Sulfated glycans have been found to be associated with various diseases and therefore have significant potential in molecular pathology as biomarkers. Although lectins are useful reagents for detecting glycans, there is a paucity of sulfate-recognizing lectins, and those that exist, such as from Maackia amurensis , display mixed specificities. Recombinant lectin engineering offers an emerging tool for creating novel glycan recognition by altering and/or enhancing endogenous specificities. The present study demonstrated the use of computational approaches in the engineering of a mutated form of E-selectin that displayed highly specific recognition of 6′-sulfo-sialyl Lewis X (6′-sulfo-sLe x ), with negligible binding to its endogenous nonsulfated ligand, sLe x . This new specificity mimics that of the unrelated protein Siglec-8, for which 6′-sulfo-sLe x is its preferred ligand. Molecular dynamics simulations and energy calculations predicted that two point mutations (E92A/E107A) would be required to stabilize binding to the sulfated oligosaccharide with E-selectin. In addition to eliminating putative repulsions between the negatively charged side chains and the sulfate moiety, the mutations also abolished favorable interactions with the endogenous ligand. Glycan microarray screening of the recombinantly expressed proteins confirmed the predicted specificity change but also identified the introduction of unexpected affinity for the unfucosylated form of 6′-sulfo-sLe x (6′-sulfo-sLacNAc). Three key requirements were demonstrated in this case for engineering specificity for sulfated oligosaccharide: 1) removal of unfavorable interactions with the 6′-sulfate, 2) introduction of favorable interactions for the sulfate, and 3) removal of favorable interactions with the endogenous ligand.
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Systematic synthesis of bisected N -glycans and unique recognitions by glycan-binding proteins
Bisected N -glycans represent a unique class of protein N -glycans that play critical roles in many biological processes. Herein, we describe the systematic synthesis of these structures. A bisected N -glycan hexasaccharide was chemically assembled with two orthogonal protecting groups attached at the C2 of the branching mannose residues, followed by sequential installation of GlcNAc and LacNAc building blocks to afford two asymmetric bisecting “cores”. Subsequent enzymatic modular extension of the “cores” yielded a comprehensive library of biantennary N -glycans containing the bisecting GlcNAc and presenting 6 common glycan determinants in a combinatorial fashion. These bisected N -glycans and their non-bisected counterparts were used to construct a distinctive glycan microarray to study their recognition by a wide variety of glycan-binding proteins (GBPs), including plant lectins, animal lectins, and influenza A virus hemagglutinins. Significantly, the bisecting GlcNAc could bestow (PHA-L, rDCIR2), enhance (PHA-E), or abolish (ConA, GNL, anti-CD15s antibody, etc. ) N -glycan recognition of specific GBPs, and is tolerated by many others. In summary, synthesized compounds and the unique glycan microarray provide ideal standards and tools for glycoanalysis and functional glycomic studies. The microarray data provide new information regarding the fine details of N -glycan recognition by GBPs, and in turn improve their applications.
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- Award ID(s):
- 1933525
- NSF-PAR ID:
- 10406413
- Date Published:
- Journal Name:
- Chemical Science
- Volume:
- 13
- Issue:
- 25
- ISSN:
- 2041-6520
- Page Range / eLocation ID:
- 7644 to 7656
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract 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.
Contact wonpil@lehigh.edu
Supplementary information Supplementary data are available at Bioinformatics online.
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null (Ed.)Metabolic glycan engineering (MGE) coupled with nitroxide spin-labeling (SL) was utilized to investigate the heterogeneous environment of cell surface glycans in select cancer and normal cells. This approach exploited the incorporation of azides into cell surface glycans followed by a click reaction with a new nitroxide spin label. Both sialic acid and N -acetylglucosamine (GlcNAc) were targeted for spin labelling. Although each of these moieties experiences a diverse and heterogeneous glycan environment, their EPR spectra and hence mobility are both characterized as a linear combination of two distinct spectra where one component reflects a highly mobile or uncrowded micro-environment with the second component reflecting more restricted motion, reflective of increased crowding and packing within the glycocalyx. What differs among the spectra of the targeted glycans is the relative percentage of each component, with sialic acid moieties experiencing on average an ∼80% less crowded environment, where conversely GlcNAc/GalNAz labeled sites reported on average a ∼50% more crowded environment. These distinct environments are consistent with the organization of sugar moieties within cellular glycans where some residues occur close to the cell membrane/protein backbone ( i.e. more restricted) and others are more terminal in the glycan ( i.e. more mobile). Strikingly, different cell lines displayed varied relative populations of these two components, suggesting distinctive glycan packing, organization, and composition of different cells. This work demonstrates the capability of SDSL EPR to be a broadly useful tool for studying glycans on cells, and interpretation of the results provides insights for distinguishing the differences and changes in the local organization and heterogeneity of the cellular glycocalyx.more » « less
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Abstract Glycans are the major components of the cellular membranes and mediate many cellular processes via their interactions with lectins. A kinetic Monte Carlo (kMC) model was proposed previously to incorporate the key features of glycan‐lectin interactions such as multivalency and glycan diffusion, and its accuracy has been validated by experiments. However, computational cost of the kMC model is its major bottleneck. In this study, a hybrid model combining a partial differential equation (PDE) with the kMC model is proposed to greatly reduce the computational cost while preserving the accuracy. Specifically, glycan diffusion is simulated by the PDE for improving computational efficiency since the glycan diffusion execution through the kMC is computationally expensive. The hybrid PDE‐kMC model is employed to simulate the binding dynamics between cholera toxin subunit B and gangliosides on cellular membranes. The accuracy and efficiency of the proposed model was demonstrated by comparing with the sole kMC model.
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SUMMARY Microbial and plant cell walls have been selected by the plant immune system as a source of microbe‐ and plant damage‐associated molecular patterns (MAMPs/DAMPs) that are perceived by extracellular ectodomains (ECDs) of plant pattern recognition receptors (PRRs) triggering immune responses. From the vast number of ligands that PRRs can bind, those composed of carbohydrate moieties are poorly studied, and only a handful of PRR/glycan pairs have been determined. Here we present a computational screening method, based on the first step of molecular dynamics simulation, that is able to predict putative ECD‐PRR/glycan interactions. This method has been developed and optimized with Arabidopsis LysM‐PRR members CERK1 and LYK4, which are involved in the perception of fungal MAMPs, chitohexaose (1,4‐β‐
d ‐(GlcNAc)6) and laminarihexaose (1,3‐β‐d ‐(Glc)6). Ourin silico results predicted CERK1 interactions with 1,4‐β‐d ‐(GlcNAc)6whilst discarding its direct binding by LYK4. In contrast, no direct interaction between CERK1/laminarihexaose was predicted by the model despite CERK1 being required for laminarihexaose immune activation, suggesting that CERK1 may act as a co‐receptor for its recognition. Thesein silico results were validated by isothermal titration calorimetry binding assays between these MAMPs and recombinant ECDs‐LysM‐PRRs. The robustness of the developed computational screening method was further validated by predicting that CERK1 does not bind the DAMP 1,4‐β‐d ‐(Glc)6(cellohexaose), and then probing that immune responses triggered by this DAMP were not impaired in the Arabidopsiscerk1 mutant. The computational predictive glycan/PRR binding method developed here might accelerate the discovery of protein–glycan interactions and provide information on immune responses activated by glycoligands.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/d1sc05435j
