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Record W4388655361 · doi:10.3390/molecules28227579

Therapies from Thiopeptides

2023· review· en· W4388655361 on OpenAlexafffund
Hee-Jong Hwang, Marco A. Ciufolini

Bibliographic record

VenueMolecules · 2023
Typereview
Languageen
FieldChemistry
TopicCarbohydrate Chemistry and Synthesis
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaShionogiKorea Health Industry Development InstituteCanada Research ChairsUniversity of LeicesterUniversity of British ColumbiaRice UniversityNational Institutes of HealthNational Science Foundation
KeywordsComputational biologyComputer scienceBiology

Abstract

fetched live from OpenAlex

The first part of this contribution describes solutions that were developed to achieve progressively more efficient syntheses of the thiopeptide natural products, micrococcins P1 and P2 (MP1–MP2), with an eye toward exploring their potential as a source of new antibiotics. Such efforts enabled investigations on the medicinal chemistry of those antibiotics, and inspired the development of the kinase inhibitor, Masitinib®, two candidate oncology drugs, and new antibacterial agents. The studies that produced such therapeutic resources are detailed in the second part. True to the theme of this issue, “Organic Synthesis and Medicinal Chemistry: Two Inseparable Partners”, an important message is that the above advances would have never materialized without the support of curiosity-driven, academic synthetic organic chemistry: a beleaguered science that nonetheless has been—and continues to be—instrumental to progress in the biomedical field.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.004

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 head0.075
GPT teacher head0.309
Teacher spread0.234 · 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 designNot applicable
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

Citations3
Published2023
Admission routes2
Has abstractyes

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