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Record W4401285048 · doi:10.1021/acs.jmedchem.4c00688

Expanding Structure–Activity Relationships of Human Urotensin II Peptide Analogues: A Proposed Key Role of the N-Terminal Region for Novel Urotensin II Receptor Modulators

2024· article· en· W4401285048 on OpenAlexaff
Francesco Merlino, Agnese Secondo, Emma Mitidieri, Raffaella Sorrentino, Rosa Bellavita, Nicola Grasso, David Chatenet, Anna Pannaccione, Paolo Grieco, Roberta d’Emmanuele di Villa Bianca, Alfonso Carotenuto

Bibliographic record

VenueJournal of Medicinal Chemistry · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular, Neuropeptides, and Oxidative Stress Research
Canadian institutionsInstitut National de la Recherche Scientifique
FundersRegione Campania
KeywordsUrotensin-IIChemistryPeptideKey (lock)ReceptorTerminal (telecommunication)BiochemistryBiologyEcology

Abstract

fetched live from OpenAlex

While the urotensinergic system plays a role in influencing various pathologies, its potential remains untapped because of the absence of therapeutically effective urotensin II receptor (UTR) modulators. Herein, we developed analogues of human urotensin II ( h U-II ) peptide in which, along with well-known antagonist-oriented modifications, the Glu 1 residue was subjected to single-point mutations. The generated library was tested by a calcium mobilization assay and ex vivo experiments, also in competition with selected ligands. Interestingly, many derivatives showed noncompetitive modulation that was rationalized by the lateral allostery concept applied to a G protein-coupled receptor (GPCR) multimeric model. UPG-108 showed an unprecedented ability to double the efficacy of h U-II, while UPG-109 and UPG-111 turned out to be negative allosteric modulators of UTR. Overall, our investigation will serve to explore and highlight the expanding possibilities of modulating the UTR system through N-terminally modified h U-II analogues and, furthermore, will aim to elucidate the intricate nature of such a GPCR system.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.041
GPT teacher head0.307
Teacher spread0.266 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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