| Chemical Information | |
| Antiviral agent ID | DrugRepV_1616 | |
| Antiviral agent name | Pyronaridine tetraphosphate | |
| IUPAC Name | 4-[(7-chloro-2-methoxy-1,5-dihydrobenzo[b][1,5]naphthyridin-10-yl)imino]-2,6-bis(pyrrolidin-1-ylmethyl)cyclohexa-2,5-dien-1-one;phosphoric acid |  |
| SMILES (canonical) | COC1=NC2=C(C3=C(C=C(C=C3)Cl)N=C2C=C1)NC4=CC(=C(C(=C4)CN5CCCC5)O)CN6CCCC6.OP(=O)(O)O.OP(=O)(O)O.OP(=O)(O)O.OP(=O)(O)O | |
| Molecular Formula | C29H44ClN5O18P4 | |
| Molecular Weight (g/mol) | 910.033 | |
| InChl | InChI=1S/C29H32ClN5O2.4H3O4P/c1-37-26-9-8-24-28(33-26)27(23-7-6-21(30)16-25(23)32-24)31-22-14-19(17-34-10-2-3-11-34)29(36)20(15-22)18-35-12-4-5-13-35;4*1-5(2,3)4/h6-9,14-16,32-33H,2-5,10-13,17-18H2,1H3;4*(H3,1,2,3,4) | |
| Synonyms | Pyranoridine phosphate | UNII-2T289F9ACO | Pyranoridine tetraphosphate | |
| Structural Information | |
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| Clinical Information | |
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Category | Antiparasitic products, Insectisides and Repellents
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Primary Indication (Clinical trial phases) | Approved
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| Biological Information | |
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Primary Indication (Disease Category) | Infectious Disease
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Primary Indication (Disease) | Malaria
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Secondary Indication | Ebola virus (EBOV) NA Recombinant, infectious Ebola virus encoding green fluorescent protein |   |
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Secondary Indication (Approaches) | Experimental | |
| Secondary Indication (Methods) | In-vitro | |
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Secondary Indication (Model system) [cell lines/ animal models] | HeLa
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Secondary Indication (Mode of viral infection) | Adsorption
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Secondary Indication (Viral titer) | 0.05 to 0.15 MOI
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Secondary Indication (Mode of drug delivery) | Culture
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Secondary Indication (Time of drug delivery) | Post infection
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Secondary Indication (Duration of drug delivery) | 24 hours
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Secondary Indication (Drug concentration) | 0.42 μM
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Secondary Indication (Cell based assay) | Cell based assay
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Secondary Indication (Change) | Decrease
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Secondary Indication (Type of Inhibition) | EC50 [ 50 % ] | |
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Secondary Indication (Cytotoxicity) | 3.1 μM | |
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Reference | Ekins S, Freundlich JS, Clark AM, Anantpadma M, Davey RA, Madrid P..Machine learning models identify molecules active against the Ebola virus in vitro..Version 3. F1000Res. 2015 Oct 20 [revised 2017 Jan 1];4:1091. doi: 10.12688/f1000research.7217.3. eC PMID:26834994
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Comment | Data sets with less than 1,000 molecules can produce validated machine learning models that can in turn be utilized to identify novel EBOV inhibitors in vitro.
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