title: Optimization of collective enzyme activity via spatial localization.
abstract: The spatial organization of enzymes often plays a crucial role in the functionality and efficiency of enzymatic pathways. To fully understand the design and operation of enzymatic pathways, it is therefore crucial to understand how the relative arrangement of enzymes affects pathway function. Here we investigate the effect of enzyme localization on the flux of a minimal two-enzyme pathway within a reaction-diffusion model. We consider different reaction kinetics, spatial dimensions, and loss mechanisms for intermediate substrate molecules. Our systematic analysis of the different regimes of this model reveals both universal features and distinct characteristics in the phenomenology of these different systems. In particular, the distribution of the second pathway enzyme that maximizes the reaction flux undergoes a generic transition from co-localization with the first enzyme when the catalytic efficiency of the second enzyme is low, to an extended profile when the catalytic efficiency is high. However, the critical transition point and the shape of the extended optimal profile is significantly affected by specific features of the model. We explain the behavior of these different systems in terms of the underlying stochastic reaction and diffusion processes of single substrate molecules.
authors.affiliation: Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Ludwig-Maximilians-Universität, 80333 München, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Buchner
authors.forename: Filipe
authors.initials: F
authors.lastname: Tostevin
authors.forename: Florian
authors.initials: F
authors.lastname: Hinzpeter
authors.forename: Ulrich
authors.initials: U
authors.lastname: Gerland
mesh_terms: D002462:Cell Membrane / Q000737:chemistry / Q000201:enzymology*; D004058:Diffusion; D004798:Enzymes / Q000378:metabolism* / Q000502:physiology; D008954:Models, Biological
chemical_list: D004798:Enzymes