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Record W4388907778 · doi:10.1016/j.bcp.2023.115937

High-throughput screening of compounds targeting RNA editing in Trypanosoma brucei: Novel molecular scaffolds with broad trypanocidal effects

2023· article· en· W4388907778 on OpenAlexaff
Mojtaba Rostamighadi, Arezou Kamelshahroudi, Vaibhav Mehta, Fu‐Yue Zeng, Ian Pass, Thomas D.Y. Chung, Reza Salavati

Bibliographic record

VenueBiochemical Pharmacology · 2023
Typearticle
Languageen
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsMcGill University
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsTrypanosoma bruceiRNA editingRNABiologyLeishmaniaGuide RNADrug discoveryHigh-throughput screeningRNA interferenceComputational biologyBiochemistryLeishmania majorGeneCell biologyGenome editingGenomeParasite hosting

Abstract

fetched live from OpenAlex

Mitochondrial uridine insertion/deletion RNA editing, catalyzed by a multiprotein complex (editosome), is essential for gene expression in trypanosomes and Leishmania parasites. As this process is absent in the human host, a drug targeting this mechanism promises high selectivity and reduced toxicity. Here, we successfully miniaturized our FRET-based full-round RNA editing assay, which replicates the complete RNA editing process, adapting it into a 1536-well format. Leveraging this assay, we screened over 100,000 compounds against purified editosomes derived from Trypanosoma brucei, identifying seven confirmed primary hits. We sourced and evaluated various analogs to enhance the inhibitory and parasiticidal effects of these primary hits. In combination with secondary assays, our compounds marked inhibition of essential catalytic activities, including the RNA editing ligase and interactions of editosome proteins. Although the primary hits did not exhibit any growth inhibitory effect on parasites, we describe eight analog compounds capable of effectively killing T. brucei and/or Leishmania donovani parasites within a low micromolar concentration. Whether parasite killing is - at least in part - due to inhibition of RNA editing in vivo remains to be assessed. Our findings introduce novel molecular scaffolds with the potential for broad antitrypanosomal effects.

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 score0.050
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.320
Teacher spread0.302 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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