Modeling of noncovalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-2 considering the protein flexibility by using molecular dynamics and cross-docking

datacite.creatorValdés Albuernes, Jorge Luis
datacite.creatorDíaz Pico, Erbio
datacite.creatorAlfaro, Sergio
datacite.creatorCaballero, Julio
datacite.date.issued2024
datacite.identifierDOI
datacite.identifier.doi10.3389/fmolb.2024.1374364
datacite.identifier.issn2296-889X
datacite.identifier.orcid0000-0003-0182-1444
datacite.identifier.wosidWOS:001198857700001
datacite.rightsAcceso abierto
datacite.subjectPapain-like protease
datacite.subjectPLpro inhibitors
datacite.subjectSARS-CoV-2
datacite.subjectDocking energy-activity correlation
datacite.subjectFlexible molecular docking
datacite.subjectMolecular dynamics
datacite.titleModeling of noncovalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-2 considering the protein flexibility by using molecular dynamics and cross-docking
dc.date.accessioned2024-10-15T20:48:48Z
dc.date.available2024-10-15T20:48:48Z
dc.description.abstractThe papain-like protease (PLpro) found in coronaviruses that can be transmitted from animals to humans is a critical target in respiratory diseases linked to Severe Acute Respiratory Syndrome (SARS-CoV). Researchers have proposed designing PLpro inhibitors. In this study, a set of 89 compounds, including recently reported 2-phenylthiophenes with nanomolar inhibitory potency, were investigated as PLpro noncovalent inhibitors using advanced molecular modeling techniques. To develop the work with these inhibitors, multiple structures of the SARS-CoV-2 PLpro binding site were generated using a molecular sampling method. These structures were then clustered to select a group that represents the flexibility of the site. Subsequently, models of the protein-ligand complexes were created for the set of inhibitors within the chosen conformations. The quality of the complex models was assessed using LigRMSD software to verify similarities in the orientations of the congeneric series and interaction fingerprints to determine the recurrence of chemical interactions. With the multiple models constructed, a protocol was established to choose one per ligand, optimizing the correlation between the calculated docking energy values and the biological activities while incorporating the effect of the binding site's flexibility. A strong correlation (R2 = 0.922) was found when employing this flexible docking protocol.
dc.description.pages15 p.
dc.identifier.folio1210138
dc.identifier.urihttps://repositorio.utalca.cl/repositorio/handle/1950/14301
dc.languageInglés
dc.publisherFrontiers
dc.relation.urihttps://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2024.1374364/full
dc.sourceFrontiers in Molecular Biosciences
oaire.citationTitleFrontiers in Molecular Biosciences
oaire.fundingReferenceThe author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research was funded by FONDECYT Regular grant number 1210138 (JC).
oaire.licenseConditionhttp://creativecommons.org/licenses/by/4.0/
oaire.licenseCondition.urihttp://creativecommons.org/licenses/by/4.0/
oaire.resourceTypeArtículo de Revista
oaire.versionVersión Publicada
utalca.catalogadorPAG
utalca.facultadUniversidad de Talca (Chile). Facultad de Ingeniería. Centro de Bioinformática Simulación y Modelado.
utalca.idcargapag15102024
utalca.indexArtículo indexado en Web of Science
utalca.indexArtículo indexado en Scopus
utalca.informaciondegeneroHombre
utalca.odsSalud y bienestar
utalca.odsIndustria, innovación e infraestructura
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