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Record W2060215666 · doi:10.1021/jm401779d

Synthesis and Structure–Activity Relationship Studies of N-Terminal Analogues of the Antimicrobial Peptide Tridecaptin A<sub>1</sub>

2014· article· en· W2060215666 on OpenAlexaff
Stephen A. Cochrane, Christopher T. Lohans, Jeremy R. Brandelli, George L. Mulvey, Glen D. Armstrong, John C. Vederas

Bibliographic record

VenueJournal of Medicinal Chemistry · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsChemistryAntimicrobialKlebsiella pneumoniaeCampylobacter jejuniEscherichia coliChemical synthesisStereochemistryStructure–activity relationshipPeptideBacteriaCombinatorial chemistryLipopeptideBiochemistryIn vitroOrganic chemistry

Abstract

fetched live from OpenAlex

Chemical synthesis was used to increase the potency of the antimicrobial lipopeptide tridecaptin A1. Lipid tail modification proved to be an ideal platform for synthesizing structurally simpler analogues that are not readily accessible by isolation. The stereochemical elements of the tridecaptin A1 lipid tail are not essential for antimicrobial activity and could be replaced with hydrophobic aliphatic or aromatic groups. Some simpler analogues displayed potent antimicrobial activity against Gram-negative bacteria, including Campylobacter jejuni, Escherichia coli O157:H7, and multidrug resistant Klebsiella pneumoniae.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.008
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.244
Teacher spread0.227 · 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

Citations72
Published2014
Admission routes1
Has abstractyes

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