Microarrays for the screening and identification of carbohydrate-binding peptides

2019 
The development of carbohydrate-binding ligands is crucial for expanding knowledge on the glycocode and for achieving systematic carbohydrate targeting. Amongst such ligands, carbohydrate-binding peptides (CBPs) are attractive for use in bioanalytical and biomedical systems due to their biochemical and physicochemical properties; moreover, given the biological significance of lectin–carbohydrate interactions, these ligands offer an opportunity to study peptide sequence and binding characteristics to inform on natural target/ligand interactions. Here, a high-throughput microarray screening technique is described for the identification and study of CBPs, with a focus on polysialic acid (PSA), a polysaccharide found on neural stem cells. The chemical and biological uniqueness of PSA suggests that an ability to exclusively target this glycan may promote a number of diagnostic and therapeutic applications. PSA-binding peptides from phage display screening and from epitope mapping of an ScFv for oligosialic acid were screened in an optimized microarray format with three ligand density conditions. Hypothesis-driven mutations were additionally applied to select peptides to modulate peptide affinity and selectivity to PSA. Peptide compositional and positional analyses revealed the significance of various residues for PSA binding and suggested the importance of basic residue positioning for PSA recognition. Furthermore, selectivity studies performed directly on microarrays with chondroitin sulfate A (CS-A) demonstrated the value of screening for both affinity and selectivity in the development of CBPs. Thus, the integrated approach described, with attention to design strategy, screening, and peptide characterization, successfully identified novel PSA-binding ligands and offers a platform for the identification and study of additional polysaccharide-binding peptides.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    59
    References
    2
    Citations
    NaN
    KQI
    []