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Article

Drugs Repurposing Using QSAR, Docking and Molecular Dynamics for Possible Inhibitors of the SARS-CoV-2 Mpro Protease

1
Grupo de Bio-Quimioinformática, Universidad de Las Américas, Quito 170513, Ecuador
2
Facultad de Ingeniería y Ciencias Aplicadas, Universidad de Las Américas, Quito 170513, Ecuador
3
Faculty of Computer Science, Centre for Information and Communications Technology Research (CITIC), University of A Coruna, 15007 A Coruña, Spain
4
Biomedical Research Institute of A Coruña (INIBIC), University Hospital Complex of A Coruna (CHUAC), 15006 A Coruña, Spain
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Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito 170129, Ecuador
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Latin American Network for Implementation and Validation of Clinical Pharmacogenomics Guidelines (RELIVAF-CYTED), 28029 Madrid, Spain
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Carrera de Enfermería, Facultad de Ciencias de la Salud, Universidad de Las Américas, Quito 170513, Ecuador
8
Escuela de Ciencias Físicas y Matemáticas, Universidad de Las Américas, Quito 170513, Ecuador
*
Authors to whom correspondence should be addressed.
Academic Editors: Alla P. Toropova and James W. Gauld
Molecules 2020, 25(21), 5172; https://doi.org/10.3390/molecules25215172
Received: 26 September 2020 / Revised: 28 October 2020 / Accepted: 4 November 2020 / Published: 6 November 2020
(This article belongs to the Special Issue QSAR and QSPR: Recent Developments and Applications II)
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 (Mpro) 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 Mpro 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 Mpro enzyme. Five other compounds showed also a negative but small free energy of binding: nikethamide, nifurtimox, rebimastat, apomine and rebastinib. View Full-Text
Keywords: SARS-CoV-2; COVID-19; QSAR; drugs repurposing; molecular dynamics SARS-CoV-2; COVID-19; QSAR; drugs repurposing; molecular dynamics
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MDPI and ACS Style

Tejera, E.; Munteanu, C.R.; López-Cortés, A.; Cabrera-Andrade, A.; Pérez-Castillo, Y. Drugs Repurposing Using QSAR, Docking and Molecular Dynamics for Possible Inhibitors of the SARS-CoV-2 Mpro Protease. Molecules 2020, 25, 5172. https://doi.org/10.3390/molecules25215172

AMA Style

Tejera E, Munteanu CR, López-Cortés A, Cabrera-Andrade A, Pérez-Castillo Y. Drugs Repurposing Using QSAR, Docking and Molecular Dynamics for Possible Inhibitors of the SARS-CoV-2 Mpro Protease. Molecules. 2020; 25(21):5172. https://doi.org/10.3390/molecules25215172

Chicago/Turabian Style

Tejera, Eduardo, Cristian R. Munteanu, Andrés López-Cortés, Alejandro Cabrera-Andrade, and Yunierkis Pérez-Castillo. 2020. "Drugs Repurposing Using QSAR, Docking and Molecular Dynamics for Possible Inhibitors of the SARS-CoV-2 Mpro Protease" Molecules 25, no. 21: 5172. https://doi.org/10.3390/molecules25215172

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