Lee Byoungkoo, Leduc Philip R, Schwartz Russell
Joint Program in Computational Biology, Carnegie Mellon University and University of Pittsburgh, 654 Mellon Institute, 4400 Fifth Avenue, Pittsburgh, Pennsylvania 15213, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Sep;78(3 Pt 1):031911. doi: 10.1103/PhysRevE.78.031911. Epub 2008 Sep 12.
The environment inside a living cell is dramatically different from that found in in vitro models, presenting a problem for computational models of biochemistry that are only beginning to capture these differences. This deviation between idealized in vitro models and more realistic intracellular conditions is particularly problematic for models of molecular self-assembly, but also specifically hard to address because the large sizes and long assembly times of biological self-assembly systems force the use of highly simplified models. We have developed a prototype of a molecular self-assembly simulator based on the Green's function reaction dynamics (GFRD) model to achieve more realistic models of assembly in the crowded conditions of the cell without unduly sacrificing tractability. We tested the model on a simple representation of dimer assembly in a two-dimensional space. Our simulations verify that the model is computationally efficient, provides a realistic quantitative model of reaction kinetics in uncrowded conditions, and exhibits expected excluded volume effects under conditions of high crowding. This work confirms the effectiveness of the GFRD technique for more realistic coarse-grained modeling of self-assembly in crowded conditions and helps lay the groundwork for exploring the effects of in vivo crowding on more complex assembly systems.
活细胞内部的环境与体外模型中的环境截然不同，这给生物化学计算模型带来了问题，因为这些模型才刚刚开始捕捉这些差异。理想化的体外模型与更现实的细胞内条件之间的这种偏差，对于分子自组装模型来说尤其成问题，但也特别难以解决，因为生物自组装系统的大尺寸和长组装时间迫使人们使用高度简化的模型。我们基于格林函数反应动力学（GFRD）模型开发了一个分子自组装模拟器的原型，以在不过度牺牲可处理性的情况下，实现更真实的细胞拥挤条件下的组装模型。我们在二维空间中对二聚体组装的简单表示上测试了该模型。我们的模拟验证了该模型在计算上是高效的，在非拥挤条件下提供了一个现实的反应动力学定量模型，并且在高拥挤条件下表现出预期的排阻体积效应。这项工作证实了GFRD技术在更真实地对拥挤条件下的自组装进行粗粒度建模方面的有效性，并有助于为探索体内拥挤对更复杂组装系统的影响奠定基础。
