While new direct-acting antiviral agents for the treatment of chronic hepatitis C virus (HCV) infection have been approved, there is a continued need for novel antiviral agents that act on new targets and can be used in combination with current therapies to enhance efficacy and to restrict the emergence of drug-resistant viral variants. To this end, we have identified a novel class of small molecules, exemplified by PTC725, that target the nonstructural protein 4B (NS4B). PTC725 inhibited HCV 1b (Con1) replicons with a 50% effective concentration (EC 50 ) of 1.7 nM and an EC 90 of 9.6 nM and demonstrated a >1,000-fold selectivity window with respect to cytotoxicity. The compounds were fully active against HCV replicon mutants that are resistant to inhibitors of NS3 protease and NS5B polymerase. Replicons selected for resistance to PTC725 harbored amino acid substitutions F98L/C and V105M in NS4B. Anti-replicon activity of PTC725 was additive to synergistic in combination with alpha interferon or with inhibitors of HCV protease and polymerase. Immunofluorescence microscopy demonstrated that neither the HCV inhibitors nor the F98C substitution altered the subcellular localization of NS4B or NS5A in replicon cells. Oral dosing of PTC725 showed a favorable pharmacokinetic profile with high liver and plasma exposure in mice and rats. Modeling of dosing regimens in humans indicates that a once-per-day or twice-per-day oral dosing regimen is feasible. Overall, the preclinical data support the development of PTC725 for use in the treatment of chronic HCV infection.C hronic hepatitis C virus (HCV) infection is a worldwide epidemic disease with an estimate of over 170 million people chronically infected worldwide (1). Approximately 60 to 85% of HCV infections result in chronic hepatitis that can lead to liver fibrosis, cirrhosis, and hepatocellular carcinoma (2). The current standard of care (SOC) for chronic hepatitis C infection, pegylated alpha interferon in combination with ribavirin, has serious side effects and limited efficacy, especially for infection with HCV genotype 1, which is the most prevalent HCV genotype (3, 4). Two HCV protease inhibitors, boceprevir (Victrelis) and telaprevir (Incivek), for the therapy of HCV genotype 1 infection in combination with the SOC were approved for use nearly 2 years ago. In addition, a number of other direct-acting antivirals (DAAs) in clinical trials have demonstrated encouraging efficacy in combination therapies (5). Currently, the HCV antivirals in preclinical and clinical development are inhibitors of the viral protease, polymerase, or nonstructural protein 5A (NS5A) (6). Due to the emergence of viral variants resistant to the DAAs, even in combination therapy with the SOC (7-9) and the potential for viral rebound after cessation of antiviral therapy, it is essential to discover and develop novel HCV inhibitors that act on new targets and can be used in combination with the SOC and/or DAAs to enhance efficacy and to delay or possibly prevent the emergence of drug-resistant...
A major challenge to successful antiviral therapy is the emergence of drug-resistant viruses. Recent studies have developed several automated analyses of HIV sequence polymorphism based on calculations of selection pressure (Ka/Ks) to predict drug resistance mutations. Similar resistance analysis programs for HCV inhibitors are not currently available. Taking advantage of the recently available sequence data of patient HCV samples from a Phase II clinical study of protease inhibitor boceprevir, we calculated the selection pressure for all codons in the HCV protease region (amino acid 1–181) to identify potential resistance mutations. The correlation between mutations was also calculated to evaluate linkage between any two mutations. Using this approach, we identified previously known major resistant mutations, including a recently reported mutation V55A. In addition, a novel mutation V158I was identified, and we further confirmed its resistance to boceprevir in protease enzyme and replicon assay. We also extended the approach to analyze potential interactions between individual mutations and identified three pairs of correlated changes. Our data suggests that selection pressure-based analysis and correlation mapping could provide useful tools to analyze large amount of sequencing data from clinical samples and to identify new drug resistance mutations as well as their linkage and correlations.
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