Computational design of antiviral RNA interference strategies that resist human immunodeficiency virus escape
Computational design of antiviral RNA interference strategies that resist human immunodeficiency virus escape
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DOI：
10.1128/jvi.79.3.1645-1654.2005
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发表时间：
2005-02-01
影响因子：
5.4
通讯作者：
Schaffer, DV
中科院分区：
文献类型：
--
作者：
Leonard, JN;Schaffer, DV
最近开发的基于RNA干扰（RNAi）的抗病毒策略，利用先天细胞系统靶向下调基因表达，似乎非常有前途，并提供替代方法，以传统的高活性抗逆转录病毒治疗或努力开发艾滋病疫苗。然而，RNAi面临着必须克服的几个挑战，以充分实现其承诺。具体而言，它以高度序列特异性的方式降解靶RNA，因此容易发生病毒突变逃逸，并且在诱导RNAi的递送系统中也存在挑战。为了帮助开发抗人类免疫缺陷病毒（抗HIV）RNAi疗法，我们开发了一种新的随机计算模型，该模型在分子水平上详细模拟表达RNAi的细胞中HIV感染的传播。该模型提供了关于如何靶向HIV基因组中的多个位置的定量预测，同时保持总体RNAi强度恒定，显着提高疗效。此外，它证明了递送系统必须是高效的，以防止留下未受保护的细胞库，在那里病毒可以繁殖、突变并最终压倒整个系统。它还预测了治疗成功如何取决于RNAi强度与递送效率和均匀性之间的关系。最后，如果正确选择RNAi靶序列，则靶向基本病毒元件（在这种情况下为HIV TAR区域）可以非常成功。除了为如何优化临床治疗提供具体的预测外，该系统还可以作为未来研究病毒进化更基本问题的工具。
Recently developed antiviral strategies based upon RNA interference (RNAi), which harnesses an innate cellular system for the targeted down-regulation of gene expression, appear highly promising and offer alternative approaches to conventional highly active antiretroviral therapy or efforts to develop an AIDS vaccine. However, RNAi is faced with several challenges that must be overcome to fully realize its promise. Specifically, it degrades target RNA in a highly sequence-specific manner and is thus susceptible to viral mutational escape, and there are also challenges in delivery systems to induce RNAi To aid in the development of anti-human immunodeficiency virus (anti-HIV) RNAi therapies, we have developed a novel stochastic computational model that simulates in molecular-level detail the propagation of an HIV infection in cells expressing RNAi. The model provides quantitative predictions on how targeting multiple locations in the HIV genome, while keeping the overall RNAi strength constant, significantly improves efficacy. Furthermore, it demonstrates that delivery systems must be highly efficient to preclude leaving reservoirs of unprotected cells where the virus can propagate, mutate, and eventually overwhelm the entire system. It also predicts how therapeutic success depends upon a relationship between RNAi strength and delivery efficiency and uniformity. Finally, targeting an essential viral element, in this case the HIV TAR region, can be highly successful if the RNAi target sequence is correctly selected. In addition to providing specific predictions for how to optimize a clinical therapy, this system may also serve as a future tool for investigating more fundamental questions of viral e,volution.