Computational Evolution of Threonine-Rich β-Hairpin Peptides Mimicking Specificity and Affinity of Antibodies

Hongxia Hu, Christian Kofoed, Ming Li, Juliana Pereira Lopes Gonçalves, Jonas Hansen, Martin Wolfram, Axel Kornerup Hansen, Camilla Hartmann Friis Hansen, Frederik Diness, Sanne Schoffelen, Morten Meldal*

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

10 Citationer (Scopus)
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Abstract

The development of recognition molecules with antibody-like properties is of great value to the biotechnological and bioanalytical communities. The recognition molecules presented here are peptides with a strong tendency to form β-hairpin structures, stabilized by alternate threonines, which are located at one face of the peptide. Amino acids at the other face of the peptide are available for interaction with the target molecule. Using this scaffold, we demonstrate that recognition molecules can efficiently be designed in silico toward four structurally unrelated proteins, GFP, IL-1β, IL-2, and IL-6. On solid support, 10 different antibody-mimetic recognition molecules were synthesized. They displayed high affinity and no cross-reactivity, as observed by fluorescence microscopy. Stabilized variants were readily obtained by incorporation of azido acids and propargylglycine followed by cyclization via the Cu(I)-catalyzed alkyne-azide cycloaddition reaction. As this new class of antibody mimics can be designed toward essentially any protein, the concept is believed to be useful to a wide range of technologies. Here, their use in protein separation and in the detection of proteins in a sandwich-type assay is demonstrated.

OriginalsprogEngelsk
TidsskriftACS Central Science
Vol/bind5
Udgave nummer2
Sider (fra-til)259-269
Antal sider11
ISSN2374-7943
DOI
StatusUdgivet - 27 feb. 2019

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