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Prediction of Novel Inhibitors of the Main Protease (M-pro) of SARS-CoV-2 through Consensus Docking and Drug Reposition

Since the outbreak of the COVID-19 pandemic in December 2019 and its rapid spread worldwide, the scientific community has been under pressure to react and make progress in the development of an effective treatment against the virus responsible for the disease. Here, we implement an original virtual...

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Autores principales: Gimeno, Aleix, Mestres-Truyol, Júlia, Ojeda-Montes, María José, Macip, Guillem, Saldivar-Espinoza, Bryan, Cereto-Massagué, Adrià, Pujadas, Gerard, Garcia-Vallvé, Santiago
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7312484/
https://www.ncbi.nlm.nih.gov/pubmed/32471205
http://dx.doi.org/10.3390/ijms21113793
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author Gimeno, Aleix
Mestres-Truyol, Júlia
Ojeda-Montes, María José
Macip, Guillem
Saldivar-Espinoza, Bryan
Cereto-Massagué, Adrià
Pujadas, Gerard
Garcia-Vallvé, Santiago
author_facet Gimeno, Aleix
Mestres-Truyol, Júlia
Ojeda-Montes, María José
Macip, Guillem
Saldivar-Espinoza, Bryan
Cereto-Massagué, Adrià
Pujadas, Gerard
Garcia-Vallvé, Santiago
author_sort Gimeno, Aleix
collection PubMed
description Since the outbreak of the COVID-19 pandemic in December 2019 and its rapid spread worldwide, the scientific community has been under pressure to react and make progress in the development of an effective treatment against the virus responsible for the disease. Here, we implement an original virtual screening (VS) protocol for repositioning approved drugs in order to predict which of them could inhibit the main protease of the virus (M-pro), a key target for antiviral drugs given its essential role in the virus’ replication. Two different libraries of approved drugs were docked against the structure of M-pro using Glide, FRED and AutoDock Vina, and only the equivalent high affinity binding modes predicted simultaneously by the three docking programs were considered to correspond to bioactive poses. In this way, we took advantage of the three sampling algorithms to generate hypothetic binding modes without relying on a single scoring function to rank the results. Seven possible SARS-CoV-2 M-pro inhibitors were predicted using this approach: Perampanel, Carprofen, Celecoxib, Alprazolam, Trovafloxacin, Sarafloxacin and ethyl biscoumacetate. Carprofen and Celecoxib have been selected by the COVID Moonshot initiative for in vitro testing; they show 3.97 and 11.90% M-pro inhibition at 50 µM, respectively.
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spelling pubmed-73124842020-06-29 Prediction of Novel Inhibitors of the Main Protease (M-pro) of SARS-CoV-2 through Consensus Docking and Drug Reposition Gimeno, Aleix Mestres-Truyol, Júlia Ojeda-Montes, María José Macip, Guillem Saldivar-Espinoza, Bryan Cereto-Massagué, Adrià Pujadas, Gerard Garcia-Vallvé, Santiago Int J Mol Sci Article Since the outbreak of the COVID-19 pandemic in December 2019 and its rapid spread worldwide, the scientific community has been under pressure to react and make progress in the development of an effective treatment against the virus responsible for the disease. Here, we implement an original virtual screening (VS) protocol for repositioning approved drugs in order to predict which of them could inhibit the main protease of the virus (M-pro), a key target for antiviral drugs given its essential role in the virus’ replication. Two different libraries of approved drugs were docked against the structure of M-pro using Glide, FRED and AutoDock Vina, and only the equivalent high affinity binding modes predicted simultaneously by the three docking programs were considered to correspond to bioactive poses. In this way, we took advantage of the three sampling algorithms to generate hypothetic binding modes without relying on a single scoring function to rank the results. Seven possible SARS-CoV-2 M-pro inhibitors were predicted using this approach: Perampanel, Carprofen, Celecoxib, Alprazolam, Trovafloxacin, Sarafloxacin and ethyl biscoumacetate. Carprofen and Celecoxib have been selected by the COVID Moonshot initiative for in vitro testing; they show 3.97 and 11.90% M-pro inhibition at 50 µM, respectively. MDPI 2020-05-27 /pmc/articles/PMC7312484/ /pubmed/32471205 http://dx.doi.org/10.3390/ijms21113793 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gimeno, Aleix
Mestres-Truyol, Júlia
Ojeda-Montes, María José
Macip, Guillem
Saldivar-Espinoza, Bryan
Cereto-Massagué, Adrià
Pujadas, Gerard
Garcia-Vallvé, Santiago
Prediction of Novel Inhibitors of the Main Protease (M-pro) of SARS-CoV-2 through Consensus Docking and Drug Reposition
title Prediction of Novel Inhibitors of the Main Protease (M-pro) of SARS-CoV-2 through Consensus Docking and Drug Reposition
title_full Prediction of Novel Inhibitors of the Main Protease (M-pro) of SARS-CoV-2 through Consensus Docking and Drug Reposition
title_fullStr Prediction of Novel Inhibitors of the Main Protease (M-pro) of SARS-CoV-2 through Consensus Docking and Drug Reposition
title_full_unstemmed Prediction of Novel Inhibitors of the Main Protease (M-pro) of SARS-CoV-2 through Consensus Docking and Drug Reposition
title_short Prediction of Novel Inhibitors of the Main Protease (M-pro) of SARS-CoV-2 through Consensus Docking and Drug Reposition
title_sort prediction of novel inhibitors of the main protease (m-pro) of sars-cov-2 through consensus docking and drug reposition
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7312484/
https://www.ncbi.nlm.nih.gov/pubmed/32471205
http://dx.doi.org/10.3390/ijms21113793
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