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A Retrospective Look at the Impact of Binding Site Environment on the Optimization of TRPA1 Antagonists

2021· article· en· W3186435586 on OpenAlexaff
Elisia Villemure, Jack A. Terrett, Robin Larouche‐Gauthier, Martin Déry, Huifen Chen, Rebecca M. Reese, Shannon D. Shields, Jun Chen, Steven Magnuson, Matthew Volgraf

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2021
Typearticle
Languageen
FieldNeuroscience
TopicIon Channels and Receptors
Canadian institutionsParaza Pharma (Canada)
Fundersnot available
KeywordsAntagonistBinding siteSulfonamideChemistryDrug discoveryPharmacologyBiophysicsMedicineReceptorBiochemistryBiologyStereochemistry

Abstract

fetched live from OpenAlex

Transient receptor potential ankyrin 1 (TRPA1) antagonists have generated broad interest in the pharmaceutical industry for the treatment of both pain and asthma. Over the past decade, multiple antagonist classes have been reported in the literature with a wide range of structural diversity. Our own work has focused on the development of proline sulfonamide and hypoxanthine-based antagonists, two antagonist classes with distinct physicochemical properties and pharmacokinetic (PK) trends. Late in our discovery program, cryogenic electron microscopy (cryoEM) studies revealed two different antagonist binding sites: a membrane-exposed proline sulfonamide transmembrane site and an intracellular hypoxanthine site near the membrane interface. A retrospective look at the discovery program reveals how the different binding sites, and their location relative to the cell membrane, influenced the optimization trajectories and overall drug profiles of each antagonist class.

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 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 score0.013
Threshold uncertainty score0.783

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 communication0.0000.000
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 head0.016
GPT teacher head0.246
Teacher spread0.231 · 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

Citations19
Published2021
Admission routes1
Has abstractyes

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