Modeling of the HIV-1 life cycle in productively infected cells to predict novel therapeutic targets

Shcherbatova, Olga; Grebennikov, Dmitry; Sazonov, Igor; Meyerhans, Andreas; Bocharov, Gennady A.

doi:http://dx.doi.org/10.3390/pathogens9040255

Modeling of the HIV-1 life cycle in productively infected cells to predict novel therapeutic targets

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Shcherbatova O, Grebennikov D, Sazonov I, Meyerhans A, Bocharov G. Modeling of the HIV-1 life cycle in productively infected cells to predict novel therapeutic targets. Pathogens. 2020; 9(4). pii: E255. DOI: 10.3390/pathogens9040255

Abstract

There are many studies that model the within-host population dynamics of Human Immunodeficiency Virus Type 1 (HIV-1) infection. However, the within-infected-cell replication of HIV-1 remains to be not comprehensively addressed. There exist rather few quantitative models describing the regulation of the HIV-1 life cycle at the intracellular level. In treatment of HIV-1 infection, there remain issues related to side-effects and drug-resistance that require further search "...for new and better drugs, ideally targeting multiple independent steps in the HIV-1 replication cycle" (as highlighted recently by Teldury et al., The Future of HIV-1 Therapeutics, 2015). High-resolution mathematical models of HIV-1 growth in infected cells provide an additional analytical tool in identifying novel drug targets. We formulate a high-dimensional model describing the biochemical reactions underlying the replication of HIV-1 in target cells. The model considers a nonlinear regulation of the transcription of HIV-1 mediated by Tat and the Rev-dependent transport of fully spliced and singly spliced transcripts from the nucleus to the cytoplasm. The model is calibrated using available information on the kinetics of various stages of HIV-1 replication. The sensitivity analysis of the model is performed to rank the biochemical processes of HIV-1 replication with respect to their impact on the net production of virions by one actively infected cell. The ranking of the sensitivity factors provides a quantitative basis for identifying novel targets for antiviral therapy. Our analysis suggests that HIV-1 assembly depending on Gag and Tat-Rev regulation of transcription and mRNA distribution present two most critical stages in HIV-1 replication that can be targeted to effectively control virus production. These processes are not covered by current antiretroviral treatments.