Project Summary:  Carbohydrate-binding proteins (human, bacterial or viral lectins) and carbohydrate-processing enzymes (glycosyltransferases and glycosidases) are important targets for therapeutic intervention, however the creation of drug-like molecules that can competitively inhibit carbohydrate-binding sites is uniquely challenging. Computational approaches that are specifically designed to screen analogs of carbohydrates could be invaluable aids in both increasing the objectivity of the synthetic choices and in prioritizing the synthetic effort required for glycomimetic development. The creation and validation of such a tool is the focus of this project.

Members associated: Robert J. Woods, Sawsan Mahmoud, David Montgomery, Amika Sood, Alyssa Wright, Alexander Hung Lee & Yao Xiao

Resulting publications: PMCID: PMC9564326 

Project Summary: Carbohydrates are the most abundant class of organic compounds on Earth and are found in all main macromolecular building blocks of life, including nucleic acids, proteins and lipids. Glycomaterials are carbohydrate-based polymeric materials with diverse biological functions including biochemical signaling, structural support, and water retention. Because of their complex molecular structures, glycomaterials are more difficult to design, create, and characterize than other biopolymers. There are no widely available methods for their large-scale synthesis and rapid characterization. These scientific and technological challenges hinder our understanding of these ubiquitous materials, vitally important to advancing sustainable materials, renewable energy technologies, and human health.

Anchored at Virginia Tech and the University of Georgia, GlycoMIP, an NSF Materials Innovation Platform, accelerates discovery in glycomaterials science and technology through a unique national user facility and leading-edge in-house research and advances the implementation of the Materials Genome Initiative paradigm shift in materials development. The GlycoMIP user facility supports researchers from academia, industry, and government research institutions through access to state-of-the-art equipment, world-class services, and technical data for the synthesis, characterization, and modeling of bioinspired glycomaterials at the molecular, supramolecular, and macroscopic (bulk property) levels. Strengthened by world-leading expertise at Brandeis University, Rensselaer Polytechnic Institute, and the University of North Carolina, the in-house research of GlycoMIP employs efficient convergence of physical sciences, engineering, computation, and life sciences to achieve scientific and technological breakthroughs in scalable synthesis, high-throughput characterization, and mesoscale modeling of glycomaterials.

GlycoMIP is a nationwide collaboratory, where members of the glycomaterials community share tools, samples, data, software, and know-how for the collective advancement of glycomaterials science and technology. GlycoMIP offers short courses, hands-on training courses, and tutorials on glycomaterials science and technology topics to users and potential users and trains the next generation of glycomaterials researchers in accelerated materials development.

Members associated: Robert J. Woods, Mark Baine, Lachele Foley, Oliver Grant, Paige LaMore, Sawsan Mahmoud, David Montgomery,  Amika Sood, & Alyssa Wright

Project Summary: This application addresses a major unmet need for technology that will facilitate the integration of glycomics and glycan expression with genomics, transcriptomics, and metabolomics. The rapidly developing field of glycoscience must have tools to identify and characterize the expression of human and animal glycans in the context of normal development, homeostasis, and in disease processes. Traditional studies in the glycosciences have relied on an odd assortment of plant-derived lectins and a few traditional mouse monoclonal antibodies, but such reagents have multiple limitations.

This application exploits our breakthrough technology that allows us to develop suites of specific, rigorously characterized anti-carbohydrate antibodies (ACAs). We have developed high-throughput immunization and screening technologies using variable-lymphocyte receptors (VLRBs) that are generated upon immunization of ancient sea lampreys with cells, cell-conjugates, glycoproteins, or tissues. Because of the evolutionary diversity of both their immune systems and glycomes as compared to mammals, these ancient fish generate a diverse repertoire of anti-carbohydrate VLRBs with exquisite specificity, and are able to discriminate between different linkages, motif presentation on N- and O-glycans, and the presence of functional groups on individual monosaccharides. After immunization, the cloned cDNAs encoding the VLRBs are expressed in a yeast surface display (YSD) library containing multiple individual specificities.

This innovative technology development allows us to both generate a ‘library of VLRBs’ in a single immunization protocol, as well as sequentially screen these stable YSD libraries for ACAs using our numerous and diverse glycan and glycopeptide microarrays and display technologies. Ultimately, after the VLRBs are screened for their binding to glycan antigens, recombinant and reproducible VLRB-Ig chimeras are expressed, which can be used for all types of immunological approaches to explore glycan expression and function.

We propose 3 robust and innovative Specific Aims to address the current technological deficiencies: Aim 1- Refine and expand our technology to generate permanent VLRB YSD libraries against a diverse array of human glycan targets, using multiple immunization and screening strategies. Aim 2- Enrich for and characterize monoclonal VLRBs that are specific for human glycans, which will be critical in mapping the Human Glycome, by mining the created YSD libraries. Aim 3- Generate novel VLRB specificities using targeted mutagenesis of characterized VLRBs, to create tailored antibody specificities with potentially higher affinities. The success of our studies will climax with an arsenal of rigorously vetted tools and robust reagents that will be made publicly available and accessible to the broader research community. This will ultimately encourage widespread study of these incredibly important, complex molecules that are vital in human health and disease, promote harmonization with other biological sciences, and allow for the study of expression and functions of the Human Glycome.

Members associated: Robert J. Woods, Oliver Grant, & Zhe Yang

Project Summary: Selecting HA glycosylation for improved vaccine responses This application responds to PA-18-859 "Advancing Research Needed to Develop a Universal Influenza Vaccine" and addresses the goal to “support rational design of universal influenza vaccines”. The low Influenza A virus (IAV) vaccine effectiveness (VE) stems from the ability of the virus to evade existing immunity. Its error-prone polymerase enables rapid evolution of the surface glycoprotein antigens hemagglutinin (HA) and neuraminidase (NA). Significantly, among the more prevalent mutations that occur as an IAV strain undergoes antigenic drift is the appearance of new N-glycosylation consensus sequences (sequons) on the HA globular domain. The appearance of new glycosites shields underlying amino acid residues from antibody contact. However, because the host receptor binding sites (RBSs) also reside in the HA head group, variations in head group glycosylation have the simultaneous potential to harm viral fitness by interfering with virus binding to its host receptor. HA glycosylation is macro- and micro-heterogeneous, meaning that each HA glycosite has a distribution of glycoforms that differ in their physicochemical and lectin-binding properties. HA therefore consists of heterogeneous populations that differ by glycosylation, antigenicity, and immunogenicity. Unfortunately, the glycosylated structures of HA populations most suited for vaccine use remain unknown for IAV strains. This lack of information results in over-reliance on genomic information that cannot predict the level of glycosylation at a given site, the compositions of the attached glycans, and which glycosylated populations of HA are most immunogenic. We propose to use glycoproteomics, molecular modeling, and antigenic cartography of HA glyco-populations to develop a detailed understanding of the relationship between HA glycosylation and immunogenicity for representative H1N1 strains. This study will enhance our understanding of the natural history of influenza viruses. In addition, we anticipate that this knowledge could be employed to select HA sequences for producing recombinant influenza vaccines with enhanced immunogenicity and VE. Unlike vaccines based on attenuated or inactivated virus, recombinant vaccines are created synthetically and can be prepared in advance of the emergence of a seasonal or pandemic strain of virus. Knowledge of the optimal HA glycosylation pattern would provide important guidance in recombinant vaccine design.

Members associated: Robert J. Woods, & Alyssa Wright

Project Summary: With this award, the Chemistry of Life Processes Program in the Chemistry Division is funding Dr. Anthony Serianni from the University of Notre Dame and Dr. Robert Woods from the University of Georgia to investigate the three-dimensional properties of sugar molecules, or saccharides, in solution. Saccharides embedded in cell surfaces play critical roles in biology. In humans, they are attached to soluble and membrane associated proteins and lipids, and their biological roles include cell-to-cell and immune recognition. While it is well known that the structural properties of saccharides correlate with their biological functions, it remains difficult to assign these structural details in solution by experimental methods. This difficulty has led to a heavy reliance on theoretical methods to assign structures even though these methods have been difficult to validate experimentally. This project aims to solve this problem by developing and applying a new experimental technique to determine populations of flexible domains in saccharides in solution, including the linkages connecting them together in polymers and linkages that attach them to other biomolecules. The experiment-derived information obtained can be compared to what is obtained from theory to test and/or validate the latter. Senior researchers, graduate students and undergraduates with interests and expertise in experimental and computational science collaborate to achieve the objectives of the project. This work provides valuable new tools to determine molecular structure that can be generally applied to any biomolecule in solution, including proteins and nucleic acids.

This research project uses stable isotopically labeled oligosaccharides and glycopeptides, nuclear magnetic resonance (NMR) spin-couplings, density functional theory calculations, circular statistics and X-ray crystallography to determine conformational populations of the flexible domains of oligosaccharides in solution. This experimental approach is possible because saccharides contain multiple NMR spin-couplings that report on the same conformational domain, allowing quantitative treatments that yield continuous single- and multi-state populational models. Once a given domain is parameterized (e.g., O- or N-glycosidic linkage), its conformational properties can be investigated in different structural contexts to determine the degree to which it adapts conformationally to environmental cues. Experimental models are compared to those obtained from molecular dynamics simulations to validate the latter. This work leads to new experiment-based conformational classifications of O-glycosidic linkages in oligosaccharides, and to a deeper understanding of the multiple factors that influence oligosaccharide conformation in solution.

Members associated: Robert J. Woods, & Xiaocong Wang

Project Summary: For over a decade, GLYCAM-Web (www.glycam.org) has provided the scientific community with a suite of online tools for simplifying the modeling of 3D structures of carbohydrates, glycoproteins, and their interactions with proteins. The highly plastic nature of oligosaccharides and the fact that they are typically branched means that they place unique demands on both software developers and users. This is exacerbated by their complex and archaic nomenclature. GLYCAM-web was developed by a team of people with a unique depth of expertise in carbohydrate chemistry and informatics, with the overarching goal of making carbohydrate modeling more accessible to scientists who either lack computational expertise, or whose familiarity with carbohydrates is limited. According to AWstats and in-house code GLYCAM-Web was visited by ~110,000 unique addresses and had ~11,000 PDB file downloads from 2016 to 2019. The downloads are usually associated with creating and viewing 3D structures of glycans and for offline modeling. We have included a detailed usage analysis in the Research Strategy to emphasize the significance of this resource to the NIGMS research community. The development of GLYCAM-Web has been primarily supported through an NIH NIGMS P41 grant held at the Complex Carbohydrate Research Center at the University of Georgia that has been continuously renewed since the 1990s. With the ending of the P41 program, we are not eligible for further support within the P41 program, and are seeking support that with enable us to transition GLYCAM-Web to a near self-sustaining resource whose operation costs are offset by new fee-for-service functionality targeting users who wish to perform molecular dynamics simulations, but who lack the expertise or infrastructure to do so. The decade- long development of GLYCAM-Web has seen the infrastructure grow and change with the advent of new architectures, code evolution, and increased security requirements, leading to a complex code base involving the C++, JAVA, and PYTHON languages. Thus a significant aspect of this proposal involves code refactoring to unify the code base, which will directly reduce maintenance costs. To achieve near self-sustainability, we have developed the four aims what will address the necessary improvements to code and infrastructure: usability, transferability, maintainability, and sustainability.

Members associated: Robert J. Woods, Lachele Foley, Oliver Grant, & David Montgomery, 

Resulting publications: PMCID: PMC9564326

Project Summary: Microglia are implicated in the initiation and progression of Alzheimer?s disease (AD), making their regulation a therapeutic target. As positive effectors, microglia phagocytose and clear toxic proteins; as negative effectors they release inflammatory mediators. Imbalance of microglial function is believed to contribute to AD progression. Among microglial regulatory proteins linked to AD susceptibility are immune inhibitory members of the Siglec family, sialic acid binding immunoglobulin-like lectins. Siglec overexpression results in increased susceptibility to AD; depletion decreases susceptibility, supporting the hypothesis that Siglec-mediated inhibition restricts microglial phagocytosis and exacerbates AD proteinopathy. Multiple inhibitory Siglecs are expressed on human (and mouse) microglia. They bind to complementary ligands ? sialic acid-terminated glycan chains on glycoproteins in the local brain milieu ? to trigger immune suppression. We discovered a sialoglycan ligand for microglial inhibitory Siglecs in human cerebral cortex. We propose that this ligand is responsible for Siglec- mediated microglial inhibition. Knowledge of the structure of this ligand, its expression and its function may provide new opportunities for therapeutic microglial modulation.

Project Summary: The SARS-CoV-2 virus has caused a pandemic of profound global impact. Its high infectivity enabled it to spread rapidly across the world. In severe cases, infection with SARS-CoV-2 leads to respiratory failure, septic shock, and failure of vital organs, including the liver and kidneys. In the absence of an effective vaccine or therapeutic agent, reducing the population’s exposure to the virus is the only viable strategy for preventing infections and overburdening of the health care system. Transmission of SARS-CoV-2 occurs through multiple routes. Prevention of SARS-CoV-2 transmission requires effective and easy-to-use technologies directed against all modes of transmission. Funded by the Biomaterials Program in the Division of Materials Research of the Mathematical and Physical Sciences Directorate, and cofunded by the Molecular Biophysics Program in the Division of Molecular and Cellular Biosciences of the Biological Sciences Directorate, this Rapid Response Research (RAPID) grant supports research into the development of biomimetic polymers that exploit the carbohydrate-binding properties of SARS-CoV-2 for virus immobilization. The developed polymers will be designed to produce virus-immobilizing gels and surfaces for applications in protective formulations and devices as well as functional studies, isolation, and purification of virions in scientific settings. The research serves the national interest by advancing the science of biomimetic materials and developing materials for the improvement of national health.

Project Summary: Glycoproteins represent a class of mammalian proteins that presents challenges for structural and functional characterization, particularly if the native glycosylation, which affects structure, stability and interaction with other molecules, is to be preserved. The best route to proteins with native glycosylation is expression in mammalian cell cultures. Unfortunately, for X-ray crystallography, this produces proteins with heterogenous glycosylation, often preventing formation of suitable crystals. For traditional nuclear magnetic resonance (NMR) methods, this forces use of expensive substrates for isotopic labeling and prohibits the perdeuteration often required to maintain resolution for larger proteins. The investigators involved in this proposal have worked together to develop an efficient mammalian cell expression system that produces proteins sparsely labeled using a restricted set of less expensive isotope enriched amino acids and maintains resolution without the aid of perdeuteration. This has been accompanied by the development of resonance assignment programs and data analysis protocols that allow structural and functional characterization from basic, high sensitivity, two-(and three-)dimensional NMR experiments. This project is designed to turn those developments into an integrated protocol that can be adopted by an expanded community of users. It centers on the refinement of a software package that accomplishes NMR resonance assignment of sparsely labeled proteins. It will be bolstered by extensive validation of program output, introduction of new data types and data analysis methods, and extension of program capabilities to the refinement of computer-generated models for protein structure. The potential impact will be a new route to structure and function studies of a class of proteins intimately involved with human physiology and disease.

Project Summary: Although ongoing technical advances are accelerating the pace and sophistication of data acquisition in glycoscience, the transformation of these data to glycobiology knowledge, insight, and understanding is slowed by the limited number of tools that facilitate their integration with biological knowledge from genetics, proteomics, pathology, and other disciplines. Our grant application describes the development of an integrated, extendable, and cross-disciplinary resource providing tools and data to address specific scientific questions that can currently be answered only by extensive literature-based research and manual collection of data from disparate databases and websites. Using insight gained during our planning grant activities, including a workshop focused on evaluating existing resources and community needs, we propose to develop a broadly relevant and sustainable glycoinformatics resource to connect glycoscience with the explosion of data that is revolutionizing biology. We identified critical gaps that need to be filled and challenges that must be overcome to create an enduring and sustainable glycoinformatics resource that goes beyond mapping glycan data to genes and proteins to identify and integrate diverse multidisciplinary knowledge from EMBL-EBI, NCBI, UniProt, UniCarbKB, CAZy, Gene Ontology and other sources. To maximize synergy among these resources, we propose a new glycan array data repository and enhanced ontologies to facilitate integration of glycan and glycoconjugate expression and interaction data with other information. Evaluating these data in the context of knowledge about genetic mutations, gene expression, protein function and other phenomena will provide new opportunities for systems-level understanding of the roles of glycosylation in disease and development. This comprehensive data integration framework will provide unprecedented support for complex queries spanning diverse data types relevant to glycobiology. Technical advances required to implement this framework include evidence tagging of data, ontology and standards development, and new interfaces that enable data mining, sharing, and dissemination. Community engagement, especially with scientists who do not specialize in glycobiology, will be emphasized to maximize the relevance of our resource. We will develop a portal to make all this information publicly available in standard formats supported by NCBI and EMBL-EBI and in new formats we develop, promoting sharing of data and their ultimate integration into these widely used informatics resources.

Resulting Publications: PMCID: PMC7386495, PMCID: PMC7335483

Project Summary: Structural biology plays a central role in modern molecular bioscience, enabling both a greater understanding and new mechanisms of manipulation of biomolecular action. However, despite tremendous development in tools for the generation of high resolution molecular models, large families of proteins are still poorly represented in databases of protein structure due to limitations of current technology. One method that has been used successfully to qualitatively study the structure of several of these families is hydroxyl radical protein footprinting (HRPF). HRPF is an emerging technology that has been used to study changes in protein topography by measuring changes in the apparent rate of reaction between hydroxyl radicals generated in situ and amino acid side chains on the protein surface. While this technology has been used successfully to study challenging problems in protein structure (e.g. membrane protein topography, glycoprotein-protein interactions, protein oligomerization and aggregation, protein interactions with heterogeneous ligand mixtures), such studies have always been comparative, detecting relative changes in protein topography from one conformation to another. Quantitative descriptions of protein structure have not been achieved due to a lack of knowledge of the link between HRPF reactivities and biophysical properties of the protein. Here, we propose to leverage preliminary data to develop amino acid-resolution HRPF (HR-HRPF) into a quantitative measurement of protein topography, accurately measuring the average solvent accessible surface areas () of many individual amino acids in YafO, a protein of unknown structure. By combining this data with a variety of de novo computational modeling strategies, we will generate accurate molecular models of protein structure using mass spectrometry data, testing these models against a structure of the same protein determined by NMR in a blinded fashion (in collaboration with Prof. James Prestegard, University of Georgia). We will also expand our chemistry and understanding to integral membrane proteins, developing the radical dosimetry technology and determining the empirical relationships between and HR-HRPF reactivity requires for quantitative measurements and modeling of integral membrane protein structure using bacteriorhodopsin as a model for technology development. Finally, we will develop technology and software tools to disseminate HR-HRPF technology into the broader biochemistry community, working with an established biochemistry group (Prof. Evgeny Nudler, NYUMC) to ensure technologies developed are robust and user-friendly. Together, these advances will add a new method for quantitative determination of protein structure and generation of accurate molecular models using protein chemistry and mass spectrometry.

Resulting Publication: PMCID: PMC7481795

Project Summary: The Protein Data Bank (PDB) contains more than 100,000 3D structures of proteins, many of which are directly relevant to human health and disease. Up to 10% of these structures contain carbohydrates as ligands or as post-translational modifications. While numerous tools exist to curate protein 3D structural data, no such tools have been adopted by the PDB as part of the validation checks performed upon coordinate deposition. This oversight has resulted in a large number of errors and inconsistencies in annotation and structure in the carbohydrate structural data. Here we will work with the World Wide PDB (wwPDB) to develop and implement tools to address these issues as part of a broader carbohydrate remediation initiative at the PDB. At the present time there are two serious problems that hinder the utilization of carbohydrate data stored in the protein data bank (PDB): 1) There is an unacceptably high proportion of errors in the deposited coordinates. 2) No convenient interface exists for searching for carbohydrate structures in the PDB. We will generate a software tool called ?GlyProbity for checking the accuracy and internal consistency of 3D structures of carbohydrates, and then implement this tool for the data remediation. In addition, GlyProbity will be provided as a stand-alone interface that may be used by crystallographers to validate carbohydrate structures prior to deposition in the PDB and by other researchers to validate structures obtained in any manner. Lastly, we will create a search interface, ?GlyFinder? to be implemented at GLYCAM-Web that will greatly simplify the task of locating relevant carbohydrate containing structures. Taken together, these aims should significantly impact the development of glycomimetic therapeutics, as well as the generation of structure/function relationships in glycobiology, and will be essential for achieving interoperability with additional databases or data mining services in the future.

PMCID: PMC8607818 , PMCID: PMC7347485, PMCID: PMC6583769