Modeling bispecific monoclonal antibody interaction with two cell membrane targets indicates the importance of surface diffusion.
We have developed a mathematical framework for describing a bispecific monoclonal antibody interaction with two independent membrane-bound targets that are expressed on the same cell surface. The bispecific antibody in solution binds either of the two targets first, and then cross-links with the second one while on the cell surface, subject to rate-limiting lateral diffusion step within the lifetime of the monovalently engaged antibody-antigen complex. At experimental densities, only a small fraction of the free targets is expected to lie within the reach of the antibody binding sites at any time. Using ordinary differential equation and Monte Carlo simulation-based models, we validated this approach against an independently published anti-CD4/CD70 DuetMab experimental data set. As a result of dimensional reduction, the cell surface reaction is expected to be so rapid that, in agreement with the experimental data, no monovalently bound bispecific antibody binary complexes accumulate until cross-linking is complete. The dissociation of the bispecific antibody from the ternary cross-linked complex is expected to be significantly slower than that from either of the monovalently bound variants. We estimate that the effective affinity of the bivalently bound bispecific antibody is enhanced for about 4 orders of magnitude over that of the monovalently bound species. This avidity enhancement allows for the highly specific binding of anti-CD4/CD70 DuetMab to the cells that are positive for both target antigens over those that express only one or the other We suggest that the lateral diffusion of target antigens in the cell membrane also plays a key role in the avidity effect of natural antibodies and other bivalent ligands in their interactions with their respective cell surface receptors.
a Bioengineering Science Research Group, Faculty of Engineering and the Environment, and Institute for Life Sciences , University of Southampton , Southampton , UK.
Bram G
BG
Sengers
b Division of Biomedical Engineering, Glasgow University , Glasgow , UK.
Sean
S
McGinty
c Laboratoire de Modélisation Mathématiques et Simulation Numérique, Faculté des Sciences, Université Badji-Mokhtar , Annaba , Algeria.
Fatma Z
FZ
Nouri
d Department of Bioengineering , Imperial College London , London , UK.
Maryam
M
Argungu
e Department of Mathematics , University of Surrey , Guildford , UK.
Emma
E
Hawkins
f Pharmaceutic Mineral Chemistry Laboratory, Université Badji-Mokhtar , Annaba , Algeria.
Aymen
A
Hadji
g Drug Metabolism and Pharmacokinetics, GlaxoSmithKline Plc., King of Prussia , PA , USA.
Andrew
A
Weber
h Respiratory DPU, GlaxoSmithKline Plc. , Stevenage , UK.
Adam
A
Taylor
i Drug Metabolism and Pharmacokinetics, GlaxoSmithKline Plc. , Stevenage , UK.
Armin
A
Sepp
D000818:Animals; D018033:Antibodies, Bispecific / Q000276:immunology*; D000911:Antibodies, Monoclonal / Q000276:immunology*; D000915:Antibody Affinity / Q000276:immunology*; D004058:Diffusion; D006801:Humans; D008962:Models, Theoretical; D009010:Monte Carlo Method
D018033:Antibodies, Bispecific; D000911:Antibodies, Monoclonal
Affinity; Monte Carlo; avidity; bispecific antibody; diffusion; modeling; simulation; specificity; therapeutic