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Record W3116039732 · doi:10.1021/acs.jmedchem.0c01547

Structure–Activity Relationship and Bioactivity of Short Analogues of ELABELA as Agonists of the Apelin Receptor

2020· article· en· W3116039732 on OpenAlexafffund
Kien Trân, Alexandre Murza, Xavier Sainsily, Eugénie Delile, Pierre Couvineau, Jérôme Côté, David Coquerel, Maude Peloquin, Mannix Auger‐Messier, Michel Bouvier, Olivier Lesur, Philippe Sarret, Éric Marsault

Bibliographic record

VenueJournal of Medicinal Chemistry · 2020
Typearticle
Languageen
FieldMedicine
TopicApelin-related biomedical research
Canadian institutionsInstitute for Research in Immunology and CancerUniversité de MontréalUniversité de Sherbrooke
FundersFonds de Recherche du Québec - SantéCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaUniversité de SherbrookeCanadian Institutes of Health ResearchMitacsGovernment of CanadaHeart and Stroke Foundation of Canada
KeywordsApelinChemistryReceptorDocking (animal)StereochemistryIn vivoStructure–activity relationshipBiochemistryIn vitroBiologyGenetics

Abstract

fetched live from OpenAlex

ELABELA (ELA) is the second endogenous ligand of the apelin receptor (APJ). Although apelin-13 and ELA both target APJ, there is limited information on structure–activity relationship (SAR) of ELA. In the present work, we identified the shortest bioactive C-terminal fragment ELA23-32, which possesses high affinity for APJ (Ki 4.6 nM) and produces cardiorenal effects in vivo similar to those of ELA. SAR studies on conserved residues (Leu25, His26, Val29, Pro30, Phe31, Pro32) show that ELA and apelin-13 may interact differently with APJ. His26 and Val29 emerge as important for ELA binding. Docking and binding experiments suggest that Phe31 of ELA may bind to a tight groove distinct from that of Phe13 of Ape13, while the Phe13 pocket may be occupied by Pro32 of ELA. Further characterization of signaling profiles on the Gαi1, Gα12, and β-arrestin2 pathways reveals the importance of aromatic residue at the Phe31 or Pro32 position for receptor activation.

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)0.007
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 score0.108
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
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 science0.0000.000
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 head0.034
GPT teacher head0.319
Teacher spread0.285 · 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

Citations16
Published2020
Admission routes2
Has abstractyes

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