Simulated evolution of antibody gene libraries under pathogen selection

The immune system of vertebrates is generally viewed as a prototype of a highly adaptive, distributed detection system, that identifies and neutralizes pathogenic intrusions. The immune receptors (antibodies) are able to bind to pathogens that they have not been “trained” to recognize. This anticipatory capability is thought to be due to a broad coverage of the pathogen space realized by the antibodies that the immune system can produce. We attempt to explain how this this coverage is achieved, given that the immune system uses a relatively small number of genes to construct its receptors. We use an evolutionary algorithm to explore the strategies that the antibody libraries may evolve in order to encode pathogen sets of various sizes. We derive a lower and upper bounds on the performance of the evolved antibody libraries as a function of their size and the length of the pathogen string. We also provide some insights in the strategy of the antibody libraries. We discuss the implications of our results for biological evolution of antibody libraries