General solutions to decompose heterogeneous compositions using antibody afucosylation as a model system

Area of Science:

• Biotechnology and Chemical Engineering
• Biophysics
• Computational Biology

Background:

• Characterizing ligand mixtures and their properties is crucial for understanding biological interactions.
• Existing methods often struggle to precisely determine individual ligand contributions within complex mixtures.
• Afucosylated antibodies binding to FcγRIIIa (CD16a) present a complex system for studying ligand-receptor interactions.

Purpose of the Study:

• To develop and validate mathematical models for characterizing ligand mixtures based on competitive ligand-receptor binding.
• To enable the determination of individual component ligand physical-chemical properties from mixture data.
• To predict the properties and behavior of ligand mixtures and explain experimental observations.

Main Methods:

• Development of mathematical models relating component ligand properties and mole fractions to measurable binding activities (1/K_d,apparent, 1/EC50) and kinetic rate constants (k_on,apparent, k_off,apparent).
• Incorporation of combinatorial mathematics to compute ligand mole fractions.
• Application of the developed models to published experimental data of afucosylated antibody mixtures binding to FcγRIIIa (CD16a).

Main Results:

• Successfully extracted previously elusive physical property information for component ligands within mixtures.
• Accurately predicted experimental binding observations for ligand mixtures.
• Provided explanations for previously unresolved experimental findings in afucosylated antibody-FcγRIIIa interactions.

Conclusions:

• The developed mathematical modeling approach provides a powerful tool for characterizing complex ligand mixtures.
• This method allows for the determination of intrinsic ligand properties and prediction of mixture behavior.
• The findings offer new insights into the binding mechanisms of afucosylated antibodies and FcγRIIIa.