Evidence map›Paper›PMID 40166473›Full record

ArticleFrontiers in pharmacology2025

FDA-approved drug repurposing screen identifies inhibitors of SARS-CoV-2 pseudovirus entry.

Manisha Singh, Shruthi Shanmukha, Raghda E Eldesouki, Maged M Harraz

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 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. 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

4 authors.

Manisha SinghDepartment of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States.
Shruthi ShanmukhaDepartment of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Raghda E EldesoukiGenetics Unit, Histology Department, Faculty of Medicine, Suez Canal University, Ismailia, Egypt.
Maged M HarrazDepartment of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: The coronavirus disease 2019 (COVID-19) pandemic has devastated global health and the economy, underscoring the urgent need for extensive research into the mechanisms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral entry and the development of effective therapeutic interventions. Experimental approach: We established a cell line expressing human angiotensin-converting enzyme 2 (ACE2). We used it as a model of pseudotyped viral entry using murine leukemia virus (MLV) expressing SARS-CoV-2 spike (S) protein on its surface and firefly luciferase as a reporter. We screened an U.S. Food and Drug Administration (FDA)-approved compound library for inhibiting ACE2-dependent SARS-CoV-2 pseudotyped viral entry and identified several drug-repurposing candidates. Key results: We identified 18 drugs and drug candidates, including 14 previously reported inhibitors of viral entry and four novel candidates. Pyridoxal 5'-phosphate, Dovitinib, Adefovir dipivoxil, and Biapenem potently inhibit ACE2-dependent viral entry with inhibitory concentration 50% (IC Conclusion and implications: We identified four novel FDA-approved candidate drugs for anti-SARS-CoV-2 combination therapy. Our findings contribute to the growing body of evidence supporting drug repurposing as a viable strategy for rapidly developing COVID-19 treatments.

Indexed as

ACE2 (angiotensin converting enzyme 2)COVID-19drug repurposingFDA approved drug libraryhigh-throughput screeningSARS-CoV-2tmprss2viral entry

Identifiers

PMID40166473
PMCPMC11955658

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.