Saiz Leonor, Vilar Jose M G
Integrative Biological Modeling Laboratory, Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.
Mol Syst Biol. 2006;2:2006.0024. doi: 10.1038/msb4100061. Epub 2006 May 16.
The formation and regulation of macromolecular complexes provides the backbone of most cellular processes, including gene regulation and signal transduction. The inherent complexity of assembling macromolecular structures makes current computational methods strongly limited for understanding how the physical interactions between cellular components give rise to systemic properties of cells. Here, we present a stochastic approach to study the dynamics of networks formed by macromolecular complexes in terms of the molecular interactions of their components. Exploiting key thermodynamic concepts, this approach makes it possible to both estimate reaction rates and incorporate the resulting assembly dynamics into the stochastic kinetics of cellular networks. As prototype systems, we consider the lac operon and phage lambda induction switches, which rely on the formation of DNA loops by proteins and on the integration of these protein-DNA complexes into intracellular networks. This cross-scale approach offers an effective starting point to move forward from network diagrams, such as those of protein-protein and DNA-protein interaction networks, to the actual dynamics of cellular processes.
大分子复合物的形成与调控构成了大多数细胞过程的基础，包括基因调控和信号转导。组装大分子结构的内在复杂性使得当前的计算方法在理解细胞成分之间的物理相互作用如何产生细胞的系统特性方面受到很大限制。在此，我们提出一种随机方法，从大分子复合物各组分的分子相互作用角度来研究由其形成的网络的动力学。利用关键的热力学概念，该方法既能估计反应速率，又能将由此产生的组装动力学纳入细胞网络的随机动力学中。作为原型系统，我们考虑乳糖操纵子和噬菌体λ诱导开关，它们依赖蛋白质形成DNA环以及这些蛋白质 - DNA复合物整合到细胞内网络中。这种跨尺度方法为从诸如蛋白质 - 蛋白质和DNA - 蛋白质相互作用网络的网络图推进到细胞过程的实际动力学提供了一个有效的起点。
