Network organization of antibody interactions in sequence and structure space: the RADARS model

Adaptive immunity in vertebrates represents a complex self-organizing network of protein interactions that develops throughout the lifetime of an individual. While deep sequencing of the immune-receptor repertoire may reveal clonal relationships, functional interpretation of such data is hampered by the inherent limitations of converting sequence to structure to function. In this paper a novel model of antibody interaction space and network, termed radial adjustment of system resolution, RADARS, is proposed. The model is based on the radial growth of interaction affinity of antibodies towards an infinity of directions in structure space, each direction representing particular shapes of antigen epitopes. Levels of interaction affinity appear as free energy shells of the system, where hierarchical B-cell development and differentiation takes place. Equilibrium in this immunological thermodynamic system can be described by a power-law distribution of antibody free energies with an ideal network degree exponent of phi square, representing a scale-free fractal network of antibody interactions. Plasma cells are network hubs, memory B cells are nodes with intermediate degrees and B1 cells represent nodes with minimal degree. Thus, the RADARS model implies that antibody structure space develops against an infinite antigen structure space via interactions that are individually immunologically controlled, but on a systems level are organized by thermodynamic probability distributions. The network of interactions, which control B-cell development and differentiation, represent pathways of antigen removal on systems level. Understanding such quantitative network properties of the system should help the organization of sequence-derived structural data, offering the possibility to relate sequence to function in a complex, self-organizing biological system. Graphical Abstract Graphical abstract