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Open AccessArticle

Ligand-Based and Structured-Based In Silico Repurposing Approaches to Predict Inhibitors of SARS-CoV-2 Mpro Protein

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Laboratorio de Biotecnología Farmacéutica, Centro de Biotecnología Genómica, Instituto Politécnico Nacional, Reynosa 88710, Mexico
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Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas 98000, Mexico
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Tecnológico Nacional de México/ITS de Comalcalco, Tabasco 86650, Mexico
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Laboratorio de Bioquímica Microbiana, Departamento de Microbiología, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Ciudad de México 11340, Mexico
*
Author to whom correspondence should be addressed.
Sci. Pharm. 2020, 88(4), 54; https://doi.org/10.3390/scipharm88040054
Received: 19 October 2020 / Revised: 12 November 2020 / Accepted: 12 November 2020 / Published: 19 November 2020
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a coronavirus that causes the pandemic Coronavirus Disease 2019 (COVID-19). There is no current specific treatment for this new coronavirus. In this study, we employed a virtual screening repurposing strategy to search for potential SARS-CoV-2 Mpro inhibitors. The databases PDB, ChEMBL, BindingDB and DrugBank were queried with several filtering steps based on ligand-based and structure-based approaches. As a result, we obtained 58 molecules (37 from ChEMBL and 21 from DrugBank) that potentially inhibit SARS-CoV-2 Mpro. These molecules have on their chemical structure functional groups that favor stronger docking scores than the inhibitor N3. Several of these molecules are reported experimentally as SARS-CoV Mpro inhibitors. Hence, a combined virtual screening strategy allowed finding chemical compounds with a high potential for the inhibition of SARS-CoV-2 Mpro. View Full-Text
Keywords: SARS-CoV-2; docking; virtual screening; repurposing SARS-CoV-2; docking; virtual screening; repurposing
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MDPI and ACS Style

Juárez-Saldívar, A.; Lara-Ramírez, E.E.; Reyes-Espinosa, F.; Paz-González, A.D.; Villalobos-Rocha, J.C.; Rivera, G. Ligand-Based and Structured-Based In Silico Repurposing Approaches to Predict Inhibitors of SARS-CoV-2 Mpro Protein. Sci. Pharm. 2020, 88, 54.

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