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Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research
Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for medicines that can help before vaccines are available. In this study, we present a viral-associated disease-specific chemoge...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454273/ https://www.ncbi.nlm.nih.gov/pubmed/32715315 http://dx.doi.org/10.1093/bib/bbaa155 |
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author | Feng, Zhiwei Chen, Maozi Liang, Tianjian Shen, Mingzhe Chen, Hui Xie, Xiang-Qun |
author_facet | Feng, Zhiwei Chen, Maozi Liang, Tianjian Shen, Mingzhe Chen, Hui Xie, Xiang-Qun |
author_sort | Feng, Zhiwei |
collection | PubMed |
description | Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for medicines that can help before vaccines are available. In this study, we present a viral-associated disease-specific chemogenomics knowledgebase (Virus-CKB) and apply our computational systems pharmacology-target mapping to rapidly predict the FDA-approved drugs which can quickly progress into clinical trials to meet the urgent demand of the COVID-19 outbreak. Virus-CKB reuses the underlying platform of our DAKB-GPCRs but adds new features like multiple-compound support, multi-cavity protein support and customizable symbol display. Our one-stop computing platform describes the chemical molecules, genes and proteins involved in viral-associated diseases regulation. To date, Virus-CKB archived 65 antiviral drugs in the market, 107 viral-related targets with 189 available 3D crystal or cryo-EM structures and 2698 chemical agents reported for these target proteins. Moreover, Virus-CKB is implemented with web applications for the prediction of the relevant protein targets and analysis and visualization of the outputs, including HTDocking, TargetHunter, BBB predictor, NGL Viewer, Spider Plot, etc. The Virus-CKB server is accessible at https://www.cbligand.org/g/virus-ckb. |
format | Online Article Text |
id | pubmed-7454273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-74542732020-08-31 Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research Feng, Zhiwei Chen, Maozi Liang, Tianjian Shen, Mingzhe Chen, Hui Xie, Xiang-Qun Brief Bioinform Problem Solving Protocol Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for medicines that can help before vaccines are available. In this study, we present a viral-associated disease-specific chemogenomics knowledgebase (Virus-CKB) and apply our computational systems pharmacology-target mapping to rapidly predict the FDA-approved drugs which can quickly progress into clinical trials to meet the urgent demand of the COVID-19 outbreak. Virus-CKB reuses the underlying platform of our DAKB-GPCRs but adds new features like multiple-compound support, multi-cavity protein support and customizable symbol display. Our one-stop computing platform describes the chemical molecules, genes and proteins involved in viral-associated diseases regulation. To date, Virus-CKB archived 65 antiviral drugs in the market, 107 viral-related targets with 189 available 3D crystal or cryo-EM structures and 2698 chemical agents reported for these target proteins. Moreover, Virus-CKB is implemented with web applications for the prediction of the relevant protein targets and analysis and visualization of the outputs, including HTDocking, TargetHunter, BBB predictor, NGL Viewer, Spider Plot, etc. The Virus-CKB server is accessible at https://www.cbligand.org/g/virus-ckb. Oxford University Press 2020-07-27 /pmc/articles/PMC7454273/ /pubmed/32715315 http://dx.doi.org/10.1093/bib/bbaa155 Text en © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) |
spellingShingle | Problem Solving Protocol Feng, Zhiwei Chen, Maozi Liang, Tianjian Shen, Mingzhe Chen, Hui Xie, Xiang-Qun Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research |
title | Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research |
title_full | Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research |
title_fullStr | Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research |
title_full_unstemmed | Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research |
title_short | Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research |
title_sort | virus-ckb: an integrated bioinformatics platform and analysis resource for covid-19 research |
topic | Problem Solving Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454273/ https://www.ncbi.nlm.nih.gov/pubmed/32715315 http://dx.doi.org/10.1093/bib/bbaa155 |
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