MétaCan
Menu
Back to cohort
Record W4300064496 · doi:10.17615/n3j0-fz94

Structural basis for bifunctional peptide recognition at human δ-opioid receptor

2020· article· en· W4300064496 on OpenAlexfundno aff
Jesse Coe, Vadim Cherezov

Bibliographic record

VenueUNC Libraries · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeuropeptides and Animal Physiology
Canadian institutionsnot available
FundersBasic Energy SciencesBundesministerium für Bildung und ForschungNational Institute of General Medical SciencesNational Institute of Mental HealthNational Science FoundationCanadian Institutes of Health ResearchVlaamse regeringFonds Wetenschappelijk OnderzoekDeutsche ForschungsgemeinschaftU.S. Department of EnergyNational Cancer InstituteNational Institutes of Health
KeywordsBifunctionalPeptideBasis (linear algebra)ChemistryNeurosciencePsychologyBiochemistryMathematics

Abstract

fetched live from OpenAlex

Bi-functional μ- and δ- opioid receptor (OR) ligands are potential therapeutic alternatives to alkaloid opiate analgesics with diminished side effects. We solved the structure of human δ-OR bound to the bi-functional δ-OR antagonist and μ-OR agonist tetrapeptide H-Dmt(1)-Tic(2)-Phe(3)-Phe(4)-NH2 (DIPP-NH2) by serial femtosecond crystallography, revealing a cis-peptide bond between H-Dmt(1) and Tic(2). The observed receptor-peptide interactions are critical to understand the pharmacological profiles of opioid peptides, and to develop improved analgesics.

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)0.000
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 score0.094
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.252
Teacher spread0.157 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueUNC LibrariesSame topicNeuropeptides and Animal PhysiologyFrench-language works237,207