MétaCan
Menu
Back to cohort
Record W3024478325 · doi:10.1080/07391102.2020.1768902

Potential anti-viral activity of approved repurposed drug against main protease of SARS-CoV-2: an <i>in silico</i> based approach

2020· letter· en· W3024478325 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

VenueJournal of Biomolecular Structure and Dynamics · 2020
Typeletter
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsCanadian Rural Health Research Society
Fundersnot available
KeywordsProteaseLopinavirVirologyRitonavirDrugDrug repositioningDocking (animal)CoronavirusPharmacologyChemistryBiologyCoronavirus disease 2019 (COVID-19)MedicineVirusViral loadEnzymeBiochemistryVeterinary medicine

Abstract

fetched live from OpenAlex

Ritonavir and Lopinavir. Additionally, Viomycin formed higher number of H-bonds with SARS-CoV-2 Main Protease than its co-crystallised inhibitor compound N3. Molecular dynamics simulation further showed that Viomycin embedded deeply inside the binding pocket and formed robust binding with SARS-CoV-2 Main Protease. Therefore, we propose that Viomycin may act as a potential inhibitor of the Main Protease of SARS-CoV-2. Further optimisations with the drug may support the much-needed rapid response to mitigate the pandemic.Communicated by Ramaswamy H. Sarma.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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