CORona Drug InTEractions database

Probing antiviral drugs against SARS-CoV-2 through virus-drug association prediction based on the KATZ method

Liqian Zhou, Juanjuan Wang, Guangyi Liu, Qingqing Lu, Ruyi Dong, Geng Tian, Jialiang Yang, Lihong Penga

Abstract

It is urgent to find an effective antiviral drug against SARS-CoV-2. In this study, 96 virus-drug associations (VDAs) from 12 viruses including SARS-CoV-2 and similar viruses and 78 small molecules are selected. Complete genomic sequence similarity of viruses and chemical structure similarity of drugs are then computed. A KATZ-based VDA prediction method (VDA-KATZ) is developed to infer possible drugs associated with SARS-CoV-2. VDA-KATZ obtained the best AUCs of 0.8803 when the walking length is 2. The predicted top 3 antiviral drugs against SARS-CoV-2 are remdesivir, oseltamivir, and zanamivir. Molecular docking is conducted between the predicted top 10 drugs and the virus spike protein/human ACE2. The results showed that the above 3 chemical agents have higher molecular binding energies with ACE2. For the first time, we found that zidovudine may be effective clues of treatment of COVID-19. We hope that our predicted drugs could help to prevent the spreading of COVID.

Source: PubMed

Related molecules

Name	Synonyms	Genes
Oseltamivir	(−)-oseltamivir, 1-Cyclohexene-1-carboxylic acid, 4-(acetylamino)-5-amino-3-(1-ethylpropoxy)-, ethyl ester, (3R-(3alpha,4beta,5alpha))-
Zanamivir	(4S,5R,6R)-5-Acetylamino-4-guanidino-6-[(1R,2R)-1,2,3-trihydroxypropyl]-5,6-dihydro-4H-pyran-2-carbonsäure,
Angiotensin-converting enzyme 2	ACE-related carboxypeptidase, ACE2	ACE2
Remdesivir

Related interactions

Target	Drug	Type	Result
Angiotensin-converting enzyme 2	Oseltamivir

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