Dataset of manually curated peptides against arthropod-borne viruses

Autores
Martínez, Victor; Hermosilla Mechetti, Victor; Gomez Adorno, Helena; Pinto Roa, Diego P.; Schaerer, Christian; Di Lella, Santiago; Colbes, Jose
Año de publicación
2026
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Anti-arboviral peptides are biomolecules capable of interfering with key stages of the arboviral lifecycle. We present a dataset compiling 270 peptides composed of standard amino acids with reported activity against arboviruses, along with their lengths, sequences, target specificities, peptide entry mechanisms, and interaction mechanisms. The dataset was structured to support the training of machine learning models designed to identify anti-arboviral peptides. Therefore, it facilitates the development and validation of predictive tools against arboviruses. As a carefully assembled and expert-reviewed resource, this dataset aims to serve as a reference standard for evaluating new prediction models or comparing them with automatically compiled peptide datasets. This resource provides a comprehensive overview of the antiviral mechanisms currently being explored and can serve as a foundation for designing next-generation peptides targeting arboviral infections.
Fil: Martínez, Victor. Universidad Nacional de Asunción; Paraguay
Fil: Hermosilla Mechetti, Victor. Universidad Nacional de Asunción; Paraguay
Fil: Gomez Adorno, Helena. Universidad Nacional Autónoma de México; México
Fil: Pinto Roa, Diego P.. Universidad Nacional de Asunción; Paraguay
Fil: Schaerer, Christian. Universidad Nacional de Asunción; Paraguay
Fil: Di Lella, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Colbes, Jose. Universidad Nacional de Asunción; Paraguay
Materia
DATASET
ARBOVIRUS
FLAVIVIRUS
PEPTIDES
SEQUENCES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/288582
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/288582
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Dataset of manually curated peptides against arthropod-borne virusesMartínez, VictorHermosilla Mechetti, VictorGomez Adorno, HelenaPinto Roa, Diego P.Schaerer, ChristianDi Lella, SantiagoColbes, JoseDATASETARBOVIRUSFLAVIVIRUSPEPTIDESSEQUENCEShttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Anti-arboviral peptides are biomolecules capable of interfering with key stages of the arboviral lifecycle. We present a dataset compiling 270 peptides composed of standard amino acids with reported activity against arboviruses, along with their lengths, sequences, target specificities, peptide entry mechanisms, and interaction mechanisms. The dataset was structured to support the training of machine learning models designed to identify anti-arboviral peptides. Therefore, it facilitates the development and validation of predictive tools against arboviruses. As a carefully assembled and expert-reviewed resource, this dataset aims to serve as a reference standard for evaluating new prediction models or comparing them with automatically compiled peptide datasets. This resource provides a comprehensive overview of the antiviral mechanisms currently being explored and can serve as a foundation for designing next-generation peptides targeting arboviral infections.Fil: Martínez, Victor. Universidad Nacional de Asunción; ParaguayFil: Hermosilla Mechetti, Victor. Universidad Nacional de Asunción; ParaguayFil: Gomez Adorno, Helena. Universidad Nacional Autónoma de México; MéxicoFil: Pinto Roa, Diego P.. Universidad Nacional de Asunción; ParaguayFil: Schaerer, Christian. Universidad Nacional de Asunción; ParaguayFil: Di Lella, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Colbes, Jose. Universidad Nacional de Asunción; ParaguayElsevier2026-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/288582Martínez, Victor; Hermosilla Mechetti, Victor; Gomez Adorno, Helena; Pinto Roa, Diego P.; Schaerer, Christian; et al.; Dataset of manually curated peptides against arthropod-borne viruses; Elsevier; Data in Brief; 66; 4-2026; 1-172352-3409CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S2352340926003185info:eu-repo/semantics/altIdentifier/doi/10.1016/j.dib.2026.112765info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T14:35:06Zoai:ri.conicet.gov.ar:11336/288582instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-08-25 14:35:06.498CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Dataset of manually curated peptides against arthropod-borne viruses
title Dataset of manually curated peptides against arthropod-borne viruses
spellingShingle Dataset of manually curated peptides against arthropod-borne viruses
Martínez, Victor
DATASET
ARBOVIRUS
FLAVIVIRUS
PEPTIDES
SEQUENCES
title_short Dataset of manually curated peptides against arthropod-borne viruses
title_full Dataset of manually curated peptides against arthropod-borne viruses
title_fullStr Dataset of manually curated peptides against arthropod-borne viruses
title_full_unstemmed Dataset of manually curated peptides against arthropod-borne viruses
title_sort Dataset of manually curated peptides against arthropod-borne viruses
dc.creator.none.fl_str_mv Martínez, Victor
Hermosilla Mechetti, Victor
Gomez Adorno, Helena
Pinto Roa, Diego P.
Schaerer, Christian
Di Lella, Santiago
Colbes, Jose
author Martínez, Victor
author_facet Martínez, Victor
Hermosilla Mechetti, Victor
Gomez Adorno, Helena
Pinto Roa, Diego P.
Schaerer, Christian
Di Lella, Santiago
Colbes, Jose
author_role author
author2 Hermosilla Mechetti, Victor
Gomez Adorno, Helena
Pinto Roa, Diego P.
Schaerer, Christian
Di Lella, Santiago
Colbes, Jose
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv DATASET
ARBOVIRUS
FLAVIVIRUS
PEPTIDES
SEQUENCES
topic DATASET
ARBOVIRUS
FLAVIVIRUS
PEPTIDES
SEQUENCES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Anti-arboviral peptides are biomolecules capable of interfering with key stages of the arboviral lifecycle. We present a dataset compiling 270 peptides composed of standard amino acids with reported activity against arboviruses, along with their lengths, sequences, target specificities, peptide entry mechanisms, and interaction mechanisms. The dataset was structured to support the training of machine learning models designed to identify anti-arboviral peptides. Therefore, it facilitates the development and validation of predictive tools against arboviruses. As a carefully assembled and expert-reviewed resource, this dataset aims to serve as a reference standard for evaluating new prediction models or comparing them with automatically compiled peptide datasets. This resource provides a comprehensive overview of the antiviral mechanisms currently being explored and can serve as a foundation for designing next-generation peptides targeting arboviral infections.
Fil: Martínez, Victor. Universidad Nacional de Asunción; Paraguay
Fil: Hermosilla Mechetti, Victor. Universidad Nacional de Asunción; Paraguay
Fil: Gomez Adorno, Helena. Universidad Nacional Autónoma de México; México
Fil: Pinto Roa, Diego P.. Universidad Nacional de Asunción; Paraguay
Fil: Schaerer, Christian. Universidad Nacional de Asunción; Paraguay
Fil: Di Lella, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Colbes, Jose. Universidad Nacional de Asunción; Paraguay
description Anti-arboviral peptides are biomolecules capable of interfering with key stages of the arboviral lifecycle. We present a dataset compiling 270 peptides composed of standard amino acids with reported activity against arboviruses, along with their lengths, sequences, target specificities, peptide entry mechanisms, and interaction mechanisms. The dataset was structured to support the training of machine learning models designed to identify anti-arboviral peptides. Therefore, it facilitates the development and validation of predictive tools against arboviruses. As a carefully assembled and expert-reviewed resource, this dataset aims to serve as a reference standard for evaluating new prediction models or comparing them with automatically compiled peptide datasets. This resource provides a comprehensive overview of the antiviral mechanisms currently being explored and can serve as a foundation for designing next-generation peptides targeting arboviral infections.
publishDate 2026
dc.date.none.fl_str_mv 2026-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/288582
Martínez, Victor; Hermosilla Mechetti, Victor; Gomez Adorno, Helena; Pinto Roa, Diego P.; Schaerer, Christian; et al.; Dataset of manually curated peptides against arthropod-borne viruses; Elsevier; Data in Brief; 66; 4-2026; 1-17
2352-3409
CONICET Digital
CONICET
url http://hdl.handle.net/11336/288582
identifier_str_mv Martínez, Victor; Hermosilla Mechetti, Victor; Gomez Adorno, Helena; Pinto Roa, Diego P.; Schaerer, Christian; et al.; Dataset of manually curated peptides against arthropod-borne viruses; Elsevier; Data in Brief; 66; 4-2026; 1-17
2352-3409
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S2352340926003185
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.dib.2026.112765
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1874774237362782208
score 13.24418

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