GlyGen: Computational and Informatics Resources for Glycoscience

York, William S.; Mazumder, Raja; Ranzinger, René; Edwards, Nathan; Kahsay, Robel; Aoki‐Kinoshita, Kiyoko F.; Campbell, Matthew P.; Cummings, Richard D.; Feizi, Ten; Martin, Maria Jesus; Natale, Darren A.; Packer, Nicolle H.; Woods, Robert J.; Agarwal, Gaurav; Arpinar, Sena; Bhat, Sanath; Blake, Judith A.; Castro, Leyla Jael; Fochtman, Brian C.; Gildersleeve, Jeffrey C.; Goldman, Radoslav; Holmes, Xavier; Jain, Vinamra; Kulkarni, Sujeet; Mahadik, Rupali; Mehta, Akul Y.; Mousavi, Reza; Nakarakommula, Sandeep; Navelkar, Rahi; Pattabiraman, Nagarajan; Pierce, Michael; Ross, Karen; Vasudev, Preethi; Vora, Jeet; Williamson, Tatiana; Zhang, Wenjin

doi:10.1093/glycob/cwz080

Cited by 134 publications

(91 citation statements)

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“…The MS-based glycomics data generated in these analyses and the associated annotations are presented in accordance with the MIRAGE standards and the Athens Guidelines ( Wells et al., 2013 ). Data annotation and assignment of glycan accession identifiers were facilitated by GRITS Toolbox, GlyTouCan, GNOme, and GlyGen ( Kahsay et al., 2020 ; Tiemeyer et al., 2017 ; Weatherly et al., 2019 ; York et al., 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

Zhao

Praissman

Grant

et al. 2020

Cell Host & Microbe

359

456

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Summary The SARS-CoV-2 betacoronavirus uses its highly glycosylated trimeric Spike protein to bind to the cell surface receptor angiotensin converting enzyme 2 (ACE2) glycoprotein and facilitate host cell entry. We utilized glycomics-informed glycoproteomics to characterize site-specific microheterogeneity of glycosylation for a recombinant trimer Spike mimetic immunogen and for a soluble version of human ACE2. We combined this information with bioinformatics analyses of natural variants and with existing 3D structures of both glycoproteins to generate molecular dynamics simulations of each glycoprotein both alone and interacting with one another. Our results highlight roles for glycans in sterically masking polypeptide epitopes and directly modulating Spike-ACE2 interactions. Furthermore, our results illustrate the impact of viral evolution and divergence on Spike glycosylation, as well as the influence of natural variants on ACE2 receptor glycosylation. Taken together, these data can facilitate immunogen design to achieve antibody neutralization and inform therapeutic strategies to inhibit viral infection.

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Section: Methodsmentioning

confidence: 99%

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

Zhao

Praissman

Grant

et al. 2020

Cell Host & Microbe

359

456

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Section: Star Methodsmentioning

confidence: 99%

“…The MS-based glycomics data generated in these analyses and the associated annotations are presented in accordance with the MIRAGE standards and the Athens Guidelines(65). Data annotation and assignment of glycan accession identifiers were facilitated by GRITS Toolbox, GlyTouCan, GNOme, and GlyGen(40,(66)(67)(68).Analysis of Disulfide Bonds for SARS-Cov-2 S Protein by LC-MSTwo 10-μg aliquots of SARS-CoV-2 S protein were denatured by incubating with 20% acetonitrile at room temperature and alkylated by 13.75 mM of iodoacetamide at room temperature in dark. The two aliquots of proteins were then digested respectively using alpha lytic protease, or a combination of trypsin, Lys-C and Glu-C.…”

mentioning

confidence: 99%

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

Zhao

Praissman

Grant

et al. 2020

Preprint

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SUMMARYThe current COVID-19 pandemic is caused by the SARS-CoV-2 betacoronavirus, which utilizes its highly glycosylated trimeric Spike protein to bind to the cell surface receptor ACE2 glycoprotein and facilitate host cell entry. We utilized glycomics-informed glycoproteomics to characterize site-specific microheterogeneity of glycosylation for a recombinant trimer spike mimetic immunogen and for a soluble version of human ACE2. We combined this information with bioinformatic analyses of natural variants and with existing 3D-structures of both glycoproteins to generate molecular dynamic simulations of each glycoprotein alone and interacting with one another. Our results highlight roles for glycans in sterically masking polypeptide epitopes and directly modulating Spike-ACE2 interactions. Furthermore, our results illustrate the impact of viral evolution and divergence on Spike glycosylation, as well as the influence of natural variants on ACE2 receptor glycosylation that, taken together, can facilitate immunogen design to achieve antibody neutralization and inform therapeutic strategies to inhibit viral infection.

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“…Novel directed evolution and high-throughput screening methods leveraging the power of cell-free biology are needed to identify more efficient glycoenzyme variants with precisely tailored substrate specificity. Finally, integration of the tools from cell-free synthetic glycobiology with those from other disciplines including metabolic engineering (Wratil and Horstkorte, 2017 ); (Agatemor et al, 2019 ), mathematic modeling (Umana and Bailey, 1997 ; Spahn et al, 2016 ; Wayman et al, 2019 ), and machine learning and bioinformatics (Li F. et al, 2015 ; York et al, 2019 ) will be needed to solve the most complex problems in glycoscience. Only when these unmet needs have been addressed can the full potential of cell-free synthetic glycobiology be unlocked for furthering glycoscience and its application.…”

Section: Discussionmentioning

confidence: 99%

Cell-Free Synthetic Glycobiology: Designing and Engineering Glycomolecules Outside of Living Cells

Jaroentomeechai

Taw

et al. 2020

Front. Chem.

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Glycans and glycosylated biomolecules are directly involved in almost every biological process as well as the etiology of most major diseases. Hence, glycoscience knowledge is essential to efforts aimed at addressing fundamental challenges in understanding and improving human health, protecting the environment and enhancing energy security, and developing renewable and sustainable resources that can serve as the source of next-generation materials. While much progress has been made, there remains an urgent need for new tools that can overexpress structurally uniform glycans and glycoconjugates in the quantities needed for characterization and that can be used to mechanistically dissect the enzymatic reactions and multi-enzyme assembly lines that promote their construction. To address this technology gap, cell-free synthetic glycobiology has emerged as a simplified and highly modular framework to investigate, prototype, and engineer pathways for glycan biosynthesis and biomolecule glycosylation outside the confines of living cells. From nucleotide sugars to complex glycoproteins, we summarize here recent efforts that harness the power of cell-free approaches to design, build, test, and utilize glyco-enzyme reaction networks that produce desired glycomolecules in a predictable and controllable manner. We also highlight novel cell-free methods for shedding light on poorly understood aspects of diverse glycosylation processes and engineering these processes toward desired outcomes. Taken together, cell-free synthetic glycobiology represents a promising set of tools and techniques for accelerating basic glycoscience research (e.g., deciphering the “glycan code”) and its application (e.g., biomanufacturing high-value glycomolecules on demand).

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GlyGen: Computational and Informatics Resources for Glycoscience

Cited by 134 publications

References 0 publications

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

Cell-Free Synthetic Glycobiology: Designing and Engineering Glycomolecules Outside of Living Cells

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