Evidence map›Paper›PMID 36606702›Full record

ReviewBiochemical Society transactions2023

Targeting trypanosomes: how chemogenomics and artificial intelligence can guide drug discovery.

Lionel Urán Landaburu, Mercedes Didier Garnham, Fernán Agüero

Abstract readReview
In one paragraph

Review in Biochemical Society transactions, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Lionel Urán LandaburuInstituto de Investigaciones Biotecnológicas (IIB), Universidad Nacional de San Martín (UNSAM) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Argentina.
Mercedes Didier GarnhamInstituto de Investigaciones Biotecnológicas (IIB), Universidad Nacional de San Martín (UNSAM) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Argentina.
Fernán AgüeroInstituto de Investigaciones Biotecnológicas (IIB), Universidad Nacional de San Martín (UNSAM) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Argentina.

Funding

HIGH-THROUGHPUT EPITOPE DISCOVERY: USE OF NEXT-GENERATION PEPTIDE CHIPS FOR FAST IDENTIFICATION AND FINE MAPPING OF DIAGNOSTIC AND PROGNOSTIC MARKERS FOR CHAGAS DISEASER01AI123070 · NIAID · INSTITUTE/RESEARCH/BIOTECHNOLOGY FDN · PI AGUERO, FERNAN GONZALO · 2016 to 2020
$611k
NIAID NIH HHS R01 AI123070
6 · The paper itself

Abstract

Trypanosomatids are protozoan parasites that cause human and animal neglected diseases. Despite global efforts, effective treatments are still much needed. Phenotypic screens have provided several chemical leads for drug discovery, but the mechanism of action for many of these chemicals is currently unknown. Recently, chemogenomic screens assessing the susceptibility or resistance of parasites carrying genome-wide modifications started to define the mechanism of action of drugs at large scale. In this review, we discuss how genomics is being used for drug discovery in trypanosomatids, how integration of chemical and genomics data from these and other organisms has guided prioritisations of candidate therapeutic targets and additional chemical starting points, and how these data can fuel the expansion of drug discovery pipelines into the era of artificial intelligence.

Indexed as

Artificial IntelligenceTrypanosomaAnimalsDrug DesignDrug DiscoveryGenomeGenomicsHumanschemogenomicsdrug discovery and designtrypanosomes

Identifiers

PMID36606702
PMCPMC12556717

What Socratic holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.