Remy Ingrid, Michnick Stephen W
Département de Biochimie, Université de Montréal, succursale centre-ville, Montréal, Québec, Canada.
J Cell Physiol. 2003 Sep;196(3):419-29. doi: 10.1002/jcp.10328.
Cellular biochemical machineries, what we call pathways, consist of dynamically assembling and disassembling macromolecular complexes. While our models for the organization of biochemical machines are derived largely from in vitro experiments, do they reflect their organization in living cells? We have developed a general experimental strategy that addresses this question by allowing the quantitative probing of molecular interactions in intact living cells. The experimental strategy is based on protein fragment complementation assays (PCA), a method whereby protein interactions are coupled to refolding of enzymes from cognate fragments where reconstitution of enzyme activity acts as the detector of a protein interaction. A biochemical machine or pathway is defined by grouping interacting proteins into those that are perturbed in the same way by common factors (hormones, metabolites, enzyme inhibitors, etc). In this review, we describe how we go from descriptive to quantitative representations of biochemical networks at an individual to whole genome level and how our approach will lead ultimately to better descriptions of the biochemical machineries that underlie living processes.
细胞生化机制，即我们所说的信号通路，由动态组装和解聚的大分子复合物组成。虽然我们关于生化机器组织的模型很大程度上源于体外实验，但它们是否反映了其在活细胞中的组织形式呢？我们开发了一种通用的实验策略，通过对完整活细胞中的分子相互作用进行定量探究来解决这个问题。该实验策略基于蛋白质片段互补分析（PCA），这是一种将蛋白质相互作用与同源片段中酶的重新折叠相偶联的方法，其中酶活性的重建作为蛋白质相互作用的检测器。通过将相互作用的蛋白质分组为那些受到共同因素（激素、代谢物、酶抑制剂等）相同方式扰动的蛋白质，来定义生化机器或信号通路。在这篇综述中，我们描述了我们如何从个体到全基因组水平，从生化网络的描述性表示转变为定量表示，以及我们的方法最终将如何更好地描述生命过程背后的生化机制。
