Viruses are one of the leading causes of morbidity and mortality worldwide, with Hepatitis B Virus (HBV) being one of the most infectious and prevalent among them. Roughly 250 million people worldwide suffer from chronic HBV infection, including 1-2 million in the United States. Of those infected, approximately 15-25% will develop se- rious liver problems, including cirrhosis, cancer, and ultimately failure, leading to 600,000 deaths annually. While therapies exist to manage chronic HBV infection, all target viral genomic processes such as reverse transcription and DNA replication, and none provide a cure due to viral persistence and resistance. A promising orthogonal approach to eliminating infection is to target HBV's capsid, the protein shell that encapsulates the viral genome. The Finn laboratory has previously developed compounds that induce the misdirected assembly of non-functional HBV capsids, showing that small molecules have the power to affect the structures of these large multi-protein assemblies. While much is known about the structures of the intermolecular interactions with these compounds identi?ed after the fact, little about the dynamics of such interactions has been explored, and a predictive under- standing of functional (antiviral) binding has yet to be developed. Both de?ciencies will begin to be addressed in this program. Using molecular dynamics (MD) simulations coupled with in vitro experiments on HepAD38 cells, the PIs have identi?ed seven compounds based on motifs previously unknown to interact with HBV that target the capsid assembly process. These compounds bind in a known pocket at the interface of two capsid-protein (Cp) dimers, possess moderate antiviral activity, and low toxicity. In the ?rst aim, using docking, free-energy perturba- tion, and synthetic chemistry, the PIs will optimize the lead compound to improve its ef?cacy against HBV. In the second aim, using molecular dynamics simulations, advanced free-energy calculations, and experimental assays on different HBV protein oligomers, up to and including the whole virus capsid, the PIs will determine how small molecules interfere with capsid assembly.
Both aims will bene?t from using a machine-learning-based classi?- cation scheme as well as novel enhanced sampling methods. The lessons learned here concerning how small molecules can re-direct the assembly pathway into unproductive conformations can be generalized for application to other viruses.
In spite of the dramatic increase in our understanding of the structure and properties of hepatitis B virus (HBV), this pathogen remains a major threat to human health. That knowledge also makes HBV an important test case for new antiviral strategies. This project aims to limit the impact of HBV by using computer simulations and synthetic chemistry to develop an improved understanding of the assembly process of HBV as well as new drugs that can eliminate HBV infection in ways that may be generalized to other pathogenic viruses.
