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Record W2322695360 · doi:10.1016/j.ejmech.2016.04.010

Antitrypanosomal activity of 5-nitro-2-aminothiazole-based compounds

2016· article· en· W2322695360 on OpenAlexfundno aff
Maria V. Papadopoulou, William D. Bloomer, Howard S. Rosenzweig, Shane R. Wilkinson, Joanna Szular, Marcel Kaiser

Bibliographic record

VenueEuropean Journal of Medicinal Chemistry · 2016
Typearticle
Languageen
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsnot available
FundersDrugs for Neglected Diseases initiativeSchool of Medicine, New York UniversityYork UniversityNorthShore University HealthSystemBill and Melinda Gates Foundation
KeywordsChemistryLipophilicityTrypanosoma bruceiTrypanosoma cruziBenznidazoleLeishmania donovaniTrypanosoma brucei rhodesienseAmastigoteLeishmaniaNitroChagas diseaseStereochemistryActive compoundAntiprotozoalBiochemistryIn vitroOrganic chemistryParasite hostingBiology

Abstract

fetched live from OpenAlex

A small series of 5-nitro-2-aminothiazole-based amides containing arylpiperazine-, biphenyl- or aryloxyphenyl groups in their core were synthesized and evaluated as antitrypanosomatid agents. All tested compounds were active or moderately active against Trypanosoma cruzi amastigotes in infected L6 cells and Trypanosoma brucei brucei, four of eleven compounds were moderately active against Leishmania donovani axenic parasites while none were deemed active against T. brucei rhodesiense. For the most active/moderately active compounds a moderate selectivity against each parasite was observed. There was good correlation between lipophilicity (clogP value) and antileishmanial activity or toxicity against L6 cells. Similarly, good correlation existed between clogP values and IC50 values against T. cruzi in structurally related subgroups of compounds. Three compounds were more potent as antichagasic agents than benznidazole but were not activated by the type I nitrorectusase (NTR).

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 score0.256
Threshold uncertainty score0.639

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 integrity0.0000.000
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 head0.025
GPT teacher head0.281
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.

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

Citations30
Published2016
Admission routes1
Has abstractyes

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