Design of peptides with high affinity binding to a monoclonal antibody as a basis for immunotherapy

Surendra S. Negi, Randall M. Goldblum, Werner Braun, Terumi Midoro-Horiuti

Research output: Contribution to journalArticlepeer-review


About half of the US population is sensitized to one or more allergens, as found by a National Health and Nutrition Examination Survey (NHANES). The most common treatment for seasonal allergic responses is the daily use of oral antihistamines, which can control some of the symptoms, but are not effective for nasal congestion, and can be debilitating in many patients. Peptide immunotherapy is a promising new approach to treat allergic airway diseases. The small size of the immunogens cannot lead to an unwanted allergic reaction in sensitized patients, and the production of peptides with sufficient amounts for immunotherapy is time- and cost-effective. However, it is not known what peptides are the most effective for an immunotherapy of allergens. We previously produced a unique monoclonal antibody (mAb) E58, which can inhibit the binding of multiple groups of mAbs and human IgEs from patients affected by the major group 1 allergens of ragweed (Amb a 1) and conifer pollens (Jun a 1, Cup s 1, and Cry j 1). Here, we demonstrated that a combined approach, starting from two linear E58 epitopes of the tree pollen allergen Jun a 1 and the ragweed pollen allergen Amb a 1, and residue modifications suggested by molecular docking calculations and peptide design could identify a large number of high affinity binding peptides. We propose that this combined experimental and computational approach by structural analysis of linear IgE epitopes and peptide design, can lead to potential new candidates for peptide immunotherapy.

Original languageEnglish (US)
Article number170628
StatePublished - Nov 2021


  • Allergen structure
  • Amb a 1
  • Epitope
  • Jun a 1
  • Molecular docking
  • Monoclonal antibody

ASJC Scopus subject areas

  • Biochemistry
  • Physiology
  • Endocrinology
  • Cellular and Molecular Neuroscience


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