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.
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.
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