Thermodynamic projection of the antibody interaction network :

The adaptive humoral immune system of vertebrates functions by evolving a huge repertoire of binding proteins, which target potentially all molecules that come into contact with developing B cells. The key to endowing these binders with immunological activity is the adjustment of antibody structure and affinity against molecular targets. As a result, antibodies with a wide range of affinities and specificities evolve during the lifetime of an individual. I recently developed a quantitative model for the description of antibody homeostasis and suggested that a quantitative network can describe the dynamic antibody-antigen interaction space. Here, I project this molecular interaction space onto an energy landscape defined by conformational entropy and free energy of binding. I introduce the concept of binding fountain energy landscape, which allows the thermodynamic representation of binding events and paths of multiple interactions. I further show that the hypersurface of the binding fountain corresponds to the antibody-antigen interaction network. I propose that thymus independent and thymus dependent antibody responses show distinct patterns of changes in the energy landscape. Overall, the fountain energy landscape concept of molecular interactions allows a systems biological, thermodynamic perception and description of the functioning of the clonal humoral immune system. József Prechl ( ) Corresponding author: [email protected] : Conceptualization, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Author roles: Prechl J No competing interests were disclosed. Competing interests: Prechl J. How to cite this article: Thermodynamic projection of the antibody interaction network: The fountain energy landscape of 2017, :1675 (doi: molecular interaction systems [version 1; referees: 1 approved, 1 not approved] F1000Research 6 ) 10.12688/f1000research.12614.1 © 2017 Prechl J. This is an open access article distributed under the terms of the , which Copyright: Creative Commons Attribution Licence permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) declared that no grants were involved in supporting this work. Grant information: 11 Sep 2017, :1675 (doi: ) First published: 6 10.12688/f1000research.12614.1 1