GlycoMME，一个用于从糖组学数据研究N-糖基化生物合成的马尔可夫建模平台。
GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data.
作者信息
Liang Chenguang, Chiang Austin W T, Lewis Nathan E
机构信息
Department of Pediatrics, University of California, San Diego, La Jolla, San Diego, CA 92130, USA; Department of Bioengineering, University of California, San Diego, La Jolla, San Diego, CA 92130, USA.
Department of Pediatrics, University of California, San Diego, La Jolla, San Diego, CA 92130, USA.
出版信息
STAR Protoc. 2023 Apr 21;4(2):102244. doi: 10.1016/j.xpro.2023.102244.
Variations in N-glycosylation, which is crucial to glycoprotein functions, impact many diseases and the safety and efficacy of biotherapeutic drugs. Here, we present a protocol for using GlycoMME (Glycosylation Markov Model Evaluator) to study N-glycosylation biosynthesis from glycomics data. We describe steps for annotating glycomics data and quantifying perturbations to N-glycan biosynthesis with interpretable models. We then detail procedures to predict the impact of mutations in disease or potential glycoengineering strategies in drug development. For complete details on the use and execution of this protocol, please refer to Liang et al. (2020)..
N-糖基化对糖蛋白功能至关重要，其变化会影响许多疾病以及生物治疗药物的安全性和有效性。在此，我们介绍一种使用GlycoMME（糖基化马尔可夫模型评估器）从糖组学数据研究N-糖基化生物合成的方案。我们描述了注释糖组学数据以及用可解释模型量化对N-聚糖生物合成扰动的步骤。然后，我们详细说明了预测疾病突变或药物开发中潜在糖基工程策略影响的程序。有关本方案使用和执行的完整详细信息，请参考Liang等人（2020年）的文献。
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