Optimal Selection of Enzyme Levels using Large-scale Kinetic Models
| Authors: | Nikolaev Evgeni V., Pennsylvania State University, United States
Pharkya Priti, Pennsylvania State University, United States
Maranas Costas D., Pennsylvania State University, United States
Armaou Antonios, Pennsylvania State University, United States |
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| Topic: | 8.4 Control of Biotechnological Processes |
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| Session: | Systems Biology |
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| Keywords: | biotechnology, global optimization, mathematical models, kinetic models, enzyme levels |
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Abstract
A hybrid optimization framework is introduced to identify enzyme sets and levels to meet overproduction requirements using kinetic models of metabolism. A simulated annealing algorithm is employed to navigate through the discrete space of enzyme sets while a sequential quadratic programming method is utilized to identify optimal enzyme levels. The framework is demonstrated on a model of E.coli central metabolism for serine biosynthesis. Computational results show that by optimally manipulating relatively small enzyme sets, a substantial increase in serine production can be achieved. The proposed approach thus provides a versatile tool for the elucidation of controlling enzymes with implications in biotechnology.
