CORona Drug InTEractions database
Novel and potent inhibitors targeting DHODH, a rate-limiting enzyme in de novo pyrimidine biosynthesis, are broad-spectrum antiviral against RNA viruses including newly emerged coronavirus SARS-CoV-2
Rui Xiong, Leike Zhang, Shiliang Li, Yuan Sun, Minyi Ding, Yong Wang, Yongliang Zhao, Yan Wu, Weijuan Shang, Xiaming Jiang, Jiwei Shan, Zihao Shen, Yi Tong, Liuxin Xu, Chen Yu, Yingle Liu, Gang Zou, D
Abstract
Emerging and re-emerging RNA viruses occasionally cause epidemics and pandemics worldwide, such as the on-going outbreak of coronavirus SARS-CoV-2. Existing direct-acting antiviral (DAA) drugs cannot be applied immediately to new viruses because of virus-specificity, and the development of new DAA drugs from the beginning is not timely for outbreaks. Thus, host-targeting antiviral (HTA) drugs have many advantages to fight against a broad spectrum of viruses, by blocking the viral replication and overcoming the potential viral mutagenesis simultaneously. Herein, we identified two potent inhibitors of DHODH, S312 and S416, with favorable drug-like and pharmacokinetic profiles, which all showed broad-spectrum antiviral effects against various RNA viruses, including influenza A virus (H1N1, H3N2, H9N2), Zika virus, Ebola virus, and particularly against the recent novel coronavirus SARS-CoV-2. Our results are the first to validate that DHODH is an attractive host target through high antiviral efficacy in vivo and low virus replication in DHODH knocking-out cells. We also proposed the drug combination of DAA and HTA was a promising strategy for anti-virus treatment and proved that S312 showed more advantageous than Oseltamivir to treat advanced influenza diseases in severely infected animals. Notably, S416 is reported to be the most potent inhibitor with an EC50 of 17nM and SI value >5882 in SARS-CoV-2-infected cells so far. This work demonstrates that both our self-designed candidates and old drugs (Leflunomide/Teriflunomide) with dual actions of antiviral and immuno-repression may have clinical potentials not only to influenza but also to COVID-19 circulating worldwide, no matter such viruses mutate or not.
Source: BioRxiv
Related molecules
Name | Synonyms | Genes |
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Dihydroorotate dehydrogenase (quinone), mitochondrial | DHODH, DHOdehase, Dihydroorotate oxidase | DHODH |
Leflunomide | ||
Teriflunomide | ||
Favipiravir | favilavir, Avifavir |
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