Optimal enzyme profiles in unbranched metabolic pathways
Résumé
How to optimize the allocation of enzymes in metabolic pathways has been a topic of study for many decades. Although the general problem is complex and nonlinear, we have previously shown that it can be solved by convex optimization. In this paper, we focus on unbranched metabolic pathways with simplified enzymatic rate laws and derive analytic solutions to the optimization problem. We revisit existing solutions based on the limit of mass-action rate laws and present new solutions for other rate laws. Furthermore, we revisit a known relationship between flux control coefficients and enzyme abundances in optimal metabolic states. We generalize this relationship to models with density constraints on enzymes and metabolites, and present a new local relationship between optimal reaction elasticities and enzyme amounts. Finally, we apply our theory to derive simple kinetics-based formulae for protein allocation during bacterial growth.
Mots clés
systems biology computational biology biotechnology metabolic pathway enzymatic rate law enzyme demand optimization protein allocation bacterial growth law
systems biology
computational biology
biotechnology metabolic pathway
enzymatic rate law
enzyme demand
optimization
protein allocation
bacterial growth law
Domaines
Sciences du Vivant [q-bio]
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Noor_2023_Interface_Focus_Optimal_enzyme_profiles.pdf (1.27 Mo)
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