@ru.ac.bd.

Funding

Ministry of science and technology (MoST) research project , Govt. of Bangladesh Project IDs: SRG-234567-ID, and SRG-244407-ID, 2023-2025
6 · The paper itself

Abstract

Dengue, also known as dengue fever (DF), is an infection spread by mosquitoes. It infects over 400 million people globally each year. Sometimes DF progresses to severe DF (sDF) for which patients suffer from life-threatening complications including internal bleeding, failure of cardiovascular systems and death. Although DF is a severe threat to human life, its diagnosis and therapeutic strategies have not yet reached a satisfactory level. In order to address these issues, at first, this study identified six key cell-types (myeloid dendritic cells (DCs), memory B cells, naive B cells, memory CD4 T cells, plasmacytoid DCs, and plasmablasts) associated with both DF and sDF by integrating two single-cell RNA-Seq (scRNA-seq) profile datasets (GSE220969 and GSE154386) and cell-cell communication (CCC) analyses. Top-ranked nine common host key genes (SYK, CYBB, SOCS3, HSPA5, IRF7, NFKB1, IL-6, ISG15, and TNFSF13B) were identified from the selected cell types through differential expression patterns and protein-protein interaction (PPI) network analyses, assuming their potential involvement in the development and progression of DF and sDF. The enrichment analysis of common host key-genes (chKGs) with gene ontology (GO) terms and KEGG-pathways disclosed molecular mechanisms about how chKGs are associated with the development and progression of DF to sDF. Finally, chKGs-guided three candidate drug agents (Entrectinib, Imatinib, and QL47) were recommended against dengue virus infection (DENVI) through molecular docking, drug-likeness screening, ADME/T analysis, DFT analysis. Therefore, the findings of this study may provide valuable insights for diagnosis and therapies against DENVI.

Indexed as

DengueSevere DengueSingle-Cell AnalysisComputer SimulationDendritic CellsDengue VirusDrug DiscoveryHumansProtein Interaction MapsRNA-SeqSingle-Cell Gene Expression AnalysisBioinformatics analysisDengue virus infectionDrug repurposingInfection-causing key genesSingle-cell RNA-Seq profiles

Identifiers

PMID41219276
PMCPMC12606108

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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.