Exploring the specificities of glycan-binding proteins using glycan array data and the GlycoSearch software

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

Advances in diagnostics, therapeutics, vaccines, transfusion, and organ transplantation build on a fundamental understanding of glycan-protein interactions. To aid this, we developed GlyNet, a model that accurately predicts interactions (relative binding strengths) between mammalian glycans and 352 glycan-binding proteins, many at multiple concentrations. For each glycan input, our model produces 1257 outputs, each representing the relative interaction strength between the input glycan and a particular protein sample. GlyNet learns these continuous values using relative fluorescence units (RFUs) measured on 599 glycans in the Consortium for Functional Glycomics glycan arrays and extrapolates these to RFUs from additional, untested glycans. GlyNet's output of continuous values provides more detailed results than the standard binary classification models. After incorporating a simple threshold to transform such continuous outputs the resulting GlyNet classifier outperforms those standard classifiers. GlyNet is the first multi-output regression model for predicting protein-glycan interactions and serves as an important benchmark, facilitating development of quantitative computational glycobiology.

GlyMDB: Glycan Microarray Database and analysis toolset

MOTIVATION

Glycan microarrays are capable of illuminating the interactions of glycan-binding proteins (GBPs) against hundreds of defined glycan structures, and have revolutionized the investigations of protein-carbohydrate interactions underlying numerous critical biological activities. However, it is difficult to interpret microarray data and identify structural determinants promoting glycan binding to glycan-binding proteins due to the ambiguity in microarray fluorescence intensity and complexity in branched glycan structures. To facilitate analysis of glycan microarray data alongside protein structure, we have built the Glycan Microarray Database (GlyMDB), a web-based resource including a searchable database of glycan microarray samples and a toolset for data/structure analysis.

RESULTS

The current GlyMDB provides data visualization and glycan-binding motif discovery for 5203 glycan microarray samples collected from the Consortium for Functional Glycomics. The unique feature of GlyMDB is to link microarray data to PDB structures. The GlyMDB provides different options for database query, and allows users to upload their microarray data for analysis. After search or upload is complete, users can choose the criterion for binder versus non-binder classification. They can view the signal intensity graph including the binder/non-binder threshold followed by a list of glycan-binding motifs. One can also compare the fluorescence intensity data from two different microarray samples. A protein sequence-based search is performed using BLAST to match microarray data with all available PDB structures containing glycans. The glycan ligand information is displayed, and links are provided for structural visualization and redirection to other modules in GlycanStructure.ORG for further investigation of glycan-binding sites and glycan structures.

AVAILABILITY AND IMPLEMENTATION

http://www.glycanstructure.org/glymdb.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Directed Evolution of Therapeutic Antibodies Targeting Glycosylation in Cancer

Simple Summary

We generated a platform for designing optimized functional therapeutic antibodies against cancer glycans. The target tumor-associated carbohydrate antigen is commonly expressed in colon and pancreatic cancers. We developed a system for selection of potent antibodies by yeast surface display against this carbohydrate antigen, then showed that elite clones have potent affinity, specificity, cancer cell binding, and therapeutic efficacy. These tools have broad utility for manipulating and engineering antibodies against carbohydrate antigens, and provide major innovative avenues of research in the field of cancer therapy and diagnostics.

Abstract

Glycosylation patterns commonly change in cancer, resulting in expression of tumor-associated carbohydrate antigens (TACA). While promising, currently available anti-glycan antibodies are not useful for clinical cancer therapy. Here, we show that potent anti-glycan antibodies can be engineered to acquire cancer therapeutic efficacy. We designed yeast surface display to generate and select for therapeutic antibodies against the TACA SLe^a (CA19−9) in colon and pancreatic cancers. Elite clones showed increased affinity, better specificity, improved binding of human pancreatic and colon cancer cell lines, and increased complement-dependent therapeutic efficacy. Molecular modeling explained the structural basis for improved antibody functionality at the molecular level. These new tools of directed molecular evolution and selection for effective anti-glycan antibodies, provide insights into the mechanisms of cancer therapy targeting glycosylation, and provide major methodological advances that are likely to open up innovative avenues of research in the field of cancer theranostics.

Glycomics and glycoproteomics of viruses: Mass spectrometry applications and insights toward structure-function relationships

The advancement of viral glycomics has paralleled that of the mass spectrometry glycomics toolbox. In some regard the glycoproteins studied have provided the impetus for this advancement. Viral proteins are often highly glycosylated, especially those targeted by the host immune system. Glycosylation tends to be dynamic over time as viruses propagate in host populations leading to increased number of and/or "movement" of glycosylation sites in response to the immune system and other pressures. This relationship can lead to highly glycosylated, difficult to analyze glycoproteins that challenge the capabilities of modern mass spectrometry. In this review, we briefly discuss five general areas where glycosylation is important in the viral niche and how mass spectrometry has been used to reveal key information regarding structure-function relationships between viral glycoproteins and host cells. We describe the recent past and current glycomics toolbox used in these analyses and give examples of how the requirement to analyze these complex glycoproteins has provided the incentive for some advances seen in glycomics mass spectrometry. A general overview of viral glycomics, special cases, mass spectrometry methods and work-flows, informatics and complementary chemical techniques currently used are discussed. © 2020 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.

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

Glycosylation is among the most important post-translational modifications for proteins and is of intrinsic complex character compared with DNAs and naked proteins. Indeed, over 50%-70% of proteins in circulation are glycosylated, and the "sweet attachments" have versatile structural and functional implications. Both the configuration and composition of the attached glycans affect the biological activities of consensus proteins significantly. Glycosylation is generated by complex biosynthetic pathways comprising hundreds of glycosyltransferases, glycosidases, transcriptional factors, transporters and the protein backbone. In addition, lack of direct genetic templates and glyco-specific antibodies such as those commonly used in DNA amplification and protein capture makes research on glycans and glycoproteins even more difficult, thus resulting in sparse knowledge on the pathophysiological implications of glycosylation. Fortunately, cutting-edge technologies have afforded new opportunities and approaches for investigating cancer-related glycosylation. Thus, glycans as well as aberrantly glycosylated protein-based cancer biomarkers have been increasingly recognized. This mini-review highlights the most recent developments in glyco-biomarker studies in an effort to discover clinically relevant cancer biomarkers using advanced analytical methodologies such as mass spectrometry, high-performance liquid chromatographic/ultra-performance liquid chromatography, capillary electrophoresis, and lectin-based technologies. Recent clinical-centered glycobiological studies focused on determining the regulatory mechanisms and the relation with diagnostics, prognostics and even therapeutics are also summarized. These studies indicate that glycomics is a treasure waiting to be mined where the growth of cancer-related glycomics and glycoproteomics is the next great challenge after genomics and proteomics.