Monica T J, Andersen D C, Goochee C F
Department of Chemical Engineering, Stanford University, CA 94305, USA.
Glycobiology. 1997 Jun;7(4):515-21. doi: 10.1093/glycob/7.4.515.
A mathematical model is developed of the compartmentalized sialylation of N-linked oligosaccharides in order to understand and predict the outcome of sialylation reactions. A set of assumptions are presented, including Michaelis-Menten-type dependency of reaction rate on the concentration of the glycoprotein substrate. The resulting model predicts the heterogeneous outcome of a posttranslational oligosaccharide biosynthesis step, a critical aspect that is not accounted for in the modeling of the cotranslational attachment of oligosaccharides to glycosylation sites (Shelikoff et al., Biotech. Bioeng., 50, 73-90, 1996) or general models of the secretion process (Noe and Delenick, J. Cell Sci., 92, 449-459, 1989). In the steady-state for the likely case where the concentration of substrate is much less than the Km of the sialyltransferase, the model predicts that the extent of sialylation, x, will depend upon the enzyme concentration, enzyme kinetic parameters and substrate residence time in the reaction compartment. The value of x predicted by the model using available literature data is consistent with the values of x that have been recently determined for the glycoproteins CD4 (Spellman et al., Biochemistry, 30, 2395-2406, 1991) and t-PA (Spellman et al., J. Biol. Chem., 264, 14100-14111, 1989) secreted by Chinese hamster ovary cells. For the unsaturated case, the model also predicts that x is independent of the concentration of secreted glycoprotein in the Golgi. The general modeling approach outlined in this article may be applicable to other glycosylation reactions and posttranslational modifications.
为了理解和预测唾液酸化反应的结果，建立了一个关于N-连接寡糖区室化唾液酸化的数学模型。提出了一组假设，包括反应速率对糖蛋白底物浓度的米氏型依赖性。所得模型预测了翻译后寡糖生物合成步骤的异质结果，这是一个关键方面，在寡糖共翻译附着到糖基化位点的建模（Shelikoff等人，《生物技术与生物工程》，第50卷，第73 - 90页，1996年）或分泌过程的一般模型（Noe和Delenick，《细胞科学杂志》，第92卷，第449 - 459页，1989年）中未被考虑。在底物浓度远低于唾液酸转移酶Km的可能稳态情况下，模型预测唾液酸化程度x将取决于酶浓度、酶动力学参数以及底物在反应区室中的停留时间。使用现有文献数据由模型预测的x值与最近为中国仓鼠卵巢细胞分泌的糖蛋白CD4（Spellman等人，《生物化学》，第30卷，第2395 - 2406页，1991年）和t - PA（Spellman等人，《生物化学杂志》，第264卷，第14100 - 14111页，1989年）确定的x值一致。对于不饱和情况，模型还预测x与高尔基体中分泌糖蛋白的浓度无关。本文概述的一般建模方法可能适用于其他糖基化反应和翻译后修饰。
