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Record W1975298181 · doi:10.1002/cmdc.200800214

The Use of Chemical Double‐Mutant Cycles in Biomolecular Recognition Studies: Application to HCV NS3 Protease Inhibitors

2008· article· en· W1975298181 on OpenAlexaff
Stephen H. Kawai, Murray D. Bailey, Ted Halmos, Pat Forgione, Steven R. LaPlante, Montse Llinàs‐Brunet, Julie Naud, Natalie Goudreau

Bibliographic record

VenueChemMedChem · 2008
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsBoehringer Ingelheim (Canada)
Fundersnot available
KeywordsNS3ProteaseMutantComputational biologyHepatitis C virusChemistryProtease inhibitor (pharmacology)Ligand (biochemistry)VirologyBiochemistryBiologyEnzymeVirusReceptorGene

Abstract

fetched live from OpenAlex

Things don′t always add up: Our understanding of biomolecular recognition processes is often complicated by the fact that the binding contributions of individual ligand–protein subcontacts do not add up in a linear fashion. Chemical double-mutant cycles are useful analyses to quantify the degree of nonadditivity in such binding phenomena, and peptidyl inhibitors of hepatitis C virus NS3 protease are used to exemplify this.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.166
GPT teacher head0.369
Teacher spread0.203 · 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

Citations13
Published2008
Admission routes1
Has abstractyes

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