Potentially highly potent drugs for 2019-nCoV

Duc Duy Nguyen; Kaifu Gao; Jiahui Chen; Rui Wang; Guo-Wei Wei

doi:10.1101/2020.02.05.936013

Potentially highly potent drugs for 2019-nCoV

Duc Duy Nguyen, Kaifu Gao, Jiahui Chen, Rui Wang, Guo-Wei Wei

Mathematics

Research output: Working paper › Preprint

Abstract

The World Health Organization (WHO) has declared 2019 novel coronavirus (2019-nCoV) infection outbreak a global health emergency. Currently, there is no effective anti-2019-nCoV medication. The sequence identity of the 3CL proteases of 2019-nCoV and SARS is 96%, which provides a sound foundation for structural-based drug repositioning (SBDR). Based on a SARS 3CL protease X-ray crystal structure, we construct a 3D homology structure of 2019-nCoV 3CL protease. Based on this structure and existing experimental datasets for SARS 3CL protease inhibitors, we develop an SBDR model using deep learning and mathematics to screen 1465 drugs in the DrugBank that have been approved by the U.S. Food and Drug Administration (FDA). We found that a number of FDA approved drugs are potentially highly potent to 2019-nCoV.

Original language	English
DOIs	https://doi.org/10.1101/2020.02.05.936013
State	Published - Feb 13 2020

Bibliographical note

Authors retain copyright and choose from several distribution/reuse options under which to make the article available (CC BY, CC BY-NC, CC BY-ND, CC BY-NC-ND, CC0, or no reuse).

Keywords

bioinformatics

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10.1101/2020.02.05.936013

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title = "Potentially highly potent drugs for 2019-nCoV",

abstract = "The World Health Organization (WHO) has declared 2019 novel coronavirus (2019-nCoV) infection outbreak a global health emergency. Currently, there is no effective anti-2019-nCoV medication. The sequence identity of the 3CL proteases of 2019-nCoV and SARS is 96%, which provides a sound foundation for structural-based drug repositioning (SBDR). Based on a SARS 3CL protease X-ray crystal structure, we construct a 3D homology structure of 2019-nCoV 3CL protease. Based on this structure and existing experimental datasets for SARS 3CL protease inhibitors, we develop an SBDR model using deep learning and mathematics to screen 1465 drugs in the DrugBank that have been approved by the U.S. Food and Drug Administration (FDA). We found that a number of FDA approved drugs are potentially highly potent to 2019-nCoV.",

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AU - Nguyen, Duc Duy

AU - Gao, Kaifu

AU - Chen, Jiahui

AU - Wang, Rui

AU - Wei, Guo-Wei

N1 - Authors retain copyright and choose from several distribution/reuse options under which to make the article available (CC BY, CC BY-NC, CC BY-ND, CC BY-NC-ND, CC0, or no reuse).

PY - 2020/2/13

Y1 - 2020/2/13

N2 - The World Health Organization (WHO) has declared 2019 novel coronavirus (2019-nCoV) infection outbreak a global health emergency. Currently, there is no effective anti-2019-nCoV medication. The sequence identity of the 3CL proteases of 2019-nCoV and SARS is 96%, which provides a sound foundation for structural-based drug repositioning (SBDR). Based on a SARS 3CL protease X-ray crystal structure, we construct a 3D homology structure of 2019-nCoV 3CL protease. Based on this structure and existing experimental datasets for SARS 3CL protease inhibitors, we develop an SBDR model using deep learning and mathematics to screen 1465 drugs in the DrugBank that have been approved by the U.S. Food and Drug Administration (FDA). We found that a number of FDA approved drugs are potentially highly potent to 2019-nCoV.

AB - The World Health Organization (WHO) has declared 2019 novel coronavirus (2019-nCoV) infection outbreak a global health emergency. Currently, there is no effective anti-2019-nCoV medication. The sequence identity of the 3CL proteases of 2019-nCoV and SARS is 96%, which provides a sound foundation for structural-based drug repositioning (SBDR). Based on a SARS 3CL protease X-ray crystal structure, we construct a 3D homology structure of 2019-nCoV 3CL protease. Based on this structure and existing experimental datasets for SARS 3CL protease inhibitors, we develop an SBDR model using deep learning and mathematics to screen 1465 drugs in the DrugBank that have been approved by the U.S. Food and Drug Administration (FDA). We found that a number of FDA approved drugs are potentially highly potent to 2019-nCoV.

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M3 - Preprint

BT - Potentially highly potent drugs for 2019-nCoV

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Potentially highly potent drugs for 2019-nCoV

Abstract

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Keywords

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