Exploring the Specificities of Glycan-Binding Proteins Using Glycan Array Data and the GlycoSearch Software

Abstract

Summary The glycan array is a powerful tool for investigating the specificities of glycan-binding proteins. By incubating a glycan-binding protein on a glycan array, the relative binding to hundreds of different oligosaccharides can be quantified in parallel. Based on these data, much information can be obtained about the preference of a glycan-binding protein for specific subcomponents of oligosaccharides, or motifs. In many cases the analysis and interpretation of glycan array data can be time consuming and imprecise if done manually. Recently we developed software, called GlycoSearch, to facilitate the analysis and interpretation of glycan array data based on the previously developed methods called Motif Segregation and Outlier Motif Analysis. Here we describe the principles behind the software, the use of the software, and an example application. The automated, objective, and precise analysis of glycan array data should enhance the value of the data for a broad range of research applications.

Aberrant glycosylation and cancer biomarker discovery: a promising and thorny journey

“…Fortunately, lectins have been considered as an extremely useful tool for glycomic and glycoproteomic study that can be used alone or in conjunction with other methods such as MS and CE because of the wide availability, affinity and relative specificity [93]. Several approaches based on lectins including lectin blot [94,95], lectin histochemistry/cytochemisty [29,96], lectin-antibody sandwich enzyme-linked immunosorbent assay (ELISA) [33,44,97], lectin affinity chromatography [98,99], lectin microarray [100][101][102] and lectin microfluidics [103] have been applied to capture the specific glycan of the glycoproteins [102,[104][105][106], enhancing the understanding of aberrant glycosylation and carcinogenesis, accelerating biomarkers recognition and quantitative detection. The Gao group has investigated the diagnostic and prognostic value of fucosylated fetuin A in HCC patients by AAL-based ELISA [107].…”

Directed Evolution of Therapeutic Antibodies Targeting Glycosylation in Cancer

“…293A cells (a sub clone of the human embryonic kidney cell line) were transfected with the plasmids and full-length antibodies purified by Protein-A through binding to antibody Fc region. Functional properties were then carefully analyzed by FACS, ELISA and by the powerful glycan microarray technology [ 44 , 45 , 46 ].…”

GlyNet: a multi-task neural network for predicting protein–glycan interactions

“…GlyNet outputs binding properties (i.e., RFUs) directly whereas many previous approaches instead only predict a classication, or the sub-motifs considered responsible for binding. 18,19,22,23,25,27,28,30,31,57,61,62 While it is possible to use general motif information to learn an accurate model for predicting binding, this still requires an additional learning process, which is non-trivial. GlyNet is a regression model (returning a continuous range of real-valued binding strength estimates, rather than binder/non-binder classication) and we believe that a shi towards regression, instead of just classication, is a critical improvement in protein-glycan interaction predictions as it provides more information about the interaction allowing a deeper analysis of the outputs.…”