Suppr超能文献

CHO 细胞中 -连接聚糖生物合成的计算建模。

Computational Modeling of -Linked Glycan Biosynthesis in CHO Cells.

机构信息

Department of Bioinformatics, Graduate School of Engineering, Soka University, Tokyo 192-8577, Japan.

Department of Cardiology, Keio University School of Medicine, Tokyo 160-8582, Japan.

出版信息

Molecules. 2022 Mar 8;27(6):1766. doi: 10.3390/molecules27061766.

Abstract

Glycan biosynthesis simulation research has progressed remarkably since 1997, when the first mathematical model for -glycan biosynthesis was proposed. An -glycan model has also been developed to predict -glycan biosynthesis pathways in both forward and reverse directions. In this work, we started with a set of -glycan profiles of CHO cells transiently transfected with various combinations of glycosyltransferases. The aim was to develop a model that encapsulated all the enzymes in the CHO transfected cell lines. Due to computational power restrictions, we were forced to focus on a smaller set of glycan profiles, where we were able to propose an optimized set of kinetics parameters for each enzyme in the model. Using this optimized model we showed that the abundance of more processed glycans could be simulated compared to observed abundance, while predicting the abundance of glycans earlier in the pathway was less accurate. The data generated show that for the accurate prediction of -linked glycosylation, additional factors need to be incorporated into the model to better reflect the experimental conditions.

摘要

糖链生物合成模拟研究自 1997 年提出第一个 -糖链生物合成数学模型以来取得了显著进展。还开发了 -糖链模型以预测正向和反向的 -糖链生物合成途径。在这项工作中,我们从一组瞬时转染各种糖基转移酶的 CHO 细胞的 -糖链图谱开始。目的是开发一个包含 CHO 转染细胞系中所有酶的模型。由于计算能力的限制,我们不得不专注于一组较小的糖谱,在这些糖谱中,我们能够为模型中的每个酶提出一组优化的动力学参数。使用这个优化的模型,我们表明与观察到的丰度相比,可以模拟更加工的聚糖的丰度,而预测途径早期的聚糖丰度则不太准确。生成的数据表明,为了准确预测 -连接糖基化,需要将其他因素纳入模型,以更好地反映实验条件。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7eb1/8950484/26d71729aa5b/molecules-27-01766-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验