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D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19
A highly effective medicine is urgently required to cure coronavirus disease 2019 (COVID-19). For the purpose, we developed a molecular docking based webserver, namely D3Targets-2019-nCoV, with two functions, one is for predicting drug targets for drugs or active compounds observed from clinic or in...
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/PMC7169934/ https://www.ncbi.nlm.nih.gov/pubmed/32318328 http://dx.doi.org/10.1016/j.apsb.2020.04.006 |
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author | Shi, Yulong Zhang, Xinben Mu, Kaijie Peng, Cheng Zhu, Zhengdan Wang, Xiaoyu Yang, Yanqing Xu, Zhijian Zhu, Weiliang |
author_facet | Shi, Yulong Zhang, Xinben Mu, Kaijie Peng, Cheng Zhu, Zhengdan Wang, Xiaoyu Yang, Yanqing Xu, Zhijian Zhu, Weiliang |
author_sort | Shi, Yulong |
collection | PubMed |
description | A highly effective medicine is urgently required to cure coronavirus disease 2019 (COVID-19). For the purpose, we developed a molecular docking based webserver, namely D3Targets-2019-nCoV, with two functions, one is for predicting drug targets for drugs or active compounds observed from clinic or in vitro/in vivo studies, the other is for identifying lead compounds against potential drug targets via docking. This server has its unique features, (1) the potential target proteins and their different conformations involving in the whole process from virus infection to replication and release were included as many as possible; (2) all the potential ligand-binding sites with volume larger than 200 Å(3) on a protein structure were identified for docking; (3) correlation information among some conformations or binding sites was annotated; (4) it is easy to be updated, and is accessible freely to public (https://www.d3pharma.com/D3Targets-2019-nCoV/index.php). Currently, the webserver contains 42 proteins [20 severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) encoded proteins and 22 human proteins involved in virus infection, replication and release] with 69 different conformations/structures and 557 potential ligand-binding pockets in total. With 6 examples, we demonstrated that the webserver should be useful to medicinal chemists, pharmacologists and clinicians for efficiently discovering or developing effective drugs against the SARS-CoV-2 to cure COVID-19. |
format | Online Article Text |
id | pubmed-7169934 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-71699342020-04-21 D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19 Shi, Yulong Zhang, Xinben Mu, Kaijie Peng, Cheng Zhu, Zhengdan Wang, Xiaoyu Yang, Yanqing Xu, Zhijian Zhu, Weiliang Acta Pharm Sin B Original article A highly effective medicine is urgently required to cure coronavirus disease 2019 (COVID-19). For the purpose, we developed a molecular docking based webserver, namely D3Targets-2019-nCoV, with two functions, one is for predicting drug targets for drugs or active compounds observed from clinic or in vitro/in vivo studies, the other is for identifying lead compounds against potential drug targets via docking. This server has its unique features, (1) the potential target proteins and their different conformations involving in the whole process from virus infection to replication and release were included as many as possible; (2) all the potential ligand-binding sites with volume larger than 200 Å(3) on a protein structure were identified for docking; (3) correlation information among some conformations or binding sites was annotated; (4) it is easy to be updated, and is accessible freely to public (https://www.d3pharma.com/D3Targets-2019-nCoV/index.php). Currently, the webserver contains 42 proteins [20 severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) encoded proteins and 22 human proteins involved in virus infection, replication and release] with 69 different conformations/structures and 557 potential ligand-binding pockets in total. With 6 examples, we demonstrated that the webserver should be useful to medicinal chemists, pharmacologists and clinicians for efficiently discovering or developing effective drugs against the SARS-CoV-2 to cure COVID-19. Elsevier 2020-07 2020-04-20 /pmc/articles/PMC7169934/ /pubmed/32318328 http://dx.doi.org/10.1016/j.apsb.2020.04.006 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 Shi, Yulong Zhang, Xinben Mu, Kaijie Peng, Cheng Zhu, Zhengdan Wang, Xiaoyu Yang, Yanqing Xu, Zhijian Zhu, Weiliang D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19 |
title | D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19 |
title_full | D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19 |
title_fullStr | D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19 |
title_full_unstemmed | D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19 |
title_short | D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19 |
title_sort | d3targets-2019-ncov: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against covid-19 |
topic | Original article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7169934/ https://www.ncbi.nlm.nih.gov/pubmed/32318328 http://dx.doi.org/10.1016/j.apsb.2020.04.006 |
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