Prediction of Glycan Interacting Structur e using GlycanSample Interaction Database

尽管大多数聚糖研究都集中在聚糖与样品之间的一些相互作用上，但最近的技术已经使一次观察许多聚糖与样品的相互作用成为可能。功能糖组学联合会（CFG）收集了数据，并编制了一个数据库，其中包含3000多个样本的聚糖-样本相互作用。庞大的CFG数据库为我们提供了聚糖相互作用的“鸟瞰图”，该数据库的数据可用于产生关于聚糖与样品之间相互作用的新假设或提供关于聚糖上蛋白质结合位点的新规则。在这项工作中，我们研究了聚类技术和距离度量的最佳组合，以分析大型CFG数据集。然后，我们将CFG数据与多糖结构相结合，开发了一种提取与目标样品相互作用的多糖子结构的算法。分析结果推断亚结构与流感或凝集素相互作用。

Although most glycan research has focused on a few interactions between glycans and samples, recent technology has made it possible to observe many glycan-sample interactions at once. Consortium for Functional Glycomics(CFG) has collected data and compiled a database that contains glycan-sample interactions for more than three thousand samples. The large CFG database gives us "birds-eye view" of glycan interactions and the data from this database can be used to generate new hypothesis about interactions between glycans and samples or provide new rules about protein binding sites on glycans. In this work, we investigated the best combination of clustering technique and distance metrics for analyzing the large CFG datasets. We then developed an algorithm to extract glycan sub-structure which interacts target sample by combining the CFG data and glycan structure. The analysis results infer substructures interacting with influenza or galectin.