Hepatitis C virus (HCV) infection is a major public health concern, and almost two million people are infected per year globally. This is occurred by the diverse spectrum of viral genotypes, which are directly associated with chronic liver disease (fibrosis, and cirrhosis). Indeed, the viral genome encodes three principal proteins as sequentially core, E1, and E2. Both E1 and E2 proteins play a crucial role in the attachment of the host system, but E2 plays a more fundamental role in attachment. The researchers have found the "E2-CD81 complex" at the entry site, and therefore, CD81 is the key receptor for HCV entrance in both humans, and chimpanzees. So, the researchers are trying to block the host CD81 receptor and halt the virus entry within the cellular system via plant-derived compounds. Perhaps that is why the current research protocol is designed to perform an in silico analysis of the flavonoid compounds for targeting the tetraspanin CD81 receptor of hepatocytes. To find out the best flavonoid compounds from our library, web-based tools (Swiss ADME, pKCSM), as well as computerized tools like the PyRx, PyMOL, BIOVIA Discovery Studio Visualizer, Ligplot+ V2.2, and YASARA were employed. For molecular docking studies, the flavonoid compounds docked with the targeted CD81 protein, and herein, the best-outperformed compounds are Taxifolin, Myricetin, Puerarin, Quercetin, and (-)-Epicatechin, and outstanding binding affinities are sequentially - 7.5, - 7.9, - 8.2, - 8.4, and - 8.5 kcal/mol, respectively. These compounds have possessed more interactions with the targeted protein. To validate the post docking data, we analyzed both 100 ns molecular dynamic simulation, and MM-PBSA via the YASARA simulator, and finally finds the more significant outcomes. It is concluded that in the future, these compounds may become one of the most important alternative antiviral agents in the fight against HCV infection. It is suggested that further in vivo, and in vitro research studies should be done to support the conclusions of this in silico research workflow.
Keywords: ADMET; CD81 protein; Docking protocol; Dynamic assessments; HCV infection; Liver cirrhosis; MM-PBSA.
© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.