A novel antibody humanization method based on epitopes scanning and molecular dynamics simulation.

Area of Science:

• Biotechnology
• Immunology
• Computational Biology

Background:

• Murine monoclonal antibodies like 1-17-2 targeting DEC-205 are valuable for antigen delivery to dendritic cells (DCs).
• Clinical application is hindered by the murine origin, necessitating antibody humanization.
• Traditional humanization techniques, such as CDR grafting, often compromise antibody affinity.

Purpose of the Study:

• To develop and validate a novel antibody humanization method.
• To identify and mutate specific antigenic residues in framework regions (FRs) while preserving antibody-antigen binding.
• To create a humanized antibody with retained affinity for potential therapeutic use.

Main Methods:

• Homology modeling to create a precise Fab model.
• Development of a novel epitope scanning algorithm to identify critical residues for mutation.
• Virtual mutation and molecular dynamics (MD) simulations to assess conformational impact.
• In vitro construction and binding affinity assessment using flow cytometry and surface plasmon resonance (SPR).

Main Results:

• A novel humanization strategy was successfully developed using computational modeling and bioinformatics.
• Epitope scanning and MD simulations identified key residues impacting CDR conformation.
• Five critical residues were identified for back-mutation to restore binding affinity.
• The refined humanized antibody demonstrated binding affinity comparable to the original rat antibody.

Conclusions:

• A novel, effective antibody humanization method combining epitope scanning and MD simulation has been established.
• This method successfully overcomes the affinity loss typically associated with traditional humanization techniques.
• The developed humanized antibody is suitable for further preclinical and clinical development.