tetano
Editor, Senior Moderator
Nucleic Acids Res
. 2020 Oct 9;gkaa861.
doi: 10.1093/nar/gkaa861. Online ahead of print.
DockCoV2: a drug database against SARS-CoV-2
Ting-Fu Chen[SUP] 1 [/SUP], Yu-Chuan Chang[SUP] 1 [/SUP], Yi Hsiao[SUP] 1 [/SUP], Ko-Han Lee[SUP] 1 [/SUP], Yu-Chun Hsiao[SUP] 1 [/SUP], Yu-Hsiang Lin[SUP] 1 [/SUP], Yi-Chin Ethan Tu[SUP] 1 [/SUP], Hsuan-Cheng Huang[SUP] 2 [/SUP], Chien-Yu Chen[SUP] 1 3 [/SUP], Hsueh-Fen Juan[SUP] 1 4 5 [/SUP]
Affiliations
Abstract
The current state of the COVID-19 pandemic is a global health crisis. To fight the novel coronavirus, one of the best-known ways is to block enzymes essential for virus replication. Currently, we know that the SARS-CoV-2 virus encodes about 29 proteins such as spike protein, 3C-like protease (3CLpro), RNA-dependent RNA polymerase (RdRp), Papain-like protease (PLpro), and nucleocapsid (N) protein. SARS-CoV-2 uses human angiotensin-converting enzyme 2 (ACE2) for viral entry and transmembrane serine protease family member II (TMPRSS2) for spike protein priming. Thus in order to speed up the discovery of potential drugs, we develop DockCoV2, a drug database for SARS-CoV-2. DockCoV2 focuses on predicting the binding affinity of FDA-approved and Taiwan National Health Insurance (NHI) drugs with the seven proteins mentioned above. This database contains a total of 3,109 drugs. DockCoV2 is easy to use and search against, is well cross-linked to external databases, and provides the state-of-the-art prediction results in one site. Users can download their drug-protein docking data of interest and examine additional drug-related information on DockCoV2. Furthermore, DockCoV2 provides experimental information to help users understand which drugs have already been reported to be effective against MERS or SARS-CoV. DockCoV2 is available at https://covirus.cc/drugs/.
. 2020 Oct 9;gkaa861.
doi: 10.1093/nar/gkaa861. Online ahead of print.
DockCoV2: a drug database against SARS-CoV-2
Ting-Fu Chen[SUP] 1 [/SUP], Yu-Chuan Chang[SUP] 1 [/SUP], Yi Hsiao[SUP] 1 [/SUP], Ko-Han Lee[SUP] 1 [/SUP], Yu-Chun Hsiao[SUP] 1 [/SUP], Yu-Hsiang Lin[SUP] 1 [/SUP], Yi-Chin Ethan Tu[SUP] 1 [/SUP], Hsuan-Cheng Huang[SUP] 2 [/SUP], Chien-Yu Chen[SUP] 1 3 [/SUP], Hsueh-Fen Juan[SUP] 1 4 5 [/SUP]
Affiliations
- PMID: 33035337
- DOI: 10.1093/nar/gkaa861
Abstract
The current state of the COVID-19 pandemic is a global health crisis. To fight the novel coronavirus, one of the best-known ways is to block enzymes essential for virus replication. Currently, we know that the SARS-CoV-2 virus encodes about 29 proteins such as spike protein, 3C-like protease (3CLpro), RNA-dependent RNA polymerase (RdRp), Papain-like protease (PLpro), and nucleocapsid (N) protein. SARS-CoV-2 uses human angiotensin-converting enzyme 2 (ACE2) for viral entry and transmembrane serine protease family member II (TMPRSS2) for spike protein priming. Thus in order to speed up the discovery of potential drugs, we develop DockCoV2, a drug database for SARS-CoV-2. DockCoV2 focuses on predicting the binding affinity of FDA-approved and Taiwan National Health Insurance (NHI) drugs with the seven proteins mentioned above. This database contains a total of 3,109 drugs. DockCoV2 is easy to use and search against, is well cross-linked to external databases, and provides the state-of-the-art prediction results in one site. Users can download their drug-protein docking data of interest and examine additional drug-related information on DockCoV2. Furthermore, DockCoV2 provides experimental information to help users understand which drugs have already been reported to be effective against MERS or SARS-CoV. DockCoV2 is available at https://covirus.cc/drugs/.