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Study of Inhibitors Against SARS Coronavirus by Computational Approaches
Called by many as the biology's version of Swiss army knives, proteases cut long sequences of amino acids into fragments and regulate most physiological processes. They are vitally important in life cycle and have become a main target for drug design. This Chapter is focused on a special protea...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122585/ http://dx.doi.org/10.1007/978-90-481-2348-3_1 |
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author | Chou, Kuo-Chen Wei, Dong-Qing Du, Qi-Shi Sirois, Suzanne Shen, Hong-Bin Zhong, Wei-Zhu |
author_facet | Chou, Kuo-Chen Wei, Dong-Qing Du, Qi-Shi Sirois, Suzanne Shen, Hong-Bin Zhong, Wei-Zhu |
author_sort | Chou, Kuo-Chen |
collection | PubMed |
description | Called by many as the biology's version of Swiss army knives, proteases cut long sequences of amino acids into fragments and regulate most physiological processes. They are vitally important in life cycle and have become a main target for drug design. This Chapter is focused on a special protease that plays a key role in replicating SARS (Severe Acute Respiratory Syndrome) coronavirus, the culprit of SARS disease. The progresses reported here are mainly from various computational approaches, such as structural bioinformatics, pharmacophore modelling, molecular docking, and peptide-cleavage site prediction, among others. It is highlighted that the compounds C(28)H(34)O(4)N(7)Cl, C(21)H(36)O(5)N(6) and C(21)H(36)O(5)N(6), as well as KZ7088, a derivative of AG7088, might be the promising candidates for further investigation, and that the octapeptides ATLQAIAS and ATLQAENV, as well as AVLQSGFR, might be converted to effective inhibitors against the SARS protease. Meanwhile, how to modify these octapeptides based on the “distorted key” theory to make them become potent inhibitors is explicitly elucidated. Also, a brief introduction is given for how to use computer-generated graphs to rapidly diagnose SARS coronavirus. Finally, a step-by-step protocol guide is given on how to use ProtIdent, a web-server developed recently, to identify the proteases and their types based on their sequence information alone. ProtIdent is a very user-friendly bioin-formatics tool that can provide desired information for both basic research and drug discovery in a timely manner. With the avalanche of protein sequences generated in the post-genomic age, it is particularly useful. ProtIdent is freely accessible to the public via the web-site at http://www.csbio.sjtu.edu.cn/bioinf/Protease/. |
format | Online Article Text |
id | pubmed-7122585 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71225852020-04-06 Study of Inhibitors Against SARS Coronavirus by Computational Approaches Chou, Kuo-Chen Wei, Dong-Qing Du, Qi-Shi Sirois, Suzanne Shen, Hong-Bin Zhong, Wei-Zhu Viral Proteases and Antiviral Protease Inhibitor Therapy Article Called by many as the biology's version of Swiss army knives, proteases cut long sequences of amino acids into fragments and regulate most physiological processes. They are vitally important in life cycle and have become a main target for drug design. This Chapter is focused on a special protease that plays a key role in replicating SARS (Severe Acute Respiratory Syndrome) coronavirus, the culprit of SARS disease. The progresses reported here are mainly from various computational approaches, such as structural bioinformatics, pharmacophore modelling, molecular docking, and peptide-cleavage site prediction, among others. It is highlighted that the compounds C(28)H(34)O(4)N(7)Cl, C(21)H(36)O(5)N(6) and C(21)H(36)O(5)N(6), as well as KZ7088, a derivative of AG7088, might be the promising candidates for further investigation, and that the octapeptides ATLQAIAS and ATLQAENV, as well as AVLQSGFR, might be converted to effective inhibitors against the SARS protease. Meanwhile, how to modify these octapeptides based on the “distorted key” theory to make them become potent inhibitors is explicitly elucidated. Also, a brief introduction is given for how to use computer-generated graphs to rapidly diagnose SARS coronavirus. Finally, a step-by-step protocol guide is given on how to use ProtIdent, a web-server developed recently, to identify the proteases and their types based on their sequence information alone. ProtIdent is a very user-friendly bioin-formatics tool that can provide desired information for both basic research and drug discovery in a timely manner. With the avalanche of protein sequences generated in the post-genomic age, it is particularly useful. ProtIdent is freely accessible to the public via the web-site at http://www.csbio.sjtu.edu.cn/bioinf/Protease/. 2009 /pmc/articles/PMC7122585/ http://dx.doi.org/10.1007/978-90-481-2348-3_1 Text en © Springer Science+Business Media B.V. 2009 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Chou, Kuo-Chen Wei, Dong-Qing Du, Qi-Shi Sirois, Suzanne Shen, Hong-Bin Zhong, Wei-Zhu Study of Inhibitors Against SARS Coronavirus by Computational Approaches |
title | Study of Inhibitors Against SARS Coronavirus by Computational Approaches |
title_full | Study of Inhibitors Against SARS Coronavirus by Computational Approaches |
title_fullStr | Study of Inhibitors Against SARS Coronavirus by Computational Approaches |
title_full_unstemmed | Study of Inhibitors Against SARS Coronavirus by Computational Approaches |
title_short | Study of Inhibitors Against SARS Coronavirus by Computational Approaches |
title_sort | study of inhibitors against sars coronavirus by computational approaches |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122585/ http://dx.doi.org/10.1007/978-90-481-2348-3_1 |
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