A combined computational-experimental approach to define the structural origin of antibody recognition of sialyl-Tn, a tumor-associated carbohydrate antigen

Ron Amon, Oliver C. Grant, Shani Leviatan Ben-Arye, Spandana Makeneni, Anita K. Nivedha, Tal Marshanski, Christoffer Norn, Hai Yu, John N. Glushka, Sarel J. Fleishman, Xi Chen, Robert J. Woods, Vered Padler-Karavani

Research output: Contribution to journalArticlepeer-review

Abstract

Anti-carbohydrate monoclonal antibodies (mAbs) hold great promise as cancer therapeutics and diagnostics. However, their specificity can be mixed, and detailed characterization is problematic, because antibody-glycan complexes are challenging to crystallize. Here, we developed a generalizable approach employing high-throughput techniques for characterizing the structure and specificity of such mAbs, and applied it to the mAb TKH2 developed against the tumor-associated carbohydrate antigen sialyl-Tn (STn). The mAb specificity was defined by apparent KD values determined by quantitative glycan microarray screening. Key residues in the antibody combining site were identified by site-directed mutagenesis, and the glycan-antigen contact surface was defined using saturation transfer difference NMR (STD-NMR). These features were then employed as metrics for selecting the optimal 3D-model of the antibody-glycan complex, out of thousands plausible options generated by automated docking and molecular dynamics simulation. STn-specificity was further validated by computationally screening of the selected antibody 3D-model against the human sialyl-Tn-glycome. This computational-experimental approach would allow rational design of potent antibodies targeting carbohydrates.

Original languageEnglish
Article number10786
Number of pages12
JournalScientific Reports
Volume8
Issue number1
DOIs
StatePublished - 1 Dec 2018

All Science Journal Classification (ASJC) codes

  • General

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