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Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations

The main protease (Mpro) of the novel coronavirus SARS-CoV-2, which has caused the COVID-19 pandemic, is responsible for the maturation of its key proteins. Thus, inhibiting SARS-CoV-2 Mpro could prevent SARS-CoV-2 from multiplying. Because new inhibitors require thorough validation, repurposing cur...

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Autores principales: Ngo, Son Tung, Nguyen, Hung Minh, Thuy Huong, Le Thi, Quan, Pham Minh, Truong, Vi Khanh, Tung, Nguyen Thanh, Vu, Van V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119318/
https://www.ncbi.nlm.nih.gov/pubmed/35692857
http://dx.doi.org/10.1039/d0ra07352k
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author Ngo, Son Tung
Nguyen, Hung Minh
Thuy Huong, Le Thi
Quan, Pham Minh
Truong, Vi Khanh
Tung, Nguyen Thanh
Vu, Van V.
author_facet Ngo, Son Tung
Nguyen, Hung Minh
Thuy Huong, Le Thi
Quan, Pham Minh
Truong, Vi Khanh
Tung, Nguyen Thanh
Vu, Van V.
author_sort Ngo, Son Tung
collection PubMed
description The main protease (Mpro) of the novel coronavirus SARS-CoV-2, which has caused the COVID-19 pandemic, is responsible for the maturation of its key proteins. Thus, inhibiting SARS-CoV-2 Mpro could prevent SARS-CoV-2 from multiplying. Because new inhibitors require thorough validation, repurposing current drugs could help reduce the validation process. Many recent studies used molecular docking to screen large databases for potential inhibitors of SARS-CoV-2 Mpro. However, molecular docking does not consider molecular dynamics and thus can be prone to error. In this work, we developed a protocol using free energy perturbation (FEP) to assess the potential inhibitors of SARS-CoV-2 Mpro. First, we validated both molecular docking and FEP on a set of 11 inhibitors of SARS-CoV-2 Mpro with experimentally determined inhibitory data. The experimentally deduced binding free energy exhibits significantly stronger correlation with that predicted by FEP (R = 0.94 ± 0.04) than with that predicted by molecular docking (R = 0.82 ± 0.08). This result clearly shows that FEP is the most accurate method available to predict the binding affinity of SARS-CoV-2 Mpro + ligand complexes. We subsequently used FEP to validate the top 33 compounds screened with molecular docking from the ZINC15 database. Thirteen of these compounds were predicted to bind strongly to SARS-CoV-2 Mpro, most of which are currently used as drugs for various diseases in humans. Notably, delamanid, an anti-tuberculosis drug, was predicted to inhibit SARS-CoV-2 Mpro in the nanomolar range. Because both COVID-19 and tuberculosis are lung diseases, delamanid has higher probability to be suitable for treating COVID-19 than other predicted compounds. Analysis of the complexes of SARS-CoV-2 Mpro and the top inhibitors revealed the key residues involved in the binding, including the catalytic dyad His14 and Cys145, which is consistent with the structural studies reported recently.
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spelling pubmed-91193182022-06-10 Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations Ngo, Son Tung Nguyen, Hung Minh Thuy Huong, Le Thi Quan, Pham Minh Truong, Vi Khanh Tung, Nguyen Thanh Vu, Van V. RSC Adv Chemistry The main protease (Mpro) of the novel coronavirus SARS-CoV-2, which has caused the COVID-19 pandemic, is responsible for the maturation of its key proteins. Thus, inhibiting SARS-CoV-2 Mpro could prevent SARS-CoV-2 from multiplying. Because new inhibitors require thorough validation, repurposing current drugs could help reduce the validation process. Many recent studies used molecular docking to screen large databases for potential inhibitors of SARS-CoV-2 Mpro. However, molecular docking does not consider molecular dynamics and thus can be prone to error. In this work, we developed a protocol using free energy perturbation (FEP) to assess the potential inhibitors of SARS-CoV-2 Mpro. First, we validated both molecular docking and FEP on a set of 11 inhibitors of SARS-CoV-2 Mpro with experimentally determined inhibitory data. The experimentally deduced binding free energy exhibits significantly stronger correlation with that predicted by FEP (R = 0.94 ± 0.04) than with that predicted by molecular docking (R = 0.82 ± 0.08). This result clearly shows that FEP is the most accurate method available to predict the binding affinity of SARS-CoV-2 Mpro + ligand complexes. We subsequently used FEP to validate the top 33 compounds screened with molecular docking from the ZINC15 database. Thirteen of these compounds were predicted to bind strongly to SARS-CoV-2 Mpro, most of which are currently used as drugs for various diseases in humans. Notably, delamanid, an anti-tuberculosis drug, was predicted to inhibit SARS-CoV-2 Mpro in the nanomolar range. Because both COVID-19 and tuberculosis are lung diseases, delamanid has higher probability to be suitable for treating COVID-19 than other predicted compounds. Analysis of the complexes of SARS-CoV-2 Mpro and the top inhibitors revealed the key residues involved in the binding, including the catalytic dyad His14 and Cys145, which is consistent with the structural studies reported recently. The Royal Society of Chemistry 2020-11-09 /pmc/articles/PMC9119318/ /pubmed/35692857 http://dx.doi.org/10.1039/d0ra07352k Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Ngo, Son Tung
Nguyen, Hung Minh
Thuy Huong, Le Thi
Quan, Pham Minh
Truong, Vi Khanh
Tung, Nguyen Thanh
Vu, Van V.
Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations
title Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations
title_full Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations
title_fullStr Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations
title_full_unstemmed Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations
title_short Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations
title_sort assessing potential inhibitors of sars-cov-2 main protease from available drugs using free energy perturbation simulations
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119318/
https://www.ncbi.nlm.nih.gov/pubmed/35692857
http://dx.doi.org/10.1039/d0ra07352k
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