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Record W2075989457 · doi:10.1021/ml500420y

Minor Structural Change to Tertiary Sulfonamide RORc Ligands Led to Opposite Mechanisms of Action

2014· article· en· W2075989457 on OpenAlexfundno aff
Olivier René, Benjamin P. Fauber, Gladys de Leon Boenig, Brenda Burton, Céline Eidenschenk, Christine Everett, Alberto Gobbi, S.G. Hymowitz, Adam R. Johnson, James R. Kiefer, Marya Liimatta, Peter Lockey, Maxine Norman, Wenjun Ouyang, Heidi Ackerly Wallweber, Harvey Wong

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2014
Typearticle
Languageen
FieldChemistry
TopicChemical Synthesis and Reactions
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesWestern Economic Diversification CanadaBasic Energy SciencesCanadian Light SourceNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Institutes of HealthUniversity of SaskatchewanU.S. Department of EnergyOffice of ScienceGenentechHoward Hughes Medical Institute
KeywordsSulfonamideChemistryStereochemistryMedicine

Abstract

fetched live from OpenAlex

A minor structural change to tertiary sulfonamide RORc ligands led to distinct mechanisms of action. Co-crystal structures of two compounds revealed mechanistically consistent protein conformational changes. Optimized phenylsulfonamides were identified as RORc agonists while benzylsulfonamides exhibited potent inverse agonist activity. Compounds behaving as agonists in our biochemical assay also gave rise to an increased production of IL-17 in human PBMCs whereas inverse agonists led to significant suppression of IL-17 under the same assay conditions. The most potent inverse agonist compound showed >180-fold selectivity over the ROR isoforms as well as all other nuclear receptors that were profiled.

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 score0.003
Threshold uncertainty score0.010

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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

Citations82
Published2014
Admission routes1
Has abstractyes

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Same venueACS Medicinal Chemistry LettersSame topicChemical Synthesis and ReactionsFrench-language works237,207