A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease

Detalhes bibliográficos
Autor(a) principal: Hernández González, Jorge E. [UNESP]
Data de Publicação: 2022
Outros Autores: Eberle, Raphael J., Willbold, Dieter, Coronado, Mônika A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3389/fmolb.2021.816166
http://hdl.handle.net/11449/223492
Resumo: The SARS-CoV-2 main protease, also known as 3-chymotrypsin-like protease (3CLpro), is a cysteine protease responsible for the cleavage of viral polyproteins pp1a and pp1ab, at least, at eleven conserved sites, which leads to the formation of mature nonstructural proteins essential for the replication of the virus. Due to its essential role, numerous studies have been conducted so far, which have confirmed 3CLpro as an attractive drug target to combat Covid-19 and have reported a vast number of inhibitors and their co-crystal structures. Despite all the ongoing efforts, D-peptides, which possess key advantages over L-peptides as therapeutic agents, have not been explored as potential drug candidates against 3CLpro. The current work fills this gap by reporting an in silico approach for the discovery of D-peptides capable of inhibiting 3CLpro that involves structure-based virtual screening (SBVS) of an in-house library of D-tripeptides and D-tetrapeptides into the protease active site and subsequent rescoring steps, including Molecular Mechanics Generalized-Born Surface Area (MM-GBSA) free energy calculations and molecular dynamics (MD) simulations. In vitro enzymatic assays conducted for the four top-scoring D-tetrapeptides at 20 μM showed that all of them caused 55–85% inhibition of 3CLpro activity, thus highlighting the suitability of the devised approach. Overall, our results present a promising computational strategy to identify D-peptides capable of inhibiting 3CLpro, with broader application in problems involving protein inhibition.
id UNSP_6484f2182205b1bfba744745358e692f
oai_identifier_str oai:repositorio.unesp.br:11449/223492
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease3CLproD-peptidemolecular dynamics simulationSARS-CoV-2virtual screeningThe SARS-CoV-2 main protease, also known as 3-chymotrypsin-like protease (3CLpro), is a cysteine protease responsible for the cleavage of viral polyproteins pp1a and pp1ab, at least, at eleven conserved sites, which leads to the formation of mature nonstructural proteins essential for the replication of the virus. Due to its essential role, numerous studies have been conducted so far, which have confirmed 3CLpro as an attractive drug target to combat Covid-19 and have reported a vast number of inhibitors and their co-crystal structures. Despite all the ongoing efforts, D-peptides, which possess key advantages over L-peptides as therapeutic agents, have not been explored as potential drug candidates against 3CLpro. The current work fills this gap by reporting an in silico approach for the discovery of D-peptides capable of inhibiting 3CLpro that involves structure-based virtual screening (SBVS) of an in-house library of D-tripeptides and D-tetrapeptides into the protease active site and subsequent rescoring steps, including Molecular Mechanics Generalized-Born Surface Area (MM-GBSA) free energy calculations and molecular dynamics (MD) simulations. In vitro enzymatic assays conducted for the four top-scoring D-tetrapeptides at 20 μM showed that all of them caused 55–85% inhibition of 3CLpro activity, thus highlighting the suitability of the devised approach. Overall, our results present a promising computational strategy to identify D-peptides capable of inhibiting 3CLpro, with broader application in problems involving protein inhibition.Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)Multiuser Center for Biomolecular Innovation IBILCE Universidade Estadual Paulista (UNESP), São Jose do Rio PretoLaboratory for Molecular Modeling and Dynamics Instituto de Biofísica Carlos Chagas Filho Universidade Federal do Rio de Janeiro Cidade Universitária Ilha do FundãoInstitute of Biological Information Processing (IBI-7 Structural Biochemistry) Forschungszentrum JülichInstitut für Physikalische Biologie Heinrich-Heine-Universität Düsseldorf UniversitätsstraßeJuStruct: Jülich Centre for Structural Biology Forschungszentrum JülichMultiuser Center for Biomolecular Innovation IBILCE Universidade Estadual Paulista (UNESP), São Jose do Rio PretoUniversidade Estadual Paulista (UNESP)Universidade Federal do Rio de Janeiro (UFRJ)Forschungszentrum JülichUniversitätsstraßeHernández González, Jorge E. [UNESP]Eberle, Raphael J.Willbold, DieterCoronado, Mônika A.2022-04-28T19:50:56Z2022-04-28T19:50:56Z2022-01-24info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3389/fmolb.2021.816166Frontiers in Molecular Biosciences, v. 8.2296-889Xhttp://hdl.handle.net/11449/22349210.3389/fmolb.2021.8161662-s2.0-85124938065Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengFrontiers in Molecular Biosciencesinfo:eu-repo/semantics/openAccess2022-04-28T19:50:56Zoai:repositorio.unesp.br:11449/223492Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T19:50:56Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease
title A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease
spellingShingle A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease
Hernández González, Jorge E. [UNESP]
3CLpro
D-peptide
molecular dynamics simulation
SARS-CoV-2
virtual screening
title_short A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease
title_full A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease
title_fullStr A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease
title_full_unstemmed A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease
title_sort A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease
author Hernández González, Jorge E. [UNESP]
author_facet Hernández González, Jorge E. [UNESP]
Eberle, Raphael J.
Willbold, Dieter
Coronado, Mônika A.
author_role author
author2 Eberle, Raphael J.
Willbold, Dieter
Coronado, Mônika A.
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Universidade Federal do Rio de Janeiro (UFRJ)
Forschungszentrum Jülich
Universitätsstraße
dc.contributor.author.fl_str_mv Hernández González, Jorge E. [UNESP]
Eberle, Raphael J.
Willbold, Dieter
Coronado, Mônika A.
dc.subject.por.fl_str_mv 3CLpro
D-peptide
molecular dynamics simulation
SARS-CoV-2
virtual screening
topic 3CLpro
D-peptide
molecular dynamics simulation
SARS-CoV-2
virtual screening
description The SARS-CoV-2 main protease, also known as 3-chymotrypsin-like protease (3CLpro), is a cysteine protease responsible for the cleavage of viral polyproteins pp1a and pp1ab, at least, at eleven conserved sites, which leads to the formation of mature nonstructural proteins essential for the replication of the virus. Due to its essential role, numerous studies have been conducted so far, which have confirmed 3CLpro as an attractive drug target to combat Covid-19 and have reported a vast number of inhibitors and their co-crystal structures. Despite all the ongoing efforts, D-peptides, which possess key advantages over L-peptides as therapeutic agents, have not been explored as potential drug candidates against 3CLpro. The current work fills this gap by reporting an in silico approach for the discovery of D-peptides capable of inhibiting 3CLpro that involves structure-based virtual screening (SBVS) of an in-house library of D-tripeptides and D-tetrapeptides into the protease active site and subsequent rescoring steps, including Molecular Mechanics Generalized-Born Surface Area (MM-GBSA) free energy calculations and molecular dynamics (MD) simulations. In vitro enzymatic assays conducted for the four top-scoring D-tetrapeptides at 20 μM showed that all of them caused 55–85% inhibition of 3CLpro activity, thus highlighting the suitability of the devised approach. Overall, our results present a promising computational strategy to identify D-peptides capable of inhibiting 3CLpro, with broader application in problems involving protein inhibition.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-28T19:50:56Z
2022-04-28T19:50:56Z
2022-01-24
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.3389/fmolb.2021.816166
Frontiers in Molecular Biosciences, v. 8.
2296-889X
http://hdl.handle.net/11449/223492
10.3389/fmolb.2021.816166
2-s2.0-85124938065
url http://dx.doi.org/10.3389/fmolb.2021.816166
http://hdl.handle.net/11449/223492
identifier_str_mv Frontiers in Molecular Biosciences, v. 8.
2296-889X
10.3389/fmolb.2021.816166
2-s2.0-85124938065
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Frontiers in Molecular Biosciences
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1803047373861027840