Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study

Autores
Llanos, Manuel; Gantner, Melisa Edith; Rodríguez, Santiago; Alberca, Lucas Nicolás; Bellera, Carolina Leticia; Talevi, Alan; Gavernet, Luciana
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The scientific community is working against the clock to arrive at therapeutic interventions to treat patients with COVID-19. Among the strategies for drug discovery, virtual screening approaches have the capacity to search potential hits within millions of chemical structures in days, with the appropriate computing infrastructure. In this article, we first analyzed the published research targeting the inhibition of the main protease (Mpro), one of the most studied targets of SARS-CoV-2, by docking-based methods. An alarming finding was the lack of an adequate validation of the docking protocols (i.e., pose prediction and virtual screening accuracy) before applying them in virtual screening campaigns. The performance of the docking protocols was tested at some level in 57.7% of the 168 investigations analyzed. However, we found only three examples of a complete retrospective analysis of the scoring functions to quantify the virtual screening accuracy of the methods. Moreover, only two publications reported some experimental evaluation of the proposed hits until preparing this manuscript. All of these findings led us to carry out a retrospective performance validation of three different docking protocols, through the analysis of their pose prediction and screening accuracy. Surprisingly, we found that even though all tested docking protocols have a good pose prediction, their screening accuracy is quite limited as they fail to correctly rank a test set of compounds. These results highlight the importance of conducting an adequate validation of the docking protocols before carrying out virtual screening campaigns, and to experimentally confirm the predictions made by the models before drawing bold conclusions. Finally, successful structure-based drug discovery investigations published during the redaction of this manuscript allow us to propose the inclusion of target flexibility and consensus scoring as alternatives to improve the accuracy of the methods.
Fil: Llanos, Manuel. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Gantner, Melisa Edith. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Rodríguez, Santiago. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata "Prof. Dr. Rodolfo R. Brenner". Universidad Nacional de la Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones Bioquímicas de La Plata "Prof. Dr. Rodolfo R. Brenner"; Argentina
Fil: Alberca, Lucas Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina
Fil: Bellera, Carolina Leticia. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Talevi, Alan. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Gavernet, Luciana. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Materia
Docking
MPro
COVID-19
Virtual screening
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:11336/149785
Acceder
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spelling Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case StudyLlanos, ManuelGantner, Melisa EdithRodríguez, SantiagoAlberca, Lucas NicolásBellera, Carolina LeticiaTalevi, AlanGavernet, LucianaDockingMProCOVID-19Virtual screeninghttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The scientific community is working against the clock to arrive at therapeutic interventions to treat patients with COVID-19. Among the strategies for drug discovery, virtual screening approaches have the capacity to search potential hits within millions of chemical structures in days, with the appropriate computing infrastructure. In this article, we first analyzed the published research targeting the inhibition of the main protease (Mpro), one of the most studied targets of SARS-CoV-2, by docking-based methods. An alarming finding was the lack of an adequate validation of the docking protocols (i.e., pose prediction and virtual screening accuracy) before applying them in virtual screening campaigns. The performance of the docking protocols was tested at some level in 57.7% of the 168 investigations analyzed. However, we found only three examples of a complete retrospective analysis of the scoring functions to quantify the virtual screening accuracy of the methods. Moreover, only two publications reported some experimental evaluation of the proposed hits until preparing this manuscript. All of these findings led us to carry out a retrospective performance validation of three different docking protocols, through the analysis of their pose prediction and screening accuracy. Surprisingly, we found that even though all tested docking protocols have a good pose prediction, their screening accuracy is quite limited as they fail to correctly rank a test set of compounds. These results highlight the importance of conducting an adequate validation of the docking protocols before carrying out virtual screening campaigns, and to experimentally confirm the predictions made by the models before drawing bold conclusions. Finally, successful structure-based drug discovery investigations published during the redaction of this manuscript allow us to propose the inclusion of target flexibility and consensus scoring as alternatives to improve the accuracy of the methods.Fil: Llanos, Manuel. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Gantner, Melisa Edith. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Rodríguez, Santiago. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata "Prof. Dr. Rodolfo R. Brenner". Universidad Nacional de la Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones Bioquímicas de La Plata "Prof. Dr. Rodolfo R. Brenner"; ArgentinaFil: Alberca, Lucas Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Bellera, Carolina Leticia. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Talevi, Alan. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Gavernet, Luciana. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaAmerican Chemical Society2021-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/149785Llanos, Manuel; Gantner, Melisa Edith; Rodríguez, Santiago; Alberca, Lucas Nicolás; Bellera, Carolina Leticia; et al.; Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study; American Chemical Society; Journal of Chemical Information and Modeling; 61; 8; 7-2021; 3758-37701549-9596CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/10.1021/acs.jcim.1c00404info:eu-repo/semantics/altIdentifier/doi/10.1021/acs.jcim.1c00404info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:20:47Zoai:ri.conicet.gov.ar:11336/149785instacron: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 15:20:48.192CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study
title Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study
spellingShingle Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study
Llanos, Manuel
Docking
MPro
COVID-19
Virtual screening
title_short Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study
title_full Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study
title_fullStr Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study
title_full_unstemmed Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study
title_sort Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study
dc.creator.none.fl_str_mv Llanos, Manuel
Gantner, Melisa Edith
Rodríguez, Santiago
Alberca, Lucas Nicolás
Bellera, Carolina Leticia
Talevi, Alan
Gavernet, Luciana
author Llanos, Manuel
author_facet Llanos, Manuel
Gantner, Melisa Edith
Rodríguez, Santiago
Alberca, Lucas Nicolás
Bellera, Carolina Leticia
Talevi, Alan
Gavernet, Luciana
author_role author
author2 Gantner, Melisa Edith
Rodríguez, Santiago
Alberca, Lucas Nicolás
Bellera, Carolina Leticia
Talevi, Alan
Gavernet, Luciana
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Docking
MPro
COVID-19
Virtual screening
topic Docking
MPro
COVID-19
Virtual screening
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The scientific community is working against the clock to arrive at therapeutic interventions to treat patients with COVID-19. Among the strategies for drug discovery, virtual screening approaches have the capacity to search potential hits within millions of chemical structures in days, with the appropriate computing infrastructure. In this article, we first analyzed the published research targeting the inhibition of the main protease (Mpro), one of the most studied targets of SARS-CoV-2, by docking-based methods. An alarming finding was the lack of an adequate validation of the docking protocols (i.e., pose prediction and virtual screening accuracy) before applying them in virtual screening campaigns. The performance of the docking protocols was tested at some level in 57.7% of the 168 investigations analyzed. However, we found only three examples of a complete retrospective analysis of the scoring functions to quantify the virtual screening accuracy of the methods. Moreover, only two publications reported some experimental evaluation of the proposed hits until preparing this manuscript. All of these findings led us to carry out a retrospective performance validation of three different docking protocols, through the analysis of their pose prediction and screening accuracy. Surprisingly, we found that even though all tested docking protocols have a good pose prediction, their screening accuracy is quite limited as they fail to correctly rank a test set of compounds. These results highlight the importance of conducting an adequate validation of the docking protocols before carrying out virtual screening campaigns, and to experimentally confirm the predictions made by the models before drawing bold conclusions. Finally, successful structure-based drug discovery investigations published during the redaction of this manuscript allow us to propose the inclusion of target flexibility and consensus scoring as alternatives to improve the accuracy of the methods.
Fil: Llanos, Manuel. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Gantner, Melisa Edith. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Rodríguez, Santiago. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata "Prof. Dr. Rodolfo R. Brenner". Universidad Nacional de la Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones Bioquímicas de La Plata "Prof. Dr. Rodolfo R. Brenner"; Argentina
Fil: Alberca, Lucas Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina
Fil: Bellera, Carolina Leticia. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Talevi, Alan. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Gavernet, Luciana. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
description The scientific community is working against the clock to arrive at therapeutic interventions to treat patients with COVID-19. Among the strategies for drug discovery, virtual screening approaches have the capacity to search potential hits within millions of chemical structures in days, with the appropriate computing infrastructure. In this article, we first analyzed the published research targeting the inhibition of the main protease (Mpro), one of the most studied targets of SARS-CoV-2, by docking-based methods. An alarming finding was the lack of an adequate validation of the docking protocols (i.e., pose prediction and virtual screening accuracy) before applying them in virtual screening campaigns. The performance of the docking protocols was tested at some level in 57.7% of the 168 investigations analyzed. However, we found only three examples of a complete retrospective analysis of the scoring functions to quantify the virtual screening accuracy of the methods. Moreover, only two publications reported some experimental evaluation of the proposed hits until preparing this manuscript. All of these findings led us to carry out a retrospective performance validation of three different docking protocols, through the analysis of their pose prediction and screening accuracy. Surprisingly, we found that even though all tested docking protocols have a good pose prediction, their screening accuracy is quite limited as they fail to correctly rank a test set of compounds. These results highlight the importance of conducting an adequate validation of the docking protocols before carrying out virtual screening campaigns, and to experimentally confirm the predictions made by the models before drawing bold conclusions. Finally, successful structure-based drug discovery investigations published during the redaction of this manuscript allow us to propose the inclusion of target flexibility and consensus scoring as alternatives to improve the accuracy of the methods.
publishDate 2021
dc.date.none.fl_str_mv 2021-07
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/11336/149785
Llanos, Manuel; Gantner, Melisa Edith; Rodríguez, Santiago; Alberca, Lucas Nicolás; Bellera, Carolina Leticia; et al.; Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study; American Chemical Society; Journal of Chemical Information and Modeling; 61; 8; 7-2021; 3758-3770
1549-9596
CONICET Digital
CONICET
url http://hdl.handle.net/11336/149785
identifier_str_mv Llanos, Manuel; Gantner, Melisa Edith; Rodríguez, Santiago; Alberca, Lucas Nicolás; Bellera, Carolina Leticia; et al.; Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: The Main Protease (Mpro) Case Study; American Chemical Society; Journal of Chemical Information and Modeling; 61; 8; 7-2021; 3758-3770
1549-9596
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://pubs.acs.org/doi/10.1021/acs.jcim.1c00404
info:eu-repo/semantics/altIdentifier/doi/10.1021/acs.jcim.1c00404
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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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
application/pdf
application/pdf
application/pdf
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dc.publisher.none.fl_str_mv American Chemical Society
publisher.none.fl_str_mv American Chemical Society
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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