Tuning antibody stability and function by rational designs of framework mutations.

Area of Science:

• Biotechnology
• Immunology
• Computational Biology

Background:

• Antibody engineering often focuses on complementarity-determining regions (CDRs), neglecting the immunoglobulin framework (FW).
• The FW provides structural support crucial for antibody stability and function.
• Existing artificial intelligence models may overlook FW contributions in antibody design.

Purpose of the Study:

• To develop an integrated computational-experimental workflow for rational design of FW mutations.
• To modulate antibody stability and activity by targeting the FW.
• To expand antibody engineering strategies beyond CDR-centric approaches.

Main Methods:

• Integrated computational-experimental workflow combining static structure analysis, molecular dynamics simulations, and in vitro assays.
• Analysis of antibody-specific language models for insights into FW mutagenesis.
• Design and validation of FW mutations using trastuzumab as a model antibody targeting HER2.

Main Results:

• Computational approaches using structural information outperformed language models in predicting FW mutagenesis.
• Designed stabilizing FW mutants distal to CDRs maintained antigen binding (HER2) and antibody-dependent cellular cytotoxicity.
• A specific FW mutation retained antigen binding but abolished effector functions, highlighting FW's role in distal immunological functions.

Conclusions:

• The developed workflow enables rational design of FW mutations to enhance antibody stability and function.
• Considering the entire antibody structure, including interdomain dynamics, is crucial for optimizing antibody developability.
• This approach expands antibody engineering scope beyond CDRs, emphasizing a holistic perspective for improved therapeutic antibodies.