Question: How does AI-powered affinity maturation improve the efficiency of antibody lead optimization?

Answer: Traditional affinity maturation relies on library construction and iterative screening, which is time-consuming. In contrast, AI-driven antibody affinity maturation utilizes deep learning models to predict the binding energy and stability of millions of potential mutants in silico. By analyzing sequence-structure-function relationships, the platform identifies high-probability candidates for experimental validation, significantly reducing the number of wet-lab cycles required to achieve sub-nanomolar affinity.