MétaCan
Menu
Back to cohort
Record W1988786950 · doi:10.1021/jm301829h

Paclitaxel Is an Inhibitor and Its Boron Dipyrromethene Derivative Is a Fluorescent Recognition Agent for Botulinum Neurotoxin Subtype A

2013· article· en· W1988786950 on OpenAlexaff
Saedeh Dadgar, Zack Ramjan, Wely B. Floriano

Bibliographic record

VenueJournal of Medicinal Chemistry · 2013
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsLakehead UniversityThunder Bay Regional Research Institute
FundersNational Institute of General Medical SciencesDirectorate for Biological SciencesNational Institutes of Health
KeywordsChemistryFluorescenceFörster resonance energy transferLigand (biochemistry)NeurotoxinBotulinum neurotoxinVirtual screeningBiophysicsCombinatorial chemistryBiochemistryStereochemistryToxinReceptorDrug discovery

Abstract

fetched live from OpenAlex

We have successfully identified one new inhibitor and one new fluorescent recognition agent for the botulinum neurotoxin subtype A (BoNT/A) using the virtual screening protocol "protein scanning with virtual ligand screening" (PSVLS). Hit selection used an in-house developed holistic binding scoring method. Selected hits were tested experimentally for inhibitory activity using fluorescence resonance energy transfer (FRET) assays against the light chain (catalytic domain) of BoNT/A. Ligand binding was determined against the light and heavy chain BoNT/A complex through either radiolabeled ligand binding assays (nonfluorescent ligands) or fluorescence intensity assays (fluorescent ligands). These experimental assays have confirmed one compound (paclitaxel) to inhibit BoNT/A's proteolytic activity experimentally with an IC50 of 5.2 μM. A fluorescent derivative was also confirmed to bind to the toxin and therefore is a suitable candidate for the rational design of new detection agents and for the development of fluorescence-based multiprobe detection assays.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.013
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.042
GPT teacher head0.288
Teacher spread0.246 · 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.

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

Citations12
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medicinal ChemistrySame topicBotulinum Toxin and Related Neurological DisordersFrench-language works237,207