Computational Screening of Medicinal Plant Phytochemicals to Discover Potent Inhibitors against Hepatitis B Virus

Abstract

Hepatitis B virus (HBV) infections are infamous to cause liver damage, hepatocellular carcinoma, and cirrhosis, all of which can be fatal in nature. Nucleotide analogues, which target viral reverse transcriptase, and interferon therapy, which is known to have side effects in recipients, are currently being used to treat such infections. Increasingly, the growing viral resistance towards the first line of drugs has been a concern for the healthcare system worldwide, and therefore the need for new therapeutic interventions has been noted and novel viral targets are being explored. The HBV core protein (HBc), which regulates several viral replication checkpoints in the host cell, is one such possible target for therapeutic development. In this study, we use in silico approach to investigate the potential of various phytochemicals and natural compounds to be developed as antiviral medicines that target HBc protein. For which, the compounds were collected from databases and potential candidates were screened and shortlisted based on their pharmacokinetics and drug-likeness using Lipinski’s rule of five. Further, the chosen phytochemicals were subjected to docking analysis, and binding affinities were evaluated to set a cut-off value for selecting the best interactions, which showed better binding energy values compared to standard anti-HBV drugs. Further, the two- and three-dimensional interactions of the ligand and target protein complexes were studied to gain insights into the ligand-target bonding patterns, and bioavailability and toxicity profiles were analyzed to understand the safety and efficacy of the selected compounds to be developed as anti-HBV interventions. Upon complete inspection, Ingenol was identified as the best candidate among the chosen phytochemicals, followed by I-asarinin and Withaferin. We hope that the findings from this study will be useful in the development of anti-HBV drug candidates or formulations.