MétaCan
Menu
Back to cohort
Record W4407597776 · doi:10.1016/j.mib.2025.102584

Targeted isolation of piperazate-containing molecules: bioinformatics and spectroscopy

2025· review· en· W4407597776 on OpenAlexafffund
Mostafa Hagar, Sangwook Kang, Raymond J. Andersen, Dong‐Chan Oh, Katherine S. Ryan

Bibliographic record

VenueCurrent Opinion in Microbiology · 2025
Typereview
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsUniversity of British Columbia HospitalUniversity of British ColumbiaSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyIsolation (microbiology)Computational biologyBioinformaticsMicrobiology

Abstract

fetched live from OpenAlex

Piperazic acid (Piz) is an intriguing hydrazine-containing amino acid found in a diverse variety of natural products, the majority of which are bioactive. Recently, several approaches have been reported for targeted isolation of Piz-containing molecules, combining spectroscopic techniques for screening Piz moieties with recent advances in Piz biosynthesis. Here, we highlight bioactive natural products recently isolated using these methods and bring into focus structural elucidation challenges impeding the discovery of more Piz-containing molecules.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.049
GPT teacher head0.389
Teacher spread0.339 · 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 designOther design
Domainnot available
GenreReview

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

Citations4
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueCurrent Opinion in MicrobiologySame topicComputational Drug Discovery MethodsFrench-language works237,207