This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Chronic hepatitis C virus (HCV) infection affects approximately 200 million people worldwide and is a major cause of chronic liver disease, cirrhosis and liver cancer. Although it is the most common chronic blood-borne infection in the U.S., no protective vaccine is available and only a subset of infected patients (50%) respond to the current treatment of interferon-? plus ribavirin. As mortality associated with HCV is expected to increase 2- to 3-fold within the next few years, new therapies are urgently needed. Mathematical modeling of HCV RNA levels in the serum of chronic HCV patients during therapy has provided significant insight into HCV infection dynamics and viral response kinetics to interferon/ribavirin;however, monitoring serum viremia does not address the molecular mechanisms involved in viral replication and the response to drug therapy. Thus, the mechanisms by which interferon/ribavirin act against the HCV are still unknown. Fortunately, cell culture systems are now available to study HCV and its response to treatment. These include (i) a genetically modified subgenomic replicon system that can be used to specifically characterize viral RNA replication and (ii) an infection system that recapitulates the entire viral life cycle including infectious virus production. Recently we developed the first mathematical model for this system (Dahari et al. J Virol 2007;81:750-60), thus explaining in a cohesive way a number of quantitative features of HCV replication that previously were seen as disparate observations. The model provided insights into HCV replication mechanisms and allowed the estimation of previously unknown kinetic rate constants. The new fully infectious HCV culture systems provide additional data and should help in the development of potential novel antiviral targets. Hence, we propose to expand our subgenomic replicon model to a full model that describes the entire HCV life cycle. We will use experimental data to develop this model with the objective of understanding virus-host interactions at the molecular level and exploring HCV strategies to subvert innate immune response in these cells. By fitting experimental data from treated cells (from both cell culture systems) to our mathematical models, we will evaluate the effects of therapeutic agents and explore concepts of HCV dynamics in treated patients. We anticipate that these efforts will establish a new field of modeling viral-host-drug dynamics at the molecular level. In particular, these new models may permit us to: (i) identify steps in the viral life cycle that are optimal targets for future drug development, (ii) predict the mode of action of drugs against HCV (e.g., interferon and ribavirin), and (iii) verify concepts of HCV dynamics developed based on in vivo patient data modeling.
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