What is it about?
Our immune system generates protein molecules called antibodies, which are key mediators of protection. The intriguing aspect of antibodies is that they evolve in the host organism, meaning that millions of different antibodies are produced by a specialized population of cells, B lymphocytes. This immense diversity helps the immune system to develop protection against practically any harmful molecule. Current technologies allow the identification of the sequence of distinct antibody molecules but fail to reliably estimate the structure, which is key to understanding function. This article proposes a model of how the immune system optimizes this vast collection of molecules. The model suggests that via immunological regulatory mechanisms random physical processes lead to the generation of antibody networks. By the use of networks the number of very reactive antibodies can be kept at minimum and the largest number of molecules to be disposed can be channeled for removal via those antibodies. The antibody network is thus a transportation network for antigens (targets of antibodies), an main hubs are sinks for antigen. The model also suggests that these networks are of the scale-free fractal type.
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Why is it important?
There are two basic approaches to understand how the vast collaction of antibodies are related and how they act together. The experimental approach today comprises the identification of antibody sequences present in the host organism, either in bulk or in individual cells. This set of sequences is then analyzed and sequence similarities are used for identifying patterns, families of sequenes and networks of related antibodies.This approach is hindered by the lack of a general theory of what patterns or networks we are expecting to show up. The model proposed in this paper describes such a model. Rather than being based on experimental data, it builds on laws of physics, mathematical distributions and network theory. This is a stochastic model, which could provide a theoretical framework for experimental data. Unlike other models and theories, this model builds on the affinity (binding energy) of antibodies and the structural properties related to affinity.
Perspectives
The idea that antibodies form a network has been around for a long while, even awarded a Nobel prize (Niels K. Jerne, 1984). Ever since it has been a critical goal of immunologists to figure out what rules govern the immune system on the systems level. This model is novel in the sense that it builds on physics and physical chemistry, because it focuses on the affinity of the antibody molecules, and it directly relates network properties (network node degree) to binding energy. I think the complexity of the immune system can only be understood by identifying the physical laws that apply to the system.
József Prechl
Diagnosticum
Read the Original
This page is a summary of: Network Organization of Antibody Interactions in Sequence and Structure Space: the RADARS Model, Antibodies, May 2020, MDPI AG,
DOI: 10.3390/antib9020013.
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