Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, Ontario, Canada, K1H 8L6.
J R Soc Interface. 2012 Dec 7;9(77):3411-25. doi: 10.1098/rsif.2012.0633. Epub 2012 Sep 12.
Many biomolecular systems depend on orderly sequences of chemical transformations or reactions. Yet, the dynamics of single molecules or small-copy-number molecular systems are significantly stochastic. Here, we propose state sequence analysis--a new approach for predicting or visualizing the behaviour of stochastic molecular systems by computing maximum probability state sequences, based on initial conditions or boundary conditions. We demonstrate this approach by analysing the acquisition of drug-resistance mutations in the human immunodeficiency virus genome, which depends on rare events occurring on the time scale of years, and the stochastic opening and closing behaviour of a single sodium ion channel, which occurs on the time scale of milliseconds. In both cases, we find that our approach yields novel insights into the stochastic dynamical behaviour of these systems, including insights that are not correctly reproduced in standard time-discretization approaches to trajectory analysis.
许多生物分子系统依赖于有序的化学转化或反应序列。然而,单分子或小拷贝数分子系统的动力学具有显著的随机性。在这里,我们提出了状态序列分析——一种通过计算最大概率状态序列来预测或可视化随机分子系统行为的新方法,该方法基于初始条件或边界条件。我们通过分析人类免疫缺陷病毒基因组中耐药突变的获得来验证这种方法,这一过程依赖于在数年时间尺度上发生的罕见事件,以及单个钠离子通道的随机开启和关闭行为,这一过程发生在毫秒时间尺度上。在这两种情况下,我们发现我们的方法为这些系统的随机动力学行为提供了新的见解,包括在轨迹分析的标准时间离散化方法中不能正确再现的见解。