MétaCan
Menu
Back to cohort
Record W2916219135 · doi:10.1002/jmv.25440

Antimalarial drugs and their metabolites are potent Zika virus inhibitors

2019· article· en· W2916219135 on OpenAlexafffund
Ying-Shan Han, Hanh Thi Pham, Hongtao Xu, Yudong Quan, Thibault Mésplède

Bibliographic record

VenueJournal of Medical Virology · 2019
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsZika virusMetaboliteAmodiaquineDihydroartemisininVirologyChloroquineFlavivirusDrugDrug repositioningPharmacologyVirusViral replicationChemistryBiologyMalariaPlasmodium falciparumBiochemistryArtemisininImmunology

Abstract

fetched live from OpenAlex

Studies aimed at repurposing existing drugs revealed that some antimalarial compounds possess anti-Zika virus (anti-ZIKV) activity. Here, we further tested 14 additional antimalarial drugs and their metabolites or analogs for anti-ZIKV activity using a phenotypic screening approach. We identified four compounds with varying anti-ZIKV activity, including a metabolite of amodiaquine termed desethylamodiaquine (DAQ) and N-desethylchloroquine (DECQ), a metabolite of chloroquine, which both exhibited low micromolar effective concentrations against three different ZIKV strains. Two other compounds termed dihydroartemisinin (DHA) and quinidine (QD) exhibited only partial inhibition of ZIKV replication. Characterization of the inhibitory mechanisms of DAQ and DECQ showed that both drugs target the entry step as well as postentry events of the viral replication cycle. These hits represent attractive starting points for future optimization of new anti-ZIKV drug candidates derived from antimalarial drugs and their analogs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.005
GPT teacher head0.246
Teacher spread0.241 · 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 designObservational
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

Citations42
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Medical VirologySame topicMosquito-borne diseases and controlFrench-language works237,207