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An automatic pipeline for the design of irreversible derivatives identifies a potent SARS-CoV-2 Mpro inhibitor

2021· article· en· W3174425309 on OpenAlexfundno aff
Daniel Zaidman, Paul Gehrtz, Mihajlo Filep, D. Fearon, Ronen Gabizon, A. Douangamath, Jaime Prilusky, Shirly Duberstein, Galit Cohen, David Owen, Efrat Resnick, Claire Strain‐Damerell, Petra Lukacik, Haim Barr, Martin Walsh, F. von Delft, Nir London

Bibliographic record

VenueCell chemical biology · 2021
Typearticle
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsnot available
FundersEshelman Institute for Innovation, University of North Carolina at Chapel HillHelen and Martin Kimmel Center for Molecular Design, Weizmann Institute of ScienceInnovative Medicines InitiativeMinistry of Science and Technology, IsraelWellcome TrustFundação de Amparo à Pesquisa do Estado de São PauloGenome CanadaBoehringer IngelheimTakeda Pharmaceutical CompanyEuropean Federation of Pharmaceutical Industries and AssociationsJanssen PharmaceuticalsMerck KGaAEuropean CommissionMeso Scale DiagnosticsPfizerNovartis PharmaCanada Foundation for InnovationOntario Ministry of Economic Development and InnovationIsrael Science FoundationIsrael Cancer Research Fund
KeywordsCovalent bondDocking (animal)ChemistryProtein Data Bank (RCSB PDB)Combinatorial chemistryCysteineEnzyme inhibitorStereochemistryComputational biologyEnzymeBiochemistryBiologyMedicineOrganic chemistry

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.004

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 head0.041
GPT teacher head0.301
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), 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

Citations87
Published2021
Admission routes1
Has abstractno

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