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Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking
The coronavirus disease 19 (COVID-19) is a rapidly growing pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its papain-like protease (SARS-CoV-2 PLpro) is a crucial target to halt virus replication. SARS-CoV PLpro and SARS-CoV-2 PLpro share an 82.9% sequence ident...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674952/ https://www.ncbi.nlm.nih.gov/pubmed/33251185 http://dx.doi.org/10.3389/fchem.2020.592289 |
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author | Ibrahim, Tamer M. Ismail, Muhammad I. Bauer, Matthias R. Bekhit, Adnan A. Boeckler, Frank M. |
author_facet | Ibrahim, Tamer M. Ismail, Muhammad I. Bauer, Matthias R. Bekhit, Adnan A. Boeckler, Frank M. |
author_sort | Ibrahim, Tamer M. |
collection | PubMed |
description | The coronavirus disease 19 (COVID-19) is a rapidly growing pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its papain-like protease (SARS-CoV-2 PLpro) is a crucial target to halt virus replication. SARS-CoV PLpro and SARS-CoV-2 PLpro share an 82.9% sequence identity and a 100% sequence identity for the binding site reported to accommodate small molecules in SARS-CoV. The flexible key binding site residues Tyr269 and Gln270 for small-molecule recognition in SARS-CoV PLpro exist also in SARS-CoV-2 PLpro. This inspired us to use the reported small-molecule binders to SARS-CoV PLpro to generate a high-quality DEKOIS 2.0 benchmark set. Accordingly, we used them in a cross-benchmarking study against SARS-CoV-2 PLpro. As there is no SARS-CoV-2 PLpro structure complexed with a small-molecule ligand publicly available at the time of manuscript submission, we built a homology model based on the ligand-bound SARS-CoV structure for benchmarking and docking purposes. Three publicly available docking tools FRED, AutoDock Vina, and PLANTS were benchmarked. All showed better-than-random performances, with FRED performing best against the built model. Detailed performance analysis via pROC-Chemotype plots showed a strong enrichment of the most potent bioactives in the early docking ranks. Cross-benchmarking against the X-ray structure complexed with a peptide-like inhibitor confirmed that FRED is the best-performing tool. Furthermore, we performed cross-benchmarking against the newly introduced X-ray structure complexed with a small-molecule ligand. Interestingly, its benchmarking profile and chemotype enrichment were comparable to the built model. Accordingly, we used FRED in a prospective virtual screen of the DrugBank database. In conclusion, this study provides an example of how to harness a custom-made DEKOIS 2.0 benchmark set as an approach to enhance the virtual screening success rate against a vital target of the rapidly emerging pandemic. |
format | Online Article Text |
id | pubmed-7674952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76749522020-11-27 Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking Ibrahim, Tamer M. Ismail, Muhammad I. Bauer, Matthias R. Bekhit, Adnan A. Boeckler, Frank M. Front Chem Chemistry The coronavirus disease 19 (COVID-19) is a rapidly growing pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its papain-like protease (SARS-CoV-2 PLpro) is a crucial target to halt virus replication. SARS-CoV PLpro and SARS-CoV-2 PLpro share an 82.9% sequence identity and a 100% sequence identity for the binding site reported to accommodate small molecules in SARS-CoV. The flexible key binding site residues Tyr269 and Gln270 for small-molecule recognition in SARS-CoV PLpro exist also in SARS-CoV-2 PLpro. This inspired us to use the reported small-molecule binders to SARS-CoV PLpro to generate a high-quality DEKOIS 2.0 benchmark set. Accordingly, we used them in a cross-benchmarking study against SARS-CoV-2 PLpro. As there is no SARS-CoV-2 PLpro structure complexed with a small-molecule ligand publicly available at the time of manuscript submission, we built a homology model based on the ligand-bound SARS-CoV structure for benchmarking and docking purposes. Three publicly available docking tools FRED, AutoDock Vina, and PLANTS were benchmarked. All showed better-than-random performances, with FRED performing best against the built model. Detailed performance analysis via pROC-Chemotype plots showed a strong enrichment of the most potent bioactives in the early docking ranks. Cross-benchmarking against the X-ray structure complexed with a peptide-like inhibitor confirmed that FRED is the best-performing tool. Furthermore, we performed cross-benchmarking against the newly introduced X-ray structure complexed with a small-molecule ligand. Interestingly, its benchmarking profile and chemotype enrichment were comparable to the built model. Accordingly, we used FRED in a prospective virtual screen of the DrugBank database. In conclusion, this study provides an example of how to harness a custom-made DEKOIS 2.0 benchmark set as an approach to enhance the virtual screening success rate against a vital target of the rapidly emerging pandemic. Frontiers Media S.A. 2020-11-05 /pmc/articles/PMC7674952/ /pubmed/33251185 http://dx.doi.org/10.3389/fchem.2020.592289 Text en Copyright © 2020 Ibrahim, Ismail, Bauer, Bekhit and Boeckler. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Chemistry Ibrahim, Tamer M. Ismail, Muhammad I. Bauer, Matthias R. Bekhit, Adnan A. Boeckler, Frank M. Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking |
title | Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking |
title_full | Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking |
title_fullStr | Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking |
title_full_unstemmed | Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking |
title_short | Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking |
title_sort | supporting sars-cov-2 papain-like protease drug discovery: in silico methods and benchmarking |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674952/ https://www.ncbi.nlm.nih.gov/pubmed/33251185 http://dx.doi.org/10.3389/fchem.2020.592289 |
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