Mammalian glycosaminoglycans are linear complex polysaccharides comprising heparan sulfate, heparin, dermatan sulfate, chondroitin sulfate, keratan sulfate and hyaluronic acid. They bind to numerous proteins and these interactions mediate their biological activities. GAG–protein interaction data reported in the literature are curated mostly in MatrixDB database (http://matrixdb.univ-lyon1.fr/). However, a standard nomenclature and a machine-readable format of GAGs together with bioinformatics tools for mining these interaction data are lacking. We report here the building of an automated pipeline to (i) standardize the format of GAG sequences interacting with proteins manually curated from the literature, (ii) translate them into the machine-readable GlycoCT format and into SNFG (Symbol Nomenclature For Glycan) images and (iii) convert their sequences into a format processed by a builder generating three-dimensional structures of polysaccharides based on a repertoire of conformations experimentally validated by data extracted from crystallized GAG–protein complexes. We have developed for this purpose a converter (the CT23D converter) to automatically translate the GlycoCT code of a GAG sequence into the input file required to construct a three-dimensional model.

中文翻译：

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将糖胺聚糖序列翻译成3D模型的管道。在探索糖胺聚糖构象空间中的应用

哺乳动物糖胺聚糖是线性复合多糖，包括硫酸乙酰肝素，肝素，硫酸皮肤素，硫酸软骨素，硫酸角质素和透明质酸。它们与多种蛋白质结合，这些相互作用介导了它们的生物学活性。文献中报道的GAG-蛋白质相互作用数据主要在MatrixDB数据库（http://matrixdb.univ-lyon1.fr/）中进行整理。但是，缺少用于提取这些交互数据的GAG的标准命名法和机器可读格式，以及这些信息的生物信息学工具。我们在这里报告了一个自动管道的构建，以（i）标准化与文献中人工配制的蛋白质相互作用的GAG序列的格式，（ii）将其转换为机器可读的GlycoCT格式，并转换为SNFG（聚糖的符号命名法）图像，并且（iii）将其序列转换为由建造商处理的格式，该生成器根据实验构象库生成多糖的三维结构通过从结晶的GAG-蛋白质复合物中提取的数据进行验证。为此，我们开发了一种转换器（CT23D转换器），可将GAG序列的GlycoCT代码自动转换为构建三维模型所需的输入文件。