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Record W1983115893 · doi:10.1021/ml300263x

A New Approach to Explore the Binding Space of Polysaccharide-Based Ligands: Selectin Antagonists

2012· article· en· W1983115893 on OpenAlexafffund
Mickael Calosso, Daniel Charpentier, Marc Vaillancourt, Mohammed Bencheqroun, Gabrielle St‐Pierre, Brian C. Wilkes, Yvan Guindon

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2012
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPolysaccharideSpace (punctuation)Computer scienceComputational biologyChemistryCombinatorial chemistryBiochemistryBiology

Abstract

fetched live from OpenAlex

The discovery of molecules that interfere with the binding of a ligand to a receptor remains a topic of great interest in medicinal chemistry. Herein, we report that a monosaccharide unit of a polysaccharide ligand can be replaced advantageously by a conformationally locked acyclic molecular entity. A cyclic component of the selectin ligand Sialyl Lewis(x), GlcNAc, is replaced by an acyclic tether, tartaric esters, which link two saccharide units. The conformational bias of this acyclic tether originates from the minimization of intramolecular dipole-dipole interaction and the gauche effect. The evaluation of the binding of these derivatives to P-selectin was measured by surface plasmon resonance spectroscopy. The results obtained in our pilot study suggest that the discovery of tunable tethers could facilitate the exploration of the carbohydrate recognition domain of various receptors.

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)0.0000.000
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)0.0010.000

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 head0.046
GPT teacher head0.309
Teacher spread0.262 · 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

Citations19
Published2012
Admission routes2
Has abstractyes

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Same venueACS Medicinal Chemistry LettersSame topicCell Adhesion Molecules ResearchFrench-language works237,207