CORona Drug InTEractions database
Supercomputer-aided Drug Repositioning at Scale: Virtual Screening for SARS-CoV-2 Protease Inhibitor
Sangjae Seo, Jung Woo Park, Dosik An, Junwon Yoon, Hyojung Paik, Soonwook Hwang
Abstract
Coronavirus diseases (COVID-19) outbreak has been labelled a pandemic. For the prioritization of treatments to cope with COVID-19, it is important to conduct rapid high-throughput screening of chemical compounds to repurposing the approved drugs, such as repositioning of chloroquine (Malaria drug) for COVID-19. In this study, exploiting supercomputer resource, we conducted high-throughput virtual screening for potential repositioning candidates of the protease inhibitor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Using the three dimensional structure of main protease (Mpro) of SARS-CoV-2, we evaluated binding affinity between Mpro and drug candidates listed in SWEETLEAD library and ChEMBL database. Docking scores of 19,168 drug molecules at the active site of Mpro were calculated using Autodock Vina package. Among the calculated result, we selected 43 drug candidates and ran molecular dynamics (MD) simulation to further investigate protein-drug interaction. Among compounds that bind to the active site of SARS-CoV-2, we finally selected the 8 drugs showing the highest binding affinity; asunaprevir, atazanavir, dasabuvir, doravirine, fosamprenavir, ritonavir, voxilaprevir and amprenavir, which are the antiviral drugs of hepatitis C virus or human immunodeficiency virus. We expect that the present study provides comprehensive insights into the development of antiviral medication, especially for the treatment of COVID-19.
Source: ChemRxiv
Related molecules
| Name | Synonyms | Genes |
|---|---|---|
| dasabuvir | ||
| voxilaprevir | ||
| Asunaprevir | ||
| Fosamprenavir | ||
| Doravirine | ||
| 3C-like protease | 3CLpro, Mpro, SARS coronavirus main peptidase, 3CLpro-SARS-CoV-2 | rep, ORF1a-1b |
| Atazanavir | ||
| Ritonavir |
Related interactions
| 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