mCSM-AB

mCSM-AB predicts changes in antibody-antigen binding affinity caused by mutations to support antibody engineering and escape-mutation identification.

Key Features:

• Graph-Based Signatures: Uses graph-based signatures to model structural and functional relationships within antibody-antigen complexes.
• Enhanced Predictive Accuracy: Demonstrates improved predictive accuracy for mutation-induced affinity changes compared to existing methods used in antibody engineering.

Scientific Applications:

• Antibody Engineering: Enables optimization of antibody binding by predicting how specific mutations affect affinity.
• Escape Mutation Prediction: Identifies potential escape mutations that reduce antibody recognition of antigens.
• Drug Development: Informs rational design of monoclonal antibodies and other biologics by predicting mutation impacts on antibody-antigen interactions.

Methodology:

Analyzes the structural context of antibody-antigen complexes using graph-based signatures that capture interaction networks to assess mutation-induced changes in binding affinity.