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Record W2024457305 · doi:10.1002/cbic.200790020

Cover Picture: In Vivo Screening Identifies a Highly Folded β‐Hairpin Peptide with a Structured Extension (ChemBioChem 8/2007)

2007· paratext· en· W2024457305 on OpenAlexaff
Zihao Cheng, Mark Miskolzie, Robert E. Campbell

Bibliographic record

VenueChemBioChem · 2007
Typeparatext
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFörster resonance energy transferPeptideGreen fluorescent proteinFluorescenceCyanFusion proteinYellow fluorescent proteinBiologyProtein tagBiophysicsComputational biologyRecombinant DNABiochemistryChemistryPhysicsGene

Abstract

fetched live from OpenAlex

The cover picture shows the NMR‐derived structure of a β‐hairpin peptide that was identified through a fluorescence‐based screen in live cells. A Petri dish covered in colonies of E. coli expressing recombinant fluorescent proteins was illuminated by ultraviolet light. Each bacterial colony expresses a single protein composed of a tandem fusion of a cyan (CFP) and a yellow (YFP) fluorescent protein. As shown in ribbon representations, peptide sequences are fused between these CFP and YFP units. Peptides that fold into β‐hairpin structures tend to bring the two fluorescent proteins into closer proximity, and thus a higher FRET signal is observed. Residues in the green portions of the peptides were randomized to create libraries of many hundreds of variants, and the peptide sequence that provided the highest FRET efficiency was identified by FRET‐based screening of bacterial colonies. The 3D structure of this peptide revealed that the selected residues participated in a cross‐strand cation–π interaction that held the ends of the peptide closer together. More details can be found in the article by Robert E. Campbell et al. on p. 880 ff. (Image credit: Annie Tykwinski and R.E.C.)

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 categoriesMeta-epidemiology (narrow), Research integrity, 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 score0.131
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
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 head0.008
GPT teacher head0.238
Teacher spread0.229 · 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.

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

Citations0
Published2007
Admission routes1
Has abstractyes

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