A mathematical model of N-linked glycosylation
Metabolic engineering of N‐linked oligosaccharide biosynthesis to produce novel glycoforms or glycoform distributions of a recombinant glycoprotein can potentially lead to an improved therapeutic performance of the glycoprotein product. A mathematical model for the initial stages of this process, up...
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Veröffentlicht in: | Biotechnology and bioengineering 2005-12, Vol.92 (6), p.711-728 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Metabolic engineering of N‐linked oligosaccharide biosynthesis to produce novel glycoforms or glycoform distributions of a recombinant glycoprotein can potentially lead to an improved therapeutic performance of the glycoprotein product. A mathematical model for the initial stages of this process, up to the first galactosylation of an oligosaccharide, was previously developed by Umana and Bailey (1997) (UB1997). Building on this work, an extended model is developed to include further galactosylation, fucosylation, extension of antennae by N‐acetyllactosamine repeats, and sialylation. This allows many more structural features to be predicted. A number of simplifying assumptions are also relaxed to incorporate more variables for the control of glycoforms. The full model generates 7565 oligosaccharide structures in a network of 22,871 reactions. Methods for solving the model for the complete product distribution and adjusting the parameters to match experimental data are also developed. A basal set of kinetic parameters for the enzyme‐catalyzed reactions acting on free oligosaccharide substrates is obtained from the previous model and existing literature. Enzyme activities are adjusted to match experimental glycoform distributions for Chinese Hamster Ovary (CHO). The model is then used to predict the effect of increasing expression of a target glycoprotein on the product glycoform distribution and evaluate appropriate metabolic engineering strategies to return the glycoform profile to its original distribution pattern. This model may find significant utility in the future to predict glycosylation patterns and direct glycoengineering projects to optimize glycoform distributions. © 2005 Wiley Periodicals, Inc. |
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ISSN: | 0006-3592 1097-0290 |
DOI: | 10.1002/bit.20645 |