Artificial Metabolons: Models for proximity-driven control over multienzyme pathw

描述（由申请人提供）：构成代谢途径的顺序酶通常在细胞内彼此密切相关。这种共定位提供了一种代谢区隔的方法，被认为对细胞功能至关重要。然而，由于这些多酶复合物（“代谢物”）在体内研究或在体外不受干扰地分离是相当具有挑战性的，因此序列酶邻近的动力学后果很难表征。我们将测试代谢途径可以通过改变酶的定位和关联来调节的假设。为了做到这一点，我们将采用一种“自下而上”的方法，通过构建实验模型系统来控制酶的接近度，以模拟稳定或短暂的相互作用。这些人工代谢物的结果将与(i)计算模型和（ii）激发模型的生物代谢物之一嘌呤酶体进行比较。提出了两个目标：目标1。代谢区隔模型。我们将从从头开始嘌呤生物合成途径的顺序酶连接到单层和多层几何结构的支架上，表征这些人工代谢物的结构和动力学，并将实验动力学结果与非局部控制和计算模型的预测进行比较。目标2。实验和计算模型细胞中代谢区隔的研究。与Aim 1类似的代谢区室模型将被纳入微尺度细胞模型，旨在捕捉细胞内环境的关键特征，包括扩散受阻、有限体积、有限数量的底物和酶分子。微体积的实验结果将与Aim 1的体溶液数据和计算模型进行比较。总之，这项工作将为多酶途径中空间组织的可能优势提供新的见解。我们的发现将补充体内和体外生物代谢的研究，并将提供关于共定位可能的动力学优势的信息。这项工作的影响将包括提高对代谢的理解，特别是对嘌呤酶共定位的理解。最终，这种理解可能会导致控制这些途径的全新方法。例如，从头嘌呤生物合成途径是抗癌药物设计的重要靶点；因此，这项工作的成功可能会导致基于破坏酶复合物形成的新的癌症治疗方法。我们预计，共定位将成为与特定酶抑制剂一样重要的药物设计靶标。这项工作将为多酶途径中空间组织的可能优势提供新的见解。例如，十步从头嘌呤生物合成途径是抗癌药物设计的重要靶点。从这里提出的模型系统中获得的知识将有助于指导这一途径的体内工作，这可能最终导致基于破坏酶复合物形成的新癌症治疗。

DESCRIPTION (provided by applicant): The sequential enzymes that make up metabolic pathways often exist in close association with one another within the cell. Such co-localization provides a means of metabolic compartmentation, and is thought to be crucial for cell function. However, because these multienzyme complexes ("metabolons") are quite challenging to study in vivo or to isolate without disruption in vitro, the kinetic consequences of proximity for sequential enzymes have been difficult to characterize. We will test the hypothesis that metabolic pathways can be regulated by altering enzyme localization and association. To do this, we will employ a "bottom up" approach, by constructing experimental model systems in which enzyme proximity is controlled to mimic stable or transient interactions. Results from these artificial metabolons will be compared with (i) computational models and (ii) the purinosome, one of the biological metabolons that inspires the models. Two Aims are proposed: Aim 1. Models for metabolic compartmentation. We will attach sequential enzymes from the de novo purine biosynthesis pathway to scaffolds in mono- and multilayered geometries, characterize the structure and kinetics of these artificial metabolons, and compare the experimental kinetic results to non-localized controls and to predictions from computational models. Aim 2. Investigation of metabolic compartmentation in experimental and computational model cells. Metabolic compartmentation models similar to those of Aim 1 will be incorporated within microscale cell models designed to capture key features of the intracellular environment, including hindered diffusion, limited volume, and finite numbers of substrate and enzyme molecules. Experimental results in microvolumes will be compared with bulk solution data from Aim 1 and with computational models. Together, this work will provide new insight into the possible advantages of spatial organization in multienzyme pathways. Our findings will complement in vivo and in vitro studies of biological metabolons and will provide information on possible kinetic advantages of co-localization. Impacts of this work will include improved understanding of metabolons generally, and of purinosome enzyme co-localization in particular. Ultimately, this understanding may lead to entirely new approaches for controlling these pathways. For example, the de novo purine biosynthesis pathway is an important target for anticancer drug design; success of the work proposed here could therefore lead to new cancer treatments based on disrupting the formation of enzyme complexes. We anticipate that co-localization will become as important a target for drug design as inhibitors for specific enzymes. PUBLIC HEALTH RELEVANCE: Project Narrative This work will provide new insight into the possible advantages of spatial organization in multienzyme pathways. For example, the ten-step de novo purine biosynthesis pathway is an important target for anticancer drug design. Knowledge gained from the model systems proposed here will help guide in vivo work on this pathway, which could ultimately lead to new cancer treatments based on disrupting the formation of enzyme complexes.