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Record W2321444872 · doi:10.1055/s-0033-1348561

Semi-Synthesis of a Biologically Inspired Library of Natural Product Mimics, from the Lipophilic Marine Natural Product β-Gorgonene

2013· article· en· W2321444872 on OpenAlexaff
Bradley C. Pearce, Russell G. Kerr

Bibliographic record

VenuePlanta Medica · 2013
Typearticle
Languageen
FieldChemistry
TopicAxial and Atropisomeric Chirality Synthesis
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsNatural productBiological activityCombinatorial chemistryChemistryDrug discoveryCycloadditionTotal synthesisBiotransformationOrganic chemistryStereochemistryBiochemistryCatalysisIn vitroEnzyme

Abstract

fetched live from OpenAlex

Inspired by ilimaquinone and other biologically active sesquiterpenes, we have transformed a highly lipophilic, non-drug-like, marine natural product (gorgonene), available as a by-product from the purification of pseudopterosins, into a library of more drug-like derivatives. Our strategy utilizes semi-synthesis to attach suitable structures such as substituted aromatics and heteroaromatics to the gorgonene scaffold to increase its drug-likeness and mimic natural product structures in biological systems. Several synthetic techniques are being explored to incorporate these interesting substructures in a minimum number of steps. The first strategy focuses on skeletal rearrangements and 2+3 cycloaddition. The second involves ozonolysis of gorgonene followed by introduction of structures using carbonyl chemistry. Biotransformation is being used as a third strategy to selectively oxidize synthetically inaccessible carbons on the saturated backbone to facilitate further transformations. The PTP1B (potential therapeutic target for treatment of type 2 diabetes) and cytotoxic activity of the synthesized compounds will be discussed as well as some unexpected and interesting reactivity we have observed in the 1,5-diene system present in our starting scaffold, β-gorgonene.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.187
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.188
Teacher spread0.179 · 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
Published2013
Admission routes1
Has abstractyes

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