Antibody Affinity Maturation
Antigen binding affinity is one of the most critical properties of a therapeutic antibody. Therefore, methods used for antibody affinity maturation, including random mutagenesis, targeted mutagenesis, chain shuffling and in silico approaches, are widely applied.
NBbiolab uses Computer-Based Modeling to generate a 3D structure of an antibody–antigen complex and predict mutation“hotspots”generate a large number of antibody variants with specific mutations. This, combined with Our State-of-the-Art Yeast Surface Display Platform , has resulted in significant improvements of antigen binding affinity.
Antibody affinity maturation library design based on computational design.
Computer-Based Modeling predicts the key amino acid residues in the antibody–antigen interaction interface. The green band indicates the single chain antibody and the blue band indicates the N-terminal of the antigen. The yellow bar indicates key residues in the single-chain antibody, and the red band indicates key residues in the antigen.
Affinity-improved mutation variants are obtained from yeast surface display platform.
In order to optimize the binding affinity of an antibody, a 3D structure of an antibody–antigen complex was analyzed. Antibody affinity maturation library (Fab) was constructed based on computer modeling. By performing 3 rounds of FACS sorting, affinity improved clones with high expression (anti-Kappa-PE) and binding activity (APC-Ag) were isolated for the following functional validation.
In vitro validation.
Mutations had achieved 20-200 fold improvement in affinity.