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Record W4407821252 · doi:10.1016/j.bmcl.2025.130137

N-alkyl substituted armeniaspirol analogs show potent antibiotic activity and have low susceptibility to resistance

2025· article· en· W4407821252 on OpenAlexafffund
Michael G. Darnowski, Taylor D. Lanosky, Antonio D Spada, Jason Ma, André R. Paquette, Christopher N. Boddy

Bibliographic record

VenueBioorganic & Medicinal Chemistry Letters · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryAlkylAntibioticsStereochemistryChemical synthesisAntibacterial agentAntibiotic resistanceStructure–activity relationshipPharmacologyIn vitroBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

• Eleven N -alkyl armenialspirol analogs were synthesized successful. • Analogs potently inhibited growth of multiple MRSA strains. • Four electron rich N -benyzl analogs rearranged to form a new polycyclic core. • Resistance MRSA strains could not be generated from potent new compounds. The armeniaspirol family of antibiotics have been shown to inhibit the ATP-dependent proteases ClpXP and ClpYQ and to disrupt the electrical membrane potential (ΔΨ) bacterial proton motive force. The synthesis and characterization of first generation armeniaspirol analogs shows the N -alkyl group is amenable to modification. Herein we synthesize eleven second generation N -alkyl analogs and show they display excellent antibiotic potency against multiple MRSA strains and retain the ability to disrupt membrane electrical potential. We also show that it is difficult to generate resistant MRSA mutants to these new compounds, making them appealing leads for new antibiotic development.

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 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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.218
Teacher spread0.212 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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