Department of Mathematics, California State University Northridge, Los Angeles, California, USA.
PLoS One. 2009 Dec 30;4(12):e8165. doi: 10.1371/journal.pone.0008165.
For many viruses, the ability to infect eukaryotic cells depends on their transport through the cytoplasm and across the nuclear membrane of the host cell. During this journey, viral contents are biochemically processed into complexes capable of both nuclear penetration and genomic integration. We develop a stochastic model of viral entry that incorporates all relevant aspects of transport, including convection along microtubules, biochemical conversion, degradation, and nuclear entry. Analysis of the nuclear infection probabilities in terms of the transport velocity, degradation, and biochemical conversion rates shows how certain values of key parameters can maximize the nuclear entry probability of the viral material. The existence of such "optimal" infection scenarios depends on the details of the biochemical conversion process and implies potentially counterintuitive effects in viral infection, suggesting new avenues for antiviral treatment. Such optimal parameter values provide a plausible transport-based explanation of the action of restriction factors and of experimentally observed optimal capsid stability. Finally, we propose a new interpretation of how genetic mutations unrelated to the mechanism of drug action may nonetheless confer novel types of overall drug resistance.
对于许多病毒来说，感染真核细胞的能力取决于它们在宿主细胞质和穿过核膜的运输过程。在这个过程中，病毒的内容物经过生化处理，形成能够进行核穿透和基因组整合的复合物。我们开发了一种病毒进入的随机模型，该模型包含了运输的所有相关方面，包括沿着微管的对流、生化转化、降解和核进入。根据运输速度、降解和生化转化速率，对核感染概率进行分析，结果表明关键参数的某些值如何能使病毒物质的核进入概率最大化。这种“最优”感染情况的存在取决于生化转化过程的细节，并暗示了病毒感染中可能违反直觉的影响，为抗病毒治疗提供了新的途径。这些最优参数值为限制因子的作用以及实验观察到的最佳衣壳稳定性提供了一种基于运输的合理解释。最后，我们提出了一种新的解释，即与药物作用机制无关的遗传突变如何能够赋予新型的整体药物抗性。
