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Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods
SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming process of new drug development, drug repositioning may be the only solution to the epidemic of sudden i...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7102550/ https://www.ncbi.nlm.nih.gov/pubmed/32292689 http://dx.doi.org/10.1016/j.apsb.2020.02.008 |
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author | Wu, Canrong Liu, Yang Yang, Yueying Zhang, Peng Zhong, Wu Wang, Yali Wang, Qiqi Xu, Yang Li, Mingxue Li, Xingzhou Zheng, Mengzhu Chen, Lixia Li, Hua |
author_facet | Wu, Canrong Liu, Yang Yang, Yueying Zhang, Peng Zhong, Wu Wang, Yali Wang, Qiqi Xu, Yang Li, Mingxue Li, Xingzhou Zheng, Mengzhu Chen, Lixia Li, Hua |
author_sort | Wu, Canrong |
collection | PubMed |
description | SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming process of new drug development, drug repositioning may be the only solution to the epidemic of sudden infectious diseases. We systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling. By performing target-based virtual ligand screening, a total of 21 targets (including two human targets) were screened against compound libraries including ZINC drug database and our own database of natural products. Structure and screening results of important targets such as 3-chymotrypsin-like protease (3CLpro), Spike, RNA-dependent RNA polymerase (RdRp), and papain like protease (PLpro) were discussed in detail. In addition, a database of 78 commonly used anti-viral drugs including those currently on the market and undergoing clinical trials for SARS-CoV-2 was constructed. Possible targets of these compounds and potential drugs acting on a certain target were predicted. This study will provide new lead compounds and targets for further in vitro and in vivo studies of SARS-CoV-2, new insights for those drugs currently ongoing clinical studies, and also possible new strategies for drug repositioning to treat SARS-CoV-2 infections. |
format | Online Article Text |
id | pubmed-7102550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-71025502020-03-31 Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods Wu, Canrong Liu, Yang Yang, Yueying Zhang, Peng Zhong, Wu Wang, Yali Wang, Qiqi Xu, Yang Li, Mingxue Li, Xingzhou Zheng, Mengzhu Chen, Lixia Li, Hua Acta Pharm Sin B Original article SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming process of new drug development, drug repositioning may be the only solution to the epidemic of sudden infectious diseases. We systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling. By performing target-based virtual ligand screening, a total of 21 targets (including two human targets) were screened against compound libraries including ZINC drug database and our own database of natural products. Structure and screening results of important targets such as 3-chymotrypsin-like protease (3CLpro), Spike, RNA-dependent RNA polymerase (RdRp), and papain like protease (PLpro) were discussed in detail. In addition, a database of 78 commonly used anti-viral drugs including those currently on the market and undergoing clinical trials for SARS-CoV-2 was constructed. Possible targets of these compounds and potential drugs acting on a certain target were predicted. This study will provide new lead compounds and targets for further in vitro and in vivo studies of SARS-CoV-2, new insights for those drugs currently ongoing clinical studies, and also possible new strategies for drug repositioning to treat SARS-CoV-2 infections. Elsevier 2020-05 2020-02-27 /pmc/articles/PMC7102550/ /pubmed/32292689 http://dx.doi.org/10.1016/j.apsb.2020.02.008 Text en © 2020 Chinese Pharmaceutical Association and Institute of Materia Medica, Chinese Academy of Medical Sciences. Production and hosting by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original article Wu, Canrong Liu, Yang Yang, Yueying Zhang, Peng Zhong, Wu Wang, Yali Wang, Qiqi Xu, Yang Li, Mingxue Li, Xingzhou Zheng, Mengzhu Chen, Lixia Li, Hua Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods |
title | Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods |
title_full | Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods |
title_fullStr | Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods |
title_full_unstemmed | Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods |
title_short | Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods |
title_sort | analysis of therapeutic targets for sars-cov-2 and discovery of potential drugs by computational methods |
topic | Original article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7102550/ https://www.ncbi.nlm.nih.gov/pubmed/32292689 http://dx.doi.org/10.1016/j.apsb.2020.02.008 |
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