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Record W4388084768 · doi:10.1016/j.virol.2023.109915

Broad spectrum post-entry inhibitors of coronavirus replication: Cardiotonic steroids and monensin

2023· article· en· W4388084768 on OpenAlexaff
Shahrzad Jahanshahi, Hong Ouyang, C. M. Sabbir Ahmed, Ali Zahedi‐Amiri, Subha Dahal, Yu-Qian Mao, David A. J. Van Ommen, Ramy Malty, Wenming Duan, Terek Been, Maria Mangos, Mohan Babu, Liliana Attisano, Walid A. Houry, Theo J. Moraes, Alan Cochrane

Bibliographic record

VenueVirology · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of ReginaHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMonensinDigitoxinOuabainBiologyViral replicationCoronavirusViral entryVirusVirologyPharmacologyCell biologyDigoxinChemistryBiochemistryCoronavirus disease 2019 (COVID-19)Internal medicineMedicine

Abstract

fetched live from OpenAlex

A small molecule screen identified several cardiotonic steroids (digitoxin and ouabain) and the ionophore monensin as potent inhibitors of HCoV-229E, HCoV-OC43, and SARS-CoV-2 replication with EC50s in the low nM range. Subsequent tests confirmed antiviral activity in primary cell models including human nasal epithelial cells and lung organoids. Addition of digitoxin, ouabain, or monensin strongly reduced viral gene expression as measured by both viral protein and RNA accumulation. Furthermore, the compounds acted post virus entry. While the antiviral activity of digitoxin was dependent upon activation of the MEK and JNK signaling pathways but not signaling through GPCRs, the antiviral effect of monensin was reversed upon inhibition of several signaling pathways. Together, the data demonstrates the potent anti-coronavirus properties of two classes of FDA approved drugs that function by altering the properties of the infected cell, rendering it unable to support virus replication.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.346
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2023
Admission routes1
Has abstractyes

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