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Design, Synthesis and Pharmacological Characterization of Endomorphin Analogues with Non‐Cyclic Amino Acid Residues in Position 2

2009· article· en· W1984328121 on OpenAlexaff
Renata Perlikowska, Jakub Fichna, Anna Wyrębska, Jeroen Poels, Jozef Vanden Broeck, Géza Tóth, Martin Storr, Jean‐Claude do Rego, Anna Janecka

Bibliographic record

VenueBasic & Clinical Pharmacology & Toxicology · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuropeptides and Animal Physiology
Canadian institutionsUniversity of Calgary
FundersVlaamse regeringUniwersytet ŁódzkiCentre National de la Recherche Scientifique
KeywordsCyclic peptideIn vivoSarcosineChemistryAmino acidStereochemistryPeptideOpioid peptideIn vitroEnkephalinAminopeptidaseBiochemistryOpioidReceptorLeucineGlycineBiology

Abstract

fetched live from OpenAlex

A series of endomorphin-1 (EM-1) and endomorphin-2 (EM-2) analogues, containing non-cyclic amino acids (Ala, D-Ala, beta-Ala, NMeAla, D-NMeAla or Sar) instead of Pro in position 2 was synthesized, where NMeAla = N-methylalanine and Sar = N-methylglycine, sarcosine. The opioid activity profiles of these peptides were determined in mu and delta opioid receptor (MOR and DOR)-representative binding assays and bioassays in vitro, as well as in the mouse hot-plate test in vivo. Finally, the degradation rates of all analogues in the presence of either rat brain homogenate or selected proteolytic enzymes were determined. Analogues of EM-2 were generally more potent than the respective analogues of EM-1. EM-2 analogues with D-Ala or D-NMeAla were about twofold more potent than the parent peptide and were least prone to degradation by brain homogenate, dipeptydyl peptidase IV and aminopeptidase M. In the in vivo test, [D-Ala(2)]EM-2 and [D-NMeAla(2)]EM-2 showed much higher analgesic potency than EM-2 which confirmed the usefulness of structural modifications in obtaining new leads for pain-relief therapeutics.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.069
GPT teacher head0.349
Teacher spread0.281 · 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

Citations17
Published2009
Admission routes1
Has abstractyes

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