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

doi:10.1021/acscentsci.8b00614

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

Kemisk Institut

6 Citationer (Scopus)

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.

Originalsprog	Engelsk
Tidsskrift	ACS Central Science
Vol/bind	5
Udgave nummer	2
Sider (fra-til)	259-269
Antal sider	11
ISSN	2374-7943
DOI	https://doi.org/10.1021/acscentsci.8b00614
Status	Udgivet - 27 feb. 2019

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10.1021/acscentsci.8b00614Licens: Andet

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@article{a40494054af14ae1b68baa39a60cdd0f,

title = "Computational Evolution of Threonine-Rich β-Hairpin Peptides Mimicking Specificity and Affinity of Antibodies",

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.",

author = "Hongxia Hu and Christian Kofoed and Ming Li and Gon{\c c}alves, {Juliana Pereira Lopes} and Jonas Hansen and Martin Wolfram and Hansen, {Axel Kornerup} and {Friis Hansen}, {Camilla Hartmann} and Frederik Diness and Sanne Schoffelen and Morten Meldal",

year = "2019",

month = feb,

day = "27",

doi = "10.1021/acscentsci.8b00614",

language = "English",

volume = "5",

pages = "259--269",

journal = "ACS Central Science",

issn = "2374-7943",

publisher = "American Chemical Society",

number = "2",

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TY - JOUR

T1 - Computational Evolution of Threonine-Rich β-Hairpin Peptides Mimicking Specificity and Affinity of Antibodies

AU - Hu, Hongxia

AU - Kofoed, Christian

AU - Li, Ming

AU - Gonçalves, Juliana Pereira Lopes

AU - Hansen, Jonas

AU - Wolfram, Martin

AU - Hansen, Axel Kornerup

AU - Friis Hansen, Camilla Hartmann

AU - Diness, Frederik

AU - Schoffelen, Sanne

AU - Meldal, Morten

PY - 2019/2/27

Y1 - 2019/2/27

N2 - 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.

AB - 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.

U2 - 10.1021/acscentsci.8b00614

DO - 10.1021/acscentsci.8b00614

M3 - Journal article

C2 - 30834314

AN - SCOPUS:85061225946

SN - 2374-7943

VL - 5

SP - 259

EP - 269

JO - ACS Central Science

JF - ACS Central Science

IS - 2

ER -

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

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