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Record W4213046817 · doi:10.1021/acschembio.1c00978

Fluorinated Phosphoadenosine 5′-Phosphosulfate Analogues for Continuous Sulfotransferase Activity Monitoring and Inhibitor Screening by <sup>19</sup>F NMR Spectroscopy

2022· article· en· W4213046817 on OpenAlexfundno aff
Agnieszka Młynarska-Cieślak, Mikołaj Chromiński, Tomasz Śpiewla, Marek R. Baranowski, Marcelina Bednarczyk, Jacek Jemielity, Joanna Kowalska

Bibliographic record

VenueACS Chemical Biology · 2022
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Disorders and Syndromes
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNarodowe Centrum Nauki
KeywordsChemistryCofactorEnzymeFluorine-19 NMRSulfotransferaseNuclear magnetic resonance spectroscopyTrifluoromethylFluorineStereochemistryBiochemistryCombinatorial chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Sulfotransferases (STs) are ubiquitous enzymes that participate in a vast number of biological processes involving sulfuryl group (SO3) transfer. 3′-phosphoadenosine 5′-phosphosulfate (PAPS) is the universal ST cofactor, serving as the “active sulfate” source in cells. Herein, we report the synthesis of three fluorinated PAPS analogues that bear fluorine or trifluoromethyl substituents at the C2 or C8 positions of adenine and their evaluation as substitute cofactors that enable ST activity to be quantified and real-time-monitored by fluorine-19 nuclear magnetic resonance (19F NMR) spectroscopy. Using plant AtSOT18 and human SULT1A3 as two model enzymes, we reveal that the fluorinated PAPS analogues show complementary properties with regard to recognition by enzymes and the working 19F NMR pH range and are attractive versatile tools for studying STs. Finally, we developed an 19F NMR assay for screening potential inhibitors against SULT1A3, thereby highlighting the possible use of fluorinated PAPS analogues for the discovery of drugs for ST-related diseases.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.270
Teacher spread0.256 · 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 teacher head, not a consensus.

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

Citations5
Published2022
Admission routes1
Has abstractyes

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