Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking

Autores
Ribone, Sergio Roman; Paz, Sergio Alexis; Abrams, Cameron F.; Villarreal, Marcos Ariel
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Screening already approved drugs for activity against a novel pathogen can be an important part of global rapid-response strategies in pandemics. Such high-throughput repurposing screens have already identifed several existing drugs with potential to combat SARS-CoV-2. However, moving these hits forward for possible development into drugs specifcally against this pathogen requires unambiguous identifcation of their corresponding targets, something the high-throughput screens are not typically designed to reveal. We present here a new computational inverse-docking protocol that uses all-atom protein structures and a combination of docking methods to rank-order targets for each of several existing drugs for which a plurality of recent high-throughput screens detected anti-SARS-CoV-2 activity. We demonstrate validation of this method with known drug-target pairs, including both non-antiviral and antiviral compounds. We subjected 152 distinct drugs potentially suitable for repurposing to the inverse docking procedure. The most common preferential targets were the human enzymes TMPRSS2 and PIKfyve, followed by the viral enzymes Helicase and PLpro. All compounds that selected TMPRSS2 are known serine protease inhibitors, and those that selected PIKfyve are known tyrosine kinase inhibitors. Detailed structural analysis of the docking poses revealed important insights into why these selections arose, and could potentially lead to more rational design of new drugs against these targets.
Fil: Ribone, Sergio Roman. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica; Argentina
Fil: Paz, Sergio Alexis. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Teórica y Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina
Fil: Abrams, Cameron F.. Drexel University; Estados Unidos
Fil: Villarreal, Marcos Ariel. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Teórica y Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina
Materia
SARS-COV-2
INVERSE DOCKING
HIGH-THROUGHPUT
REPURPOSING
TMPRSS2
PIKfyve
COVID-19
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/149938
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/149938
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse dockingRibone, Sergio RomanPaz, Sergio AlexisAbrams, Cameron F.Villarreal, Marcos ArielSARS-COV-2INVERSE DOCKINGHIGH-THROUGHPUTREPURPOSINGTMPRSS2PIKfyveCOVID-19https://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Screening already approved drugs for activity against a novel pathogen can be an important part of global rapid-response strategies in pandemics. Such high-throughput repurposing screens have already identifed several existing drugs with potential to combat SARS-CoV-2. However, moving these hits forward for possible development into drugs specifcally against this pathogen requires unambiguous identifcation of their corresponding targets, something the high-throughput screens are not typically designed to reveal. We present here a new computational inverse-docking protocol that uses all-atom protein structures and a combination of docking methods to rank-order targets for each of several existing drugs for which a plurality of recent high-throughput screens detected anti-SARS-CoV-2 activity. We demonstrate validation of this method with known drug-target pairs, including both non-antiviral and antiviral compounds. We subjected 152 distinct drugs potentially suitable for repurposing to the inverse docking procedure. The most common preferential targets were the human enzymes TMPRSS2 and PIKfyve, followed by the viral enzymes Helicase and PLpro. All compounds that selected TMPRSS2 are known serine protease inhibitors, and those that selected PIKfyve are known tyrosine kinase inhibitors. Detailed structural analysis of the docking poses revealed important insights into why these selections arose, and could potentially lead to more rational design of new drugs against these targets.Fil: Ribone, Sergio Roman. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica; ArgentinaFil: Paz, Sergio Alexis. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Teórica y Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Abrams, Cameron F.. Drexel University; Estados UnidosFil: Villarreal, Marcos Ariel. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Teórica y Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaSpringer2021-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/149938Ribone, Sergio Roman; Paz, Sergio Alexis; Abrams, Cameron F.; Villarreal, Marcos Ariel; Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking; Springer; Journal of Computer-Aided Molecular Design; 2021; 11-2021; 1-130920-654XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://link.springer.com/10.1007/s10822-021-00432-3info:eu-repo/semantics/altIdentifier/doi/10.1007/s10822-021-00432-3info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:27:07Zoai:ri.conicet.gov.ar:11336/149938instacron: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:34982025-10-15 14:27:08.225CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking
title Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking
spellingShingle Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking
Ribone, Sergio Roman
SARS-COV-2
INVERSE DOCKING
HIGH-THROUGHPUT
REPURPOSING
TMPRSS2
PIKfyve
COVID-19
title_short Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking
title_full Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking
title_fullStr Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking
title_full_unstemmed Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking
title_sort Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking
dc.creator.none.fl_str_mv Ribone, Sergio Roman
Paz, Sergio Alexis
Abrams, Cameron F.
Villarreal, Marcos Ariel
author Ribone, Sergio Roman
author_facet Ribone, Sergio Roman
Paz, Sergio Alexis
Abrams, Cameron F.
Villarreal, Marcos Ariel
author_role author
author2 Paz, Sergio Alexis
Abrams, Cameron F.
Villarreal, Marcos Ariel
author2_role author
author
author
dc.subject.none.fl_str_mv SARS-COV-2
INVERSE DOCKING
HIGH-THROUGHPUT
REPURPOSING
TMPRSS2
PIKfyve
COVID-19
topic SARS-COV-2
INVERSE DOCKING
HIGH-THROUGHPUT
REPURPOSING
TMPRSS2
PIKfyve
COVID-19
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Screening already approved drugs for activity against a novel pathogen can be an important part of global rapid-response strategies in pandemics. Such high-throughput repurposing screens have already identifed several existing drugs with potential to combat SARS-CoV-2. However, moving these hits forward for possible development into drugs specifcally against this pathogen requires unambiguous identifcation of their corresponding targets, something the high-throughput screens are not typically designed to reveal. We present here a new computational inverse-docking protocol that uses all-atom protein structures and a combination of docking methods to rank-order targets for each of several existing drugs for which a plurality of recent high-throughput screens detected anti-SARS-CoV-2 activity. We demonstrate validation of this method with known drug-target pairs, including both non-antiviral and antiviral compounds. We subjected 152 distinct drugs potentially suitable for repurposing to the inverse docking procedure. The most common preferential targets were the human enzymes TMPRSS2 and PIKfyve, followed by the viral enzymes Helicase and PLpro. All compounds that selected TMPRSS2 are known serine protease inhibitors, and those that selected PIKfyve are known tyrosine kinase inhibitors. Detailed structural analysis of the docking poses revealed important insights into why these selections arose, and could potentially lead to more rational design of new drugs against these targets.
Fil: Ribone, Sergio Roman. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica; Argentina
Fil: Paz, Sergio Alexis. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Teórica y Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina
Fil: Abrams, Cameron F.. Drexel University; Estados Unidos
Fil: Villarreal, Marcos Ariel. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Teórica y Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina
description Screening already approved drugs for activity against a novel pathogen can be an important part of global rapid-response strategies in pandemics. Such high-throughput repurposing screens have already identifed several existing drugs with potential to combat SARS-CoV-2. However, moving these hits forward for possible development into drugs specifcally against this pathogen requires unambiguous identifcation of their corresponding targets, something the high-throughput screens are not typically designed to reveal. We present here a new computational inverse-docking protocol that uses all-atom protein structures and a combination of docking methods to rank-order targets for each of several existing drugs for which a plurality of recent high-throughput screens detected anti-SARS-CoV-2 activity. We demonstrate validation of this method with known drug-target pairs, including both non-antiviral and antiviral compounds. We subjected 152 distinct drugs potentially suitable for repurposing to the inverse docking procedure. The most common preferential targets were the human enzymes TMPRSS2 and PIKfyve, followed by the viral enzymes Helicase and PLpro. All compounds that selected TMPRSS2 are known serine protease inhibitors, and those that selected PIKfyve are known tyrosine kinase inhibitors. Detailed structural analysis of the docking poses revealed important insights into why these selections arose, and could potentially lead to more rational design of new drugs against these targets.
publishDate 2021
dc.date.none.fl_str_mv 2021-11
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/11336/149938
Ribone, Sergio Roman; Paz, Sergio Alexis; Abrams, Cameron F.; Villarreal, Marcos Ariel; Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking; Springer; Journal of Computer-Aided Molecular Design; 2021; 11-2021; 1-13
0920-654X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/149938
identifier_str_mv Ribone, Sergio Roman; Paz, Sergio Alexis; Abrams, Cameron F.; Villarreal, Marcos Ariel; Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking; Springer; Journal of Computer-Aided Molecular Design; 2021; 11-2021; 1-13
0920-654X
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://link.springer.com/10.1007/s10822-021-00432-3
info:eu-repo/semantics/altIdentifier/doi/10.1007/s10822-021-00432-3
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
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
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