Glycan and Life Systems Integration Center, Soka University, Tokyo, Japan.
Graduate School of Science and Engineering, Soka University, Tokyo, Japan.
Anal Bioanal Chem. 2024 Jul;416(16):3687-3696. doi: 10.1007/s00216-024-05331-8. Epub 2024 May 15.
Glycans participate in a vast number of recognition systems in diverse organisms in health and in disease. However, glycans cannot be sequenced because there is no sequencer technology that can fully characterize them. There is no "template" for replicating glycans as there are for amino acids and nucleic acids. Instead, glycans are synthesized by a complicated orchestration of multitudes of glycosyltransferases and glycosidases. Thus glycans can vary greatly in structure, but they are not genetically reproducible and are usually isolated in minute amounts. To characterize (sequence) the glycome (defined as the glycans in a particular organism, tissue, cell, or protein), glycosylation pathway prediction using in silico methods based on glycogene expression data, and glycosylation simulations have been attempted. Since many of the mammalian glycogenes have been identified and cloned, it has become possible to predict the glycan biosynthesis pathway in these systems. By then incorporating systems biology and bioprocessing technologies to these pathway models, given the right enzymatic parameters including enzyme and substrate concentrations and kinetic reaction parameters, it is possible to predict the potentially synthesized glycans in the pathway. This review presents information on the data resources that are currently available to enable in silico simulations of glycosylation and related pathways. Then some of the software tools that have been developed in the past to simulate and analyze glycosylation pathways will be described, followed by a summary and vision for the future developments and research directions in this area.
糖链参与了生物体在健康和疾病状态下的大量识别系统。然而，由于没有能够完全表征糖链的测序技术，因此无法对其进行测序。与氨基酸和核酸不同，糖链没有复制的“模板”。相反，糖链是由大量糖基转移酶和糖苷酶的复杂协调合成的。因此，糖链在结构上可能有很大的差异，但它们不是遗传上可复制的，通常只能以微量分离出来。为了对糖组（定义为特定生物体、组织、细胞或蛋白质中的糖链）进行（序列）表征，人们尝试了基于糖基因表达数据的计算方法进行糖基化途径预测和糖基化模拟。由于许多哺乳动物糖基因已经被鉴定和克隆，因此有可能预测这些系统中的糖生物合成途径。然后，通过将系统生物学和生物加工技术纳入这些途径模型，在给定正确的酶学参数（包括酶和底物浓度以及动力学反应参数）的情况下，就可以预测途径中潜在合成的糖链。这篇综述介绍了目前可用于进行糖基化和相关途径的计算模拟的现有数据资源。然后，将描述过去开发的一些用于模拟和分析糖基化途径的软件工具，接着总结并展望该领域未来的发展和研究方向。
