Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.

Rivara-Espasandín, Martín - Palumbo, Miranda Clara - Sosa, Ezequiel J. - Radío, Santiago - Turjanski, Adrián G. - Sotelo Silveira, José Roberto - Fernández Do Porto, Dario - Smircich, Pablo

Resumen:

Introduction: Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches. Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development. Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discovery


Detalles Bibliográficos
2023
Trypanosomatids
Drug discovery
Genomics
Neglected disease
Target selection
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/43273
Acceso abierto
Licencia Creative Commons Atribución (CC - By 4.0)
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author Rivara-Espasandín, Martín
author2 Palumbo, Miranda Clara
Sosa, Ezequiel J.
Radío, Santiago
Turjanski, Adrián G.
Sotelo Silveira, José Roberto
Fernández Do Porto, Dario
Smircich, Pablo
author2_role author
author
author
author
author
author
author
author_facet Rivara-Espasandín, Martín
Palumbo, Miranda Clara
Sosa, Ezequiel J.
Radío, Santiago
Turjanski, Adrián G.
Sotelo Silveira, José Roberto
Fernández Do Porto, Dario
Smircich, Pablo
author_role author
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collection COLIBRI
dc.contributor.filiacion.none.fl_str_mv Rivara-Espasandín Martín, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología.
Palumbo Miranda Clara
Sosa Ezequiel J.
Radío Santiago, IIBCE
Turjanski Adrián G.
Sotelo Silveira José Roberto, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología.
Fernández Do Porto Dario
Smircich Pablo, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología.
dc.creator.none.fl_str_mv Rivara-Espasandín, Martín
Palumbo, Miranda Clara
Sosa, Ezequiel J.
Radío, Santiago
Turjanski, Adrián G.
Sotelo Silveira, José Roberto
Fernández Do Porto, Dario
Smircich, Pablo
dc.date.accessioned.none.fl_str_mv 2024-04-01T13:38:12Z
dc.date.available.none.fl_str_mv 2024-04-01T13:38:12Z
dc.date.issued.none.fl_str_mv 2023
dc.description.abstract.none.fl_txt_mv Introduction: Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches. Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development. Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discovery
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dc.identifier.citation.es.fl_str_mv Rivara-Espasandín, M, Palumbo, M, Sosa, E y otros. "Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections". Frontiers in Pharmacology. [en línea] 2023, 14: 1136321. 10 h. DOI: 10.3389/fphar.2023.1136321.
dc.identifier.doi.none.fl_str_mv 10.3389/fphar.2023.1136321
dc.identifier.issn.none.fl_str_mv 1663-9812
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/43273
dc.language.iso.none.fl_str_mv en
eng
dc.publisher.es.fl_str_mv Frontiers
dc.relation.ispartof.es.fl_str_mv Frontiers in Pharmacology, 2023, 14: 1136321.
dc.rights.license.none.fl_str_mv Licencia Creative Commons Atribución (CC - By 4.0)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.es.fl_str_mv Trypanosomatids
Drug discovery
Genomics
Neglected disease
Target selection
dc.title.none.fl_str_mv Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.
dc.type.es.fl_str_mv Artículo
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description Introduction: Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches. Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development. Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discovery
eu_rights_str_mv openAccess
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identifier_str_mv Rivara-Espasandín, M, Palumbo, M, Sosa, E y otros. "Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections". Frontiers in Pharmacology. [en línea] 2023, 14: 1136321. 10 h. DOI: 10.3389/fphar.2023.1136321.
1663-9812
10.3389/fphar.2023.1136321
instacron_str Universidad de la República
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language eng
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publishDate 2023
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repository.mail.fl_str_mv mabel.seroubian@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
rights_invalid_str_mv Licencia Creative Commons Atribución (CC - By 4.0)
spelling Rivara-Espasandín Martín, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología.Palumbo Miranda ClaraSosa Ezequiel J.Radío Santiago, IIBCETurjanski Adrián G.Sotelo Silveira José Roberto, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología.Fernández Do Porto DarioSmircich Pablo, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología.2024-04-01T13:38:12Z2024-04-01T13:38:12Z2023Rivara-Espasandín, M, Palumbo, M, Sosa, E y otros. "Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections". Frontiers in Pharmacology. [en línea] 2023, 14: 1136321. 10 h. DOI: 10.3389/fphar.2023.1136321.1663-9812https://hdl.handle.net/20.500.12008/4327310.3389/fphar.2023.1136321Introduction: Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches. Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development. Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discoverySubmitted by Pintos Natalia (nataliapintosmvd@gmail.com) on 2024-03-20T14:20:31Z No. of bitstreams: 2 license_rdf: 24251 bytes, checksum: 71ed42ef0a0b648670f707320be37b90 (MD5) 10.3389.fphar.2023.1136321.pdf: 1077060 bytes, checksum: 0ad4e93a3a43a1b19b943a643bdb0c0c (MD5)Approved for entry into archive by Faget Cecilia (lfaget@fcien.edu.uy) on 2024-04-01T12:25:42Z (GMT) No. of bitstreams: 2 license_rdf: 24251 bytes, checksum: 71ed42ef0a0b648670f707320be37b90 (MD5) 10.3389.fphar.2023.1136321.pdf: 1077060 bytes, checksum: 0ad4e93a3a43a1b19b943a643bdb0c0c (MD5)Made available in DSpace by Seroubian Mabel (mabel.seroubian@seciu.edu.uy) on 2024-04-01T13:38:12Z (GMT). No. of bitstreams: 2 license_rdf: 24251 bytes, checksum: 71ed42ef0a0b648670f707320be37b90 (MD5) 10.3389.fphar.2023.1136321.pdf: 1077060 bytes, checksum: 0ad4e93a3a43a1b19b943a643bdb0c0c (MD5) Previous issue date: 202310 h.application/pdfenengFrontiersFrontiers in Pharmacology, 2023, 14: 1136321.Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución (CC - By 4.0)TrypanosomatidsDrug discoveryGenomicsNeglected diseaseTarget selectionOmics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.Artículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaRivara-Espasandín, MartínPalumbo, Miranda ClaraSosa, Ezequiel J.Radío, SantiagoTurjanski, Adrián G.Sotelo Silveira, José RobertoFernández Do Porto, DarioSmircich, PabloLICENSElicense.txtlicense.txttext/plain; charset=utf-84267http://localhost:8080/xmlui/bitstream/20.500.12008/43273/5/license.txt6429389a7df7277b72b7924fdc7d47a9MD55CC-LICENSElicense_urllicense_urltext/plain; charset=utf-844http://localhost:8080/xmlui/bitstream/20.500.12008/43273/2/license_urla0ebbeafb9d2ec7cbb19d7137ebc392cMD52license_textlicense_texttext/html; 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- Universidad de la Repúblicafalse
spellingShingle Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.
Rivara-Espasandín, Martín
Trypanosomatids
Drug discovery
Genomics
Neglected disease
Target selection
status_str publishedVersion
title Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.
title_full Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.
title_fullStr Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.
title_full_unstemmed Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.
title_short Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.
title_sort Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.
topic Trypanosomatids
Drug discovery
Genomics
Neglected disease
Target selection
url https://hdl.handle.net/20.500.12008/43273