AI-assisted Antibody Affinity Maturation/Modification

Backgrounds:

Antibody affinity maturation refers to a normal immune function status of the body. In humoral immunity, the phenomenon where antibodies produced during a secondary response have a higher average affinity than those produced during the primary response is called antibody affinity maturation. In recent years, with the launch of various antibody drugs, research on antibodies has become a hot topic in the biopharmaceutical field. Antibody affinity affects the role of antibodies in disease diagnosis, treatment and prevention. However, low-affinity antibodies produced by current antibody preparation technologies hinder the further application of antibodies. Therefore, technology based on simulating in vivo affinity maturation to produce in vitro affinity maturation has become a current research hotspot. ABLINK combines AI-assisted mutation site design, recovery mutation, phage display and high-throughput panning technology to provide customers with advanced and mature in vitro antibody affinity maturation services.

Procedure:

ABLINK uses AI-assisted structural analysis to determine mutation hotspots based on the target antibody's 3D structure provided by the customer, and uses Kunkel's method and phage display to construct recovery mutation libraries. Affinity-improved antibodies are screened and verified. For antibodies without 3D structures, ABLINK also supports affinity maturation services. Through the construction of first-generation saturation mutation libraries and panning, key sites and high-frequency substitute amino acids that can enhance affinity are identified, and high-affinity antibodies are finally screened in the constructed second-generation combined mutation library. At the same time, ABLINK also supports the use of hydrogen-deuterium exchange mass spectrometry (HDX-MS) to analyze the antibody's mutation hotspot regions.

Service Advantages and Features:

1. Antibody affinity maturation technology based on phage display can increase affinity by 10-100 times

2. AI-assisted antibody recovery mutation design greatly improves efficiency and saves time.

3. Multiple mutation site design strategies are provided, and there is no mandatory requirement for antibody 3D structure, reducing customer burden.

Cases: