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Record W2173701041 · doi:10.1517/13543776.2016.1115836

Transglutaminase inhibitors: a patent review

2015· review· en· W2173701041 on OpenAlexaff
Jeffrey W. Keillor, Kim Yang-Ping Apperley

Bibliographic record

VenueExpert Opinion on Therapeutic Patents · 2015
Typereview
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTissue transglutaminaseDeamidationGlutamineEnzymeDiseaseGTP'CancerBiochemistryPharmacologyChemistryMedicineBiologyCancer researchAmino acidInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Transglutaminases (TGases) are a class of enzymes that play multifunctional roles. Their protein-crosslinking activity has been linked to fibrosis and Huntington's disease, their glutamine deamidation activity has been related to celiac disease and their GTP-binding activity has been implicated in cancer. All of these physiological disorders have prompted the development of inhibitors, which has accelerated dramatically over the past decade. AREAS COVERED: This review presents an overview of TGase inhibitors published in the patent literature, from the first compounds developed in the late 1980's, to the current date. This article is focussed on the chemical structure of new inhibitors and their probable mechanism of action. EXPERT OPINION: Comparison of effective TGase inhibitors reveals common structural features that may guide future design. Many of these elements are embodied in the first TGase inhibitor to recently enter into clinical trials.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.004

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 head0.349
GPT teacher head0.418
Teacher spread0.069 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations46
Published2015
Admission routes1
Has abstractyes

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