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Record W2901171758 · doi:10.1021/acs.jmedchem.8b01000

Bisphosphonate Inhibitors of Mammalian Glycolytic Aldolase

2018· article· en· W2901171758 on OpenAlexafffund
Paul Heron, Marta Abellán-Flos, L. Salmon, J. Sygusch

Bibliographic record

VenueJournal of Medicinal Chemistry · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversité de Montréal
FundersAgence Nationale de la RechercheNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsChemistryAldolase AGlycolysisBisphosphonateBiochemistryFructose-bisphosphate aldolaseEnzymeInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

The glycolytic enzyme aldolase is an emerging drug target in diseases such as cancer and protozoan infections which are dependent on a hyperglycolytic phenotype to synthesize adenosine 5'-triphosphate and metabolic precursors for biomass production. To date, structural information for the enzyme in complex with phosphate-derived inhibitors has been lacking. Thus, we determined the crystal structure of mammalian aldolase in complex with naphthalene 2,6-bisphosphate (1) that served as a template for the design of bisphosphonate-based inhibitors, namely, 2-phosphate-naphthalene 6-bisphosphonate (2), 2-naphthol 6-bisphosphonate (3), and 1-phosphate-benzene 4-bisphosphonate (4). All inhibitors targeted the active site, and the most promising lead, 2, exhibited slow-binding inhibition with an overall inhibition constant of ∼38 nM. Compound 2 inhibited proliferation of HeLa cancer cells, whereas HEK293 cells expressing a normal phenotype were not inhibited. The crystal structures delineated the essential features of high-affinity phosphate-derived inhibitors and provide a template for the development of inhibitors with prophylaxis potential.

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 score0.002
Threshold uncertainty score0.003

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 integrity0.0000.000
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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Medicinal ChemistrySame topicCancer, Hypoxia, and MetabolismFrench-language works237,207