Abstract

On 2022 October 5, The Royal Swedish Academy of Sciences announced its decision to award the Nobel Prize in Chemistry 2022 to Carolyn R. Bertozzi (Stanford University), Morten Meldal (University of Copenhagen), and K. Barry Sharpless (Scripps Research) “for the development of click chemistry and bioorthogonal chemistry.” The glycobiology community was exultant! To understand why, one must appreciate how challenges in glycoscience research motivated the development of these transformative chemical tools. Glycoscience has a storied history contributing significant discoveries to hematology, metabolism, microbiology, and other fields of biomedical research throughout much of the 20th century. But when the 1970s and 80s ushered in new molecular biology methods that accelerated studies of nucleic acid and protein function, studies of glycans began to lag behind (National Research Council 2012; Agre et al. 2016). Fortunately, since then, vast improvements have been made in areas such as carbohydrate synthesis and glycan arrays (Rillahan and Paulson 2011; Li and Bennett 2022), availability of glyco-enzymes and small molecule inhibitors (Moremen et al. 2018; Almahayni et al. 2022), mass spectrometry analysis of glycans and glycopeptides (Ruhaak et al. 2018; Suttapitugsakul et al. 2020; Bagdonaite et al. 2022), as well understanding of biological systems (Varki 2017), all of which have facilitated studies of glycan function. Notwithstanding these and other important advances, glycan detection has presented a recurrent challenge. Indeed, much of the modern practice of biological research hinges on the ability to specifically address a biomolecule of interest so that it can be isolated, visualized, or quantified. For nucleic acids, this can often be achieved via hybridization, whereas specific proteins can be detected and tracked using antibodies or protein tagging methods. But genetically encoded tags cannot be used to track glycans, which are not primary gene products. For the glycobiologist, lectins and antibodies have been essential tools but can suffer from limitations relating to specificity and affinity (Cummings et al. 2022).

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