Velpatasvir (1377049-84-7) is an extremely potent pan-genotypic hepatitis C virus (HCV) NS5A inhibitor.1 It is a component of Epclusa and Vosevi, two clinically useful medications with 98% and 97%, respectively, cure rates for HCV. It displayed EC50’s for GTs 1-4, 6a ranging from 6-16 pM, GT5a at 75 pM, and GT6e at 130 pM. Velpatasvir also displayed an excellent barrier to viral resistance. It has been shown in silico, that velpatasvir binds to the SARS-CoV-2 spike protein and may be a potential therapeutic.2
Velpatasvir is a NS5A inhibitor in patients with hepatitis C (HCV) infection.
ChEBI: Velpatasvir is a complex organic heteropentacyclic compound that is a hepatitis C virus nonstructural protein 5A inhibitor used in combination with sofosbuvir (under the brand name Epclusa) for treatment of patients with chronic hepatitis C of all six major genotypes. It has a role as an antiviral drug and a hepatitis C virus nonstructural protein 5A inhibitor. It is an organic heteropentacyclic compound, a N-acylpyrrolidine, a L-valine derivative, a carbamate ester, a member of imidazoles, a ring assembly and an ether.
Epclusa, Sofosvel, Velpanat (all in combination with sofosbuvir)
Velpatasvir (10 mg/kg/d, p.o.) alone or in combination with Sofosbuvir (HY-15005) (20 mg/kg/d) inhibits liver fibrosis in the CCl4-induced non-HCV rat model[3].
| Animal Model: | CCl4-induced non-HCV rat model[3] |
| Dosage: | 10 mg/kg/d alone, or in combination with Sofosbuvir (20 mg/kg/d) |
| Administration: | p.o. |
| Result: | Decreased the levels of TNF-a, NF-κB and IL-6 in serum and hepatic tissues.
Inhibited hepatic stellate cells (HSCs).
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[1] JOHN O. LINK . Discovery of velpatasvir (GS-5816): A potent pan-genotypic HCV NS5A inhibitor in the single-tablet regimens Vosevi® and Epclusa®[J]. Bioorganic & Medicinal Chemistry Letters, 2019, 29 16: Pages 2415-2427. DOI:
10.1016/j.bmcl.2019.04.027[2] ONAT KADIOGLU . Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning[J]. Computers in biology and medicine, 2021, 133: Article 104359. DOI:
10.1016/j.compbiomed.2021.104359
