Try an example: Nelfinavir

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 the spike protein priming. Thus in order to speed up the discovery of therapeutic agents, we develop DockCoV2, a drug database for SARS-CoV2. DockCoV2 focuses on predicting the binding affinity of FDA-approved and Taiwan National Health Insurance (NHI) drugs with the seven proteins mentioned above, 5 major SARS-CoV-2 variant proteins and other 67 human proteins, that were identified to be associated with SARS-CoV-2 from GWAS analysis and protein-virus interactions. This database contains a total of 3,548 drugs. DockCoV2 is easy to use and search against, is well cross-linked to external databases, and provides 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. DockCoV2 also provides validation information to help users understand which drugs have already been reported to be effective against MERS or SARS-CoV. Furthermore, we propose a custom literature-based knowledge graph embedding tool, pubmedKB, for identifying drug and disease relations from published COVID-19-related papers. Specifically, pubmedKB mined over 160 thousand PubMed Central (PMC) full-text literature curated by CORD-19 by applying the state-of-the-art text mining tools from annotation to identification of the drug-disease relations.

Please cite our publication if you use DockCoV2.
Chen, T.-F., Chang, Y.-C., Hsiao, Y., Lee, K.-H., Hsiao, Y.-C., Lin, Y.-H., Tu, Y.-C. E., Huang, H.-C., Chen, C.-Y.* , Juan, H.-F.*
DockCoV2: a drug database against SARS-CoV-2. Nucleic Acids Research 2021 Jan 8;49(D1):D1152-D1159. doi: 10.1093/nar/gkaa861.
Database Statistics
Taiwan NHI Drugs 1,478
FDA Approved Drugs 2,285
Last Updated: 2021.04.08
2021.07.01 Version 2.0 is now online. New features include added graph view for drug-protein/protein-protein interactions, AI-generated drug-related literature information, and recently added new docking results for spike protein variants and potential human protein targets.
2021.06.30 Add Delta variant (spike protein) and Lambda variant (spike protein).
2021.06.29 Add PubMedKB for drug disease relation.
2021.05.20 Add Gamma variant (spike protein).
2021.04.08 Add 67 new proteins.
2021.04.07 Add Alpha variant (spike protein) and Beta variant (spike protein).
2020.09.11 Add other poses data.
2020.09.01 Add N protein and TMPRSS2.
2020.06.23 New layout updated.
2020.06.01 Add lingand info and validation info.
2020.05.18 First version of DockCoV2 updated.