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Machine intelligence design of 2019-nCoV drugs

Wuhan coronavirus, called 2019-nCoV, is a newly emerged virus that infected more than 9692 people and leads to more than 213 fatalities by January 30, 2020. Currently, there is no effective treatment for this epidemic. However, the viral protease of a coronavirus is well-known to be essential for it...

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Autores principales: Gao, Kaifu, Nguyen, Duc Duy, Wang, Rui, Wei, Guo-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217289/
https://www.ncbi.nlm.nih.gov/pubmed/32511308
http://dx.doi.org/10.1101/2020.01.30.927889
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author Gao, Kaifu
Nguyen, Duc Duy
Wang, Rui
Wei, Guo-Wei
author_facet Gao, Kaifu
Nguyen, Duc Duy
Wang, Rui
Wei, Guo-Wei
author_sort Gao, Kaifu
collection PubMed
description Wuhan coronavirus, called 2019-nCoV, is a newly emerged virus that infected more than 9692 people and leads to more than 213 fatalities by January 30, 2020. Currently, there is no effective treatment for this epidemic. However, the viral protease of a coronavirus is well-known to be essential for its replication and thus is an effective drug target. Fortunately, the sequence identity of the 2019-nCoV protease and that of severe-acute respiratory syndrome virus (SARS-CoV) is as high as 96.1%. We show that the protease inhibitor binding sites of 2019-nCoV and SARS-CoV are almost identical, which means all potential anti-SARS-CoV chemotherapies are also potential 2019-nCoV drugs. Here, we report a family of potential 2019-nCoV drugs generated by a machine intelligence-based generative network complex (GNC). The potential effectiveness of treating 2019-nCoV by using some existing HIV drugs is also analyzed.
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spelling pubmed-72172892020-06-07 Machine intelligence design of 2019-nCoV drugs Gao, Kaifu Nguyen, Duc Duy Wang, Rui Wei, Guo-Wei bioRxiv Article Wuhan coronavirus, called 2019-nCoV, is a newly emerged virus that infected more than 9692 people and leads to more than 213 fatalities by January 30, 2020. Currently, there is no effective treatment for this epidemic. However, the viral protease of a coronavirus is well-known to be essential for its replication and thus is an effective drug target. Fortunately, the sequence identity of the 2019-nCoV protease and that of severe-acute respiratory syndrome virus (SARS-CoV) is as high as 96.1%. We show that the protease inhibitor binding sites of 2019-nCoV and SARS-CoV are almost identical, which means all potential anti-SARS-CoV chemotherapies are also potential 2019-nCoV drugs. Here, we report a family of potential 2019-nCoV drugs generated by a machine intelligence-based generative network complex (GNC). The potential effectiveness of treating 2019-nCoV by using some existing HIV drugs is also analyzed. Cold Spring Harbor Laboratory 2020-02-04 /pmc/articles/PMC7217289/ /pubmed/32511308 http://dx.doi.org/10.1101/2020.01.30.927889 Text en http://creativecommons.org/licenses/by-nc/4.0/It is made available under a CC-BY-NC 4.0 International license (http://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Article
Gao, Kaifu
Nguyen, Duc Duy
Wang, Rui
Wei, Guo-Wei
Machine intelligence design of 2019-nCoV drugs
title Machine intelligence design of 2019-nCoV drugs
title_full Machine intelligence design of 2019-nCoV drugs
title_fullStr Machine intelligence design of 2019-nCoV drugs
title_full_unstemmed Machine intelligence design of 2019-nCoV drugs
title_short Machine intelligence design of 2019-nCoV drugs
title_sort machine intelligence design of 2019-ncov drugs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217289/
https://www.ncbi.nlm.nih.gov/pubmed/32511308
http://dx.doi.org/10.1101/2020.01.30.927889
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