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Potent Opioid Peptide Agonists Containing 4′‐[<i>N</i>‐((4′‐phenyl)‐phenethyl)carboxamido]phenylalanine (Bcp) in Place of Tyr

2008· article· en· W1980866072 on OpenAlexaff
Grazyna Weltrowska, Thi M.‐D. Nguyen, Carole Lemieux, Nga N. Chung, Peter W. Schiller

Bibliographic record

VenueChemical Biology & Drug Design · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuropeptides and Animal Physiology
Canadian institutionsMontreal Clinical Research Institute
FundersNational Institute on Drug AbuseNational Institutes of Health
KeywordsChemistryDynorphinStereochemistryDynorphin AAgonistNociceptin receptorOpioid peptidePeptideOpioid receptorReceptorPhenylalanineSubstituentPartial agonistOpioidBiochemistryAmino acid

Abstract

fetched live from OpenAlex

Analogues of the opioid peptides H-Tyr-c[D-Cys-Gly-Phe(pNO2)-D-Cys]NH2 (non-selective), H-Tyr-D-Arg-Phe-Lys-NH2 (mu-selective) and dynorphin A(1-11)-NH2 (kappa-selective) containing 4'-[N-((4'-phenyl)-phenethyl)carboxamido]phenylalanine (Bcp) in place of Tyr1 were synthesized. All three Bcp1-opioid peptides retained high mu opioid receptor binding affinity, but showed very significant differences in the opioid receptor selectivity profiles as compared with the corresponding Tyr1-containing parent peptides. The cyclic peptide HBcp-c[D-Cys-Gly-Phe(pNO2)-D-Cys]NH2 turned out to be an extraordinarily potent, mu-selective opioid agonist, whereas the Bcp1-analogue of dynorphin A(1-11)-NH2 displayed partial agonism at the mu receptor. The obtained results suggest that the large biphenylethyl substituent contained in these compounds may engage in a hydrophobic interaction with a receptor subsite and thereby may play a role in the ligand's ability to induce a specific receptor conformation or to bind to a distinct receptor conformation in a situation of conformational receptor heterogeneity.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.042
GPT teacher head0.254
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 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

Citations7
Published2008
Admission routes1
Has abstractyes

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