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Drugs Repurposing Using QSAR, Docking and Molecular Dynamics for Possible Inhibitors of the SARS-CoV-2 M(pro) Protease
dc.contributor.author | Tejera, Eduardo | |
dc.contributor.author | MUNTEANU -, CRISTIAN ROBERT | |
dc.contributor.author | López-Cortés, Andrés | |
dc.contributor.author | Cabrera-Andrade, Alejandro | |
dc.contributor.author | Pérez-Castillo, Yunierkis | |
dc.date.accessioned | 2022-03-08T08:49:30Z | |
dc.date.available | 2022-03-08T08:49:30Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 1420-3049 | |
dc.identifier.other | https://www.ncbi.nlm.nih.gov/pubmed/33172092 | es |
dc.identifier.uri | http://hdl.handle.net/20.500.11940/16195 | |
dc.description.abstract | Wuhan, China was the epicenter of the first zoonotic transmission of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) in December 2019 and it is the causative agent of the novel human coronavirus disease 2019 (COVID-19). Almost from the beginning of the COVID-19 outbreak several attempts were made to predict possible drugs capable of inhibiting the virus replication. In the present work a drug repurposing study is performed to identify potential SARS-CoV-2 protease inhibitors. We created a Quantitative Structure-Activity Relationship (QSAR) model based on a machine learning strategy using hundreds of inhibitor molecules of the main protease (M(pro)) of the SARS-CoV coronavirus. The QSAR model was used for virtual screening of a large list of drugs from the DrugBank database. The best 20 candidates were then evaluated in-silico against the M(pro) of SARS-CoV-2 by using docking and molecular dynamics analyses. Docking was done by using the Gold software, and the free energies of binding were predicted with the MM-PBSA method as implemented in AMBER. Our results indicate that levothyroxine, amobarbital and ABP-700 are the best potential inhibitors of the SARS-CoV-2 virus through their binding to the M(pro) enzyme. Five other compounds showed also a negative but small free energy of binding: nikethamide, nifurtimox, rebimastat, apomine and rebastinib. | en |
dc.rights | Atribución 4.0 Internacional | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject.mesh | Pandemics | * |
dc.subject.mesh | Drug Repositioning | * |
dc.subject.mesh | Small Molecule Libraries | * |
dc.subject.mesh | Protease Inhibitors | * |
dc.subject.mesh | Binding Sites | * |
dc.subject.mesh | Protein Binding | * |
dc.subject.mesh | Thyroxine | * |
dc.subject.mesh | Quantitative Structure-Activity Relationship | * |
dc.subject.mesh | Thermodynamics | * |
dc.subject.mesh | Humans | * |
dc.subject.mesh | Drug Discovery | * |
dc.subject.mesh | Amobarbital | * |
dc.subject.mesh | Molecular Docking Simulation | * |
dc.subject.mesh | Molecular Dynamics Simulation | * |
dc.subject.mesh | Computer Simulation | * |
dc.subject.mesh | Software | * |
dc.subject.mesh | Antiviral Agents | * |
dc.title | Drugs Repurposing Using QSAR, Docking and Molecular Dynamics for Possible Inhibitors of the SARS-CoV-2 M(pro) Protease | en |
dc.type | Journal Article | es |
dc.authorsophos | Tejera, Eduardo;Munteanu, Cristian R;López-Cortés, Andrés;Cabrera-Andrade, Alejandro;Pérez-Castillo, Yunierkis | |
dc.identifier.doi | 10.3390/molecules25215172 | |
dc.identifier.pmid | 33172092 | |
dc.identifier.sophos | 35786 | |
dc.issue.number | 21 | es |
dc.journal.title | MOLECULES | es |
dc.organization | Servizo Galego de Saúde::Estrutura de Xestión Integrada (EOXI)::Instituto de Investigación Biomédica da Coruña (INIBIC) | es |
dc.relation.publisherversion | https://mdpi-res.com/d://attachment/molecules/molecules-25-05172/article://deploy/molecules-25-05172.pdf | es |
dc.rights.accessRights | openAccess | |
dc.subject.decs | amobarbital | * |
dc.subject.decs | unión proteica | * |
dc.subject.decs | programas informáticos | * |
dc.subject.decs | antivíricos | * |
dc.subject.decs | simulación de acoplamiento molecular | * |
dc.subject.decs | pandemias | * |
dc.subject.decs | bibliotecas de moléculas pequeñas | * |
dc.subject.decs | sitios de unión | * |
dc.subject.decs | simulación de dinámicas moleculares | * |
dc.subject.decs | nuevas indicaciones de medicamentos | * |
dc.subject.decs | tiroxina | * |
dc.subject.decs | relación cuantitativa estructura-actividad | * |
dc.subject.decs | humanos | * |
dc.subject.decs | inhibidores de proteasas | * |
dc.subject.decs | simulación por ordenador | * |
dc.subject.decs | descubrimiento de fármacos | * |
dc.subject.decs | termodinámica | * |
dc.subject.keyword | INIBIC | es |
dc.typefides | Artículo Original | es |
dc.typesophos | Artículo Original | es |
dc.volume.number | 25 | es |