A new strategy to HER2-specific antibody discovery through artificial intelligence-powered phage display screening based on the Trastuzumab framework.
Journal:
Biochimica et biophysica acta. Molecular basis of disease
PMID:
40056877
Abstract
Human epidermal growth factor receptor 2 (HER2) is a recognized drug target, and it serves as a critical target for various cancer treatments, necessitating the discovery of more antibodies for therapeutic and detection purposes. Here, we have developed an innovative workflow for antibody generation through Artificial Intelligence-powered Phage Display Screening (AIPDS). This workflow integrates artificial intelligence-driven antibody CDRH3 sequence design, high-throughput DNA synthesis and phage display screening. We applied AIPDS workflow to generate promising antibodies against the human epidermal growth factor receptor 2 (HER2), offering a template for streamlined antibody generation. Seven novel antibodies stood out, demonstrating promising efficacy in various functional assays. Notably, DYHER2-02 demonstrates strong performance across all experimental tests. In summary, our study introduces a novel methodology to generate new antibody variants of an existing antibody using an AI-assisted phage display approach. These new antibody variants hold potential applications in research, diagnosis, and therapeutic applications.