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2000
Volume 22, Issue 3
  • ISSN: 1570-1638
  • E-ISSN: 1875-6220

Abstract

Introduction

Human Immunodeficiency Virus (HIV) is a retrovirus with single-stranded RNA that leads to the challenging disease of acquired immunodeficiency syndrome (AIDS). Combination antiretroviral therapy (cART) can prevent the progression of the disease, but it is not capable of long-term HIV elimination. One of the significant obstacles to treating HIV-1-infected individuals is the creation of latent cell reservoirs early in the infection. Gene-based therapies that utilize RNA interference (RNAi) to silence host or viral gene expression are considered promising therapeutic approaches. It has been demonstrated that RUNX1, a T-cell-specific transcription factor, may significantly affect HIV replication and infection. According to accumulating evidence on the role of interfering RNA techniques in inhibiting gene expression and considering the role of RUNX1 in the replication of HIV-1. In this study, we aim to design shRNAs against RUNX1 that can target the replication of HIV-1.

Methods

Several computational methods, including target alignment, similarity search, and secondary structure prediction, have been employed in the design of shRNA against RUNX1.

Results

Seven shRNA molecules with the highest efficiency were designed and validated using computational methods to silence the RUNX1 gene.

Conclusion

In the present study, we designed shRNA against RUNX1, which can target latent cells infected with HIV. Suppression of RUNX1 by shRNA reactivates HIV in the latent cells and subsequently potentiates the immune response toward identifying accurate virus-infected cells. This process may lead to an effective and efficient reduction of the volume of cell reservoirs infected with HIV.

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2025-09-04

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In silico Approach: Design an Optimized shRNA against RUNX1 Gene to Target HIV
Current Drug Discovery Technologies 22, E250424229316 (2025); https://doi.org/10.2174/0115701638291312240415151051
/content/journals/cddt/10.2174/0115701638291312240415151051
/content/journals/cddt/10.2174/0115701638291312240415151051
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  • Article Type:     Research Article
Keyword(s): CD4+ cells; HIV; In silico; RNAi; RUNX1; ShRNA

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