MétaCan
Menu
Back to cohort
Record W4393751478 · doi:10.5281/zenodo.6281992

Dipeptidyl peptidase 11 (PgDPP11); A Target Enabling Package

2022· dataset· en· W4393751478 on OpenAlexaff
Catherine Tham, Jesse A. Coker, William R. Foster, T. Krojer, Lizbe Koekomer, Yuko Ohara‐Nemoto, Takayuki Nemoto, Wyatt W. Yue, F. von Delft, G.A. Bezerra

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typedataset
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsDiscovery Centre
FundersWellcome
KeywordsDipeptidyl peptidaseR packageDipeptidyl peptidase-4ChemistryComputer scienceComputational biologyBiologyBiochemistryEnzymeEndocrinologyDiabetes mellitusType 2 diabetesComputational science

Abstract

fetched live from OpenAlex

<em>Porphyromonas</em> gingivalis (<em>P. gingivalis</em>) is the main causative agent of Periodontitis, the most widespread inflammatory condition world-wide. Recently this organism has been implicated in several systemic conditions, such as Alzheimer’s disease and type 2 diabetes. <em>P. gingivalis</em> does not ferment carbohydrates, instead it uses proteases to generate energy and carbon source. Dipeptidyl peptidase 11 plays a central role in the energy metabolism of this bacterium and has been proposed as an attractive drug target. This TEP provide early tools to develop inhibitors of PgDPP11, including purification protocols of recombinant proteins, a crystal structure of the protein in complex with a dipeptide, crystallisation conditions suitable for crystallography-based fragment screening, an inhibition assay and fragment hits in the active site and an allosteric site. These molecules provide a promising starting point for the development of more specific and potent PgDPP11 inhibitors.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.621
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.6350.014

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 head0.032
GPT teacher head0.267
Teacher spread0.235 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicPeptidase Inhibition and AnalysisFrench-language works237,207