CORona Drug InTEractions database
Reversal of Infected Host Gene Expression Identifies Repurposed Drug Candidates for COVID-19
Jing Xing, Rama Shankar, Aleksandra Drelich, Shreya Paithankar, Eugene Chekalin, Thomas Dexheimer, Surender Rajasekaran, Chien-Te Kent Tseng, Bin Chen
Abstract
Repurposing existing drugs is a timely option to cope with COVID-19. We predicted therapeutic candidates that could reverse the gene expression of coronavirus-infected host cells. Thirteen expression signatures computed from various experimental conditions and preclinical models could be reversed by those compounds known to be effective against SARS- or MERS-CoV, as well as the drug candidates recently shown to be effective against SARS-CoV-2. We selected ten novel candidates to further evaluate their in vitro efficacy against SARS-CoV-2 infection. Four compounds bortezomib, dactolisib, alvocidib and methotrexate inhibited the formation of virus infection-induced cytopathic effect in Vero E6 cells at 1 uM, yet such a concentration seems toxic to the cells as well. While the evaluation in other permissive cells and the prediction of toxicity are needed to optimize and minimize their antiviral activity and cytotoxicity, respectively, this computational approach has the potential to rapidly and rationally identify drug candidates against COVID-19.
Source: BioRxiv
Related molecules
Related interactions
| Target | Drug | Type | Result |
|---|---|---|---|
| 3C-like protease | Bortezomib | ||
| 3C-like protease | dactolisib | ||
| 3C-like protease | alvocidib | ||
| 3C-like protease | Methotrexate |
| Target | Target affiliation | Drug | Type | Result |
|---|---|---|---|---|
| Target | Target affiliation | Drug | Type | Result |
| Name | Synonyms | Genes | Origin |
|---|---|---|---|
| Name | Synonyms | Genes | Origin |
| Name | Synonyms | PubChem | DrugBank | RCSB PDB | ATC |
|---|---|---|---|---|---|
| Name | Synonyms | PubChem | DrugBank | RCSB PDB | ATC |
| Title | Authors | DOI | Source | Article type | Date |
|---|---|---|---|---|---|
| Title | Authors | DOI | Source | Article type | Date |
| Title | Status | Phases | Start Date | Prim. Comp. Date | Comp. Date | First Post. Date |
|---|---|---|---|---|---|---|
| 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