CORona Drug InTEractions database
Repurposing FDA-Approved Drugs for COVID-19 Using a Data-Driven Approach
Rodrigo R. R. Duarte, Dennis C. Copertino Jr., Luis P. Iñiguez, Jez L. Marston, Douglas F. Nixon, Timothy R. Powell
Abstract
There have been more than 116,000 recorded deaths worldwide to-date caused by the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), the etiological agent of the Coronavirus Disease 2019 (COVID-19), and over 1.8 million individuals are currently infected. Although there are now hundreds of clinical trials for COVID-19, there are currently no effective licensed treatments, while the numbers of infected individuals continue to rise at an exponential rate in many parts of the world. Here, we used a data-driven approach utilizing connectivity mapping and the transcriptional signature of lung carcinoma cells infected with SARS-CoV-2, to search for drugs across the spectrum of medicine that have repurposing potential for treating COVID-19. We also performed chemoinformatic analyses to test whether the identified compounds were predicted to physically interact with the SARS-CoV-2 RNA-dependent RNA polymerase or main protease enzymes. Our study identified commonly prescribed FDA-approved molecules as important candidates for drug repositioning against COVID-19, including flupentixol, reserpine, fluoxetine, trifluoperazine, sunitinib, atorvastatin, raloxifene, butoconazole, and metformin. These drugs should not be taken for treating or preventing COVID-19 without a doctor’s advice, as further research and clinical trials are now needed to elucidate their efficacy for this purpose.
Source: ChemRxiv
Related molecules
Related interactions
Target | Target affiliation | Drug | Type | Result |
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Target | Target affiliation | Drug | Type | Result |
Name | Synonyms | Genes | Origin |
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Name | Synonyms | Genes | Origin |
Name | Synonyms | PubChem | DrugBank | RCSB PDB | ATC |
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Name | Synonyms | PubChem | DrugBank | RCSB PDB | ATC |
Title | Authors | DOI | Source | Article type | Date |
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Title | Authors | DOI | Source | Article type | Date |
Title | Status | Phases | Start Date | Prim. Comp. Date | Comp. Date | First Post. Date |
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Title | Status | Phases | Start Date | Prim. Comp. Date | Comp. Date | First Post. Date |
CORDITE (CORona Drug InTEractions database) collects and aggregates data from PubMed, MedRxiv, BioRxiv, ChemRxiv and PMC for SARS-CoV-2. Its main focus is set on drug interactions either addressing viral proteins or human proteins that could be used to treat COVID. It collects and provides up-to-date information on computational predictions, in vitro, as well as in vivo study data.
The information provided is for research only and we cannot guarantee the correctness of the data.
Please contact dominik.heider@uni-muenster.de for further information.
Programmable access
There is an open API for access programmatically to the database. The API will print a JSON output:
- Interactions
https://cordite-api.uni-muenster.de/api.php?action=list&table=interaction
- Targets
https://cordite-api.uni-muenster.de/api.php?action=list&table=target
- Drugs
https://cordite-api.uni-muenster.de/api.php?action=list&table=drug
- Publications
https://cordite-api.uni-muenster.de/api.php?action=list&table=publication
- Clinical trials
https://cordite-api.uni-muenster.de/api.php?action=list&table=clinical_trial