Recombinant antibodies are of profound clinical significance; yet, anti-carbohydrate antibodies are prone to undesirable cross-reactivity with structurally related-glycans. Here we introduce a new technology called Computational Carbohydrate Grafting (CCG), which enables a virtual library of glycans to be assessed for protein binding specificity, and employ it to define the scope and structural origin of the binding specificity of antibody JAA-F11 for glycans containing the Thomsen-Friedenreich (TF) human tumor antigen. A virtual library of the entire human glycome (GLibrary-3D) was constructed, from which 1,182 TF-containing human glycans were identified and assessed for their ability to fit into the antibody combining site. The glycans were categorized into putative binders, or non-binders, on the basis of steric clashes with the antibody surface. The analysis employed a structure of the immune complex, generated by docking the TF-disaccharide (Galβ1-3GalNAcα) into a crystal structure of the JAA-F11 antigen binding fragment, which was shown to be consistent with saturation transfer difference (STD) NMR data. The specificities predicted by CCG were fully consistent with data from experimental glycan array screening, and confirmed that the antibody is selective for the TF-antigen and certain extended core-2 type mucins. Additionally, the CCG analysis identified a limited number of related putative binding motifs, and provided a structural basis for interpreting the specificity. CCG can be utilized to facilitate clinical applications through the determination of the three-dimensional interaction of glycans with proteins, thus augmenting drug and vaccine development techniques that seek to optimize the specificity and affinity of neutralizing proteins, which target glycans associated with diseases including cancer and HIV.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3554700PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0054874PLOS

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Article Synopsis
  • The Thomsen-Friedenreich antigen (TF-Ag-α) is prevalent in around 85% of human cancers but is not present in normal tissues, making it a key target for cancer treatment.
  • Two humanized antibodies, hJAA-F11-H2aL2a and hJAA-F11-H3L3, specifically target TF-Ag-α, with H3L3 having a significantly higher affinity but potentially lower tumor penetration.
  • In studies with mouse models of various cancers, the H2aL2a antibody was shown to effectively decrease tumor growth and may be more effective than H3L3 for certain therapeutic applications, although H3L3 might be better for bi-specific therapies.
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