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Updated: May 21, 2025

Scalable High Throughput Selection From Phage-displayed Synthetic Antibody Libraries
Published on: January 17, 2015
A synthetic heavy chain variable domain antibody library (VHL) provides highly functional antibodies with favorable
Guiying Pang1,2,3, Ruixue Wang2, Hongxu Yang2
1College of Pharmacy, Anhui University of Traditional Chinese Medicine, Hefei, People's Republic of China.
Abstract:
Synthetic antibody libraries have been developed as an efficient source for the discovery of the heavy chain variable (VH) domain, which exhibits low immunogenicity, high tissue penetration, and diverse binding epitopes in therapeutic biopharmaceuticals. In this study, the human IGHV3-23*04 germline gene was chosen as the scaffold with a high expression level and favorable thermal stability. Amino acid diversity was introduced into the complementarity determining region 3 (CDR3) to exclude potential sequence liabilities. A library containing 2.6 × 1011 independent clones was successfully constructed. The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein, interleukin-17A (IL17A), B-cell maturation antigen (BCMA), and G-protein coupled receptor family C group 5 member D (GPRC5D) were used as target antigens to screen and identify VHs. In each case, Thirty-one to fifty-five VHs were screened out. The VH-Fc antibodies showed superior affinities (as high as 4.6 nM) to the corresponding antigens but did not bind to antigen-irrelevant cell CHO-S. Furthermore, the anti-RBD and anti-IL17A VH-Fc antibodies showed strong functional activity in the receptor-blocking assays. The VH-Fc antibodies from the synthetic library exhibited favorable developability (thermal stability, colloidal stability, hydrophilicity, anti-aggregation ability, and no interaction with human IgGs). We demonstrated that high-affinity and highly functional VH domain antibodies were generated from the rationally designed library with desired physicochemical properties. This approach is generally universal to target any antigen and has significant potential to accelerate candidate selection.
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