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In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs

The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires treatments with rapid clinical translatability. Here we develop a multi-target and multi-ligand virtual screening method to identify FDA-approved drugs with potential activity against SARS-CoV-2 at t...

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Autores principales: Chan, Wallace K. B., Olson, Keith M., Wotring, Jesse W., Sexton, Jonathan Z., Carlson, Heather A., Traynor, John R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963407/
https://www.ncbi.nlm.nih.gov/pubmed/35351926
http://dx.doi.org/10.1038/s41598-022-08320-y
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author Chan, Wallace K. B.
Olson, Keith M.
Wotring, Jesse W.
Sexton, Jonathan Z.
Carlson, Heather A.
Traynor, John R.
author_facet Chan, Wallace K. B.
Olson, Keith M.
Wotring, Jesse W.
Sexton, Jonathan Z.
Carlson, Heather A.
Traynor, John R.
author_sort Chan, Wallace K. B.
collection PubMed
description The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires treatments with rapid clinical translatability. Here we develop a multi-target and multi-ligand virtual screening method to identify FDA-approved drugs with potential activity against SARS-CoV-2 at traditional and understudied viral targets. 1,268 FDA-approved small molecule drugs were docked to 47 putative binding sites across 23 SARS-CoV-2 proteins. We compared drugs between binding sites and filtered out compounds that had no reported activity in an in vitro screen against SARS-CoV-2 infection of human liver (Huh-7) cells. This identified 17 “high-confidence”, and 97 “medium-confidence” drug-site pairs. The “high-confidence” group was subjected to molecular dynamics simulations to yield six compounds with stable binding poses at their optimal target proteins. Three drugs—amprenavir, levomefolic acid, and calcipotriol—were predicted to bind to 3 different sites on the spike protein, domperidone to the Mac1 domain of the non-structural protein (Nsp) 3, avanafil to Nsp15, and nintedanib to the nucleocapsid protein involved in packaging the viral RNA. Our “two-way” virtual docking screen also provides a framework to prioritize drugs for testing in future emergencies requiring rapidly available clinical drugs and/or treating diseases where a moderate number of targets are known.
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spelling pubmed-89634072022-03-30 In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs Chan, Wallace K. B. Olson, Keith M. Wotring, Jesse W. Sexton, Jonathan Z. Carlson, Heather A. Traynor, John R. Sci Rep Article The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires treatments with rapid clinical translatability. Here we develop a multi-target and multi-ligand virtual screening method to identify FDA-approved drugs with potential activity against SARS-CoV-2 at traditional and understudied viral targets. 1,268 FDA-approved small molecule drugs were docked to 47 putative binding sites across 23 SARS-CoV-2 proteins. We compared drugs between binding sites and filtered out compounds that had no reported activity in an in vitro screen against SARS-CoV-2 infection of human liver (Huh-7) cells. This identified 17 “high-confidence”, and 97 “medium-confidence” drug-site pairs. The “high-confidence” group was subjected to molecular dynamics simulations to yield six compounds with stable binding poses at their optimal target proteins. Three drugs—amprenavir, levomefolic acid, and calcipotriol—were predicted to bind to 3 different sites on the spike protein, domperidone to the Mac1 domain of the non-structural protein (Nsp) 3, avanafil to Nsp15, and nintedanib to the nucleocapsid protein involved in packaging the viral RNA. Our “two-way” virtual docking screen also provides a framework to prioritize drugs for testing in future emergencies requiring rapidly available clinical drugs and/or treating diseases where a moderate number of targets are known. Nature Publishing Group UK 2022-03-29 /pmc/articles/PMC8963407/ /pubmed/35351926 http://dx.doi.org/10.1038/s41598-022-08320-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Chan, Wallace K. B.
Olson, Keith M.
Wotring, Jesse W.
Sexton, Jonathan Z.
Carlson, Heather A.
Traynor, John R.
In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs
title In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs
title_full In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs
title_fullStr In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs
title_full_unstemmed In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs
title_short In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs
title_sort in silico analysis of sars-cov-2 proteins as targets for clinically available drugs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963407/
https://www.ncbi.nlm.nih.gov/pubmed/35351926
http://dx.doi.org/10.1038/s41598-022-08320-y
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