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Record W4401460829 · doi:10.1021/acsinfecdis.4c00394

Pilot-Scale Screening of Clinically Approved Drugs to Identify Uridine Insertion/Deletion RNA Editing Inhibitors in <i>Trypanosoma brucei</i>

2024· article· en· W4401460829 on OpenAlexaff
Mojtaba Rostamighadi, Arezou Kamelshahroudi, Vanessa Pitsitikas, Kenneth A. Jacobson, Reza Salavati

Bibliographic record

VenueACS Infectious Diseases · 2024
Typearticle
Languageen
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsMcGill University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsTrypanosoma bruceiRNA editingGuide RNABiologyDrug discoveryComputational biologyRNAAfrican trypanosomiasisDNA ligaseBiochemistryGenome editingEnzymeGeneVirologyCRISPRTrypanosomiasis

Abstract

fetched live from OpenAlex

RNA editing pathway is a validated target in kinetoplastid parasites ( Trypanosoma brucei, Trypanosoma cruzi, and Leishmania spp.) that cause severe diseases in humans and livestock. An essential large protein complex, the editosome, mediates uridine insertion and deletion in RNA editing through a stepwise process. This study details the discovery of editosome inhibitors by screening a library of widely used human drugs using our previously developed in vitro biochemical Ribozyme Insertion Deletion Editing (RIDE) assay. Subsequent studies on the mode of action of the identified hits and hit expansion efforts unveiled compounds that interfere with RNA-editosome interactions and novel ligase inhibitors with IC 50 values in the low micromolar range. Docking studies on the ligase demonstrated similar binding characteristics for ATP and our novel epigallocatechin gallate inhibitor. The inhibitors demonstrated potent trypanocidal activity and are promising candidates for drug repurposing due to their lack of cytotoxic effects. Further studies are necessary to validate these targets using more definitive gene-editing techniques and to enhance the safety profile.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.021
GPT teacher head0.346
Teacher spread0.324 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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