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dc.date.available
2026-03-10T11:05:01Z
dc.identifier.citation
Urán Landaburu, Héctor Lionel; Didier Garnham, Mercedes Monica; Salas Sarduy, Emir; Agüero, Fernan Gonzalo; (2026): Prioritization of chemical scaffolds using the TDR Targets database: An integrative workflow for Trypanosoma cruzi drug discovery. Consejo Nacional de Investigaciones Científicas y Técnicas. (dataset). http://hdl.handle.net/11336/282756
dc.identifier.uri
http://hdl.handle.net/11336/282756
dc.description.abstract
Prioritization of chemical scaffolds using the TDR Targets database: an integrative workflow for Trypanosoma cruzi drug discovery
Chagas disease, caused by the parasite Trypanosoma cruzi, faces a critical innovation gap in drug development, with current treatments hindered by toxicity and limited efficacy. To address this, we implemented an integrative chemogenomic workflow using the TDR Targets database to prioritize drug candidates. To prioritize repurposing candidates for T. cruzi, we designed a query to retrieve compounds active against validated targets in other organisms, provided an orthologous gene exists in T. cruzi and the compound has no recorded activity against trypanosomatids and their associations predicted by the TDR Targets multilayer network. On those associations we applied sequential filters based on metabolic relevance, and commercial availability via the MolPort API obtaining a focused set of 378 high-priority compounds. A central feature of this workflow was the partitioning of these compounds into 16 distinct chemical libraries, each defined by unique scaffolds such as benzamidines, sulfonamides, and azoles. For experimental validation, we manually curated two of these libraries, containing piperazine and nitro derivatives. From the 21 compounds acquired for in vitro testing against T. cruzi in intracellular models of infection, 7 demonstrated selective trypanocidal activity, with two lead hits achieving submicromolar EC50 values. Crucially, while our experimental focus was on these two series, the remaining 14 curated libraries, representing a broad range of chemical space and putative target associations, which are fully available for public exploration and further biological assaying. These results demonstrate the efficiency of our prioritization pipeline and provide the scientific community with a pre-filtered, commercially accessible resource to accelerate the discovery of new leads for Chagas disease.
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.title
Prioritization of chemical scaffolds using the TDR Targets database: An integrative workflow for Trypanosoma cruzi drug discovery
dc.type
dataset
dc.date.updated
2026-03-10T10:08:27Z
dc.description.fil
Fil: Urán Landaburu, Héctor Lionel. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; Argentina
dc.description.fil
Fil: Didier Garnham, Mercedes Monica. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; Argentina
dc.description.fil
Fil: Salas Sarduy, Emir. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; Argentina
dc.description.fil
Fil: Agüero, Fernan Gonzalo. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; Argentina
dc.datacite.PublicationYear
2026
dc.datacite.Creator
Urán Landaburu, Héctor Lionel
dc.datacite.Creator
Didier Garnham, Mercedes Monica
dc.datacite.Creator
Salas Sarduy, Emir
dc.datacite.Creator
Agüero, Fernan Gonzalo
dc.datacite.affiliation
Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas
dc.datacite.affiliation
Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas
dc.datacite.affiliation
Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas
dc.datacite.affiliation
Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas
dc.datacite.publisher
Consejo Nacional de Investigaciones Científicas y Técnicas
dc.datacite.subject
Bioquímica y Biología Molecular
dc.datacite.subject
Ciencias Biológicas
dc.datacite.subject
CIENCIAS NATURALES Y EXACTAS
dc.datacite.date
2021/2023
dc.datacite.DateType
Creado
dc.datacite.language
eng
dc.datacite.AlternateIdentifierType
info:eu-repo/semantics/altIdentifier/url/https://github.com/trypanosomatics/TDR-screening/
dc.datacite.version
1.0
dc.datacite.description
# Description of the data and file structure
## Prioritization and Screening of compounds using the TDR Targets Database
The materials in this repository are data, code, and research outputs that form part of the supporting materials for the paper:
"Prioritization of chemical scaffolds using the TDR Targets database: an integrative workflow for Trypanosoma cruzi drug discovery" by Lionel Urán Landaburu, Mercedes Didier Garnham, Emir Salas-Sarduy and Fernán Agüero.
## Contents
data -- datasets used in this work
code -- interactive Jupyter Notebook (Python)
network-based-library -- chemical libraries produced (research outputs)
### Files and variables:
File: commercial-compounds-molport.csv
Format: TXT, comma-separated-values
Description: Molport: All commercially available drugs (at the time of searching)
Variables:
Query String: SMILES of query
Search Type: EXACT
Search Result: search outcome
Search Result Message: message provided by Molport API
Canonical SMILES: SMILES of subject (Molport hit)
MolPort ID: Identifier of the molecule at Molport
Verified amount (mg): literal
Unverified amount (mg): literal
Link: link to Molport website
File: structures.sdf
Format: TXT, Structure-data file (chemical)
Description: Drugbank: all approved and withdrawn drugs
File: tcr_ndp_gdi.tsv.gz
Format: GZIP, compressed TXT file (comma-separated-values)
Description: TDR Targets: All putative gene-drug interactions for T. cruzi
Variables:
mol_id: unique identifier for chemicals
smiles: SMILES lexicographic representation for chemicals
inchikey: standard unique hash of the INCHI identifier for chemicals
gene_name: unique identifier for genes / targets
gene_product: description (annotation) of genes / targets
File: tested-tryps.smiles
Description: TDR Targets: All drugs tested (active and inactive) against trypanosomes (Trypanosoma spp, Leishmania spp)
File: tcr_cherrypicked_routes.csv
Description: TDR Targets: Targets matching pathways for carbon and amminoacid metabolism.
Variables:
gene_name: accession, identifier
gene_product: gene product description (annotation)
Weight: TDR Targets prioritization cumulative weight
Query 5 Carbo (weight): weight assigned to this query
Query 4 Lipids (weight): weight assigned to this query
Query 6 aminoacids (weight): weight assigned to this query
File: libraryPreparation.ipynb
Description: Code (Jupyter Python Notebook)
File: libraryAgg_adenine.html
Description: Adenine sublibrary
File: libraryAgg_benzamidine.html
Description: Benzamidine sublibrary
File: libraryAgg_chromenes.html
Description: Chromene sublibrary
File: libraryAgg_furan.html
Description: Furan sublibrary
File: libraryAgg_azole.html
Description: Azole sublibrary
File: libraryAgg_indole.html
Description: Indole sublibrary
File: libraryAgg_morpholine.html
Description: Morpholine sublibrary
File: libraryAgg_benzothiazole.html
Description: Benzothiazole sublibrary
File: libraryAgg_picolinamide.html
Description: Picolinamide sublibrary
File: libraryAgg_oxazole.html
Description: Oxazole sublibrary
File: libraryAgg_resto.html
Description: Other sublibrary
File: libraryAgg_nitro.html
Description: Nitro sublibrary
File: libraryAgg_piperazine.html
Description: Piperazine sublibrary
File: libraryAgg_pirrolone.html
Description: Pirrolone sublibrary
File: libraryAgg_sulfonamide.html
Description: Sulfonamide sublibrary
File: libraryAgg_thiazoleidine.html
Description: Thiazoleidine sublibrary
File: libraryAgg_thiazole.html
Description: Thiazole sublibrary
File: libraryAgg_napthalene_diimide.html
Description: Naphtalene diimide sublibrary
File: libraryAgg_waltherione.html
Description: Waltherione sublibrary
Code/software:
Jupyter Python Notebook used to prepare chemical libraries
Dependencies: pandas, numpy, rdkit, matplotlib, seaborn, multiprocessing, re, requests, os, pickle, glob, random, base64, io
## Access information
Other publicly accessible locations of the data:
https://github.com/trypanosomatics/TDR-screening/ (except gene-drug-interaction data due to size restrictions)
## Data was derived from the following sources:
- TDR Targets database (https://tdrtargets.org)
- ChEMBL (https://www.ebi.ac.uk/chembl/)
- Molport (https://www.molport.com/)
dc.datacite.DescriptionType
Información Técnica
dc.datacite.FundingReference
00013-2019-PICT
dc.datacite.FunderName
Ministerio de Ciencia. Tecnología e Innovación Productiva. Agencia Nacional de Promoción Científica y Tecnológica
dc.subject.keyword
Drug discovery
dc.subject.keyword
Enfermedad de chagas
dc.subject.keyword
Chagas disease
dc.subject.keyword
Trypanosoma cruzi
dc.subject.keyword
TDR Targets
dc.subject.keyword
Chemical libraries
dc.datacite.resourceTypeGeneral
dataset
dc.conicet.datoinvestigacionid
31862
dc.datacite.awardTitle
Identificación y reposicionamiento de compuestos bioactivos para el tratamiento de la Enfermedad de Chagas
dc.conicet.justificacion
Son datos integrados, extraidos de genomas de referencia ya secuenciados y datos de fármacos y sus actividades provenientes de la literatura.
dc.datacite.formatedDate
2021-2023
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