Dataset Information

Positional Scanning MUC1 Glycopeptide Library Reveals the Importance of PDTR Epitope Glycosylation for Lectin Binding.

ABSTRACT: One of the main barriers to explaining the functional significance of glycan-based changes in cancer is the natural epitope heterogeneity found on the surface of cancer cells. To help address this knowledge gap, we focused on designing synthetic tools to explore the role of tumor-associated glycans of MUC1 in the formation of metastasis via association with lectins. In this study, we have synthesized for the first time a MUC1-derived positional scanning synthetic glycopeptide combinatorial library (PS-SGCL) that vary in number and location of cancer-associated Tn antigen using the "tea bag" approach. The determination of the isokinetic ratios necessary for the equimolar incorporation of (glyco)amino acids mixtures to resin-bound amino acid was determined, along with developing an efficient protocol for on resin deprotection of O-acetyl groups. Enzyme-linked lectin assay was used to screen PS-SGCL against two plant lectins, Glycine max soybean agglutinin and Vicia villosa. The results revealed a carbohydrate density-dependent affinity trend and site-specific glycosylation requirements for high affinity binding to these lectins. Hence, PS-SGCLs provide a platform to systematically elucidate MUC1-lectin binding specificities, which in the long term may provide a rational design for novel inhibitors of MUC1-lectin interactions involved in tumor spread and glycopeptide-based cancer vaccines.

SUBMITTER: Singh Y

PROVIDER: S-EPMC7012140 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Publications

Positional Scanning MUC1 Glycopeptide Library Reveals the Importance of PDTR Epitope Glycosylation for Lectin Binding.

Singh YashoNandini Y Rodriguez Benavente Maria C MC Al-Huniti Mohammed H MH Beckwith Donella D Ayyalasomayajula Ramya R Patino Eric E Miranda William S WS Wade Alex A Cudic Maré M

The Journal of organic chemistry 20191218 3

One of the main barriers to explaining the functional significance of glycan-based changes in cancer is the natural epitope heterogeneity found on the surface of cancer cells. To help address this knowledge gap, we focused on designing synthetic tools to explore the role of tumor-associated glycans of MUC1 in the formation of metastasis via association with lectins. In this study, we have synthesized for the first time a MUC1-derived positional scanning synthetic glycopeptide combinatorial libra ...[more]

PMID: 31799848

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Project description:The Major Histocompatibility Complex (MHC) is a critical element in mounting an effective immune response in vertebrates against invading pathogens. Studies of MHC in wildlife populations have typically focused on assessing diversity within the peptide binding regions (PBR) of the MHC class II (MHC II) family, especially the DQ receptor genes. Such metrics of diversity, however, are of limited use to health risk assessment since functional analyses (where changes in the PBR are correlated to recognition/pathologies of known pathogen proteins), are difficult to conduct in wildlife species. Here we describe a means to predict the binding preferences of MHC proteins: We have developed a model positional scanning library analysis (MPSLA) by harnessing the power of mixture based combinatorial libraries to probe the peptide landscapes of distinct MHC II DQ proteins. The algorithm provided by NNAlign was employed to predict the binding affinities of sets of peptides generated for DQ proteins. These binding affinities were then used to retroactively construct a model Positional Scanning Library screen. To test the utility of the approach, a model screen was compared to physical combinatorial screens for human MHC II DP. Model library screens were generated for DQ proteins derived from sequence data from bottlenose dolphins from the Indian River Lagoon (IRL) and the Atlantic coast of Florida, and compared to screens of DQ proteins from Genbank for dolphin and three other cetaceans. To explore the peptide binding landscape for DQ proteins from the IRL, combinations of the amino acids identified as active were compiled into peptide sequence lists that were used to mine databases for representation in known proteins. The frequency of which peptide sequences predicted to bind the MHC protein are found in proteins from pathogens associated with marine mammals was found to be significant (p values <0.0001). Through this analysis, genetic variation in MHC (classes I and II) can now be associated with the binding repertoires of the expressed MHC proteins and subsequently used to identify target pathogens. This approach may be eventually applied to evaluate individual population and species risk for outbreaks of emerging diseases.

Dataset Information

Positional Scanning MUC1 Glycopeptide Library Reveals the Importance of PDTR Epitope Glycosylation for Lectin Binding.

Publications

Positional Scanning MUC1 Glycopeptide Library Reveals the Importance of PDTR Epitope Glycosylation for Lectin Binding.

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