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Generation of predictive pharmacophore model for SARS-coronavirus main proteinase
Pharmacophore-based virtual screening is an effective, inexpensive and fast approach to discovering useful starting points for drug discovery. In this study, we developed a pharmacophore model for the main proteinase of severe acute respiratory syndrome coronavirus (SARS-CoV). Then we used this phar...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier SAS.
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115589/ https://www.ncbi.nlm.nih.gov/pubmed/15642409 http://dx.doi.org/10.1016/j.ejmech.2004.09.013 |
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author | Zhang, Xue Wu Yap, Yee Leng Altmeyer, Ralf M. |
author_facet | Zhang, Xue Wu Yap, Yee Leng Altmeyer, Ralf M. |
author_sort | Zhang, Xue Wu |
collection | PubMed |
description | Pharmacophore-based virtual screening is an effective, inexpensive and fast approach to discovering useful starting points for drug discovery. In this study, we developed a pharmacophore model for the main proteinase of severe acute respiratory syndrome coronavirus (SARS-CoV). Then we used this pharmacophore model to search NCI 3D database including 250, 251 compounds and identified 30 existing drugs containing the pharmacophore query. Among them are six compounds that already exhibited anti-SARS-CoV activity experimentally. This means that our pharmacophore model can lead to the discovery of potent anti-SARS-CoV inhibitors or promising lead compounds for further SARS-CoV main proteinase inhibitor development. |
format | Online Article Text |
id | pubmed-7115589 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | Elsevier SAS. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71155892020-04-02 Generation of predictive pharmacophore model for SARS-coronavirus main proteinase Zhang, Xue Wu Yap, Yee Leng Altmeyer, Ralf M. Eur J Med Chem Original Article Pharmacophore-based virtual screening is an effective, inexpensive and fast approach to discovering useful starting points for drug discovery. In this study, we developed a pharmacophore model for the main proteinase of severe acute respiratory syndrome coronavirus (SARS-CoV). Then we used this pharmacophore model to search NCI 3D database including 250, 251 compounds and identified 30 existing drugs containing the pharmacophore query. Among them are six compounds that already exhibited anti-SARS-CoV activity experimentally. This means that our pharmacophore model can lead to the discovery of potent anti-SARS-CoV inhibitors or promising lead compounds for further SARS-CoV main proteinase inhibitor development. Elsevier SAS. 2005-01 2004-11-05 /pmc/articles/PMC7115589/ /pubmed/15642409 http://dx.doi.org/10.1016/j.ejmech.2004.09.013 Text en Copyright © 2004 Elsevier SAS. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Article Zhang, Xue Wu Yap, Yee Leng Altmeyer, Ralf M. Generation of predictive pharmacophore model for SARS-coronavirus main proteinase |
title | Generation of predictive pharmacophore model for SARS-coronavirus main proteinase |
title_full | Generation of predictive pharmacophore model for SARS-coronavirus main proteinase |
title_fullStr | Generation of predictive pharmacophore model for SARS-coronavirus main proteinase |
title_full_unstemmed | Generation of predictive pharmacophore model for SARS-coronavirus main proteinase |
title_short | Generation of predictive pharmacophore model for SARS-coronavirus main proteinase |
title_sort | generation of predictive pharmacophore model for sars-coronavirus main proteinase |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115589/ https://www.ncbi.nlm.nih.gov/pubmed/15642409 http://dx.doi.org/10.1016/j.ejmech.2004.09.013 |
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