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Sweet drugs Against Bad Bugs: Naphthoquinone-fused Enediyne Sugar Polysulfates for Nanomolar Inhibition of Coronavirus

2024· preprint· en· W4399922593 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldChemistry
TopicCyclization and Aryne Chemistry
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsEnediyneCoronavirusChemistryCoronavirus disease 2019 (COVID-19)VirologyViral entryPharmacologyBiologyBiochemistryMedicineStereochemistryInfectious disease (medical specialty)VirusViral replication

Abstract

fetched live from OpenAlex

It has been four years since the emergence of the COVID-19 pandemic, and the ongoing threat it poses to human health and life un-derscores the continued need for the development of antiviral medications as a means of mitigating future viral outbreaks. In this study, we present a novel class of antiviral compounds known as naphthoquinone-fused enediyne sugar polysulfates, which have demonstrated efficacy against coronaviruses by targeting the conserved receptor binding domain on spike proteins. These compounds induce irreversible damage to the viral structure, resulting in inhibition of viral infection at nanomolar concentrations with minimal cytotoxic effects. Notably, the selectivity index of these compounds exceeds 50,000, suggesting significant potential for further de-velopment in antiviral therapeutics against coronavirus.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.277
Teacher spread0.258 · 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

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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