Department of Mathematics and Computer Science, Free University Berlin, Berlin, Germany.
PLoS Comput Biol. 2012 Jan;8(1):e1002359. doi: 10.1371/journal.pcbi.1002359. Epub 2012 Jan 19.
Nucleoside analogs (NAs) are used to treat numerous viral infections and cancer. They compete with endogenous nucleotides (dNTP/NTP) for incorporation into nascent DNA/RNA and inhibit replication by preventing subsequent primer extension. To date, an integrated mathematical model that could allow the analysis of their mechanism of action, of the various resistance mechanisms, and their effect on viral fitness is still lacking. We present the first mechanistic mathematical model of polymerase inhibition by NAs that takes into account the reversibility of polymerase inhibition. Analytical solutions for the model point out the cellular- and kinetic aspects of inhibition. Our model correctly predicts for HIV-1 that resistance against nucleoside analog reverse transcriptase inhibitors (NRTIs) can be conferred by decreasing their incorporation rate, increasing their excision rate, or decreasing their affinity for the polymerase enzyme. For all analyzed NRTIs and their combinations, model-predicted macroscopic parameters (efficacy, fitness and toxicity) were consistent with observations. NRTI efficacy was found to greatly vary between distinct target cells. Surprisingly, target cells with low dNTP/NTP levels may not confer hyper-susceptibility to inhibition, whereas cells with high dNTP/NTP contents are likely to confer natural resistance. Our model also allows quantification of the selective advantage of mutations by integrating their effects on viral fitness and drug susceptibility. For zidovudine triphosphate (AZT-TP), we predict that this selective advantage, as well as the minimal concentration required to select thymidine-associated mutations (TAMs) are highly cell-dependent. The developed model allows studying various resistance mechanisms, inherent fitness effects, selection forces and epistasis based on microscopic kinetic data. It can readily be embedded in extended models of the complete HIV-1 reverse transcription process, or analogous processes in other viruses and help to guide drug development and improve our understanding of the mechanisms of resistance development during treatment.
核苷类似物（NAs）被用于治疗多种病毒感染和癌症。它们与内源性核苷酸（dNTP/NTP）竞争，掺入新生的 DNA/RNA 中，并通过阻止随后的引物延伸来抑制复制。迄今为止，仍然缺乏一种可以分析其作用机制、各种耐药机制以及它们对病毒适应性影响的综合数学模型。我们提出了第一个考虑到聚合酶抑制的可逆性的核苷类似物对聚合酶抑制的机制数学模型。该模型的解析解指出了抑制的细胞和动力学方面。我们的模型正确预测了 HIV-1，对核苷逆转录酶抑制剂（NRTIs）的耐药性可以通过降低其掺入率、增加其切除率或降低其对聚合酶酶的亲和力来赋予。对于所有分析的 NRTIs 及其组合，模型预测的宏观参数（功效、适应性和毒性）与观察结果一致。发现不同靶细胞之间 NRTI 的功效差异很大。令人惊讶的是，dNTP/NTP 水平低的靶细胞可能不会赋予对抑制的超敏感性，而 dNTP/NTP 含量高的细胞可能赋予天然抗性。我们的模型还通过整合突变对病毒适应性和药物敏感性的影响来量化突变的选择优势。对于齐多夫定三磷酸（AZT-TP），我们预测这种选择优势以及选择胸腺嘧啶相关突变（TAMs）所需的最小浓度高度依赖于细胞。所开发的模型允许基于微观动力学数据研究各种耐药机制、固有适应性效应、选择力和上位性。它可以很容易地嵌入到完整 HIV-1 逆转录过程或其他病毒中类似过程的扩展模型中，有助于指导药物开发并提高我们对治疗过程中耐药性发展机制的理解。
