HIV latency simulation and prediction

What: Predict the life expectancy of the HIV infected latent T cells.

Why: The human immunodeficiency virus (HIV) is remarkable for several reasons: (1) it predominantly infects immune system cells; (2) shows a high genetic variation throughout the infection in a single individual due to the high error rate in the reverse transcription; (3) it induces apoptosis, or cellular suicide, in the “healthy” bystander) immune cells; Simulated reaction and (4) normal immune system function can cause some HIV-infected T cells to become latent, entering a reversibly nonproductive state of infection. Since the latent cells are transcriptionally silent, they are virtually indistinguishable from the uninfected cells. Also, the number of latently infected cells is relatively small, around 3% of the T cells, which makes current technology in biochemistry require large numbers of the molecules/cells to be studied. It is widely believed that the latently infected CD4+ T cells represent the last barrier to an HIV cure.
The research represents an initial modeling effort for the apoptosis (programmed cell death) of latently infected T cells. We will focus on the apoptotic modeling (reason 3), since it is the avenue through which the virus destroys the effectiveness of the host's immune system. We will base our model on the previous modeling work of Lauffenberger’s group, using the simulation technique developed by Paun and Jack. Furthermore, in order to make the modeling effort easier and due to the high genetic variability (reason 2) of the viral genome, we will combine several similar processes together into single reactions. The kinetic constants for the new reactions, modeling the biochemical interactions involving viral proteins with the host extract samples form the domain using an importance weight function.