Deep sequencing combined with high‐throughput screening enables efficient development of a <scp>pH</scp>‐dependent high‐affinity binding domain targeting <scp>HER3</scp>

In vitro methods for developing binding domains have been well-established for many years, owing to the cost-efficient synthesis of DNA and high-throughput selection and screening technologies. However, generating high-affinity binding domains often requires the development of focused maturation libraries for a second selection, which typically demands a detailed understanding of the binding surfaces from the initial selection, a process that can be time-consuming. In this study, we accelerated this process by using deep sequencing data from the first selection to guide the design of the maturation library. Additionally, we employed a high-throughput screening system using flow cytometry based on Escherichia coli display to identify conditional binding domains from the selection output. This approach enabled the development of a high-affinity binder targeting the cancer biomarker HER3, with a binding affinity of 3.3 nM at extracellular pH 7.4, 100 times higher than the first-generation binding domain. Notably, the binding domain features a pH-dependent release mechanism, enabling rapid release in slightly acidic environments (pH ≈6), which resemble endosomal conditions. When conjugated to the cytotoxin mertansine (DM1), the binding domain demonstrated specific cytotoxic activity against HER3-expressing cell lines, with an IC50 of 2-5 nM. The presented approach enables the efficient development of conditional binding domains which hold promise for therapeutic applications.

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Publication Details

Journal
Protein Science
Published
2025-07-26
DOI
https://doi.org/10.1002/pro.70247
Primary Topic
Monoclonal and Polyclonal Antibodies Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Deep sequencing combined with high‐throughput screening enables efficient development of a pH‐dependent high‐affinity binding domain targeting HER3

Johan Rockberg, Marit Möller, Sophia Hober, Hanna Tegel et al.
Protein Science
Monoclonal and Polyclonal Antibodies Research
article

Deep sequencing combined with high‐throughput screening enables efficient development of a pH‐dependent high‐affinity binding domain targeting HER3

Johan Rockberg, Marit Möller, Sophia Hober, Hanna Tegel, John Löfblom, Malin Jönsson, Magnus Lundqvist
article en

Abstract

In vitro methods for developing binding domains have been well-established for many years, owing to the cost-efficient synthesis of DNA and high-throughput selection and screening technologies. However, generating high-affinity binding domains often requires the development of focused maturation libraries for a second selection, which typically demands a detailed understanding of the binding surfaces from the initial selection, a process that can be time-consuming. In this study, we accelerated this process by using deep sequencing data from the first selection to guide the design of the maturation library. Additionally, we employed a high-throughput screening system using flow cytometry based on Escherichia coli display to identify conditional binding domains from the selection output. This approach enabled the development of a high-affinity binder targeting the cancer biomarker HER3, with a binding affinity of 3.3 nM at extracellular pH 7.4, 100 times higher than the first-generation binding domain. Notably, the binding domain features a pH-dependent release mechanism, enabling rapid release in slightly acidic environments (pH ≈6), which resemble endosomal conditions. When conjugated to the cytotoxin mertansine (DM1), the binding domain demonstrated specific cytotoxic activity against HER3-expressing cell lines, with an IC50 of 2-5 nM. The presented approach enables the efficient development of conditional binding domains which hold promise for therapeutic applications.

Protein ScienceVol. 34(8)
KTH Royal Institute of Technology (SE)
Cancerfonden, Vetenskapsrådet
Openalex Percentile: Top 73%
Monoclonal and Polyclonal Antibodies Research
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