A Predictive Model of Antibody Binding in the Presence of IgG-Interacting Bacterial Surface Proteins

• DOI: 10.3389/fimmu.2021.629103
• Publication Date: 2021-03-22T04:59:15Z
• Authors: Vibha Kumra Ahnlide; Therese de Neergaard; Martin Sundwall; Tobias Ambjörnsson; Pontus Nordenfelt
• Keywords: biophysical model; M protein; Streptococcus pyogenes; THP-1 Cells; Immunology; Binding, Competitive; Epitopes; 03 medical and health sciences; Phagocytosis; antibody treatment; Antibody Specificity; Humans; group A Streptoccocus; antibody interactions; Antigens, Bacterial; 0303 health sciences; Models, Immunological; Antibodies, Monoclonal; RC581-607; Antibodies, Bacterial; 3. Good health; Immunoglobulin G; antibody binding; Binding Sites, Antibody; Immunologic diseases. Allergy; Carrier Proteins; Bacterial Outer Membrane Proteins; Protein Binding

Many bacteria can interfere with how antibodies bind to their surfaces. This bacterial antibody targeting makes it challenging predict the immunological function of bacteria-associated antibodies. The M and M-like proteins group A streptococci (GAS) exhibit IgGFc-binding regions, which they use reverse IgG binding orientation depending on host environment. Unraveling mechanism behind these characteristics may identify conditions under bound drive an efficient immune response. Here, we have developed a biophysical model for describing complex protein-antibody interactions. We show be used as tool studying behavior various samples protein by performing in silico simulations correlating this data experimental measurements. Besides its mechanistic understanding, could potentially aid development treatments. illustrate simulating GAS serum is altered specified amounts monoclonal or pooled added. Phagocytosis experiments link physiological demonstrate that possible effect treatment our model. Our study gives understanding provides predicting treatments presence IgG-modulating surface proteins.