Perfecting tools to define the glycan-protein interactome - Glycans, sugar structures on glycoproteins and glycolipids, are abundant on cell surfaces where they regulate cell physiology, often by interacting with glycan-specific binding proteins. Deciphering the “glycan code” of cell regulation is a key goal for glycobiology with great potential to impact human health in many clinical areas including cancer diagnosis and therapy, immune system disorders, and nervous system diseases. This “Focused Technology Research and Development” application, based on recent advances by our team, merges bioortho- gonal chemistry and deep learning tools to experimentally and computationally explore the glycan interactome. Our approach focuses on a subset of the human glycome, gangliosides, which offer great technical advantages for these efforts. Gangliosides, sialic acid-bearing glycans carried on ceramide lipids, are embedded in the outer leaflet of the plasma membrane of all human cells with their glycans facing outward. They function in diverse regulatory pathways involved in cell-cell adhesion, signal transduction, and ion transport. Ganglioside expression is linked to human diseases including cancer, diabetes, neurodegeneration, and infectious diseases. As probes of the glycan interactome they have the great advantage of being “stand-alone” functional units, each with a well- defined glycan structure. They are chemically accessible and readily deliverable to live cells. We capitalized on these properties to synthesize proof-of-concept bifunctional ganglioside probes bearing photoaffinity diazirines and click alkyne tags. We delivered these to human cancer cell lines, captured their ganglioside-protein interactome, and characterized it by proteomic mass spectrometry. The next phases of technology development constitute the focus of the current application. Aim 1: Human gangliosides are quantitatively dominated by just eight glycan structures, each carried on a ceramide lipid. Our proof-of-concept study focused on three of these (GM3, GM1, GD1a) representing a range of glycan sizes. Each was derivatized individually with minimally disruptive bifunctional diazirine-alkyne tags on the ceramide lipid, the sialic acid, and (where feasible) the terminal galactose. The current proposal extends the repertoire and scale of synthesis to embrace cancer-associated gangliosides GM2, GD3, and GD2 and major brain gangliosides GD1b and GT1b, completing the eight-ganglioside set. These will be validated using human cancer and neural cells. The outcomes will be used to evaluate and optimize deep learning computational tools designed to independently identify glycan-protein interactions. Aim 2: Gangliosides with bifunctional probes installed on their glycan sialic acid moiety capture proteins via a covalent bond to each protein’s glycan binding site. Subsequent protein depolymerization, tagged peptide capture, and release for mass spectrometric identification will allow us to catalog glycan binding sites simultaneously on numerous glycan-interacting proteins in a single experiment. The sites will be computationally compared to deep learning all-atom models optimized for glycan-protein binding.
