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Antiviral Res. 2013 Apr;98(1):121-9. doi: 10.1016/j.antiviral.2013.02.011. Epub 2013 Feb 21.

Antiviral strategies combining antiretroviral drugs with RNAi-mediated attack on HIV-1 and cellular co-factors.

Author information

1
Department of Medical Microbiology, Center for Infection and Immunity Amsterdam-CINIMA, Academic Medical Center, University of Amsterdam, The Netherlands.

Abstract

To improve the care of HIV-1/AIDS patients there is a critical need to develop tools capable of blocking viral evolution and circumventing therapy-associated problems. An emerging solution is gene therapy either as a stand-alone approach or as an adjuvant to pharmacological drug regimens. Combinatorial RNAi by multiplexing antiviral RNAi inhibitors through vector-mediated delivery has recently shown significant superiority over conventional mono-therapies. Viral as well as cellular co-factor targets have been identified, but they are generally attacked separately. Here, we hypothesized that a mixture of shRNAs directed against highly conserved viral RNA sequences and the mRNAs of cellular components that are involved in HIV replication could restrict mutational escape by enhanced synergistic inhibition. We screened for potent silencer cocktails blending inhibitors acting scattered along the viral replication cycle. The results show enhanced and extended suppression of viral replication for some combinations. To further explore the power of combinatorial approaches, we tested the influence of RNAi-mediated knockdown on the activity of conventional antiretroviral drugs (fusion, RT, integrase and protease inhibitors). We compared the fold-change in IC₅₀ (FCIC₅₀) of these drugs in cell lines stably expressing anti-HIV and anti-host shRNAs and measured increased values that are up by several logs for some combinations. We show that high levels of additivity and synergy can be obtained by combining gene therapy with conventional drugs. These results support the idea to validate the therapeutic potential of this anti-HIV approach in appropriate in vivo models.

PMID:
23439083
DOI:
10.1016/j.antiviral.2013.02.011
[Indexed for MEDLINE]

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