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Record W2094814259 · doi:10.1021/jo060485v

Screening for Galectin-3 Inhibitors from Synthetic Lacto-<i>N</i>-biose Libraries Using Microscale Affinity Chromatography Coupled to Mass Spectrometry

2006· article· en· W2094814259 on OpenAlexaff
Sébastien Fort, H.S. Kim, O. Hindsgaul

Bibliographic record

VenueThe Journal of Organic Chemistry · 2006
Typearticle
Languageen
FieldImmunology and Microbiology
TopicGalectins and Cancer Biology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChemistryMicroscale chemistryChromatographyMass spectrometryCombinatorial chemistry

Abstract

fetched live from OpenAlex

The synthesis and screening of two beta-D-Galp-(1-3)-beta-d-GlcpN (lacto-N-biose) disaccharide libraries are reported. Solution-phase synthetic modifications at the HO-2' and NH positions were performed in an effort to enhance the affinity toward galectin-3, a galactose-binding protein involved in tumor metastasis, apoptosis, and inflammation. The libraries were screened for galectin-3 binding by microscale frontal affinity chromatography coupled to mass spectrometry (FAC/MS) allowing for rapid ranking of the different inhibitors and the determination of the galectin-3 binding Kd's. Compounds bearing a hydrophobic substituent on the NH group showed the highest affinity for the lectin. The N-naphthoyl derivative (Kd = 10.6 microM) was the best inhibitor with a 7 times increased affinity as compared to the N-acetyl parent compound (Kd = 73.3 microM).

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.001

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 head0.010
GPT teacher head0.217
Teacher spread0.208 · 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

Citations37
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Organic ChemistrySame topicGalectins and Cancer BiologyFrench-language works237,207